The Pre-Crime Society: Crime, Culture and Control in the Ultramodern Age 9781529205268

Table of contents :
Front Cover
The Pre-Crime Society: Crime, Culture and Control in the Ultramodern Age
Copyright information
Dedication
Table of contents
Notes on Contributors
Foreword
Introduction: The Ultramodern Age of Criminology, Control Societies and ‘Dividual’ Justice Policy
Part I Theories, Theorists and Theoretical Perspectives
1 The ‘Risk’ Society Thesis and the Culture(s) of Crime Control
Introduction
Section I: the problem of reification and the culture(s) of control
Marx and reification
The Situationists and reification
The hyper-realists and reification
Section II: on the interdependent forces of reification and their interrelated forms of risk management
The symbolic forces of risk currency: on the mind’s jurisprudence
The linguistic forces of risk currency: on subjectivity’s politics
The material forces of risk currency: on power’s microphysics
The cultural forces of risk currency: on risk’s governance
Section III: the ultramodern era of pre-crime, post-criminology, and of risk management
Conclusion
Notes
References
2 The Security Society: On Power, Surveillance and Punishments
Introduction
Sovereign power
Disciplinary power
Control power
Interventions: from exclusion to inclusion
Sovereign power
Disciplinary power
Control power
Psychopower
Conclusion
References
3 Pre-Crime and the ‘Control Society’: Mass Preventive Justice and the Jurisprudence of Safety
Risk and dangerousness: pre-crimes and preventive crimes
From pre-crimes to risk crimes
Control and the emergence of mass preventive justice
Resistance, risk crimes and the domain of control
Conclusion
Notes
References
4 The Negation of Innocence: Terrorism and the State of Exception
Introduction
Who is killing whom in the digital age?4
The state of exception
Non-state terrorism and the state of exception
State of exception or state of permanence?
States of exception and the negation of innocence
Cinematic shock, the aesthetics of violence and real life
Conclusion
Notes
References
Part II Institutions, Organizations and the Surveillance Industrial Complex
5 Visions of the Pre-Criminal Student: Reimagining School Digital Surveillance
Introduction
Pre-crime
Techno-realist transactions: digital surveillance technologies, schools and pre-crime
The political economy of possible futures: neoliberal governmentality and pre-crime surveillance in schools
Envisioning the pre-criminal student
Conclusion
References
6 Commodification of Suffering
Introduction
Cultural assumptions and commodification
Suffering as commodity
Mental health surveillance
Mental health deinstitutionalization and incarceration
Outcomes
Conclusion
References
Part III Dataveillance, Governance and Policing Control Societies
9 Cameras and Police Dataveillance: A New Era in Policing
Introduction
Historical context
Three eras of policing
Populating databases through dataveillance
Closed- circuit television
License plate readers
In- vehicle cameras
Body- worn cameras
Video recording as police dataveillance
Moving forward
Conclusion
References
10 Theorizing Surveillance in the Pre- Crime Society
Introduction
Background and context: surveillance, pre-crime and policing
The politics of pre- crime in the field of policing
Responsibilization and pre- crime policing
Data politics and the technological field of expertise
Conclusion
Notes
References
11 Dataveillance and the Dividuated Self: The Everyday Digital Surveillance of Young People
Introduction
Dataveillance, the dividuated self and young people
Visual
Biometric and wearable technologies
Spatial
Algorithmic
Conclusion
Note
References
12 The Bad Guys Are Everywhere; the Good Guys Are Somewhere
Introduction
Early problematizations of national security and high policing
Human intelligence and counterintelligence
Five Eyes signals intelligence
Intelligence- led policing, integration and fusion
Integration and fusion
Post 9/ 11 signals intelligence
Is anything being done to curtail national security states of exception?
Conclusion
Notes
References
Part IV Systems of Surveillance, Discipline and the New Penology
13 Supermax Prison Isolation in Pre- Crime Society
Solitary confinement and supermax prisons
Risk assessment and technology
Surveillance
What does race have to do with it?
Horace
A self-fulfilling prophecy
Conclusion
Notes
References
14 Mass Monitoring: The Role of Big Data in Tracking Individuals Convicted of Sex Crimes
Introduction
The use of technology: the rise of registration and public notification
History, logic, and constitutionality
Amassing data through SORN: registries
Sharing data through SORN: public notification
SORNA and new federal data collection requirements
SORNA and public notification
SORN and the public
Awareness and action
Perceptions of public notification
The use of technology: the rise of electronic monitoring
History, logic and constitutionality
Types of electronic-monitoring data
State models
Florida
California
Massachusetts
Law enforcement and the use of electronic-monitoring data
Electronic monitoring and recidivism
Discussion
Pre-crime society implications
Conclusion
References
15 Towards Predictivity? Immediacy and Imminence in the Electronic Monitoring of Offenders
Introduction
Immediacy, compliance and containment
Electronic monitoring and the problem of punitiveness in the US
The National Institute for Justice and data analytics
Electronic monitoring companies and ‘the new predictivity’
Towards ultra-punitive electronic monitoring?
Conclusion
References
16 The Digital Technologies of Rehabilitation and Reentry
Introduction
Framing digital technology in the reentry process
Digital inequalities
Digital skills
Digital inequalities and reentry
Existing digital skills programs for returning citizens
Evidence from the field
Pre-crime society, dataveillance, surveillance and reentry
Pre-crime and dataveillance
The mass surveillance state and hyper-securitization
Conclusion
References
Part V Globalizing Surveillance, Human Rights and (In)Security
17 Surveilling the Civil Death of the Criminal Class
Introduction
Felon disenfranchisement
Felon disenfranchisement as pre-crime control
Disenfranchisement as civil death
The power of voter fraud and electoral illegitimacy
Ubiquitous marginalizing surveillance
The vagaries of exclusion
Conclusion
References
18 Big Data, Cyber Security and Liberty
Introduction
Benefits and challenges of big data
Benefits of big data
Challenges with big data
Big data and industry
Big data and criminological inquiry
Cybersecurity risks and implications of big data
Conclusion
Note
References
19 Drone Justice: Kill, Surveil, Govern
Introduction
A short history of drones
‘Power without vulnerability’: drones, the re-ordering of global power and international justice
‘We kill people based on metadata’:7 biopolitical drones
Pandemic drones
Conclusion
Notes
References
20 Global Surveillance: The Emerging Role of Radio Frequency Identification (RFID) Technology
Introduction
Overview of RFID’s historical emergence and system components
Practical applications
Manufacturing and supply chain management
Healthcare systems and the pharmaceutical industry
Transportation
School securitization
Cashless electronic payment
Criminal justice applications
Human implantation
Theoretical analysis
Conclusion
References
Afterword: ‘Pre-Crime’ Technologies and the Myth of Race Neutrality
Neutrality logics
Fusion of risk-focused penality, neo-conservatism and neoliberal logics
Labeling and self-fulfilling prophesies
Notes
References
Index
Back Cover

Citation preview

THE PRE- CRIME SOCIET Y CRI M E , CU LTU RE , AND CO NTROL IN THE U LTR A MODERN AGE E D ITE D BY B RUCE A . A RRIGO A N D B RIA N G . S E LLE R S FO RE WO RD BY IAN WARREN

THE PRE-​CRIME SOCIETY Crime, Culture and Control in the Ultramodern Age Edited by Bruce A. Arrigo and Brian G. Sellers With a Foreword by Ian Warren

First published in Great Britain in 2021 by Bristol University Press 1–​9 Old Park Hill Bristol BS2 8BB UK t: +44 (0)117 954 5940 www.bristoluniversitypress.co.uk © Bristol University Press 2021 British Library Cataloguing in Publication Data A catalogue record for this book is available from the British Library ISBN 978-​1-​5292-​0525-​1 hardcover ISBN 978-​1-​5292-​0527-​5 ePub ISBN 978-​1-​5292-​0526-​8 ePdf The right of Bruce A. Arrigo and Brian G. Sellers to be identified as editors of this work has been asserted by them in accordance with the Copyright, Designs and Patents Act 1988. All rights reserved: no part of this publication may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, electronic, mechanical, photocopying, recording, or otherwise without the prior permission of Bristol University Press. Every reasonable effort has been made to obtain permission to reproduce copyrighted material. If, however, anyone knows of an oversight, please contact the publisher. The statements and opinions contained within this publication are solely those of the editors and contributors and not of the University of Bristol or Bristol University Press. The University of Bristol and Bristol University Press disclaim responsibility for any injury to persons or property resulting from any material published in this publication. Bristol University Press works to counter discrimination on grounds of gender, race, disability, age and sexuality. Cover design by Liam Roberts Front cover: image Alamy/​Brain light Bristol University Press uses environmentally responsible print partners Printed in and bound in Great Britain by CPI Group (UK) Ltd, Croydon, CR0 4YY

For my wife, Kathy, who shows me each day why being in love is so magical.—​Bruce A. Arrigo For my daughter, Addison, who remarkably demonstrates to me daily that kindness, courage and hope are what is needed to overcome hate, fear and despair. Being your father is the most joyful, influential and meaningful part of my life. Please continue to stand strong, voice your perspective and reach for the stars! May your life be filled with compassion, adventure and happiness, and always remember that your Papa loves you!—​Brian G. Sellers

Contents Notes on Contributors Foreword by Ian Warren

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Introduction: The Ultramodern Age of Criminology, Control Societies and ‘Dividual’ Justice Policy Bruce A. Arrigo, Brian G. Sellers and Faith Butta PART I Theories, Theorists and Theoretical Perspectives 1 The ‘Risk’ Society Thesis and the Culture(s) of Crime Control Bruce A. Arrigo and Brian G. Sellers 2 The Security Society: On Power, Surveillance and Punishments Marc Schuilenburg 3 Pre-​Crime and the ‘Control Society’: Mass Preventive Justice and the Jurisprudence of Safety Pat O’Malley and Gavin J.D. Smith 4 The Negation of Innocence: Terrorism and the State of Exception David Polizzi PART II Institutions, Organizations and the Surveillance Industrial Complex 5 Visions of the Pre-​Criminal Student: Reimagining School Digital Surveillance Andrew Hope 6 Commodification of Suffering Matthew Draper, Brett Breton and Lisa Petot 7 Surveillance, Substance Misuse and the Drug Use Industry Aaron Pycroft

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The Politics of Actuarial Justice and Risk Assessment Andrew Day and Armon Tamatea

PART III Dataveillance, Governance and Policing Control Societies 9 Cameras and Police Dataveillance: A New Era in Policing Janne E. Gaub and Marthinus C. Koen 10 Theorizing Surveillance in the Pre-​Crime Society Michael McCahill 11 Dataveillance and the Dividuated Self: The Everyday Digital Surveillance of Young People Clare Southerton and Emmeline Taylor 12 The Bad Guys Are Everywhere; the Good Guys Are Somewhere John E. Deukmedjian PART IV Systems of Surveillance, Discipline and the New Penology 13 Supermax Prison Isolation in Pre-​Crime Society Terry A. Kupers 14 Mass Monitoring: The Role of Big Data in Tracking Individuals Convicted of Sex Crimes Kristen M. Budd and Christina Mancini 15 Towards Predictivity? Immediacy and Imminence in the Electronic Monitoring of Offenders Mike Nellis 16 The Digital Technologies of Rehabilitation and Reentry Bianca C. Reisdorf and Julia R. DeCook PART V Globalizing Surveillance, Human Rights and (In)Security 17 Surveilling the Civil Death of the Criminal Class Natalie Delia Deckard 18 Big Data, Cyber Security and Liberty Jin Ree Lee and Thomas J. Holt 19 Drone Justice: Kill, Surveil, Govern Birgit Schippers

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Contents

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Global Surveillance: The Emerging Role of Radio Frequency Identification (RFID) Technology Brian G. Sellers

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Afterword: ‘Pre-​Crime’ Technologies and the Myth of Race Neutrality Pamela Ugwudike

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Index

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Notes on Contributors Bruce A. Arrigo, Ph.D., is Professor of Criminology, Law and Society,

and of Public Policy within the Department of Criminal Justice and Criminology at the University of North Carolina at Charlotte. He holds secondary appointments in the Department of Public Health Sciences, the Department of Psychological Science and the School of Data Science. Dr Arrigo—​often with his many students and colleagues—​has produced more than 225 scholarly publications. He recently served as general editor for The SAGE Encyclopedia of Surveillance, Security, and Privacy (2018). Dr Arrigo is a recipient of the Lifetime Achievement Award from the American Society of Criminology (Division on Critical Criminology and Social Justice) and from the Society for the Study of Social Problems (Division on Crime and Juvenile Delinquency). Brett Breton, Ph.D., is Associate Professor of Psychology at Utah

Valley University. He holds a Ph.D. in theoretical, philosophical and social psychology, as well as a dual master’s degree in mental health counseling and school psychology. His areas of specialty include social psychology, motivation and emotion, psycho-​educational assessment, cross-​cultural psychology, interpersonal relations and theoretical and philosophical psychology. He has held a separate appointment as Director of Multicultural Student Services. Kristen M. Budd, Ph.D., is Associate Professor of Sociology and

Criminology at Miami University, Oxford, OH. Her research focuses on interpersonal violence, law and policy, including how they intersect with perpetrator and victim sociodemographic characteristics. Currently, she researches patterns and predictors of offending behavior in relation to sexual assault, public perceptions of criminal behavior, law, criminal justice policy and practice, and social and legal responses to interpersonal violence and other social problems. She is a recipient of the Scholarly Achievement Award for research from the Society for the Study of Social Problems, Crime and Juvenile Delinquency Division.

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Notes on Contributors

Faith Butta, M.P.A., is a Ph.D. candidate in public policy at the

University of North Carolina at Charlotte, studying social inequality specifically as it relates to homelessness service provision by nonprofit organizations and local government. Faith earned her M.P.A. from the University of North Carolina at Charlotte with a concentration in nonprofit management. Andrew Day, D.Clin.Psy., is Enterprise Professor in Criminology

in the School of Social and Political Sciences at the University of Melbourne in Australia and holds an adjunct appointment at James Cook University, Australia. He is a registered forensic and clinical psychologist and a fellow of the Australian Psychological Society. Current interests include developing interventions to prevent prison violence as part of the MBIE-​funded Nga Tūmanakotanga project in New Zealand. Natalie Delia Deckard, Ph.D., is Assistant Professor of Criminology

within the Department of Sociology, Anthropology, and Criminology at the University of Windsor, Ontario, Canada. Dr Delia Deckard has published work in Citizenship Studies, The Sociological Quarterly, Latino Studies, The Journal of African American Studies, Women and Criminal Justice and other distinguished academic journals. Her work in Critical Criminology, Race and Ethnicity, Migration, and Feminist Criminology has been supported by The Russell Sage Foundation and the National Science Foundation. Dr Delia Deckard sits on the Board of Directors for the Windsor chapter of the John Howard Society, the oldest organization for prison reform in Canada. Julia R. DeCook, Ph.D., is Assistant Professor of Advocacy and Social

Change in the School of Communication at Loyola University Chicago. In addition, she is also a fellow with the Institute for Research on Male Supremacism and a fellow and research unit head at the Centre for the Analysis of the Radical Right. DeCook has published articles about the nature of online extremist groups’ visual discourse, connections between white supremacy and men’s rights, and the nature of trolling in politics. Her research focuses mostly on the nature of platforms and online infrastructure in sustaining extremist movements, but she has also done research about the nature of the digital divide among returning citizens and elderly persons, and the implications of lack of knowledge of digital technologies for these vulnerable populations.

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John E. Deukmedjian, Ph.D., is Associate Professor of Criminology

within the Department of Sociology, Anthropology and Criminology, and a research associate within the Cross-​Border Institute at the University of Windsor, Ontario, Canada. Dr Deukmedjian has produced key publications in the areas of surveillance, national security and policing, including ‘Making Sense of Neoliberal Securitization in Urban Policing and Surveillance’, (2013, Canadian Review of Sociology, 50(1), 52–​73) and ‘Securitization, Infopolitics and the Suppression of Liberty’, (2014, Gill, M. ed. The Handbook of Security, 2nd edition. UK: Palgrave Macmillan). Matthew Draper, Ph.D., is Professor of Psychology within the

Department of Behavioral Sciences at Utah Valley University. He also works in the evenings as clinical director of an intensive outpatient treatment center. He produced more than 100 scholarly publications and presentations, as well as dozens of clinical trainings for therapists in the region. Academically, he focuses on moral issues in psychotherapy, particularly clinical forensics, as well as scaffolding the next generation of scholars. He has received numerous teaching awards for his efforts. Clinically, he focuses on psychotherapy of addictions and for those coping with the criminal justice system. Janne E. Gaub, Ph.D., is Assistant Professor in the Department of

Criminal Justice and Criminology at the University of North Carolina at Charlotte. She received her Ph.D. in criminology and criminal justice from Arizona State University in 2015. Her research centers on policing, primarily addressing body-​worn cameras (BWCs), specialty units and use of force. Her work has appeared in outlets including Criminology, Criminology & Public Policy, Journal of Experimental Criminology and Police Quarterly. Dr Gaub is also a subject matter expert and training and technical assistance lead for the Bureau of Justice Assistance Body-​Worn Camera Policy and Implementation Program. Thomas J. Holt, Ph.D., is Director and Professor in the School of

Criminal Justice at Michigan State University. His research focuses on computer hacking, malware and the role of the Internet in facilitating all manner of crime and deviance. His work has been published in various journals including Crime and Delinquency, Deviant Behavior, the Journal of Criminal Justice and Youth and Society. Andrew Hope, Ph.D., is Professor of Sociology and Dean of the

School of Arts at Federation University Australia. He is also a

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Notes on Contributors

fellow of digital education research at Monash University. He has published widely and has an international research profile in two main areas: young people’s risky online activities, as well as the use of school surveillance technologies. Recently, these interests have grown into a focus on social justice issues relating to youth, pre-​crime and problematic antiterrorism strategies. Marthinus C. Koen, Ph.D., is Assistant Professor of Criminal Justice

within the Criminal Justice Department at the State University of New York Oswego (SUNY Oswego) where he teaches classes concerning policing, research methods and criminal justice organizations. His research interests lie in police organizational change, police technology and criminal justice education. Dr Koen’s most recent published works have focused on the impacts of body-​worn cameras on police organizational structures, practices, accountability and technological frames. Marthinus is also an editorial board member of the American Journal of Qualitative Research. Terry A. Kupers, M.D., M.S.P., is Institute Professor Emeritus at

The Wright Institute and Distinguished Life Fellow of the American Psychiatric Association. He provides expert testimony in class action litigation regarding the psychological effects of prison conditions, including isolated confinement, the quality of correctional mental health care and the effects of sexual abuse in correctional settings. He is author of Solitary: The Inside Story of Supermax Isolation and How We Can Abolish It (University of California Press, 2017) and Prison Madness: The Mental Health Crisis Behind Bars and What We Must Do About It (1999). He is co-​editor of Prison Masculinities (2002) and contributing editor of Correctional Mental Health Report. He received the 2005 Exemplary Psychiatrist Award and 2020 Gloria Huntley Award from the National Alliance on Mental Illness (NAMI). Jin Ree Lee, M.A., is a Ph.D. student in the School of Criminal Justice

at Michigan State University. His research interests are in cybercrime, online interpersonal violence, cybersecurity, cyberpsychology, computer-​mediated communications and big data. Jin is a member of Michigan State University’s International Interdisciplinary Research Consortium on Cybercrime (IIRCC). His recent work has appeared in Crime & Delinquency; Journal of Interpersonal Violence; Policing: An International Journal; International Journal of Offender Therapy and Comparative Criminology; Terrorism and Political Violence; Archives of Sexual Behavior; Frontiers in Psychology; International Criminal Justice

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Review; Computers in Human Behavior; and Information, Communication & Society. Christina Mancini, Ph.D., is Associate Professor in the Wilder

School of Government and Public Affairs at Virginia Commonwealth University. Dr Mancini’s research seeks to improve public safety by examining the efficacy of societal responses to offending. She is the author of two books and over 35 peer-​reviewed articles, which appear in a variety of law and policy journals covering these topics. Dr Mancini holds several editorial advisory appointments and is a co-​founder of the nonprofit organization, Sexual Offense Policy Research (SOPR) workgroup, which seeks to inform the public and policymakers about best practices to prevent sexual violence. Michael McCahill, Ph.D., is Senior Lecturer in Criminology within

the Department of Criminology and Sociology at the University of Hull, UK. His research focuses on the social impact of ‘new surveillance’ technologies in the context of policing and criminal justice. He has published widely on the topic of surveillance, including two prize-​ winning monographs. These are The Surveillance Web (2002), winner of the 2003 British Society of Criminology Book Prize, and Surveillance, Capital and Resistance (2014), joint-​winner of the 2015 Surveillance Studies Network Book Prize. Mike Nellis, Ph.D., is Emeritus Professor of Criminal and Community

Justice in the Law School, University of Strathclyde, Glasgow, UK. He has written widely on probation services and electronic monitoring (EM), including Electronically Monitored Punishment: International and Critical Perspectives, (2013) co-​edited with Kristel Beyens and Dan Kaminski. Though increasingly critical of EM, he has served on two government working parties on EM in Britain, was long associated with the Council of Europe’s (European) EM conferences and has co-​ advised the Council of Europe on the ethics of EM. He participated in the Pew Centre’s EM Advisory Group in Washington, US in 2018, and was briefly international editor for the Journal of Offender Monitoring. Pat O’Malley, Ph.D., is Distinguished Honorary Professor in the

Research School of the Social Sciences, Australian National University and Adjunct Research Professor in Sociology at Carleton University, Canada. Previously he was Professorial Research Fellow in Law at the University of Sydney and a Canada Research Chair. He was elected a fellow of the Academy of Social Sciences in Australia, and

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Notes on Contributors

is the recipient of various awards including the American Society of Criminology Thorsten Sellin and Sheldon and Eleanor Glueck Award, and the British Journal of Criminology Radzinowicz Memorial Prize. Lisa Petot is an adjunct instructor in the Behavioral Science

Department at Utah Valley University. Her research expertise lies in the areas of clinical mental health and public health. David Polizzi, Ph.D., is Professor in the School of Criminology and

Security Studies at Indiana State University and is editor of the Journal of Theoretical & Philosophical Criminology. He has authored and edited a number of texts including A Philosophy of the Social Construction of Crime; Solitary Confinement: Lived Experience & Ethical Implications; A Phenomenological Hermeneutic of Antiblack Racism in the Autobiography of Malcolm X and the edited collection titled Jack Katz: Seduction, The Street, and Emotion, as well as numerous journal articles and book chapters. He is currently working on a book-​length manuscript focused on the phenomenology of terrorism. Aaron Pycroft, Ph.D., is Reader in Criminal Justice and Social

Complexity, in the Institute of Criminal Justice Studies at the University of Portsmouth, UK. He has extensive practice experience in the criminal justice, health and welfare sectors in working with substance misuse. He has published widely and his academic research focuses on developing new theoretical resources grounded in an application of phenomenology and complexity theory to the practice of probation officers and social workers. His current focus is on the dynamic nature of forgiveness in justice and the relationships between criminology, philosophy and theology to inform therapeutic relationships. Bianca C. Reisdor f, D.Phil., is Assistant Professor in the

Department of Communication Studies at the University of North Carolina at Charlotte. Her work focuses on the intersection of social inequalities and digital media and the Internet, with a focus on digital inequalities among marginalized populations. In her recent research, Dr Reisdorf has been focusing on Internet access in correctional settings, and how returning citizens navigate a technology-​dependent world after release. In addition, she is interested in proxy Internet use as well as how Internet users look for and evaluate information from various media sources.

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Birgit Schippers, Ph.D., is Senior Lecturer in Politics at St Mary’s

University College Belfast and a visiting research fellow at the Senator George J. Mitchell Institute for Global Peace, Security and Justice at Queen’s University Belfast. Her research examines the ethics and politics of new technologies with a particular focus on artificial intelligence and biometric technologies. Dr Schippers is the author of Julia Kristeva and Feminist Thought (EUP, 2011) and The Political Philosophy of Judith Butler (Routledge, 2014), and editor of Critical Perspectives on Human Rights (RLI, 2019) and The Routledge Handbook to Rethinking Ethics in International Relations (2020). Marc Schuilenburg, Ph.D., is Assistant Professor at the Department

of Criminal Law and Criminology, VU University Amsterdam. His research focuses on politics and crime control, governance of security, social order, theoretical criminology, popular culture and French philosophy. His recent books include Hysteria: Crime, Media, and Politics (Routledge, 2021) and The Securitization of Society: Crime, Risk, and Social Order (NYU-​Press, 2015). His website is: www. marcschuilenburg.nl. Brian G. Sellers, Ph.D., is Associate Professor of Criminology at

Eastern Michigan University. His research focuses on juvenile justice policy, juvenile homicide, justice studies, restorative justice, school violence, psychology and law, and surveillance studies. He is co-​author of Ethics of Total Confinement: A Critique of Madness, Citizenship, and Social Justice (Oxford University Press). His work has appeared in Criminal Justice & Behavior, Behavioral Sciences & the Law, Contemporary Justice Review, Youth Violence & Juvenile Justice, Feminist Criminology, and Children and Youth Services Review. Dr Sellers is a trained civil court mediator, victim-​offender conference facilitator and peacemaking circle keeper. Gavin J.D. Smith, M.A., M.Res., Ph.D. is Associate Professor in

Sociology at the Australian National University. His current research explores the social impacts and implications of the use of facial recognition systems in public space. He is specifically interested in the biopolitics of recognition, where the face becomes akin to a trackable and traceable ID, and is made the subject of new forms of bio-​power. Smith has published extensively on the biopolitics of surveillance, and his ideas appear in leading journals such as Body & Society, Big Data & Society, Critical Public Health, Theoretical Criminology, Surveillance & Society and The British Journal of Criminology. His first book, Opening

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Notes on Contributors

the Black Box: The Work of Watching (Routledge, 2015) comprised an ethnographic analysis of the sensory and affective culture of CCTV camera operation. He was previously co-​editor of the international journal, Surveillance & Society. Clare Southerton, Ph.D., is Postdoctoral Research Fellow in the

Vitalities Lab, Social Policy Research Centre and Centre for Social Research in Health, UNSW Sydney. Her published research has explored the intersections of social media, privacy, surveillance and sexuality. Her current research projects are focused on how intimacy and collective affects are cultivated on platforms and with devices, and potentials in these spaces for health and sexuality education. Her work has been published in New Media & Society, Social Media + Society and Girlhood Studies. Armon Tamatea, Ph.D., is a clinical psychologist who has served

as a psychologist and senior research advisor for the New Zealand Department of Corrections before being appointed as Senior Lecturer in Psychology at the University of Waikato where he is involved in clinical psychology training. He has worked extensively in the assessment and treatment of men and young people with violent and sexual offense histories, and has contributed to the design and implementation of an experimental prison-​based violence prevention program for high-​r isk offenders diagnosed with psychopathy. Armon’s research interests include prison violence, psychopathy, New Zealand gang communities and exploring culturally-​informed approaches to offender management. He is also the President of the Australian & New Zealand Association for the Treatment of Sexual Abuse (ANZATSA). In addition to providing clinical and academic advice to government and non-​government organizations, Armon currently divides his professional time between teaching, research, supervision and clinical practice in the criminal justice arena. Emmeline Taylor, Ph.D., is Associate Professor in Criminology at

City, University of London, UK. Her surveillance related interests focus on young people and schools, as well as new police technologies. Dr Taylor has published extensively across these topics, including the books: Surveillance Schools (Palgrave, 2013), Surveillance Futures (Routledge, 2017, with Tonya Rooney) and The Palgrave International Handbook of School Discipline, Surveillance, and Social Control (Palgrave, 2018, with Jo Deakin and A. Kupchik). She is Co-​Director of the

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Surveillance Studies Network (SSN) and a member of the editorial board for the Surveillance & Society journal. Pamela Ugwudike, Ph.D., is Associate Professor of Criminology

at the University of Southampton, UK, a Fellow of the Alan Turing Institute, and from 2021 onwards, Editor-​in-​Chief of Criminology and Criminal Justice journal, which is the flagship journal of the British Society of Criminology. Pamela is currently leading multidisciplinary research projects that are exploring Artificial Intelligence (AI) ethics and governance, with a focus on the data-​driven algorithms that inform decision-​making in justice systems. She sits on a number of advisory boards including the advisory group for Ada Lovelace Institute’s legal review of the governance of biometric data in the UK. Ian Warren, Ph.D. is Senior Lecturer in Criminology at Deakin

University, Geelong, Australia and a member of the Alfred Deakin Institute for Citizenship and Globalisation. He has written widely in the areas of transnational policing and surveillance, comparative criminal justice administration and domestic security. He is co-​author of Global Criminology (Thomson Reuters, 2015) and has undertaken various research projects examining emerging crime prevention technologies, with a particular emphasis on the need for more stringent regulation and accountability.

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Foreword Ian Warren

The pre-​crime society is expanding. It relies on a growing range of routine and highly specialist surveillance technologies (see McCulloch & Wilson, 2016) to represent a core characteristic of our ultramodern era (Arrigo, Sellers & Sostakas, 2020). This volume is both a significant and sobering resource on the implications of these developments in a control society (Deleuze, 1992) constituted by an increasingly expanding web of criminal justice agencies, pre-​emptive laws and corrective interventions that are enacted through ubiquitous and readily accessible data about people. Underpinning these developments is an equally intricate process of scientific reasoning that has informed various modes of disciplinary and biopolitical governance. Technologies have historically classified information (Hacking, 1991), and people (see McCahill in this volume), to pursue both beneficial and highly problematic social policies. In the ultramodern pre-​crime society, these patterns of classification are magnified by the speed and immediacy of data-​driven modes of identifying and preventing crime and recidivism. Formal authorities view people not as individuals but through their digitized informational personas (Koopman, 2019, pp. 17–​19). As dividuals (Deleuze, 1992, p. 5), subjects are composed through ‘(l)ittle pieces of past patterns’ of behavior or conduct, which are simultaneously used to ‘train’ the algorithms that make the formal decisions about their future (Amoore, 2020, p. 54). As people often voluntarily contribute information that is used to generate more intricate data doubles (Haggerty & Ericson, 2000), there is a greater desire for governments and private companies to exploit this information to demarcate law-​abiding people from convicted offenders, and predict who might be criminal at some indeterminate point in the future through increasingly nebulous risk and pre-​crime classifications (McCulloch & Wilson, 2016).

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Bruce A. Arrigo, Brian G. Sellers and each contributor to this volume are to be commended for providing detailed yet accessible explanations about how these processes are currently evolving. The chapters in this volume offer a range of theoretically informed critiques pointing to the limits of these developments in a range of criminal justice, law enforcement and penal contexts. The Pre-​Crime Society: Crime, Culture and Control in the Ultramodern Age covers an extensive scope of issues documented by respected researchers and theorists in the fields of criminology, surveillance studies and penology. Despite its breadth and theoretical sophistication, this important text is highly accessible to newcomers to these fields and provides grounding for further theoretical and empirical developments that interrogate the problem of pre-​crime in an age of ubiquitous digital surveillance. This foreword offers a few avenues to contemplate in this regard. Julie E. Cohen (2019, p. 2) presciently indicates the ‘ownership of information-​age resources and accountability for information-​age harms have become pervasive sources of conflict’ that are aligned with a new era of domestic and transnational laws, enforcement processes, economic developments and conceptions of rights. In extending the surveillance capitalism thesis (Zuboff, 2019), the transformative socio-​ technical importance of ‘information capitalism’ under a neoliberal governmentality is characterized by ‘processes of private economic ordering … [that] reshape government processes in their image’ (Cohen, 2019, pp. 6–​7). The ensuing injection of ‘a competitive and capitalist ethos’ (Cohen, 2019, p. 7) into the functioning of law provides enormous impetus for governments and law enforcement agencies to deploy an increasing array of predictive analytic tools (Ferguson, 2017). An ambitious quest to eliminate crime through the automated analysis and identification of correlations from masses of data increasingly uses algorithms designed to identify and pre-​empt ‘risks’ that are considered to undermine the security of the state, the economic order, or other people. This is the essence of the pre-​crime society (Zedner, 2007; McCulloch & Wilson, 2016). When criminal law is informed by a precautionary logic, more intrusive and punitive interventions aimed at enhancing security that also undermine civil liberties are enacted (Jochelson et al, 2017, p. 11). When sign-​optics that incorporate panoptic, synoptic and banoptic controls (Arrigo, Sellers & Sostakas, 2020; see Arrigo & Sellers and Schuilenberg in this volume) are tethered to administrative logics of risk-​based and precautionary control, an increasingly diverse range of human activities, geographic movements and behaviors detected through sensing, scanning, tracing and mapping technologies can

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be analyzed and interpreted almost instantaneously. The seemingly limitless scale, speed and accessibility of AI and automated data sorting technologies operate on the basis that ‘correlation is enough’ (Amoore, 2020, p. 44). As the manual surveillance practices of disciplinary societies (Galič, Timan & Koops, 2017) enter warp speed, a growing array of pre-​crime and shadow carceral processes (Beckett & Murakawa, 2012; Carrington et al, 2018, p. 112) constitute the base standard for control in ultramodern society. Many of the devices we voluntarily purchase to make life easier, such as ‘the ubiquitous “smart phone” ’, are now entwined in this multifaceted social control ecosystem (Skeptycki, 2020, p. 168; Bowling, Reiner & Sheptycki, 2019, pp. 161–​2), where mass dataveillance and social sorting (Lyon, 2003) occur through complex automated processes developed and managed by an array of private and state actors. These processes are increasingly hidden from public view, yet aim to make individual actions more visible to the gaze of authority, while fostering the images of perfect prevention and perfect enforcement of law (Mulligan, 2008). The chapters in this volume demonstrate how these developments have become embedded in many routine regulatory and social contexts. They range from the mass surveillance processes that enable the automated tracking of vehicles on major roads and streamlined enforcement of traffic violations (O’Malley and Smith), to the intensification of visual, biometric, spatial and algorithmic practices targeting the activities of young people (Southerton and Taylor). They also include important critiques of how processes of virtualization embed injustices by negating or eliminating the prospect that targeted individuals and populations can be conceived as innocent (Polizzi). Multiple forms of continuous surveillance are now built into the urban infrastructure to produce ‘spaces of security’ where the precise sources of legal authority are often difficult to trace (Schuilenburg). Indeed, as society moves towards ‘total information awareness’ (Deukmedjian), the global and transnational reach of these processes of data collection, sharing, analysis and pre-​emptive regulation seem to confound any attempts at meaningful regulatory control. Many developments described throughout this volume have become further normalized during the global COVID-​19 pandemic. Contact tracing apps are widely advocated for promoting responsible citizenship, by enabling a mobile phone user’s geographic movements to be monitored and matched with the movements of other responsible citizens who have had their positive diagnostic records entered into these data systems. In some jurisdictions, these surveillance measures are supplemented by area bans, curfews and lockdowns, as well as

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hefty fines and potential imprisonment terms for detected breaches. Military and private security personnel have also been deployed to assist with pandemic enforcement at shopping malls, private homes or designated checkpoints (Mclean & Huf, 2020; Sheptycki, 2020). While these measures are considered necessary to prevent the spread of an invisible enemy, the criminal enforcement consequences of these developments are more questionable. This matrix of developments is open to an array of interpretations that build on established techno-​social (Frischman & Selinger, 2018) and digital criminological (Powell, Stratton & Cameron, 2017) perspectives. For example, Southern Criminology specifically interrogates the transnational elements of criminological knowledge production and circulation (Carrington et al, 2018, p. 188). By questioning ‘power relations embedded in the hierarchical production of criminological knowledge’ (Carrington, Hogg & Sozzo, 2016, p. 2), Southern Criminology offers a pertinent site for challenging the risk-​based precautionary logic underpinning many pre-​crime and surveillance measures, which reflect the ‘metropolitan thinking’ that informs crime prevention strategies emanating primarily from the United States. These developments rely on surveillance to identify, and punitive laws to prevent, a variety of crimes that range in seriousness, by invoking a ‘linear, panoramic, and unifying standpoint in which space, and geo-​ political and social difference, are erased in the imperial narrative of time’ (Carrington et al, 2018, p. 4). As Connell (2007, p. 241) points out, the ‘metropole-​apparatus’, or the ‘capacity to act as metropole’, is expanding globally and evolving in ways that are largely autonomous from the social order and institutions of developed nations from which these processes originate. The underlying knowledges associated with governing through pre-​crime legitimize law enforcement access to swathes of digital information, while undermining the autonomy and local dynamics of decision-​making in peripheral societies. This means alternative views that challenge the theoretical and empirical truths associated with securitization, risk, precaution and pre-​emption are easy to dismiss from the calculus that validates a sign-​optic governmentality characterized by ubiquitous surveillance, control and exclusion (see Arrigo and Sellers in this volume). Focusing on the transfer of formal crime control and state policies between the North and South can aid the ‘Southernizing of knowledge’, by establishing a political project that challenges colonial and neo-​colonial relations (Carrington & Hogg, 2017), as well as major shifts in the nature of empire (Carrington et al, 2018, pp. 188–​90). These shifts include those associated with the control of economic

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and legal power that are linked to the development, marketing and deployment of digital and surveillance technologies (Zuboff, 2019; Cartwright, 2020), as well as the dynamics of information capitalism that promote the identification and control of ‘at-​risk’ behaviors associated with pre-​crime. A pertinent example that questions these processes is Day and Tamatea’s insight in this volume, which outlines how a Southern epistemology recognizes the failure of actuarial and algorithmic risk assessment technologies to incorporate knowledge about the potential positive impacts of culture and relationships in the correctional process. While Southern Criminology ‘can and will be different things to different people’ (Brown, 2018, p. 101), this divergence is necessary to recognize given the diffuse transnational reach of major pre-​crime and surveillance developments. Additional sites of potential critique include numerous questions relating to the remoteness and lack of transparency associated with much pre-​crime decision-​making, which is primarily based on discrete fragments of information about ‘dividual’ selves (see McCahill and Southerton & Taylor in this volume) and technical processes that detect minor correlations in massive data sets that are impossible for humans to understand or explain (Amoore, 2020). At the same time, a Southern perspective can be useful in identifying ‘the potentially selective, biased, prejudicial or counterintuitive impacts’ (Kennedy & Warren, 2018, p. 102) of the laws, criminal justice policies and criminological theories that sanction these processes. A pertinent illustration involves attempts by United States authorities to accommodate the rapid nature of transnational data flows used in many pre-​crime initiatives and formal criminal investigations. Digital communications invariably move rapidly beyond the geographic boundaries that constitute criminal jurisdiction, which also place legal limits on the scope and reach of police surveillance (Mann & Daly, 2020). This fact about transnational data movements generates a paradox about the appropriate regulatory limits that should attach to police access to, and uses of, electronic data, which is complicated by the corporate imperatives underlying the development and use of surveillance technologies for law enforcement purposes (Zuboff, 2019). The capacity for police agencies to use malware or network investigative techniques to remotely access a device’s location, operating system, camera and its user’s keystrokes, is an important example of a surveillance technology that transcends characterization through jurisdictional principles based on physical geography (Warren, Mann & Molnar, 2020).

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United States law enforcement agencies and courts have attempted to reconcile this jurisdictional paradox by actively subverting the weak transnational regulatory structure for offshore evidence exchange. This is justified by the view that any data in the control of a United States technology company should be open for scrutiny by United States law enforcement agents regardless of its geographic location (Warren, 2015). This framing of transnational data transmission and storage as a question of ownership and control has enormous implications in a pre-​crime society. As the majority of technology companies in the English-​speaking world are based in the United States, the ownership and control rule recalibrates the legal scope of online surveillance to allow United States law enforcement almost unlimited access to global digital communications for a range of investigative and intelligence purposes. A Southern Criminological focus reveals why this tethering of United States economic, technological and criminal enforcement power contributes to a highly problematic form of legal imperialism that directly influences the justice systems of many other nations, regardless of their classification as Northern or Southern (Mann & Warren, 2018; Brown, 2018). Domestic legislative reforms in the United States have taken this development much further. A new era of transnational data exchange between law enforcement agencies and technology companies has been fostered through the legal acceptance of corporate data control as the basis for expanding police jurisdiction. This process actively seeks to remove the complex layers of judicial and executive review associated with mutual legal assistance requests that traditionally facilitated the transnational exchange of evidence in criminal investigations. The Clarifying Lawful Overseas Use of Data (CLOUD) Act is a domestic law enabling the United States to negotiate executive agreements with preferred countries, including the United Kingdom and Australia. These agreements enable national law enforcement agencies access to data about suspected individuals through direct requests to technology companies, rather than the relevant administrative arms of government (Mulligan, 2018). While designed to eliminate the cumbersome, technical and lengthy processes of judicial and executive review of mutual legal assistance requests that can delay access to offshore data, these United States provisions have extensive extraterritorial reach, and even apply when ‘foreign governments seek data of their own citizens and residents pursuant to their own legal authorities’ (Daskal, 2019, p. 1039). An executive agreement will be made if the partner jurisdiction has or proposes reciprocal laws that meet United States evidentiary and civil liberties standards (Mulligan, 2018). However,

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United States legal scholarship has also colonized the knowledge underpinning the necessity for these measures (Carrington et al, 2018, pp. 1–​2). As such, the CLOUD Act is considered beneficial because it establishes ‘baseline substantive and procedural rules’ (Daskal, 2019, p. 1048) in a context where pre-​existing transnational data exchange processes are universally considered inadequate. Worryingly, that baseline is set purely on United States standards. ‘If every country around the globe adopted the provisions on judicial review; targeted collection; speech protections; limitations on use, dissemination, and retention; and the accountability mechanism; the result would be a net gain in privacy and civil liberties’ (Daskal, 2019, p. 1048). A Southern emphasis challenges the emphatic and imperial nature of such assertions that favor United States theoretical, procedural, legal and surveillance developments in the policing field more generally (Mann & Warren, 2018). At the same time, it questions the corporate influence in promoting a pre-​crime society through the development and commercial marketing of data-​driven technologies that fuel problematic forms of informational capitalism, formal decision-​making and governmental policy that are widely documented throughout this volume. As such, each chapter provides a useful platform for building a more rigorous and politically engaged critique of recent advances in pre-​crime law enforcement and the use of technology for surveillance purposes that is shaped by a neoliberal governmentality and a seemingly all-​pervasive crisis in contemporary security (McCulloch & Wilson, 2016). The template for critique established in this important work offers an opportunity to contemplate why the various forms of social sorting that are normalized in pre-​crime society are even necessary. This means drawing on alternate knowledges that show why it is problematic to define some people as greater than or less than others (Yunkapoorta, 2019, p. 30), despite the embeddedness of these processes in many technological and justice processes. It means incorporating understandings of spiritual, emotional, physical and material restoration (Tuhiwai Smith, 2012, p. 153), as well as other cultural facets of respect and connectedness, that enable subaltern voices to enter meaningful political dialogues for addressing social problems of common or universal concern. It means extending understandings of corporate harm and social responsibility to encompass the human impacts of surveillance and data capitalism, while providing opportunities for meaningful input into the development of substantial regulatory reforms, rather than unenforceable voluntary codes of practice (Shamir, 2005, p. 102). It also means being open to ‘free-​ranging patterns’ of thought about crime, harm and justice, and recognizing that some

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cultures and schools of thought ‘don’t have a word for non-​linear … because nobody would consider travelling, thinking or talking in a straight line in the first place’ (Yunkapoorta, 2019, p. 21). References Amoore, L. (2020). Cloud Ethics: Algorithms and the Attributes of Ourselves and Others. Durham, NC: Duke University Press. Arrigo, B.A., Sellers, B.G. & Sostakas, J. (2020). Pre-​crime, post-​ criminology and the captivity of ultramodern desire. International Journal for the Semiotics of Law 33 (2): 497–​514. Beckett, K. & Murakawa, N. (2012). Mapping the shadow carceral state: Toward an institutionally capacious approach to punishment. Theoretical Criminology 16 (2): 221–​44. Bowling, B., Reiner, R. & Sheptycki, J. (2019). The Politics of the Police (5th ed.). Oxford, UK: Oxford University Press. Brown, M. (2018). Southern criminology in the post-​colony: More than a ‘derivative discourse’? In K. Carrington, R. Hogg, J. Scott & M. Sozzo (eds.) The Palgrave Handbook of Criminology and the Global South. Cham, CH: Palgrave Macmillan (pp. 83–​104). Carrington, K. & Hogg, R. (2017). Deconstructing criminology’s origin stories. Asian Criminology 12: 181–​97. Carrington, K., Hogg, R. & Sozzo, M. (2016). Southern criminology. British Journal of Criminology 56 (1): 1–​20. Carrington, K., Hogg, R., Scott, J., Sozzo, M. & Walters, R. (2018). Southern Criminology. Abingdon, UK: Routledge. Cartwright, M. (2020). Internationalising state power through the internet. Google, Huawei and geopolitical struggle. Internet Policy Review 9 (3) DOI: 10.14763/​2020.3.1494 Cohen, J.E. (2019). Between Truth and Power: The Legal Constructions of Informational Capitalism. New York, NY: Oxford University Press. Connell, R. (2007). Southern Theory. Crows Nest, NSW: Allen & Unwin. Daskal, J. (2019). Privacy and security across borders. The Yale Law Journal Forum 128: 1029–​51. Deleuze, G. (1992). Postscript on the societies of control. October 59: 3–​7. Ferguson, A.G. (2017). The Rise of Big Data Policing: Surveillance, Race and the Future of Law Enforcement. New York, NY: New York University Press. Frischmann, B. & Selinger, E. (2018). Re-​Engineering Humanity. Cambridge, UK: Cambridge University Press.

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Galič, M., Timan, T. & Koops, B.-​J. (2017). Bentham, Deleuze and beyond: An overview of surveillance theories from the panoptical to participation. Philosophy and Technology 30: 9–​37. Haggerty K. & Ericson R. (2000). The surveillant assemblage. The British Journal of Sociology 51 (4): 605–​22. Hacking, I. (1991). The Taming of Chance. Cambridge, UK: Cambridge University Press. Jochleson, R., Gacek, J., Menzie, L., Kramar, K. & Dorkesen, M. (2017). Criminal Law and Precrime: Legal Studies in Canadian Punishment and Surveillance in Anticipation of Criminal Guilt. Abingdon, UK: Routledge. Kennedy, S. & Warren, I. (2018). Southern criminology, law and the ‘right’ to consular notification in Australia, New Zealand and the United States. International Journal for Crime, Justice and Social Democracy 7 (4): 100–​14. Koopman, C. (2019). How We Became Our Data: A Genealogy of the Informational Person. Chicago, IL: University of Chicago Press. Lyon, D. (2003). Surveillance as social sorting: computer codes and mobile bodies. In D. Lyon (ed.) Surveillance as Social Sorting: Privacy, Risk, and Digital Discrimination. Abingdon, UK: Routledge (pp. 13–​30). Mann, M. & Daly, A. (2020). Geopolitics, jurisdiction and surveillance. Internet Policy Review 9 (3). DOI: 10.14763/​2020.3.1501 Mann, M. & Warren, I. (2018). The digital and legal divide: Silk road, transnational online policing and southern criminology. In K. Carrington, R. Hogg, J. Scott & M. Sozzo (eds.) The Palgrave Handbook of Criminology and the Global South. Cham, CH: Palgrave Macmillan (pp. 245–​60). McCulloch, J. & Wilson, D. (2016). Pre-​Crime, Pre-​Emption, Pre-​ Caution and the Future. Abingdon, UK: Routledge. Mclean, H. & Huf, B. (2020). Emergency Powers, Public Health and COVID-​19 (Research Paper No 2). Melbourne, AU: Department of Parliamentary Services. Mulligan, C.P. (2008). Perfect enforcement of law: When to limit and when to use technology. Richmond Journal of Law and Technology 14 (4): 13. Available at: http://​jolt.richmond.edu/​jolt-​archive/​v14i4/​ article13.pdf Mulligan, S.P. (2018). Cross-​border data sharing under the CLOUD Act. Congressional Research Service, R45173. Available at: https://​ crsreports.congress.gov/​product/​pdf/​R/​R45173 Powell, A., Stratton, G., & Cameron, R. (2017). Digital Criminology: Crime and Justice in Digital Society. New York, NY: Routledge.

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Shamir, R. (2005). Corporate social responsibility: A case of hegemony and counter-​hegemony. In B. de Sousa Santos and C.A. Rodriguez-​Garavito (eds.) Law and Globalization from Below: Towards a Cosmopolitan Legality. Cambridge, UK: Cambridge University Press (pp. 92–​117). Sheptycki, J. (2020). The politics of policing a pandemic. The Australian and New Zealand Journal of Criminology 53 (2): 157–​73. Tuhiwai Smith, L. (2012). Decolonizing Methodologies: Research and Indigenous Peoples. London, UK: Zed Books. Warren, I. (2015). Surveillance, criminal law and sovereignty. Surveillance & Society 13 (2): 300–​5. Warren, I., Mann, M. & Molnar, A. (2020). Lawful illegality: Authorizing extraterritorial police surveillance. Surveillance & Society 18 (3): 357–​69. Yunkapoorta, T. (2019). Sand talk: How Indigenous Thinking Can Save the World. Melbourne, AU: Text Publishing. Zedner, L. (2007). Pre-​crime and post-​criminology? Theoretical Criminology 11 (2): 261–​81. Zuboff, S. (2019). The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. New York, NY: Hachette.

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Introduction: The Ultramodern Age of Criminology, Control Societies and ‘Dividual’ Justice Policy Bruce A. Arrigo, Brian G. Sellers and Faith Butta

There are no private lives. This [absence is] a most important aspect of modern life. One of the biggest transformations we have seen in our society is the diminution of the sphere of the private. We must reasonably now all regard the fact that there are no secrets and nothing is private. Everything is public. (Dick, 1956) It is just when people are all engaged in snooping on themselves and one another that they become anesthetized to the whole process. … As information itself becomes the largest business in the world, data banks know more about individual people than the people do themselves. The more the data banks record about each one of us, the less we exist. (McLuhan, 1970, pp. 12–​13) In the societies of control, on the other hand, what is important is no longer either a signature or a number, but a code: the code is a password, while on the other hand [Foucauldian] disciplinary societies are regulated by watchwords (as much as from the point of view of integration as from that of resistance). The numerical

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language of control is made of codes that mark access to information, or reject it. We no longer find ourselves dealing with the mass/​individual pair. Individuals have become ‘dividuals’, and masses, samples, data, markets, or ‘banks’. … The disciplinary [subject] was a discontinuous producer of energy, but the [subject] of control is undulatory, in orbit, in a continuous network. (Deleuze, 1992, p. 6) What happens to culture when the experience of privacy, as we have lived it, disappears? What happens to (co)existence when the commercialism of surveillance capitalism fetishizes ‘life mining’ (van Dijck, 2014, p. 198) expressed through the recursive logics of new social media? What happens to human subjectivity when all of reality is reduced to the predictive analytics of dataism (i.e. the algorithmic scrutiny of metadata and the cyber-​construction of networked profiles) (e.g. Powell, Stratton & Cameron, 2018)? These are the information technology conditions of the current era. These conditions reflect a collective, undulating consciousness. Within the ‘hardwiring’ or circuitry of this consciousness lurk the passions of law and the emotions of crime reassembled as ‘dividual’ justice (Deleuze, 1992, p. 6). This volume both probes and dissects the criminological landscape of this consciousness that we, and others, have termed the ultramodern (Arrigo, 2012; Arrigo, Sellers & Sostakas, 2020; Shantz, 2014).1 As a point of critical departure and as a matter of historical record, the criminological landscape of ultramodern consciousness finds initial expression in Dick’s (1956) prescient observations about pre-​crime culture.2 Both this exit and this narrative are vitalized in McLuhan’s (1964, 1970) prophetic insights about the ontological effects of ubiquitous information technology deployed as medium of human extension and abstraction. Still further, this escape and journey find purchase in Deleuze’s (1992, see also Deleuze & Guattari, 1987) schizo-​analytic critique of disassembled subjectivity re-​territorialized as ‘algorithmic humanity’ (Arrigo et al, 2020, p. 497). From fiction, to conviction, to philosophy, this consciousness now, and increasingly, is populated by a new form of people-​making3 requiring a novel diagnostic framework or ‘criminological imagination’ (Pfohl, 2015, p. 99). This framework—​in theory and in methods, through pedagogy and by way of practice—​must be sufficient to treat ultramodernity’s human sequelae. We submit that this imagination and these sequelae are themselves under scrutiny in this volume.4 Perhaps, for the reader, it comes as no small surprise that this offering, The Pre-​Crime Society, appears in print and upon the horizon of public

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discourse at this unique moment in time. This is the occasion when the liminal spaces of risk and governance (e.g. Foucault, 1980) coalesce with the forces of crime control, data science and new media culture in ways that are progressively borderless and seemingly boundless. In part, this is what Presdee (2001, p. 159) meant when discussing ‘the creeping criminalization of everyday life’. In these spaces of ever-​ expansive transgression, relations of power are instantly dynamic and always dramaturgic (Yar, 2012), often fueling a cauldron of psychic discontent, civil unrest and indiscriminate dis-​ease (Arrigo, 2013).5 The fear that pulsates amid COVID-​19 and the pandemic’s spread, the uncertainty that lingers worldwide from the virus’s tsunami-​like political-​economic effects, and the outrage that grips new social movements such as Black Lives Matter, are spectacularly illustrative of this noxious liminality.6 Therefore, to be clear, in Deleuzian control societies, the ultramodern culture of risk and governance is itself on trial. This culture consists of pre-​crime analytics, post-​criminology dataveillance, and hyper-​ securitization optics (e.g. Zedner, 2007; Esposti, 2014; Ashworth & Zedner, 2014: McCulloch & Wilson, 2016). Within this culture, in maddening fashion, we are reminded that ‘freedom, privacy, and sovereignty are all illusions because people, events, objects, and spaces are all sites of information to be processed and policed through passwords’ (Sellers & Arrigo, 2018, p. 133). In the people-​making of the post-​disciplinary society, human risk (e.g. fear, uncertainty, outrage) gets translated into algorithms that can be used to catalog, monitor, profile and predict ‘the situation’ (Lippens, 2011, p. 175; see also Esposti, 2014). Increasingly, the situation is the neoliberal site of in-f​ ormational abstraction. Its responsibilizing by-​products include digital forms of governmentality (e.g. pre-​crime-​control policy). These by-​products signify the diffusion of power (e.g. institutional dataveillance), and it is this diffusion that places subjectivity all the more under the reifying restrictions of techno-​rationality (e.g. hyper-​securitization optics) and the neoliberal constraints of cyber-​capitalism (Dyer-​Witheford, 1999; Zuboff, 2019). And so, the question is begged: What are we to make of ultramodern consciousness and its people-​making culture of crime, law and justice? This volume provides both a critical response and a humanistic provocation.

Organization The Pre-​Crime Society: Crime, Culture and Control in the Ultramodern Age, is organized around five core themes. One theme is developed

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in each of the book’s five distinct parts. These themes reflect the editors’ assessment of criminology’s embryonic and emboldened directions in the ultramodern age of control societies and dividuated justice. In Part I, the volume emphasizes theory, theorists and theoretical perspectives. This part situates the conversation about the culture of risk and governance, pre-​crime control science, and dataveillance technology. In Chapter 1, Bruce A. Arrigo and Brian G. Sellers trace the intellectual history of risk, emphasizing its relevancies for the culture(s) of crime control. They explain how risk-​as-​currency (i.e. the management of human relating) is both historically contingent and made manifest through the process of reification, and they review reification’s modern, late modern and postmodern risk-​as-​currency incarnations. Additionally, the authors specify what the psychoanalytic and jurisprudential forces of reification are, and they explain how the interdependencies of these forces produce interrelated forms (i.e. reified forms) of risk management. Arrigo and Sellers speculate on what the currency of human relating and of economic exchange are in the ultramodern era, and they consider the ontological and epistemological captivity that follows from excessive investments in this era’s reified forms of risk management. In Chapter 2, Marc Schuilenburg problematizes what he describes as the security society’. In this society, power, surveillance and forms of punishment are all reassembled in Deleuzian fashion. The author explains the differences between three distinct forms of power: sovereign, disciplinary and control. Extending Deleuze’s writings on control, Schuilenburg conceptualizes the power of data. Whether one defines this in terms of ‘infopower’, ‘expository power’, or ‘psychopower’, the author makes evident that the embedded nature of algorithms and their role in governance (i.e. security and safety) need to be revisited and reconsidered. In Chapter 3, Pat O’Malley and Gavin J.D. Smith focus on the relationship between pre-​crime and Deleuze’s control society. They rely on examples such as speeding, drink driving and their respective risk-​reduction penalties to explore the manner in which human risk has become a statistical probability. According to the authors, a society of mass preventive justice calculated on the basis of an algorithmically derived jurisprudence of safety epitomizes Deleuze’s notion of control societies and functions as an assemblage rife with emergent forms of de-​ territorializing resistance (i.e. predictive expertise can be challenged). O’Malley and Smith conclude by questioning the efficacy of this resistance in an age of increasing digitization, remote sensing and

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Introduction

risk-​reduction prevention efforts based on the behavioral economics of statistical probabilities. In Chapter 4, David Polizzi draws both theoretical and clinical inspiration from Agamben’s work on the state of exception (i.e. the suspension of law by a given state) and zones of indifference (the psychic apparatus that constructs ‘the other’). Polizzi considers the case of non-​ state actors (i.e. terrorists) and explains how the exception that justifies the terrorist as ‘other’ is ontologically and epistemologically detrimental for those targeted. In support of this thesis, the author describes how that which is undone through such indifference-​making, is the negation of innocence. Polizzi contends that the cyber-​construction of non-​state actors does not alter the existential-​phenomenological critique that he offers. In Part II of the volume contributors examine the surveillance industrial complex, focusing on both criminal institutions and organizations of justice administration. This part considers the function and maintenance of data in relation to specific criminal subjects or offender groups of surveillance. In Chapter 5, Andrew Hope investigates school digital surveillance and the pre-​crime student. He assesses the connections between pre-​crime technologies and schools, focusing on the burgeoning use of digital surveillance practices. He argues that despite growing technological capacities, no evidence currently exists to legitimately claim that pre-​crime processes occur in schools. However, by turning to Gane’s discussion of neoliberal governmentalities, Hope maintains that commercial pressures do exist for student data to be used in risk-​calculated ways. The author concludes by commenting upon the problematic notion of the pre-​criminal student. He develops his commentary by reviewing techno-​realist narratives that promise to stop future crime, by describing cultural perspectives that highlight the potential destructiveness of such labels and by proposing a political economy approach that raises concerns about the commercial forces behind increasingly invasive school surveillance technologies. In Chapter 6, Matthew Draper, Brett Breton and Lisa Petot diagnose the commodification of suffering. This is suffering that impacts the everyday lives of mental health systems users. The authors explain how the institutional collection of algorithmic data about suffering is an industry in which categories about mental illness are constructed. They go on to recount how these statistically derived probability categories inform mental health policy and clinical practice. Under these conditions, profits rather than people are privileged. The authors point to examples of profit-​tied data (i.e. population prevalence) to substantiate their thesis.

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In Chapter 7, Aaron Pycroft offers a hermeneutical account of substance misuse surveillance and the drug use industry in ultramodern democracies. His critique centers on the technologies of new public management. In this management schema, outcome monitoring, drug testing, risk profiling, and meta-​analytic methods are deployed as a hermeneutic of suspicion. This dialogic makes possible a form of utilitarian scapegoating. The author goes on to describe a hermeneutic of affirmation. Drawing inspiration from trans-​disciplinary sources, Pycroft considers the problem of complicity that reifies the techno-​ bureaucratic trade in surveillance drug misuse. He calls for a process of humanistic discovery rather than a process of state repressive recovery to guide substance treatment systems in courses of individual care. In Chapter 8, Andrew Day and Armon Tamatea consider the politics that underlie actuarial justice and risk assessment throughout the systems (the industries) of criminal justice. For Day and Tamatea, the digital technologies of risk reflect narrow cultural values and interests, and they fail to include the beliefs and goods of Indigenous peoples and other minority communities. As the authors note, the cultural experiences of these peoples and communities are absent in the technologies of risk, notwithstanding the disproportionate presence of such citizens in the systems of criminal justice. Day and Tamatea’s analysis highlights a set of critical questions about the socio-​political context in which risk assessment occurs, including the need to identify alternative ways of understanding pre-​crime. In Part III of the volume, contributors assess the persistence of dataveillance, explore the status of cyber-​governance and critique the policing of control societies. This part examines the science and politics of governance technology, the everyday surveillance of youth and the intersections of pre-​crime intelligence, national security and global population control. In Chapter 9, Janne E. Gaub and Marthinus C. Koen offer a theoretical and historical assessment of ‘big data’ or predictive policing, including a critique of their deployment during the current crisis in law enforcement legitimacy. Gaub and Marthinus argue that video surveillance (e.g. CCTV, license plate readers, in-​vehicle cameras and now body-​worn cameras) combined with the redirected focus from the war on terrorism has created a new dataveillance era of policing. In Chapter 10, Michael McCahill examines the politics of pre-​crime and surveillance in the field of policing. Relying on Bourdieu and field theory for conceptual guidance, the author examines how social phenomenon such as risk, actuarial thinking and predictive analytics are mediated by agents of the surveillance industrial complex. These

6

Introduction

agents include police officers and managers, intelligence analysts and private security officers, and citizens going about their routine activities in various sectors of the pre-​crime society (e.g. welfare offices, shopping malls, airports and rooms of CCTV control). McCahill concludes by advocating for research that investigates the informal networks that exist (or might emerge) between big data-​driven policing and the experience of pre-​crime subjects. In Chapter 11, Clare Southerton and Emmeline Taylor investigate the everyday digital surveillance of young people in the Western world, arguing that ubiquitous dataveillance has rendered them Deleuzian dividuated selves. The authors note that surveillance encounters choreograph the routines of children and adolescents at a micro-​logical level and at the same time, reproduce structural inequalities through processes of social sorting at the macro-​logical level. As the authors make clear, dividuation endlessly fragments the body into streams of data and coded information for purposes of mass analysis from which life decisions are then made for and about the person. Southerton and Taylor explore the felt experience of such dataveillance fragmentation on the lives of young people. In Chapter 12, John E. Deukmedjian shines a spotlight on the post-​9/​ 11 securitized society and the ever-​expanding integrated and networked international intelligence community. The author maintains that the totality of intervention capabilities from an integrated international intelligence community fused with intelligence-​led policing and big data technology companies has created ‘total information awareness’. It is this state of awareness that renders everyone an assumed risk and potential criminal. According to the author, the fundamental goal of total information awareness is global population control. In Part IV of the volume contributors focus on the new penology of actuarial risk management and the manner in which it reproduces and reifies disciplinary systems of institutional and community surveillance. This part showcases how the deployment of datafication for specific correctional supervision and treatment purposes both programs and monitors criminal offenders, as well as classifies and predicts criminal behavior. Contributors address the limits of such control. In Chapter 13, Terry A. Kupers examines the system of supermax solitary confinement. He explains how the algorithmic calculation of prisoner violence reconfigures danger, disease and disorder in ways that appear more scientific but are nonetheless racially biased. Kupers maintains that risk assessment derived from datafication efforts all too often contain an unexplored self-​fulfilling prophecy. In short, prisoners assessed at high risk for future criminality are treated in ways

7

THE PRE-​CRIME SOCIETY

that increase the likelihood of their violent reoffending. The high-​ risk prisoner is sent to supermax isolation or merely denied parole for an extended period of time. Kupers comments on the physical and mental health fall-​out stemming from solitary confinement and argues that increased reliance on datafication prison methods reduces prospects for ‘going straight’ as reflected in higher recidivism rates and greater mortality. In Chapter 14, Kristen M. Budd and Christina Mancini systematically review the role of big data in the mass electronic monitoring (EM) of convicted sex offenders in the United States. The authors explore several essential facets of EM. These facets include types of electronic monitoring, legislation and the use of electronic monitoring in relation to individuals convicted of sex crimes, relevant case law developments (e.g. lifetime GPS monitoring as public safety and prevention versus punishment), advantages and disadvantages of EM in relation to community management, the intersection between EM and law enforcement, sex crime recidivism in relation to EM, cost-​benefit analysis of EM, and public opinion about the application of electronic monitoring with convicted sex offenders. In Chapter 15, Mike Nellis examines the community corrections allure of predictive analytics and ‘coercive connectivity’ in relation to criminal offenders subjected to remote, real-​time (i.e. immediate) electronic monitoring control in the United Kingdom. The author terms this new predictivity ‘imminence detection’. He argues that an EM surveillance industry already exists. Specifically, Nellis maintains that artificial intelligence and smartphone monitoring will have a transformational impact on community corrections, and the allure of predictivity will play a part in establishing this change. However, as he concludes, the allure of algorithmic prediction will not become a definitive feature of the resulting programming. Thus, the immediacy of control will still matter more than the imminence of detection. In Chapter 16, Bianca C. Reisdorf and Julia R. DeCook assess the readiness of ex-​offenders in the United States to confront a technology-​dependent world and a hyper-​secured society in which digital skills and access to digital devices (including the Internet) are essential for community rehabilitation efforts and successful reentry engagement. The authors explain that most returning citizens lack the necessary information technology training. Reisdorf and DeCook indicate that while localized attempts to run digital skills programs with recently released populations have occurred, such training is usually not a part of prisoner reentry practices, and much of it does not go beyond basic computer skills. The authors provide an

8

Introduction

overview of the kinds of technologies returning citizens encounter during rehabilitation and reentry, and comment on the small but increasing number of reentry programs that focus on integrating digital technologies and digital literacy into their curricula. They conclude with a discussion on the implications that follow from a lack of such community-​centered programming for returning citizens, and they assess the potential benefits of digital literacy training during the reentry process. In Part V of the volume contributors explore the problem of globalizing surveillance, human rights and (in)security. This part features the tension between the democratic values of individual rights and civil liberties on the one hand, and the risk governance needs of cyber security and datveillance on the other hand. In Chapter 17, Natalie Delia Deckard explores what she defines as the civil death of the criminal class. She explores the underlying logic of felony disenfranchisement as pre-​crime, and she reviews its development as a modality of carceral governmentality. Particular attention is paid to the power of voter fraud as threat to electoral legitimacy and the legitimation of the process for the legal resumption of voting rights. The chapter then details the intersections between disenfranchisement as goal and surveillance as praxis: at each step of the criminalization process that excludes individuals particularly and communities broadly, actions and reactions are comprehensively logged, reviewed and reported. The author contends that this process of documentation is central to the neoliberal project overall and as such, surveillance functions as data collection towards the justification of widespread civil death. Invoking the insights of Agamben on states of exception, Deckard concludes by asserting that the legally endorsed surveillance mechanisms through which marginalization is constructed and maintained guarantee a permanent zone of indifference with respect to disenfranchise felons, notwithstanding the political control that this very electorate would otherwise exercise in the democratic state. In Chapter 18, Jin Ree Lee and Thomas J. Holt examine the relationship between big data and its sundry uses by industry personnel as well as by academic researchers. Specifically, the authors consider the various developments that support and/​or challenge wider assumptions about increasing reliance on predictive analytics for purposes of ensuring cyber security and/​or for promoting individual liberty. Lee and Holt define the essential characteristics of big data. They then consider how it is deployed by both industry professionals and academic researchers. The authors conclude with a discussion on the human risks and justice implications that big data poses.

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In Chapter 19, Birgit Schippers demonstrates how drones, as a central element of the contemporary techno-​political assemblage of global violence, scramble and rescript the boundaries between the domestic and the international; between the private and the public; between territoriality and extra-​territoriality; and between lawfulness and the extrajudicial. Schippers argues that drones materialize and visualize justice as spectacle, whereby they project a global ‘power without vulnerability’ and their deployment generates structures of unequal risk distributions. These distributions enable the networked construction of digital subjects as killable. The chapter reviews the history of drone development and usage, and it theorizes the role that drone technology and drone strikes play in re-​organizing global power dynamics. Schippers further explores the biopolitical effects of drone strikes through pattern-​of-​life analyses. In order to investigate these effects, Schippers surveys drone usage during the current coronavirus pandemic. She concludes with a reflection on mechanisms for resistance and counter-​conduct that envision new perspectives regarding justice in an age of drones. In Chapter 20, Brian G. Sellers investigates how Radio Frequency Identification (RFID) technology—​which uses electromagnetic radio waves to automatically identify people, animals or objects—​has become perhaps the most pervasive computing technology in history, as well as a tool for global surveillance. The author begins with an historical overview of the literature pertaining to the emergence of RFID and its evolving system components. RFID’s four broad usage categories, including electronic article surveillance, portable data capture, networked systems and global positioning systems. These are reviewed in detail. The author then examines RFID’s numerous practical applications and their function as a mechanism for global surveillance in the Internet of Things (IoT). As IoT devices, RFID implantable chips have the potential to collect vast amounts of data on citizens and hold great conceivable risks for privacy and security. Brian Sellers then undertakes a theoretical analysis of the significance that RFID technology plays in the globalization of surveillance. He explains how RFID, as an emerging crime control technology, is geared towards global post-​panoptic surveillance, banoptic social sorting, the responsibilization of citizens and new forms of ‘people-​ making’ culture in coordination with the aims of the global pre-​crime society. Furthermore, Sellers argues that RFID technology is crucial to the exercise of bio-​power. Bio-​power is necessary for normalizing and nurturing this crime control enterprise and its subsequent

10

Introduction

governmentality. This is an enterprise whereby informational strategies and digital techniques are employed by regulatory institutions to achieve full or hyper-​securitization worldwide. The author concludes with a critique related to the liberty, privacy and citizenship concerns of RFID implementation and human chipping.

The pre-​crime society When privacy disappears as we know it, when coexistence is mediated by dataveillance regimes of human extension and abstraction, and when subjectivity is endlessly transformed into algorithmic profiles, then the society of pre-​crime prevails. This is the destabilizing condition of the ultramodern age. In this society, the activities of risk-​avoidance and threat analytics represent governing modes of human relating. Technology is pivotal to normalizing and nurturing this crime control enterprise. What this means, therefore, is that predictive policing, actuarial justice and surveillance penology are the in-​formational strategies and bio-​digital techniques that regulatory institutions employ to achieve full or hyper-​securitization. But, such securitization comes at a human cost. Indeed, in the ultramodern era, crime is reassembled. The creeping criminalization of everyday life is guaranteed, and correspondingly, new and disturbing forms of people-​making (i.e. of human relating) abound. Body cameras and the simulation of surveillance, zero-​tolerance school policy and the hermeneutics of suspicion are two such cultural forms. The Pre-​Crime Society: Crime, Culture and Control in the Ultramodern Age investigates the pre-​crime society of the ultramodern age. This is a society where justice has become a datafication industry and punishment is administered through dataveillance regimes. This industry and these regimes are cyber-​systems of thought that bio-​digitally manufacture, market, and manage the crime control industrial complex, implicating all of its inhabitants (i.e. the kept and their keepers, the watched and their watchers). The Pre-​Crime Society: Crime, Culture, and Control in the Ultramodern Age explains how the pre-​crime society operates, discusses the reach of its destabilizing effects and theorizes new directions in securitization policy and practice. Notes 1

The ultramodern represents a critical assessment of and engagement with the cultural conditions that reify a particular version of shared humanity. In the ultramodern age, algorithmic humanity or the cyber-​conceived incarnations of human subjectivity populates this era of people-​making. In Chapter 1 of this

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2

3

4

5

6

volume, the authors present the intellectual history on the modern, late modern, postmodern and ultramodern coexistent lacunae of each age. We also note the significance of Orwell’s (1961) classic, 1984, in which he depicts a dystopian government whose commitment to mass surveillance controls the relational narratives of social life. We further note the importance of the volume’s Afterword penned by the humanistic philosopher, psychoanalyst and social psychologist, Erich Fromm. Fromm famously decried the de-​humanizing capitalist imperatives of technology (e.g. Fromm, 1956; 1970). Recent scholarship has revisited the relevance of Fromm’s insights in the digital age of surveillance technology (Fuchs, 2020). This new era is ‘punctuated by social sorting technologies, hyper-​securitization optics, the in-​formationalizing of the citizen as suspect, and surveillance nodes of capitalism. In this era, algorithmic humanity both redesigns and redefines the new people-​making’ (Arrigo et al, 2020, p. 497). Mills (1959) makes clear the significance of this inquiry. As he explained: ‘It is the political task of the social scientist—​as of any liberal educator—​to continually translate personal troubles into public issues, and public issues into the terms of their meaning for a variety of individuals’ (p. 166). Consistent with this view, Flynn (2014, p. 361) noted the following: ‘A rich tradition of philosophical, social and cultural theory has demonstrated the centrality of emotion to social life, in particular collective feelings of ‘estrangement’, ‘anxiety’, ‘separation’ and ‘isolation’ engendered by materialistic conditions of capitalism.’ It is our contention that, in the ultramodern age, the information processing conditions of surveillance capitalism have altered (digitized) the relations of power and have further abstracted (commodified) subjectivity, producing heightened feelings of resentment (Nietzsche, 2003). The swell of oppositional voices (Seattle’s Capitol Hill autonomous zone) and the surge in dissenting views (international defund the police efforts) are indicative of this moral antipathy and liminal rebuke. Regrettably, similar to prior periods of liminal unrest, the geo-​p olitical response will likely include the deployment of more ‘quick-​fix’ solutions. In the ultramodern age, hasty remediation is derived from the analytics of pre-​crime. Examples include dataveillance protocols and population surveillance, drone intelligence and other thinking machines, and tracking and monitoring devices. These technologically-​inspired solutions increase security and social control. Their ostensible goal is the amelioration of social problems (e.g. global pandemic, police brutality and racial injustice) and the simultaneous reduction of human error (e.g. quarantine non-​compliance, neutralize systemic racial prejudice). Nevertheless, these very same novel responses may actually perpetuate the social problems they claim to remedy.

References Ar r igo, B.A. (2012). The ultramoder n condition: On the phenomenology of the shadow as transgression. Human Studies: A Journal for Philosophy and the Social Sciences 35 (3): 429–​45. Arrigo, B.A. (2013). Managing risk and marginalizing identities: On the society-​of-​captives thesis and the harm of social dis-​ease. International Journal of Offender Therapy and Comparative Criminology 57: 672–​93.

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Arrigo, B.A., Sellers, B.G. & Sostakas, J. (2020). Pre-​crime, post-​ criminology and the captivity of ultramodern desire. International Journal for the Semiotics of Law 33 (2): 497–​514. Ashworth, A. & Zedner, L. (2014). Preventive Justice. Oxford, UK: Oxford University Press. Deleuze, G. (1992). Postscript on the society of control. October 59: 3–​7. Deleuze, G. & Guattari, F. (1987). A Thousand Plateaus: Capitalism and Schizophrenia. Minneapolis, MN: University of Minnesota Press. Dick, P.K. (1956/​2016). The Minority Report and Other Classic Stories by Phillip K. Dick. New York, NY: Citadel. Dyer-​Witheford, N. (1999). Cyber-​Marxism: Cycles and Circuits of Struggle in High Technology Capitalism. Urbana-Champaign IL: University of Illinois Press. Esposti, S. (2014). When bid data meets dataveillance: The hidden side of analytics. Surveillance & Society 12 (2): 209–​25. Flynn, N. (2014). Advancing emotionally intelligent justice within public life and popular culture. Theoretical Criminology 18 (1): 354–​70. Foucault, M. (1980). Power/​Knowledge: Selected Interviews and Other Writings. London, UK: Harvester. Fromm, E. (1956). The Sane Society. Abingdon, UK: Routledge. Fromm, E. (1970). The Revolution of Hope: Toward a Humanized Technology. Riverdale, NY: American Mental Health Foundation Books. Fuchs, C. (2020). Er ich Fromm and the cr itical theory of communication. Humanity & Society 44 (3): 298–​325. Lippens, R. (2011). Mystical sovereignty and the emergence of control society. In J. Hardie-​Beck & R. Lippens (eds.) Crime, Governance and Existential Predicaments. London, UK: Palgrave Macmillan (pp. 175–​93). McLuhan, M. (1964). Understanding Media: The Extensions of Man. New York, NY: Signet. McLuhan, M. (1970). From Cliché to Archetype. New York, NY: Pocket Books. McCulloch, J. & Wilson, D. (2016). Pre-​crime, Pre-​emption, Pre-​caution and the Future. Abingdon, UK: Routledge. Nietzsche, F.W. (2003). The Genealogy of Morals. Mineola, NY: Dover Publications. Orwell, G. (1960). 1984. New York, NY: Signet Classics. Pfohl, S. (2015). The criminological imagination in an age of global cybernetic power. In J. Frauley (ed.) C. Wright Mills and the Criminological Imagination: Prospects for Creative Inquiry. Surrey, UK: Ashgate (pp. 99–​134).

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Powell, A., Stratton, G. & Cameron, R. (2018). Digital Criminology: Crime and Justice in Digital Society. New York, NY: Routledge. Presdee, M. (2001). Cultural Criminology and the Carnival of Crime. Abingdon, UK and New York, NY: Routledge. Sellers, B.G. & Arrigo, B.A. (2018). Postmodern criminology and technocrime. In K.F. Steinmetz & M.R. Nobles (eds.) Technocrime and Criminological Theory. Boca Raton, FL: CRC Press (pp. 133–​46). Shantz, J. (2014). Criminology, ultramodern. In B.A. Arrigo (ed.) Encyclopedia of Criminal Justice Ethics. Thousand Oaks, CA: SAGE Publications (pp. 1198–​201). Van Dijck, Jose. (2014). Datafication, dataism, and dataveillance: Big data between scientific paradigm and ideology. Surveillance & Society 12 (2): 197–​208. Wright Mills, C. (1959). The Sociological Imagination. New York, NY: Oxford University Press. Yar, M. (2012). Crime, media, and the will-​to-​representation: Reconsidering relationships in the new media age. Crime, Media, Culture 8 (3): 245–​60. Zedner, L. (2007). Pre-​crime, post-​criminology? Theoretical Criminology 11 (2): 261–​81. Zuboff, S. (2019). The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. New York, NY: Hachette.

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PART I

Theories, Theorists and Theoretical Perspectives

1

The ‘Risk’ Society Thesis and the Culture(s) of Crime Control Bruce A. Arrigo and Brian G. Sellers

Introduction It is or contention that this book, The Pre-​Crime Society: Crime, Culture and Control in the Ultramodern Age, furthers a project that was initiated and subsequently developed within two of our previous volumes (Arrigo & Milovanovic, 2009; Arrigo, Bersot & Sellers, 2011). Among the themes shared by these volumes was a sustained focus on the philosophical currents and cultural intensities that produce de-​vitalizing and finalizing laws of shared human captivity (Arrigo & Sellers, 2018).1 These laws originate in the captivity of forms (Plato, 2008), including the forms of human abstraction and their sequelae (Arrigo & Polizzi, 2018). In the first of these volumes, Bruce Arrigo and Dragan Milovanovic (2009) argued for a ‘revolution in penology’ (pp. 3–​8). As the authors explained, this revolution begins with a radical critique of subjectivity (i.e. human capital abstracted) and the constitutive forces into and out of which this subjectivity both shapes and is shaped by a ‘society of captives’ (pp. 170–​95). This is the captivity of the kept and their keepers, the watched and their watchers in which risk-​as-​currency prevails as trade. The authors further asserted that when the excesses of this captivity are maintained in consciousness, through dialogical encounters, and in material expressions of the same, then they (these excesses) nurture the captivity of society. This is the captivity of ontology (i.e. of being human), and of epistemology (i.e. of human

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relating).2 The maintenance of these conditions forestalls a ‘people yet to come’ (Deleuze & Guattari, 1994, p. 108), and forecloses what Hardt and Negri (2004) have described as the ‘multitude’ (pp. 97–​157). The ubiquity of the prison form is revealing of captivity, both as meditation on and metaphor about risk, the risk of being human and of evolving in humanness (Nietzsche, 1966), amidst the culture of crime control that the management of human risk inevitably spawns (e.g. Ericson & Haggerty, 1997; O’Malley, 2004). By prison form we mean its symbols and discourses (Sloop, 1996; Brown, 2009), its architecture and environmental designs (Johnston, 2006; Day, 2013; Reiter and Koenig, 2015), its industries and mechanisms (Alexander, 2011; Geunther, 2013). In this regard, we might think of the prison form as what Foucault (1980) described as a dispositif: an apparatus of discipline and of disciplining whose systems of thought reproduce a network of discursively structured power/​knowledge relations (pp. 194–​228). These relations find transactional (i.e. commodity-​like) expression in schools and factories, jails and hospitals and in other centers for detention or settings of confinement.3 In the second volume, Arrigo, Bersot and Sellers (2011) extended and refined the thesis on the risk society. In this volume, the authors turned to case and statutory law as well as social science evidence to critique how current crime control policies are reified through forms of legal moralism masquerading as democratic governance. By focusing on three, worst of the worst offender groups, the authors were able to explain how ‘power as harm’ (Milovanovic & Henry, 2001 p. 165)4 is institutionally legitimized at the level of judicial decision-​making. Arrigo et al (2011) demonstrated how this legitimacy as harm (e.g. to criminalize, to pathologize, to demonize) is expressed through juridical attitudes or temperaments sourced in underlying, and narrowly construed, ontological and epistemological (i.e. human risk management) commitments (see also Bersot & Arrigo, 2015). These commitments find discursive form in the precedential language of the law. Specifically, and problematically, when it comes to ‘incompetent’ and ‘at-​risk’ juveniles waived to the adult system, or to ‘dangerous’ and ‘ill’ prisoners placed in isolation, or to ‘mentally abnormal’ and ‘deviant’ sex offenders subjected to protracted and permanent offender monitoring practices, the currency in risk and its management reifies forms of ‘totalizing madness’ (Arrigo et al, pp. 3–​5). These are forms of governing through crime and a culture of fear (Simon, 2009). In these instances, the ethical calculation of competing interests and the

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The ‘Risk’ Society Thesis

absolute imperatives of categorical duties displace the virtue logic of human flourishing (Aristotle, 1976). The limit-​setting and denial-​ imposing judgments about human capital (i.e. potential relatedness and possible relating) that follow from hyper-​reliance on these ethical commitments are far-​reaching, especially in how risk is ontologically categorized and epistemologically calibrated. As Arrigo et al (2011) summarized: ‘[W]‌hen the logic of risk management governs choice, action, and progress, policy efforts that support experimentation and innovation are not simply perceived generally with caution, they are interpreted mostly as hazardous. This is the disturbing prism through which total confinement practices are currently enacted, nurtured, and sustained’ (p. 4).

Section I: the problem of reification and the culture(s) of control How is risk-​as-​currency (i.e. the management of human relating) both historically contingent and made manifest through the process of reification, and what are reification’s modern, late modern and postmodern risk-​as-​currency Platonic forms or human abstractions. Our view on the management of human relating (i.e. governing the risk of being and the risk of becoming) is informed by the project of constitutive criminology (Henry & Milovanovic, 1996, 1999). This is the project of ‘(dis)identities and (dis)continuities’ (Arrigo & Milovanovic, 2009, pp. 133–​60). (Dis)identities refer to the struggle to be human and to coexist as subjectivity in recovery. Recovery entails overcoming the limit-​setting and denial-​imposing categories into which human subjectivity is inserted and out of which this subjectivity inhabits ‘relations of humanness’ (Arrigo, 2015, p. 7). This relatedness extends to and from the kept and their keepers as well as to and from the watched and their watchers. (Dis)continuities refer to awaiting human subjectivity; that is, to humanness and coexistence that remain in-​process and non-​linear (Kristeva, 1984), emergent and rhizomatic (Deleuze & Guattari, 1994). This is interrelatedness pending transformation. Human recovery begins by recognizing that ‘the substance of being human must … entail what precede[s]‌us as biography, what looms ahead as prospect, caught in the contingent moment of the here and now, plowed by the discordant strands of unconscious processes’ (Henry & Milovanovic, 1996, p. 36). Human transformation consists of the ‘presently un-​ representable’ (Cornell, 1991 p. 169). These presences are forms of the good for a people to come. What the recovery and transformation of

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subjectivity implies, therefore, is that ‘human agents, acting in a socio-​ political context and shaped by historical forces of the time, are the active co-​producers and re-​producers of their dynamic worlds’ (Arrigo & Milovanovic, 2009, p. 6). Thus, the historical contingency of risk-​as-​ currency or the management of relatedness is guaranteed because of such active human agency and constitutive forces of (co)existence. The problem of reification helps to amplify the constitutive perspective on the historical contingency of risk and the project of (dis)identifies and (dis)continuities. According to Hungarian philosopher Georg Lukács (1971), reification occurs when ‘the subject and social relations become object-​like, thing-​like … and commodity-​like’ (as cited in Baldwin, 2009, p. 381). As process, this physicalizing occurs when human agents assign concrete qualities to the very ideologies that they construct, including the assigning of value to one’s productivity or labor. These reified constructions are then experienced as ‘facts of nature, [the] result of cosmic laws, or manifestations of divine will’ (Berger & Luckman, 1966, p. 33). Lukács (1971, p. 86) refers to the iterative nature of this process as ‘the fetishism of the commodity form’.5 Reification therefore fosters a state of (co)existence in which the distinction between subjectivity as recoverable and transformable and objects outside the remit of these forms of humanity are, in essence, no longer recognizable. Put differently, ‘human creative agency loses sight of its contribution to what it produces as the reified object of its own subjectivity’ (Arrigo & Milovanovic, 2009, p. 8). As such, an examination of reification as process entails an assessment of human subjectivity and how the risk that subjectivity constitutes is managed, individual and collective consciousness and how this consciousness is held captive, and freedom of choice and action and how limits to or denials of both establish harm that must be overcome (Lukács, 1971).6 Three risk society transitions are worth noting with respect to the reification problem. These transitions are enumerated, respectively, in Marx’s modernist critique of capital logic, in The Situationists’ late modern critique of techno-​rationality and in the hyper-​realists’ postmodern critique of sign-​systems theory. In what follows, we outline the historical currents and cultural intensities that helped to physicalize these shifting reification configurations deployed in the management of human subjectivity. We argue that the currency in risk administration increasingly, and problematically, abstracts (co)existence. As we explain, these abstractions represent inversions in being and becoming, Platonic forms of captivity to manage, and harms to human shared capital. Each of these reified conversions establishes a culture of crime control.

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The ‘Risk’ Society Thesis

Marx and reification The first risk-​as-​currency transition is found in the work of German philosopher, Karl Marx (1990, 1995). The management of human relating is sourced in his economic theory regarding class consciousness and the ‘abstraction of the worker’ (Arrigo, 2006, p. 45). In the political economy of industrial capitalism, Marx (1990) argued that the continual circulation of money—​derived from reliance on capital logic—​served to reify this commodity form. In so doing, the process of reification rendered the commodity form a substitute for subjectivity and human relatedness. Specifically, as Marx (1990) noted, when the object of production is equated with the accumulation of pecuniary abundance, then (co)existence is abstracted. This is because capital logic fundamentally advances the competitive imperatives of acquisition and consumption rather than the generative and creative capacities of labor-​ power including being (as recovery) and becoming (as transformative) through one’s own self-​sufficient production. For Marx (1995), when the risk of human relatedness shifted to the currency of the commodity form and its fetishisms, then collectivist struggle was necessary in order to overcome the harm-​sustaining (i.e. alienating) conditions of economic production and circulation. Indeed, as Marx (1990) asserted, in the capitalist mode of risk governance, the intrinsic use-​value of one’s labor was assigned a fixed, although artificial (i.e. monetary), exchange-​value capable of being purchased in the marketplace. In this way, the worker and the products of one’s labor were, in essence, rendered thing-​like. Marx (1990, pp. 138–​9) described this inversion as follows: Not an atom of matter enters into the objectivity of commodities as values; in this it is the direct opposite of the coarsely sensuous objectivity of commodities as physical objects. We may twist and turn a single commodity as we wish; it remains impossible to grasp it as a thing possessing value. However, let us remember that commodities possess an objective character as values only in so far as they are all expressions of an identical social substance, human labor, that their objective character as values is therefore purely social. From this it follows self-​evidently that it can only appear in the social relation between commodity and commodity. Made abstract, Marx (1995, p. 70) posited that the worker ‘sinks to the level of a commodity and becomes indeed the most wretched of

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commodities’. Accordingly, recoverable and transformative qualities intrinsic to (co)existence, including compassion, love, courage and friendship, ‘enter into commerce’ (Marx, 1995, p. 36) altering the nature of the human relationship from one of authentic interaction to one of mere transaction. Commenting on the psychological properties of this phenomenon, Fromm (1994) observed: It becomes [the individual’s] fate to contribute to the growth of the economic system, to amass capital, not for the purpose of [one’s] own happiness or salvation, but as an end in itself. [The individual thus becomes] a cog in the vast economic machine—​an important one if he [or she] has capital, an insignificant one if he [or she] has none—​but always a cog to serve a purpose outside of the [self]. (p. 110) In the political economy of industrial capitalism, then, the notion of having rather than being/​becoming (or re-​acquiring rather than re-​ originating) insidiously triumphs, disrupting organic social relations and alienating possibility/​potential for communal good. In the modernist era, this state of captivity promulgated through capital logic abstraction became pervasive. It extended from the kept (workers) to their keepers (factory owners), from their managers (institutional decision-​brokers) to their watchers (state government bureaucrats) (Arrigo and Milovanovic, 2009, pp. 69–​97).

The Situationists and reification The second risk-​as-​currency transition was developed by a group of predominately European activists and artists known as the Situationists (e.g. Debord, 1983, 1998). Building on the insights of Marx (1990, 1995), the Situationists reasoned that the management of human relating and the problem of reification were made evident in the techno-​rational forms of (co)existence that populated late modernity. Indeed, the Situationists depicted a new form of class consciousness derived not from the object of production but from the object’s ever-​ present images (Vaneigem, 2012). Aligned most closely with libertarian Marxism (Knabb, 2007), the Situationists claimed that with monopoly capitalism, human subjectivity was equated with the commodity’s form as spectacle and not the commodity’s form as object of productive exchange (Debord, 1983). The spectacle refers to a counterfeit society in which people passively consume media-​manufactured constructions of phenomena (e.g. advertisements about crime reduction or drug

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The ‘Risk’ Society Thesis

treatments, commercials about prison reform or psychiatric care), rather than experiencing the same through ongoing observation or direct participation. What is produced and consumed through the spectacle is another inversion of abstracted (co)existence that is designed to manage (reductively and repressively) the risk of human subjectivity (Best, 1989). The false equivalency to which this relatedness is imperiled positions the exchange-​value of appearing over the use-​value of being/​ becoming, and the mass production of image-​objects over the objects of human/​social production themselves. Under these conditions, individual and collectivist consciousness are confined by the captivity of styles, the commodification of illusion and the fetishism of the consumable subject reified through the logic of techno-​rational capitalism (Vanneigem, 2012). When iterative imitation outpaces lived experience as normalized industry and when appearance vanquishes reality for the purpose of mass-​marketed circulation, then the spectacle culturalizes use-​value. Indeed, ‘this is the moment when the commodity [as image] attains the total consumption of social life’ (Debord, 1983, p. 42). In the simulated age of media-​propagated consumerism and omnipresent commercialism, freedom (of choice and in action) for the recovering and transforming subject is therefore limited to and overcome by choreographed differences, programmed options and staged preferences. The reification of the spectacle as the new currency in risk management signified the ontological and epistemological ascendancy of the proliferating image-​object. According to the Situationists, the Platonic form of repetitive representational consumption functioned to captivate and to constrain human relatedness (Debord, 1998). Indeed, the spectacle’s allure not only gripped those who gazed upon it (the kept, the watched) but imprisoned those who profited from it (their keepers, their watchers). Given these harm-​generating social relations, matter and materiality were supplanted by replicas and façades. Thus, subjectivity as human capital was further abstracted through the continuous reproduction of counterfeit realities that caricaturized, sensationalized and de-​realized visceral (i.e. embodied) (co)existence.

The hyper-​realists and reification The third risk society transition was developed by the hyper-​realists. Following the Situationists’ notion of the spectacle (appearing over being/​becoming), these theorists chiefly concerned themselves with discerning whether artificial representations (i.e. images

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of reality) were more real than the reality on which they (these contrivances) were based. In response, the hyper-​realists proposed a unique cultural theory that ‘elevated the commodification of illusion to a novel and disturbing (alienating) level of abstraction’ (Arrigo, 2006, p. 49). One of the preeminent hyper-​realists, French philosopher Jean Baudrillard (1972), asserted that postmodern society was not organized around production and consumption (i.e. having) as Marx had asserted. Instead, Baudrillard (1983) argued that in the new reification age, social life was mediated by ‘miniaturized models of reality, imitation units of authentic’ (co)existence (pp. 20–​5). This was an era that no longer made sustainable the replication of appearance over being/​becoming as a cultural artifact. In its place, simulation (i.e. the replication and proliferation of image) made systems of communication and their encoded sign meanings the essential objects of risk management currency. Indeed, in an age of discursive simulacra, reality (or the appearance of it) became irrelevant (Baudrillard, 1983). In its place, the ascendancy of the code’s status (and with it the un-​grounding of existence and its manifold illusions) reigned supreme. This led Baudrillard (1993) to conclude that social life as we knew it had ended. As he proclaimed: The end of labor. The end of production. The end of political economy. The end of the signifier/​signified dialectic which facilitates the accumulation of knowledge and of meaning, the linear syntagma of cumulative discourse. And, at the same time, the end simultaneously of the exchange value/​use value dialectic which is the only thing that makes accumulation and social production possible. The end of linear dimensions of discourse. The end of the linear dimension of the commodity. The end of the classical era of the sign. The end of the era of production. (p. 8) As such, Baudrillard (1972, 1983) suggested that within postmodern culture, significance, or value was singularly expressed through sign-​ exchange-​value. In this new era, commodity forms ‘circulate[d]‌in the marketplace of signs, anchored, although temporarily, in the dominant sign meanings assigned to them in a particular political economy’ (Arrigo 2006, p. 48). Consequently, consumption signified nothing real other than the hyper-​fictionalized fear that it nurtured for a simulated society of sign-​messaging captives. Indeed, in the society of simulacra,

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‘there [was] no longer a real to be recovered behind the illusion [and, thus,] there [was] no illusion either’ (Best, 1989, p. 37). Given these harm-​sustaining conditions of reification, human capital’s potential as ontologically recoverable and its possibility as epistemologically transformative was obliterated.

Section II: on the interdependent forces of reification and their interrelated forms of risk management What are the psychoanalytic and jurisprudential forces of reification, and how do their interdependencies produce interrelated forms (i.e. reified forms) of risk management? Thus far, we have explained how risk and its management have always been the currency of interrelating. In support of this claim, we described three risk-​as-​currency transitions. In each instance, a set of historical currents and corresponding cultural intensities helped to physicalize the contingency of subjectivity through the process of reification. Moreover, as we posited, excessive investments in the abstractions of human capital can be (and have been) the source of ontological and epistemological harms, expressed through reductive limits to being (human recovery) and repressive denials of becoming (human transformation). Problematically, the extremities of these harms can be (and have been) normalized through the hyper-​commodification of that which is reified as risk. During the period of modernity the philosophy of risk currency was best expressed through the Marxist inversion of having over being. Human capital was reduced to and equated with commodity fetishism when use-​value was ontologically and epistemologically recalibrated as risk capital. During the late modern era, the currency in risk governance further abstracted human capital. For the Situationist, this abstraction depicted a culture that elevated the virtual realm of appearing over the visceral realm of having. During postmodernity, a third transition emerged. As delineated by the hyper-​realists, the currency of managed human risk was predicated on the ascendancy of sign-​systems and their messaging that displaced the appearances of, for, and about the same. It is our contention that each era reified a culture of (crime) control. These are the crimes that reduce and repress subjectivity and the interrelatedness that follows when harms to human capital prevail. What we have yet to examine are the psychoanalytic justifications and jurisprudential dynamics on which the reification process depends,

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sufficient to produce through its interdependent forces the forms of risk governance that we previously enumerated. In order to address the philosophical contours of this matter, it is necessary to review how human subjectivity emerges in consciousness, gets encoded in thought and is inhabited through action. As we subsequently argue, these forces are symbolic, linguistic, material, and cultural in essential complexion and iterative composition. At the outset, we draw attention to four assumptions. These suppositions ground our perspective on the relations of humanness and the risk society thesis. First, the unconscious (i.e. the psychic apparatus, the topography of the mind) is structured like a language replete with laws of semiotic-​exchange (of meaning-​making and of interrelating). Second, human subjectivity (for the kept and their keepers, for the watched and their watchers) can only ever be politicized (e.g. commodified, territorialized), given that a master discourse (a preferred system of communication) pre-​figures (appears in) and pre-​codes (composes) conscious thought. Third, power and its diffusion (e.g. epistemological standpoints) inhabit subjectivity’s politicization, producing technologies (e.g. reservoirs of knowledge and regimes of truth, systems of thought and bodies of being/​becoming). Fourth, the interdependent operation of these forces generates reified forms of risk society governance that increasingly abstract human relatedness. Put differently, the mobilization and activation of these interdependencies both nurture and sustain the cultural conditions of relational control. The first assumption maintains that our conscious human experiences are mediated by unconscious (and therefore pre-​reflective) laws. According to Lacan (1977), these laws indicate that the unconscious is structured like a language. Stated otherwise, our conscious sense of self (who we claim to be) and our conscious sense of society (what we claim to know) are both source and product of an unspoken discourse that is itself a master code or a coordinated language system of preferred meaning-​making. For Lacan, this code spoke the subject. It pre-​figured (symbolized) consciousness and the manifold depictions of conscious human experience. Lacan (1981) further maintained that this unconscious code that spoke the subject communicated lack, (i.e. the incompleteness in being; the absence in knowing) awaiting yet-​to-​be symbolization. These symbolizations are the unimagined codes of sense and registers of meaning that pre-​form that which has yet to appear in consciousness. They (these symbolizations) are un-​representable, but only for the moment. The un-​representable signifies more of what could be (human productive recovery and transformation) rather than

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the subjectivity of lack (human incompleteness) in consciousness (e.g. Deleuze & Guattari, 1987). The second assumption asserts that subjectivity is always politicized. If the laws of the unconscious symbolize human experience through a master discourse that pre-​figures consciousness as lack (in being and in knowing), then entire systems of communicating are made present in consciousness while others are suspended, silenced, and even rendered absent. But, how does this metaphysical process of meaning-​ making occur in consciousness whose source is the unconscious and its symbolizations? For Derrida (1973), the answer to this question was found in deconstructionist philosophy. Deconstruction maintains that the structure of speech and writing is derived from terms or values in binary opposition. These oppositions reveal and conceal, make present and postpone. The term order defers the value disorder. The expression competent to stand trial displaces the utterance incompetent to stand trial. The phrase peaceful resolution obscures the value violent conflict. What is privileged in each instance is the logocentric (i.e. dominating, territorializing) basis on which thought depends if shared communicative action is to follow. These dependencies consist of the presumed unambiguous meanings, the taken-​for-​granted assumptions, and the preferred hierarchies of Western (i.e. Eurocentric) civilization (Derrida, 1977). Returning to our examples, what is problematic about such dependencies and deferrals is that alternative and fuller meaning resides within the unexamined interdependencies of such binaries (Derrida, 1977, 1992). By extension, this includes the novel and awaiting forms of social relating to which they (these interdependent meanings) would otherwise direct human choice and collective action (Donati, 2012). Derrida’s (1992) ontological and epistemological perspective on the interrelatedness of being and meaning is further described in his theory on the ‘reversal of hierarchies’ (as cited in Balkin, 1987, pp. 743–​5) In these reversals, being and meaning are reconstituted much like the slave who stands above the master. However, Derrida asks how relatedness is experienced when that which was rendered absent is now made present and acknowledged as that on which interrelatedness both depends and defers?7 The third assumption contends that power’s diffusion is located in and through these politics (these standpoints) and languages (these symbolizations), producing technologies (i.e. bodies of knowledge, and correspondingly, bodies of being) (Foucault, 1973). The proliferation of these technologies yields disciplinary/​disciplining truths (e.g. in the social, behavioral and informational sciences) and regimes of comportment (for the kept and their keepers, for the watched and

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their watchers). This is what Foucault (1977, p. 194) meant when he reasoned that power produces; it produces reality; it produces domains of objects and rituals of truth’. In this important respect, then, power’s diffusion guarantees a type of microphysics and a form of biopolitics (Foucault, 1980). The former reduces being and becoming to the panoptics of suspicion; the latter represses the relations of humanness through the hermeneutics of risk society governance. Both of these neutralization techniques reenact and reproduce technologies of the marketplace (as shared truth) and subjugate technologies of subjectivity (as negative freedom). Indeed, as Foucault (1980, p. 39) observed, ‘in thinking of the mechanisms of power, I am thinking rather of its capillary forms of existence, the point where power reaches into the very grain of individuals, touches their bodies, and inserts itself into their actions and attitudes, their discourse, learning processes, and everyday lives’. This is how power manufactures bodies (of knowing and of being) that are themselves ‘docile,’ that are bodies of ‘abject utility’, in which the subject becomes nothing more than a ‘mere functionary of the State’ (Foucault, 1977, p. 210). Under these conditions, the possibilities of co-​habiting the space of relational growth and change (i.e. the space of emergent human restoration and dynamic human transformation) are reduced to finite processes of interrelating and fixed methods of coexisting. The fourth assumption maintains that when these forces of reification operate in tandem, then the interdependencies that follow reproduce interrelated forms of (co)existence. We have argued that these forms are abstractions of human capital linked to different currencies in risk management that have been (and are) culturalized. When these reified abstractions are in states of excess, then they (these excesses) nurture the psychoanalytic and sustain the jurisprudential conditions in which cultures of ontological and epistemological control can, have and do thrive. Given these four operating assumptions, we can now better specify how subjectivity as cultural currency to be managed, and as abstracted risk to be domesticated, emerges in consciousness, finds narrative coherence in thought and is embodied through purposeful action. Figure 1.1 depicts the psychoanalytic and jurisprudential forces of risk currency on which reification depends sufficient to produce forms of inverted subjectivity and their human capital sequelae (i.e. ontic and epistemic harms). These forces are symbolic, linguistic, material and cultural in essential complexion and interrelated composition. As Figure 1.1 illustrates, these forces consist of the mind’s laws, subjectivity’s politics, power’s microphysics and risk’s

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Figure 1.1: The forces of risk currency and their reified forms of abstracted subjectivity

Symbolic

Linguistic

The mind’s laws Sign-exchange-value Realm of the image Conjured as ‘lack’ Incompleteness

Subjectivity’s politics Realm of speech/writing Binary oppositions Logocentrism Finalization

Subjectivity abstracted Having/being Appearing/having Sign-messaging/appearing

Cultural

Material

Risk’s governance Semiotic captivity Mass-marketed fictions Docility in thought Complacency in action Freedom’s negation

Power’s microphysics Realm of the body Lived history Disciplinary systems Disciplining technologies

governance. The interdependencies of these forces reproduce forms of abstracted subjectivity. We note further that bi-​directional arrows extend beyond the forces of risk currency and their reified forms of conditional (co)existence. These arrows signify that the possibilities of emergent ontology and novel epistemology remain, at present, un-​representable. The various bi-​directional arrows located among the forces of reification signal the constitutive forming or assembling of subjectivity (including inter-​subjectivity and other forms of human exchange) (DeLanda, 2006). The stabilization of these forces (by way of the unconscious and through subjectivity, by way of power and

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through risk currency management) reveals the ontological complexion and epistemological composition of subjectivity. This, then, is how human capital emerges in consciousness, is encoded in thought and is inhabited through purposeful action. Once historicized (i.e. lived) and culturalized (i.e. ritualized), the combinatory effects of these forces reproduce reified forms of subjectivity.

The symbolic forces of risk currency: on the mind’s jurisprudence The symbolic forces of risk currency consist of sign-​exchange values. Sign-​exchange-​value refers to the images or representations that are mobilized and activated in the unconscious. These forces speak the subject, and by extension, breathe vitality into the meaning of subjectivity. Although the language of these images (i.e. snapshots in our psyche) is always divided, fragmented and incomplete, they (these symbolizations) nonetheless pre-​figure and pre-​compose discourse and its governing forms of coexistence. These forms of relatedness extend to and from the kept and their keepers, as well as to and from the watched and their watchers. To illustrate, consider the following question. What representations are conjured (i.e. consumed and reproduced) within the topography of the mind (within individual and collective consciousness) when it comes to adolescent delinquency, mentally disordered offending and sexual predation? If the summoned representations tell the story of aberrance, disease and dangerousness (i.e. the reification of subjectivity as the lack) then much is missing from such symbolizations. This is the subject symbolized in consciousness as shadow (Plato, 2008), as an incompleteness. Conversely, when relatedness is conjured as strange human potential, then speech is generated, transmitted and exchanged, which, although incomplete, affirms the productive desire of awaiting subjectivity (Deleuze & Guattari, 1987).

The linguistic forces of risk currency: on subjectivity’s politics The linguistic forces of risk currency consist of vitalized sign-​ exchange-​value, emanating from the unconscious. These vitalizations assume the form of speech, including the written word. Because the symbolic realm is replete with partial representations, the narratives that emerge from these conjured imaginings are likewise abbreviated and unfinished. Indeed, the conscious accounts that follow from these symbolizations communicate less than (produce less about) who we are or could become. What is produced through this semiotic process is the naming and codifying of human capital manifested by way of the

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dependencies of terms in binary opposition. As an insistent narrative, this preferred text enters the marketplace of sign-​exchange-​value and recounts the struggle of subjectivity in its own governing voice. This voice tells of risk and its management through the epistemology of logocentrism and the metaphysics of presence (Derrida, 1973, 1977, 1992). The metaphysics of presence implies that what is most readily accessible to consciousness is that which is fundamentally defined as good and virtuous. Thus, the values attached to these discernible and manifest notions are rendered true and absolute. However, under these textual conditions, the narrative that is produced and circulated is one that tends toward finalization (Bakhtin, 1982). This is subjectivity as mere shadow in words. When these fragmented renditions of truth, progress, science and human potential are spoken and written, then the possibilities for articulating alternative narratives are forestalled or, worst, foreclosed (Deleuze, 1983). As such, the texts for and about relatedness as recovering and transforming, as emergent possibilities in being and becoming, are deferred. These postponed texts await dialogical recognition, expression and emancipation.8

The material forces of risk currency: on power’s microphysics The material forces of risk currency inhabit the favored texts of human relatedness—​and all of their preferences and partialities—​as embodied truths and as lived histories. These truths function as systems of thought; these histories, as bodies of knowledge (e.g. in psychiatry, law, penology, social work, education). They (these truths and histories) domesticate and discipline subjectivity. This domestication and disciplining is power mobilized corporeally. Bio-​power depends on technologies that de-​pathologize (Foucault, 1965, 1977) and territorialize (Deleuze, 1983) being/​becoming. Under these material conditions, difference is vanquished, identity is homogenized and relatedness is sanitized.9 This is subjectivity as mere shadow in its ontic and epistemic embodiments. Indeed, as Fromm (1994) cautioned when diagnosing the status of captured human capital: The individual ceases to be [and] adopts entirely the kind of personality offered to him [or her] by the cultural patterns; and [the individual] therefore becomes exactly as all others are and as they expect [the individual] to be. The discrepancy between ‘I’ and the world disappears and with it the conscious fear of aloneness and powerlessness … [t]‌he person who gives up his [or her] individual self becomes

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an automaton, identical with millions of other automatons … [and] need not feel alone or anxious anymore. But the price [the individual] pays, however, is high; it is the loss of the self. (p. 184) Under these material conditions, then, subjects are rendered docile bodies amenable to the will of the state (Foucault, 1977). What is normalized by way of this domestication and disciplining is power as harm.

The cultural forces of risk currency: on risk’s governance The cultural forces of risk currency consist of replication and ritualization. These are the activities that reproduce and reaffirm an assemblage: dominant images (i.e. the realm of sign-​exchange-​values), texts (i.e. the realm of speech and writing), and systems of power/​truth (i.e. the realm of the body). Given the partial portraits, incomplete narratives and disembodied forms of knowledge that govern human capital, abstracted representations of each prevailed in the modern, late modern and postmodern eras. During each age, the ontic and epistemic sequelae of such cultural tendencies reified forms of subjectivity derived from semiotic captivity, mass-​marketed fictions, docility in thought, complacency in action and freedom’s negation. When all that subjectivity constitutes and is constituted as, is reduced to and repressed by all that subjectivity possesses, appears to be, or is, through its sign-​ messaging, then much of recovery (in being) and transformation (in becoming) is, and can only ever be, shadow.

Section III: the ultramodern era of pre-​crime, post-​criminology, and of risk management What is the currency in human relating and of abstracting subjectivity in the ultramodern age, and what are the ontological and epistemological harms that follow from excessive investments in this era’s reified forms of risk management? The previous section detailed the psychoanalytic and jurisprudential forces of reification and it explained how the interdependencies of these forces reproduce interrelated forms (i.e. reified forms) of risk currency and management. Since the dawning of the risk society, three forms of risk currency, of human capital as trade, have been physicalized. As we noted, in each instance the contingency of these forms was linked to a distinct set of historical and cultural dynamics.

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Problematically, these dynamics and the presidencies that each risk governance era spawned, have led to the increasing abstraction of existence, and with it, of relational humanity. For Marx and his critique of industrial capitalism, the inversion in being and becoming could be synopsized as follows: If all that I am is all that I have, then who am I if I have nothing? For Debord and the Situationists’ late modern appraisal of monopoly capitalism, the abstraction of being and becoming could be summarized as follows: If all that I am is all that my appearances suggest that I am, then who am I if I have none of these façades or derivatives on which to depict my humanity? For Baudriallard and the hyper-​realists’ postmodern assessment of simulated capitalism, the inversion in being and becoming could be restated as follows: If all that I am is all that my sign-​systems of replicated meaning-​making signify that I am, then who am I without these simulacra? As we explained, excessive investments in each of these reified conversions established ontological and epistemological harms, expressed through reductive limits to being (human recovery) and repressive denials of becoming (human transformation). The sustained harms of each conversion helped to make evident culture(s) of (crime) control. Thus, the question is begged about the current age, the age of a new people-​making. In this age, subjectivity is reified by the forces of yet another abstraction. At least, this is the thesis to which we now direct our attention and on which we speculatively conclude this chapter. Moreover, this is the thesis on which the volume’s contributors undoubtedly will conjecture. To put the matter plainly, then, what assembled forms does risk-​as-​currency assume in the ultramodern age? In this age, digital interconnectivity is a cultural medium and message. The medium reifies and the message commodifies. Subjectivity is symbolized, constructed and circulated as a ‘data dividual’ (Deleuze, 1995, pp. 181–​2). The management of this form of human abstraction and the risk society that is its tangible support are made manifest through the trade in ‘surveillance capitalism’ that physicalizes a ubiquitous ‘information civilization’ (Zuboff, 2015, p. 75). As we explain, the conditions of this trade are personified in the culture of control that this ubiquity reproduces. As a matter of speculative philosophy, the conditions of this culture consist of ‘pre-​crime, post-​ criminology and the captivity of ultramodern desire’ (Arrigo, Sellers & Sostakas, 2020, p. 497). Pre-​crime’s ontology seeks the control of bodies (i.e. would-​be offenders) engaged in geo-​temporal-​spatial patterns of would-​be offending. Pre-​crime’s epistemology endeavors to advance threat assessment knowledge and risk-​avoidance analytics. Pre-​crime’s

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ethic extolls the duties of precaution and prevention, and the virtues of calculation and prediction. However, pre-​crime’s trade in risk management and of subjectivity’s reified abstraction normalizes, in rapacious fashion, ‘the creeping criminalization of everyday life’ (Presdee, 2001, p. 159). This criminalization is yet another inversion of subjectivity, of one’s humanity, relegated to the status of risk in-​ formation abstraction. To state it otherwise, we are reduced to and repressed by our computer-​generated risk algorithms, and to the technologies of the marketplace (i.e. computer-​generated algorithms) that calculate and manage these risks. In an era of pre-​crime, we all undergo citizen-​suspect dataveillance. Indeed, this designation is our new master signifier. Under conditions of pre-​crime, much of our shared humanity is deferred and remains absent. Pre-​crime’s ontology, epistemology and ethic help to usher in the domain of post-​criminology. After the study of crime or outside the remit of criminal behavior is the study of securitization. Data science and digital technology are pivotal to normalizing and nurturing this crime control industry. Consequently, what this means is that predictive policing, actuarial justice and surveillance penology are the in-​formational strategies (i.e. algorithmic data collecting and/​ or cataloging techniques) employed by regulatory institutions to achieve not Foucault’s (1977) disciplinary society but Deleuze’s (1995) societies of control. In the Deleuzian schema, assemblages of choice and freedom, autonomy and privacy, identity and community (all qualities of restoration and transformation) are de-​contextualized and de-​personalized. They are reconfigured by the logic of cyber-​passwords and redesigned by the laws of cyber-​profiling. When this logic and these laws are in states of excess, then hyper-​ securitization ensues. Hyper-​securitization extends from Foucault’s panoptics (i.e. the few see the many), to Mathiesen’s synoptics (i.e. the viewer society, the many see the few), to Bigo’s banoptics (i.e. the few and the many are digitally profiled). These permeating optics are the harm-​generating and injury-​sustaining conditions of (co)existence. Within these conditions of relatedness, the fullness of subjectivity vanishes into the abstraction of ‘sign-​optic exchange-​ value’ (Arrigo, Sellers & Sostakas, 2020, p. 510). In addition, within these shadows of risk’s governance, pervasive harm (e.g. de-​vitalization, finalization) prevails. This harm deadens all senses as it gives sway to the currency of data doubles.10 This currency is the captivity of the ultramodern age. Located here are mutating in-​formational sign-​optics. This captivity signifies the end of being

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and becoming, and with it, society’s bio-​digital imprisonment. Both harms are totalizing. We posit, and our contributors conjecture, that the current era reproduces a fourth (and thus new) abstraction of subjectivity. Perhaps unsurprisingly, this era represents yet another fragmented social-​ ontology. This incompleteness can be stated thusly: If all that I am is all that my in-​formation digital subjectivity algorithmically signifies that I am, then who am I, who are we, without such computational meanings? This, then, is the currency in human relating and of abstracting subjectivity in the ultramodern age.

Conclusion This chapter has been an exercise in philosophical criminology. The necessity of this exercise was accounted for by drawing attention to the risk society thesis.11 As we argued, risk and its management have always been the currency of human relating. Moreover, this relatedness finds expression in symbolic, linguistic and material forms of (co)existence. Excessive investments in these forms can be (and have been) the source of ontological and epistemological captivity, expressed through harms of reduction (i.e. limits on being) and repression (i.e. denials on becoming). In the extreme, these harms can be (and have been) culturalized through the hyper-​control of that which is reified as risk. In support of this thesis, we explained how risk-​as-​currency (i.e. the management of human relating) is both historically contingent and made manifest through the process of reification, and we reviewed reification’s modern, late modern and postmodern risk-​as-​currency incarnations. Additionally, we specified what the psychoanalytic and jurisprudential forces of reification are, and we accounted for how their interdependencies produce interrelated forms (i.e. reified or physicalized forms) of risk management. Finally, we speculated on what the currency of human relating and of economic exchange is in the current or ultramodern era. We posited that ultramodernity signifies a fourth transition in risk management and of people-​making. With this conversion, it is surveillance capitalism that nurtures and sustains an information civilization. The conditions of this risk governance culture consist of pre-​crime analytics, post-​criminology dataveillance and hyper-​securitization optics. In order to elucidate this claim, we outlined the de-​vitalizing and finalizing harm that follows from excessively investing in the present era’s reified forms of risk management.

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Notes 1

2

3

4

5

6

7

As we have previously delineated, de-​vitalization and finalization are maladaptive and dysfunctional ‘conditions of human relatedness in which reciprocal consciousness, inter-​subjectivity, and shared power are neutralized (i.e. forestalled and/​or foreclosed)’ (Arrigo & Sellers, 2018, p. 81). De-​vitalization manifests itself when the discursive symbols, discourses and technologies of (co)existence preclude the project of mutual (i.e. dialectical) struggle. Finalization manifests itself when the symbols, discourses and technologies of social reality exclude the experiences of collective (i.e. dialogical) overcoming. This project and these experiences constitute necessary ontological flows and epistemological fluctuations for interdependent human flourishing to occur. This view is consistent with, and an elaboration of, Bigo’s (2008, p. 10) critique of ‘globalized (in)security’. The ‘industries of crime control’ (Christie, 2000, pp. 111–​142, 193–​201) are cultural artifacts that depict historical transitions from the modern, late modern and postmodern eras (e.g. Sloop, 1996; Brown, 2009). Power as harm finds expression in two principal forms. These forms include harms of reduction and harms of repression (Henry & Milovanovic, 1996). Harms of reduction occur when an individual’s ability to make a difference productively is forestalled through the choices/​actions of some system’s agent/​representative. For example, an ex-​offender in recovery may be prevented from earning a living wage or completing a college degree because of an addiction relapse and criminal recidivism history. The subject is rendered less than what he or she could be (i.e. as in further restored, recovered or healed in being, financially or educationally). Harms of repression occur when the subject’s ability to be different dynamically is made inconceivable given the choices/​actions of some system’s agent/​representative. Here, the subject’s innovative representational possibilities are inexpressible because of one’s reified status as an ex-​offender in substance abuse treatment. Consequently, the potential options of inhabiting one’s difference as being otherwise, or as becoming are rendered unimaginable given one’s already marginalized and finite standing. This notion is originally derived from Marx’s (1990) value-​theory of labor (see also Neocleous, 2007). More specifically, as Lukács (1971, p. 100) theorized, reification ‘stamps its imprint upon the whole [of one’s] consciousness. ... [The subject’s] qualities and abilities are no longer an organic part of [his or her] personality, they are things which [one] can “own” or “dispose of ” like the various objects of the external world. And there is no natural form in which human relations can be cast, no way in which [one] can bring his [or her] physical and psychic “qualities” into play without [them] being subjected increasingly to this reifying process’. Stahl (2011) maintains that the reification process implicates four components of human relatedness. These include the socially constructed qualities of objects (principally as commodities), the relatedness of coexistence, one’s relatedness to oneself, and the relatedness between individual subjects and society proper. Through the reification process, the qualities of objects, human subjects and social relations become ‘thing-​like’ (Baldwin, 2009, p. 381). This view is consistent with Nietzsche’s (1966) notion of transpraxis. Transpraxis retains the Marxist conviction that theory and practice need to be linked to produce change; however, it also addresses the role of language when instantiating such restorative and transformative forms of (co)existence. As method, transpraxis depends on and defers to the dialectics of linguistic struggle in which the new,

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8

9

10

11

reconstituted order does not recreate conditions that alienate, oppress or exclude. Transpraxis is a deliberate and affirmative attempt not simply to reverse hierarchies but instead, to affirm while renouncing harm (e.g. the power to limit being and to deny becoming). Transpraxis validates (affirms) in the act of resistance (negation), so that new values (epistemological standpoints) and meanings (ontological categories) can emerge in consciousness. Central to the restorative and transformative properties of transpraxis is speech, words, grammar and how we talk about (and then act upon) these emergent values and novel meanings. The structuration of dialogical expression is ‘unfinalizable’ (Bahktin, 1982, pp. 279–​280). This structuration is always in-​process and fluid. Thus, dialogical meaning is dynamic rather than static, open-​ended rather than closed-​minded. Elsewhere (Arrigo & Sellers, 2018) we have raised concerns about prospects for restoration and transformation, given the presence of disciplinary systems and disciplining technologies that de-​pathologize and territorialiize. Spaces of co-​ existence that exemplify these concerns include ‘[c]‌ivil commitment hearings, pre-​trial competency evaluations, custody classification reviews, parole board hearings, and post-​sentencing planning panels. … These settings and contexts exemplify how human relatedness is … forestalled through rituals and ceremonies that neutralize the reciprocity of shared experience (i.e. including the project of mutual struggle)’ (p. 95, n. 7). The notion of a data double is traceable to Deleuze and Guattari’s (1994) development of assemblage theory (see also DeLanda, 2006). In the sociology of surveillance, this notion has been amplified by Haggerty and Ericson (2000) in their characterization of the surveillant assemblage. The surveillant assemblage is formed from Foucauldian panoptical processes and functions by ‘abstracting human bodies from their territorial settings’ and locating these bodies into ‘discrete informational flows that are later reassembled into subsequent “data doubles” ’ (p. 605). Other scholars have examined several of the socio-​theoretical dimensions of the risk society thesis. The critical cosmopolitanism of Delanty (2009), the structuration theory of Giddens (1991), and the reflexive sociology of Beck (2009) are all noteworthy. We acknowledge the contributions made by each scholar. However, this chapter represents the outline of a different way to approach the risk society thesis.

References Alexander, M. (2011). The New Jim Crow: Mass Incarceration in the Age of Color Blindness. New York, NY: The Free Press. Aristotle. (1976). Ethics. J.A.K. Thomson (Trans.). New York, NY: Penguin. Arrigo, B.A. (2006). The ontology of crime: On the construction of the real, the image, and the hyper-​real. In B.A. Arrigo & C.R. Williams (eds.) Philosophy, Crime, and Criminology, Urbana, IL and Chicago, IL: University of Illinois Press (pp. 41–​73). Arrigo, B.A. (2015). Responding to crime: Psychological jurisprudence, normative philosophy, and trans-​desistance theory. Criminal Justice and Behavior: An International Journal 42: 7–​18.

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Arrigo, B.A. & Milovanovic, D. (2009). Revolution in Penology: Rethinking the Society of Captives. New York, NY: Rowman and Littlefield. Arrigo, B.A. & Polizzi, D. (2018). Introduction to the Special Issue: On the laws of captivity. New Criminal Law Review: An Interdisciplinary and International Journal 21 (4): 483–​91. Arrigo, B.A. & Sellers B.G. (2018). Psychological jurisprudence and the relational problems of de-​vitalization and finalization: Rethinking the society of captives thesis. In A. Mills & K. Kendall (eds.) Mental Health in Prisons: Critical Perspectives on Treatment and Confinement. London, UK: Palgrave Macmillan (pp. 73–​101). Arrigo, B.A., Bersot, H.Y. & Sellers, B.G. (2011). The Ethics of Total Confinement: A Critique of Madness, Citizenship, and Social Justice. New York, NY: Oxford University Press. Arrigo, B.A., Sellers, B.G. & Sostakas, J. (2020). Pre-​crime, post-​ criminology, and the captivity of ultramodern desire. International Journal of the Semiotics of Law 33 (2): 497–​514. Bakhtin, M. (1982). The Dialogic Imagination: Four Essays. Austin, TX: University of Texas Press. Baldwin, J. (2009). Exchange and subjectivity, commodity and gift. Semiotica 173: 377–​96. Balkin, J.M. (1987). Deconstructive practice and legal theory. Yale Law Journal 96 (4): 743–​86. Baudrillard, J. (1972). For a Critique of the Political Economy of the Sign. St. Louis, MO: Telos Press. Baudrillard, J. (1983). Simulations. New York, NY: Semiotext(e). Baudrillard, J. (1993). Symbolic Exchange and Death. London, UK: Sage. Beck, U. (2009). World at Risk. Cambridge, UK: Polity Press. Berger, P. & Luckmann, T. (1966) The Social Construction of Reality: A Treatise in the Sociology of Knowledge. New York, NY: Anchor/​Doubleday. Bersot, H.Y. & Arrigo, B.A. (2015). Responding to sex offenders: Empirical findings, judicial decision-​making, and virtue jurisprudence. Criminal Justice and Behavior: An International Journal 42: 32–​44. Best, S. (1989). The commodification of reality and the reality of commodification: Jean Baudrillard and post-​modernism. Current Perspectives in Social Theory 9: 23–​50. Bigo, D. (2008). Globalized (in)security: The field and the ban-​opticon. In D. Bigo & A. Tsoukala (eds.) Terror, Insecurity and Liberty: Illiberal Practices of Liberal Regimes after 9/​11. Abingdon, UK: Routledge (pp. 10–​49). Brown, M. (2009). The Culture of Punishment: Prison, Society, and Spectacle. New York, NY: New York University Press.

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Christie, N. (2000). Crime Control as Industry: Towards Gulags, Western Style (3rd ed.). New York, NY: Routledge. Cornell, D. (1991). Beyond Accommodation: Ethical Feminism, Deconstruction, and the Law. New York, NY: Routledge. Day, J. (2013). Corrections and Collections: Architecture for Art and Crime. New York, NY: Routledge. Debord, G. (1983). Society of the Spectacle. Detroit, MI: Black and Red. Debord, G. (1998). Comments on the Society of the Spectacle. London, UK: Verso. DeLanda, M. (2006). A New Philosophy of Society: Assemblage Theory and Social Complexity. New York, NY: Continuum Books. Delanty, G. (2009). The Cosmopolitan Imagination: The Renewal of Critical Social Theory. New York: Cambridge University Press. Deleuze, G. (1983). Nietzsche and Philosophy. New York, NY: Columbia University Press. Deleuze, G. (1995). Postscript on control societies. In G. Deleuze (ed.) Negotiations. New York, NY: Columbia University Press (pp. 177–​82). Deleuze, G. & Guattari, F. (1987) A Thousand Plateaus: Capitalism and Schizophrenia. Minneapolis, MN: University of Minnesota Press. Deleuze, G. & Guattari, F. (1994). What is Philosophy? New York, NY: Columbia University Press. Der r ida, J. (1973). Speech and Other Phenomena. Evanston, IL: Northwestern University Press. Derrida, J. (1977). Of Grammatology. Baltimore, MD: Johns Hopkins University Press. Derrida, J. (1992). Force of law: The mystical foundation of authority. In D. Cornell, M. Rosenfeld, & D. Carlson (eds.) Deconstruction and the Possibility of Justice. New York, NY: Routledge. (pp. 3–​67). Donati, P. (2012). Relational Sociology: A New Paradigm for the Social Sciences. New York, NY: Routledge. Ericson, R.V. & Haggerty, K. (1997). Policing the Risk Society. Toronto, CA: University of Toronto Press. Foucault, M. (1973). The Order of Things. New York, NY: Vintage. Foucault, M. (1965). Madness and Civilization: A History of Insanity in the Age of Reason. New York, NY: Vintage. Foucault, M. (1977). Discipline and Punish: The Birth of a Prison. New York, NY: Pantheon. Foucault, M. (1980). Power/​Knowledge: Selected Interviews and Other Writings, 1972–​1977. (C. Gordon, ed.). New York, NY: Vintage. Fromm, E. (1994). Escape from Freedom. New York, NY: Henry Holt and Company.

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Giddens, A. (1991). The Consequences of Modernity. Stanford, CA: Stanford University Press. Guenther, L. (2013). Solitary Confinement: Social Death and its Afterlives. Minneapolis, MN: University of Minnesota Press. Haggerty, K. & Ericson, R. (2000). The surveillant assemblage. British Journal of Sociology 51 (4): 605–​22. Hardt, M. & Negri, A. (2004). Multitude: War and Democracy in the Age of Empire. New York, NY: Penguin Press. Henry, S. & Milovanovic, D. (1996). Constitutive Criminology: Beyond Postmodernism. London, UK: Sage. Henry, S. & Milovanovic, D. (1999). Constitutive Criminology at Work: Applications to Crime and Justice. Albany, NY: SUNY Press. Johnston, N. (2006). Forms of Constraint: A History of Prison Architecture. Urbana-Champaign IL: University of Illinois Press. Knabb, K. (ed.) (2007). Situationist International Anthology. Berkeley, CA: Bureau of Public Secrets. Kristeva, J. (1984). Revolution in Poetic Language. New York, NY: Columbia University Press. Lacan, J. (1977). Ecrits: A Selection. New York, NY: W.W. Norton. Lacan, J. (1981). The Four Fundamental Concepts of Psychoanalysis. New York, NY: W.W. Norton. Lukács, G. (1971). History of Class Consciousness. Cambridge, MA: The MIT Press. Marx, K. (1990). Capital. Volume I. London, UK: Penguin Books. Marx, K. (1995). The Poverty of Philosophy. New York, NY: Prometheus Books. Milovanovic, D. & Henry, S. (2001). Constitutive definition of crime. In S. Henry & M. Lanier (eds.) What is Crime?: Controversies Over the Nature of Crime and What to Do about It Lanham, MD: Rowman & Littlefield (pp. 165–​78). Neocleous, M. (2007). Security, Commodity, Fetishism. Critique 35 (3): 339–​55. Nietzsche, F.W. (1886/​1966). Beyond Good and Evil: Prelude to a Philosophy of the Future (new ed.) (Walter Kaufmann, ed.). New York, NY: Vintage. O’Malley, P. (2004). Risk, Uncertainty, and Government. London, UK: The Glasshouse Press. Plato. (2008). Republic. R. Waterfield (Trans.) New York, NY: Oxford University Press. Presdee, M. (2001). Cultural Criminology and the Carnival of Crime. Abingdon, UK: Routledge.

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Reiter, K. & Koenig, A. (2015). Extreme Punishment: Comparative Studies in Detention, Incarceration and Solitary Confinement. London, UK: Palgrave Macmillan. Simon, J. (2009). Governing Through Crime: How the War on Crime Transformed American Democracy and Created a Culture of Fear. New York, NY: Oxford University Press. Sloop, J. (1996). The Cultural Prison: Discourse, Prisoners and Punishment. Tuscaloosa, AL: University of Alabama Press. Stahl, T. (2011). Verdinglichung als Pathologie zweiter Ordnung. Deutsche Zeitschrift für Philosophie 59 (5): 731–​46. Vaneigem, R. (2012). The Revolution of Everyday Life. Oakland, CA: PM Press. Zuboff, S. (2015). Big other: surveillance capitalism and the prospects of an information civilization, Journal of Information Technology 30: 75–​89.

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2

The Security Society: On Power, Surveillance and Punishments Marc Schuilenburg

Introduction A couple of years ago, on a rainy Sunday afternoon, at 1:30 PM, I went to a Sparta Rotterdam football game. Never before had I felt so conscious of the security regimes that permeated my movement across the city. I’ve supported the Dutch football club Sparta Rotterdam for many decades—​I’m a season ticket holder. Just as I was leaving for the Sunday game, a policeman patrolling the street by car told me that he was on the lookout for somebody who looked just like me—​a handsome, dark haired guy with a slightly overdue shave. According to the Dutch predictive policing system, a data-​driven system that predicts crimes through statistics based on different data sources, a number of burglars are active in my neighborhood. Convincing him that I wasn’t the burglar he was looking for wasn’t too hard, but the incident played on my mind as I made my way to the game. I started noticing the number of sound sensors and digital cameras put up by the local government in my neighborhood. I’d just read an article about the implementation of facial recognition systems, and I imagined the images of my face being processed by a databank and compared with the photos of thousands of criminals. Around half past one, I went into the local shop to grab something to eat during the game. A sticker in the window told me that this shop participated in the Collective Shop Ban project—​misbehave here (steal a candy bar, for example) and I’d be banned from the hundreds

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of shops, banks, restaurants and cinemas participating in the project. Deciding which route to take, the navigation app on my smart phone advised me to use the subway instead of the bus to the stadium of Sparta Rotterdam. By taking this route, I avoid city areas that have high crime intensity and are identified as ‘hotspots’ or ‘hotspot areas’. As I walked to the nearby subway, I noticed the municipality installed bars across the middle of benches as a way to stop homeless people from sleeping on them. By taking the subway, I entered another highly controlled zone. Rotterdam’s subway system requires passengers to use an electronic pass, preferably personalized (an anonymous one expires every year), which according to the promotion team is ‘easy, fast, and safe’. Rotterdam calls itself a smart city and in order to improve city services, it stores my travel movements in a central database. Having finally arrived at the stadium at 1:55 PM, I used my season ticket, also an electronic card, to enter via the automatic gates. Anyone committing an offense in the stadium can be barred, and stadium bans for up to a lifetime are one of the ways stewards try to keep order during the games. By the time the game began, in in less than half an hour, I had crossed—​at least—​six totally different ‘spaces of security’. In recent years, literature focusing on the issue of urban safety and the related issues of ‘policing’, ‘surveillance’ and ‘fear of crime’ have increasingly been discussed under the broader concept of ‘security’ (e.g. Johnston & Shearing, 2003; Loader & Walker, 2007; Zedner, 2009; Schuilenburg, 2015b; Crawford & Hutchinson, 2016; Dodsworth, 2019). Despite the fact that security has multiple meanings, and that it is used in a huge variety of contexts (Waldron, 2011; Hamilton, 2013), considerations of security have become increasingly about the attempt to control, avoid or prevent criminality and disorder in our urban environment. Jennifer Wood and Clifford Shearing claim that ‘it is the governance of security, through crime, that preoccupies most of our efforts’ (2007, p. 5). The focus on crime and disorder followed arguments on the limits of the sovereign state power to maintain public order and facilitate collective action (Beck, 1992; Castells, 1996; Bauman, 2000). The consequence of all this is that the police, which in the not so distant past were seen as the ‘sacred’ foundation of society (Banton, 1964), are only one of many security agents and that an increasing number of other players have assumed tasks and responsibilities relating to our security, from security guards protecting shopping malls and football stadiums to armed residents patrolling the streets of their neighborhood. The securitization of our society has been accompanied by a range of new (1) forms of surveillance,

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(2) relations of power and (3) punishments. Therefore, it is important to look more closely at the complexity of what Michel Foucault called our ‘society of security’ (2009, p. 11) and to gain insight into the radical changes that are happening now in the governance of security in our urban environment. The aim of this chapter is to explain the basis of present ‘security’ at the level of both discourse and practice by exploring the long-​ term process of transformation from a sovereign to a security society. The chapter starts with largely a schematic account of sovereign and disciplinary power that will be familiar to many readers of the French philosopher Foucault. In an extension on Foucault’s writings on power, the chapter deals with the way in which we are moving from a disciplinary society toward what Gilles Deleuze described as a control society. Writing in the early 1990s, prior to the hegemony of the Internet, Deleuze already told us that ‘information technology and computers’ (1995, p. 180) are a function of new power relations—​and so are their effects. In the final part of this chapter, I introduce a new type of power: ‘psychopower’. By making use of the work of the French philosopher Bernard Stiegler, I show how smart surveillance techniques, ranging from navigation apps to sound sensors, make it possible to channel our desires toward ‘normal’ social behavior, drawing a line between what is ‘acceptable’ and what is ‘unacceptable’. To purpose these tasks, I first deal with the sovereign character of power that gave rise to the most obvious security presence in our urban environment: the armed police.

Sovereign power For many years now, critical scholars have drawn on Foucault’s work on relations of power to explore the historical basis of present securitization of society (e.g. Garland, 2001; Johnston & Shearing, 2003; Wood & Shearing, 2007; Schuilenburg, 2015b). Foucault presents in his work a historical shift from what he called the sovereign society, the dominant form of rule in Europe from the Middle Ages up to the eighteenth century, and the disciplinary society, beginning after the French Revolution and extending into the earlier part of the twentieth century. Foucault saw sovereign power as centralized in a single person or institution. This was characterized by the absolute power of the monarch, which was implemented through the judicial system of the law. Foucault speaks of a juridical-​political form of power, delineated by a ‘juridical sovereignty and the institution of the state’ (1980, p. 102; 2003, p. 34). In such a social order, a breach of the law was

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regarded as an attack on the monarch in person. Foucault writes: ‘In every offence there was a crimen majestatis and in the least criminal a potential regicide’ (1977, p. 53). Within Foucault’s conception of the sovereign power, an important place is assigned to Thomas Hobbes’ Leviathan (1651) and Beccaria’s On Crimes and Punishments (1764). Foucault identifies Hobbes and Beccaria as seminal judicial thinkers in the tradition of state-​centered security provision, respectively by the theory of the social contract and the legalization of power in the trias politica. He speaks of ‘the Beccarian dynamic’ (2003, p. 129) with respect to the punitive power of the law and the role of legal reasoning in determining the binary distinction of legal and illegal. In his lecture series Society Must Be Defended, Foucault considers the work of Hobbes (and Machiavelli’s The Prince) as a descendent of the juridical line of thinking by which politics begins when the war ends. In his classic work Leviathan, Hobbes claims that a given social order does not exist. There is a—​hypothetical—​natural state of universal violence and an unbridled pursuit of power. By means of a social contract, a governing body is created whose function is to put an end to this situation and to assume responsibility for the safety and protection of citizens. Therefore, the question of security is centrally a national issue of ‘law and order’, implying criminal justice and the public function of the institution of the police. The Hobbesian conception of social order has been very important for the way in which public institutions as the police have been imagined, and for the way in which they have practiced policing. Hobbes argued that a functional system of social ordering would only be derived through a centralization of power and the establishment of a single authority. Without this consolidation of power, in the form of a single Leviathan, life would be intolerable. The world would come to a ‘war of all against all’ within which life would be ‘solitary, poor, nasty, brutish, and short’ (1998, p. 84). As a consequence, police see themselves, and are seen, as the tool that the Leviathan (in the form of the modern state) uses to bring about security and to avoid the war of all against all. A famous Anglo-​American metaphor used to express this is that police are the ‘thin blue line’ that separates order from anarchy. In The Functions of the Police in Modern Society, Egon Bittner speaks of the police in terms of a ‘non-​negotiable force’ (1970, p. 46). Several aspects of this sovereign conception of power are still central to the current concept of security. This is first and foremost because the associated ‘law-​and-​order’ politics is still an attractive option for the state and its uniformed police to maintain public order and security, using the framework of a ‘tough on crime’ rhetoric and a

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focus on ‘law and order’ with its associated techniques as a ‘negative’ penal power (‘power over’). As such, the notion of security is most commonly associated with terms such as ‘fighting’, ‘combating’, ‘tackling’, ‘controlling’ and ‘punishing’ (Schuilenburg, Van Steden & Oude Breuil, 2014). In this approach, the emphasis lies on, what seventeenth-​century Dutch philosopher Spinoza (1989) called ‘sad affects’ (tristitia) or ‘negative affects’, such as ‘fear’ of crime, with the state depicted as a ‘modern Leviathan focusing on combating all imaginable sources of harm’ (Ericson, 2007, p. 35; Hallsworth & Lea, 2011). This is done by a variety of surveillance techniques, ranging from patrolling the streets in marked police cars to the prediction of crime by data-​driven systems, like predictive policing that certain neighborhood areas will experience, for example, burglaries during a certain time span. The latter, for example, is used by the Dutch police at a national level (‘Criminality Anticipation System’) to predict where and when criminal activity is likely to occur (Das & Schuilenburg, 2018; Rienks & Schuilenburg, 2020).

Disciplinary power In the sovereign society, control took shape in the form of city walls and gatekeepers who checked everyone entering a city at specific points of entry. This fortified city functioned as a military model. According to the French cultural theorist and urbanist Paul Virilio: ‘Before it became the throne of totality, the Christian sanctuary was a stronghold, a bunker, a fortified church for those who remained within it; all their powers and capacities were deployed and strengthened in, through and as combat’ (1986, p. 38). The eighteenth and nineteenth centuries saw the rise of a different type of power. In this society, the functioning of power moved away from a model of sovereignty, that is, away from a centralized, identifiable and vertical power (‘state apparatus’) that operates through law and coercion. This did not mean that sovereign power stopped to exist; it was rather superimposed by a new form of disciplinary power that was exercised within the spaces left by the juridical network, the so-​ called hôpitaux généraux, in order to make people, as Foucault remarked in Discipline and Punish, productive and efficient individuals. Although Foucault does not anywhere define discipline succinctly, he understands it as a way of teaching people desired and appropriate behavior by a whole new arsenal of detailed and interchangeable techniques—​classificatory tables, training exercises, exams, timetables, panoptic observation—​that are applied behind the walls of closed and secluded institutions like schools, hospitals and prisons. On a more

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theoretical level, Foucault shows that neither the autonomous subject (‘the monarch’) nor the political sovereignty of the state (‘the police’) provide an adequate starting point for speaking about disciplinary power. This means that the analysis of power ought to be independent of more everyday representations of power, and particularly of the legal-​discursive and Marxist representation of power such as violence and suppression. Foucault claims: ‘What we need is a political philosophy that isn’t erected around the problem of sovereignty, nor therefore around the problems of law and prohibition. We need to cut off the king’s head’ (1980, p. 121). This does not mean that the influence of the state has diminished, but it does mean that security issues can no longer be approached from the standpoint of the government’s exclusive right to fight criminality and disorder. The government is slowly losing its (partly assumed) monopoly on security. Parties other than the police and the Department of Justice are becoming increasingly active in the market for security and the prevention of risk and crime. In other words: ‘The king is dead, long live the extended royal family’ (Burris, Kempa & Shearing, 2008). Inasmuch as one may speak of partners in crime, citizens, football clubs, housing corporations, shopkeepers and community organizations now belong to the security family. In terms of disciplinary power, these parties fill the gap that the juridical network treats with indifference. Despite the differences in their mode of operation, each of these parties uses the norm rather than the law as a measurement and a means of producing a common standard. Although the influence of the norm is primarily local as it is attached to a specific member of the security family, it helps to produce the generalization of discipline in our security society. The norm, then, is opposed not to (inflexible) law itself but to what Foucault framed as ‘the juridical’: the institution of the law as the expression of a sovereign’s power (Ewald, 1990; 2002). Take my favorite football club Sparta Rotterdam, for example. In addition to the law of the Dutch state, local stadium rules and regulations are also in force, including the prohibition of conduct such as the showing of offensive written banners, climbing of structures within the stadium and bringing in alcoholic drinks. By committing an offense, I can receive a sanction from the football club (e.g. a Stadium Ban) (Stott & Pearson, 2006; Hopkins, 2014). Here, one could speak of ‘contractual governance’ (Crawford, 2009), whereby local agreements function as instruments of social control, or of ‘quasi-​ criminal law’: the penalization and enforcement of classical offenses (discrimination, vandalism, drunkenness) through local agreements by parties other than the police and judicial authorities (Schuilenburg, 2011; 2015b, pp. 88–​91).

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The ‘responsibilization’ (Garland, 2001) of parties other than the police, from individuals and private tech companies to local communities, emanates from the insight that crime levels are and will probably remain high in an open and prosperous society, and that the criminal justice system of crime control, monopolized by the state and its uniformed police, has only limited possibilities to deal with this situation. Tasks in this domain are increasingly being transferred to other parties, which are increasingly being assigned ‘police-​type’ duties, such as the protection of shopping malls, university campuses, airports, football stadiums and gated communities (Shearing & Stenning, 1983; Wakefield, 2003). An example is the Collective Shop Ban, a measure taken in the Netherlands in an effort to make shops co-​responsible for maintaining safety and security within the city-​center. Depending on the severity of the conduct, an offender can be denied entry not only to the shop where the ban is imposed but also to all the shops that participate in the measure for a period of two years (Schuilenburg, 2015a; 2015b). The situation that an increasing number of people are being denied access to certain places and the corresponding facilities by banning orders occurs in several countries such as Australia (Palmer & Warren, 2014), the United Kingdom (Johnstone, 2016) and the United States (Beckett & Herbert, 2009, 2010). In the case of the Collective Shop Ban, a relevant aspect is that an increasing number of shops are using facial recognition cameras to catch shoplifters before they steal and to identify offenders with a shopping ban. Many of these stores share a digital record of the faces of these people, meaning that if one store considers you a threat, every business in that network could come to the same conclusion. How can we think about the relationship between surveillance and power, then?

Control power In an extension of Foucault’s work, the French philosopher Gilles Deleuze developed Foucault’s notion of power into a broader theory of control. Focusing on the way our behavior is organized and influenced by technical objects, Deleuze states in his lecture ‘What is the creative act?’ at the FEMIS film school in 1987 and in his short article ‘Postscript on societies of control’ (1995) that the disciplinary society, with its closed structures, is losing its influence and is shifting toward a control society, a term he borrowed from the American novelist William Burroughs. In the disciplinary society, control found its specific power within the enclosed segments (walls, boundaries, enclosures); it was an element of the interior of fixed and closed spaces (like the fabric,

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the hospital, and the prison) in themselves. In addition, the rule of the norm was attached to specific institutions and served a means of managing different populations (like scholars, the sick, and prisoners). In a control society, however, power is no longer exerted primarily within forms of enclosure as the traditional sites of confinement are in the midst of a general breakdown—​a thesis that echoes Virilio’s phrase of the ‘exhaustion’ of the physical. The transition from a disciplinary society toward a control society is most obvious in the practice of the prison. By means of electronic monitoring, where the convict undergoes his punishment outside the walls of his cell, the inmate is put under surveillance at a distance (see for example Laurie & Maglione, 2019; Daems, 2020). In this context, Malcolm Feeley and Jonathan Simon described electronic monitoring as a technique of the ‘new penology’ which ‘can best be understood in terms of managing costs and controlling dangerous populations rather than social or personal transformation’ (1992, p. 465). At the same time, through domestic care, the hospital relocates its activities to the living environment of the patient. Furthermore, education is no longer confined to schools. Nowadays, one must constantly be engaged in further education by means of training courses and study. The practice of work has also become diffuse. Work, the fabric for example, is no longer a place you leave behind after working hours. Employees take work home on the laptop so that they can work on the weekend to check their emails or finish an academic article. These transitions make it clear that once-​distinct and function-​specific locations are now becoming increasingly interwoven. In this way, one can no longer speak of a fixed form with a separate ‘inside’ and ‘outside’. Separated institutions are connected to one another so that they can subsequently function once again. Whereas Foucault talked about an internalized disciplinary view, Deleuze prefers to speak of a flexible control that works on the basis of ‘modulation … continually changing from one moment to the next’ (1995, pp. 178–​9). At the same time, it becomes clear that classic dichotomies such as ‘public’ and ‘private’ lose their meaning here. Power is no longer exerted primarily within forms of enclosure—​the separate physical shells of the most important social institutions of modern society, such as schools, factories and prisons—​but is superimposed through various forms of networks and an open-​ended system of relatively decentralized ‘smart’ control, with Wi-​Fi tracking, sound and traffic sensors, digital cameras with embedded capabilities (including people counting, detection of mood and walking patterns), the monitoring of internet content, and so on. Or, as Deleuze remarked in in his lecture ‘What is the creative act?’: ‘You don’t confine

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people with a highway. But by making highways, you multiply the means of control. I am not saying this is the only aim of highways, but people can travel infinitely and ‘freely’ without being confined while being perfectly controlled’ (2003, p. 300). As panoptic dynamics of industr ial capitalism have been disseminated and governed by the post-​war information and communication infrastructure, surveillance by the use of smart technologies gets a whole new form and content. An important aim of these devices is making the future secure and certain by the exclusion or minimizing of potential risk factors (behavior, persons, objects, groups). On the basis of this orientation toward the future, smart security techniques, understood as the material dimension of control, are being applied worldwide to an ever-​g rowing extent in our urban environment to create a risk-​free environment without the danger of crime or disorder. A crucial element here is the category of ‘risk’ and it is essential to be more specific about the term. Risk is both an imaginary as well as a performative concept that creates its own reality. Risk and imagination share the characteristic that they bring into existence what is not there. Being inherently an imaginative and future-​oriented concept, risk has enabled actuarial, pre-​emptive and preventive forms of security governance (Pali & Schuilenburg, 2019). The sound sensors and digital cameras that track and monitor my journey to the Sparta Stadium are a fitting example here. These technologies have been implemented in very large numbers in public space and are connected into a centralized network, so that large quantities of collected data can be constantly analyzed for the purposes of prediction and prevention of risks, while—​at the same time—​the behavior of citizens is monitored and anticipated, and, where necessary, subjected to interventions. The question becomes then: what type of interventions can we distinguish in a security society? In other words: What can we learn about our security society by approaching it in terms of forms of punishment?

Interventions: from exclusion to inclusion The formation of a security society means in no way that the power of law and the power of discipline disappear. Practically speaking, control tends to be accompanied by forms of sovereign and disciplinary power, as my trip to the stadium of Sparta Rotterdam illustrates. This becomes evident when we look at the array of interventions we can attribute to the three distinguished forms of power: sovereign, disciplinary power

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and control. While it is out of the scope of this chapter to make an exhaustive list of types of interventions, I focus in this paragraph on my personal example of my Sunday journey from home to the soccer game of Sparta Rotterdam.

Sovereign power In the post 9/​11 urban landscape, the governance of security clearly echoes a mere exclusive discourse, expressed by a growing tendency to remove everything that violates the social order of public space. The move towards ‘security-​obsessed urbanism’ (Davis, 1992) becomes evident, on the one hand, in making parties other than the government responsible for security problems in public space, including mass private properties such as shopping centers and football stadiums. These parties, on the other hand, also apply various forms of punitive interventions, including banning orders (e.g. Collective Shop Ban and the Stadium Ban) by which offenders are denied access to different parts of the city and the corresponding local facilities. According to Foucault, the ‘power to banish’ was central to law enforcement, referring to the expulsion from any country, province or town by the authority of the state (by the judgment of a court or monarch). The etymology of the word holds certain surprises for our contemporary understanding as the term is closely linked to the Italian word ‘banditti’ or ‘bandito’, literally meaning an outlawed man or criminal who is banished from society at large. The Italian verb ‘bandire’ means ‘to banish or put to the ban’. Although shopkeepers and the security guards at the Sparta football stadium, for example, can be seen as ‘petty sovereigns’ or ‘quasi-​kings’, refusing offenders access to these places, it may be more fitting here to speak of ‘selective exclusion’, as the latter term refers to the fact that there are all kinds of social and spatial divisions in the city that entail their own public and particular rules of behavior—​creating fragmented security at micro-​level in our urban environment (Schuilenburg, 2015a). In contrast to banishment, the emphasis by ‘selective exclusion’ lies not on the monopoly of the government, to implement punitive sanctions by means of the tools of public legislation, but on local security parties, which develop their own security program and refuse certain people access to distinct parts of urban space by giving football hooligans, for example, a Stadium Ban.

Disciplinary power Alongside the power of individual human agents involved in the securitization of society, a common trend in Western cities is a kind

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of disciplinary architecture, whose aim is to protect the public from unwanted behavior and undesirable people. The most well-​known forms of this type of architecture are concrete barriers (obstacles, roadblocks) to prevent vehicle terror attacks, strips of spikes outside luxury houses, the use of ‘uncool’ classical music and opera at subway stations, neon pink lights at underpasses, and barrel-​shaped benches (‘sadistic street furniture’) designed to deter young people and prevent certain groups from using them as a bed for the night, such as homeless people and beggars (Davis, 1992; Ferrell et al, 2008; Raymen, 2016). As crime and recidivism rates continued to rise throughout the 1980s and 1990s, these forms of ‘crime prevention through environmental design’ (Crowe, 2013) and their attempt to create a ‘defensible space’ (Newman, 1972) embedded themselves in the spatial environment, regulating indirectly the use made of public space by disciplining the behaviors within. The parallel between the Panopticon, in some sense the purest expression of the exercise of disciplinary techniques in the 18th century, as Foucault suggested in Discipline and Punish, and these objects in public space is obvious. The design of public space and the architecture of the prison are used to discipline the body and to encourage ‘proper’ conduct. In the case of the so-​called bum-​proof benches that I encountered during my journey to Sparta, this means: ‘Sitting yes, lying down no’. Although the design against unwanted behavior has been successful in reducing certain forms of criminality, for example burglary and shoplifting, the ‘designing out’ of unwanted people or unacceptable activities also has normative consequences that can scarcely be overestimated. The creation of sterile and homogenized environments leads to a different view on the function of public space and also put pressure on classical legal principles and social ideals. In sociological terms, for instance, public space is measured according to its openness and accessibility, inviting social mingling and chance encounters between people, without commercial motives or a profit-​and-​loss mentality being involved (Lofland, 1973; Sennett, 1977; Joseph, 1998). Although this sociological perspective on public space is an ideal-​typical view, it stands in sharp contrast to the hostile and disciplinary architecture that aims to exclude certain uses, or certain groups of people, from using that space.

Control power Much public space is designed in such a way that unexpected occurrences can be largely neutralized or prevented. In an attempt

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to avoid or reduce risks and criminality, control techniques have been employed to identify likely targets and future criminals, such as facial recognition systems, advanced video monitoring and predictive policing. With enough ubiquitous surveillance, data and processing power, ‘the goal is to render the whole city—​every place, every moment—​knowable and controllable’ (Sadowski, 2019). Here, it is important to avoid confusion techniques of control and techniques of discipline, the latter described by Foucault as being methods concerned with the managing of individual bodies with the goal to make them productive, efficient, and obedient. The distinction lies in the fact that, due to their reflective nature, techniques of control explicitly point to the future, making it possible to predict crime and disorder and thus prevent them. In the case of predictive policing, it is possible to predict where, when and by whom crimes are more likely to be committed. In Chicago, for example, an algorithmically derived ‘heat list’ ranks people at risk of becoming victims or perpetrators of gun violence (e.g. Ferguson, 2017; Smith, 2018). The underlying assumption is that both crimes as criminal behavior are, to a large extent, predictable, because criminals with a distinguishable profile tend to commit the same type of crime, at roughly the same location and time of the day (Bennett Moses & Chan, 2016; Peeters & Schuilenburg, 2018). As a consequence, it is not the criminal but the future criminal who is the object of intervention. The implications of such developments are wide-​ranging, especially considering that techniques of control no longer focus on the physical body of the individual. As Deleuze notes: ‘We’re no longer dealing with a duality of mass and individual. Individuals have become “dividuals”, and masses become samples, data, markets, or “banks” ’. (1990, p. 180; see also Deleuze & Guattari, 1987, pp. 341, 483). This means that in our security society, the centrality of the physically embodied human subject is disappearing and is being substituted with data representations via techniques of control. As a consequence, the individual is the outcome of a process of collecting data and these data are used to target ‘risky’ persons who deviate from the expected and normal patterns.

Psychopower On my afternoon trip from home to the soccer game of Sparta Rotterdam, I moved from one space of security to the next within no more than 25 minutes. In this way, I traveled through a rhizome of controls, in which diverse public and private parties are responsible

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for the security of a part of the route to the stadium. What this example primarily shows is that in our urban environment there is a complex interplay of sovereign, disciplinary and control power. These forms of power operate distinctively through knowledge in the form of a range of security practices. At the same time, these practices employ technologies of surveillance, normalization, differentiation, categorization and calculation. Besides interventions such as (1) banning orders, (2) disciplinary architecture and (3) the filtering of potential (and not previously identified) suspects across very large data sets, I have pointed to another complex phenomenon: the navigation app on my iPhone that includes an ‘Avoid Dangerous Neighborhoods’ functionality. By means of which power relation does this app function? Focusing on the way my behavior is organized and influenced by a variety of technical objects; there is a close connection here to what the French philosopher Bernard Stiegler called a psychopolitical perspective on the influence of technologies of control. In his work, Stiegler speaks of ‘psychopower’ (psychopouvoir) as ‘the systematic organization of the capture of attention made possible by the psychotechnologies that have developed with the radio (1920), with television (1950) and with digital technologies (1990), spreading all over the planet through various forms of networks, and resulting in a constant industrial canalization of attention’ (2006). Smart sensors and devices, for example, allow streetlights to dim or brighten automatically based on the activity on the streets, to ensure both efficiency and safety. At the same time, these sensors and devices help people to travel the most effective routes, avoiding noise and areas that have a high crime intensity. This is made possible by wearable technology like smart watches and smart glasses, wholly centered upon individual needs. In sharp contrast to Foucault’s notion of ‘bio-​power’ (1998; 2008; 2009), which was above all a somatic matter, Stiegler considers psychopower not in terms of the subjugations of bodies and the control of populations by the state, but as the manipulation of our consciousness as a product of the economic marketplace. As these sensors and devices take the step from tracking to shaping and intervening in behavior, Stiegler writes that ‘the state’s bio-​power is transformed into market psychopower’ (2010, p. 128). Focusing on the way our behavior is organized and influenced by technical objects, there is a close connection here to what Deleuze called ‘societies of control’. In a control society, viewed through the lens of Stiegler (2014), power relations no longer mainly aim at disciplining the individual body, which deprives the individual of his or her freedom to choose, or at regulating life through institutions of the nation-​state that monitor,

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modify and control life processes, but at conditioning the psyche to stimulate consumption and at creating consumer subjects. To discuss the relation between control and our behavior, Stiegler writes: ‘A control society does not only consist in the installation, throughout society, of social control, but rather penetrates into consciousness … and thus reinstates corporate control’ (2011, p. 82). In other words, the focus of attention needs to be shifted to the role of, what Stiegler terms, mnemotechniques or mnemotechnologies, from imaging to storytelling to writing to the digital database, which are currently being put into service by the industries of consumer capitalism. To be clear, for Stiegler, technology is not necessarily something bad that will alienate modern humanity. Following Jacques Derrida’s (1992) suggestion, Stiegler characterizes the mnemotechnical system as a pharmakon in the sense that each gift can turn to poison (the German word for poison is Gift). In other words, mnemotechniques can ‘support the emancipation and edification of the mind, but it can also be used to control the mind and keep it in a state of docility’ (Van Camp, 2012). Thus far, the potential and implications of psychopolitical power have remained an overlooked subject in the literature on the securitization of society. Contrary to classical interventions such as commands and banning orders, psychopolitical techniques, such as the navigation app on my smart phone which advises me to take the subway instead of the bus, are non-​regulatory forms of power that aim to influence individuals to change their behavior through subtle and cost-​effective changes in their environment, for example, traveling through a safer neighborhood. This means that the struggle for power and control in society is no longer associated with the population and its relationship to production but rather by the techniques of automated engineered behavior modification. In this context, scholars speak of ‘hypernudges’ (Yeung, 2017), drawing in algorithms and big data to nudge individuals to effectively change their lifestyle. It is important to underline that these psychopolitical techniques are not an amoral approach but a deeply normative way of governing security with the aim to create a safer environment for everyone. In our urban environment, there seems to be more freedom, but there is also more control, precisely because these psychopolitical techniques actively influence the mind of citizens to make ‘smarter’ choices. As a consequence, critics point out that these techniques raise a series of concerns related to their democratic legitimacy and accountability as behaviorally informed conditioning of the mind can enter into conflict with the principle of individual autonomy, that is, the ability to order our lives according to our decisions (Alemanno & Spina, 2014).

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Conclusion Security has become the preferred context of governance in our society, for which reason scholars such as Michel Foucault have begun to refer to our society as a ‘security society’. By governance, I refer not only the actions of the state but all efforts intended to guide the conduct of others (and ourselves). This means that security has become the interface of what is ‘seen and spoken about’ and everything that could have been ‘seen and spoken about’. In the words of Mark Neocleous, our ‘language and culture has become saturated by “security” ’, in such a way that ‘the paradigm of (in)security has come to shape our imaginations and social being. Every day is Security Awareness Day’ (2008, pp. 2–​3). The way security colonizes our legal and moral rules, ways of acting, practices and the language in which we communicate, is undisputedly a creation of power. But how? And which forms of power? In order to answer questions about the kinds of relations of knowledge and power we face in our security society, I have discerned a four-​fold typology of power: sovereign, disciplinary, control and psychopower. When these forms of power coincide with our present-​day society—​it unavoidably provokes critical questions. What causes the transition between these different forms of power at a certain moment? How are they related to one another, blend into one another and ultimately partially replace one another? Data-​driven surveillance, for example, has roots in a longue durée history, which it is helpful to keep in view when attempting to periodize developments closer to the present. To the extent that the word ‘security’ comes from the Latin word securitas, which denotes a condition of being without care, free from cares and untroubled (sē-​cura), and can be already found in the work of writers such as Cicero and Seneca, it is important to realize that it serves nowadays as an assemblage of a range of discourses and practices concerned with the governance of crime and disorder. In this way, our security society emerges, to paraphrase Deleuze, ‘like a series of “building blocks”, with gaps, traces and reactivations of former elements that survive under the new rules’ (1986, p. 30). This means that the discerned forms of power are not mutually exclusive; they are underpinned by the notion of security, which can be used to address different aspects of power relations. This new situation is illustrated by the technique of predictive policing, arguably the biggest shift in the governance of security since the criminal justice system began accepting social science and other expert evidence more than a century ago. Predictive policing

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is a consequence of increased technological opportunities, and of governmental efforts to pre-​empt risks as opposed to merely responding to events by primarily repressive driven measures. In relation to the question of power, it can be argued that predictive policing is a form of state surveillance (sovereign power), which operates, however, through data-​driven technologies that can track and monitor the behavior and movements of people (control). Therefore, in the security society there is no question of any substitution of sovereign power by disciplinary power and subsequently the replacement of a disciplinary society by a control or psychopolitical society. Rather, the security society is about a change of accent and the appearance of new objectives generating new forms of surveillance and punishments. And the Sparta Rotterdam game? Well, Sparta lost for the third time in a row and were relegated to the second division. References Alemanno, A. & Spina, A. (2014). Nudging legally: On the checks and balances of behavioral regulation, International Journal of Constitutional Law 12 (2): 429–​56. Banton, M. (1964). The Policeman in the Community. London, UK: Tavistock Publications. Bauman, Z. (2000). Liquid Modernity. Cambridge, UK: Polity Press. Beccaria, C. (1963). On Crimes and Punishments. New York, NY: Prentice-​Hall (first published: 1764). Beck, U. (1992). Risk Society: Towards a New Modernity. London, UK: Sage. Beckett, K. & Herbert, S. (2009). Banished. The New Social Control in Urban America, New York, NY: Oxford University Press. Beckett, K. & Herbert, S. (2010). Penal boundaries: Banishment and the expansion of punishment. Law and Social Inquiry 35 (1): 1–​38. Bennett Moses, L. & Chan, J. (2018). Algorithmic prediction in policing: Assumptions, evaluation, and accountability. Policing and Society 28 (7): 806–​22. Bittner, E. (1970). The Functions of Police in Modern Society: A Review of Background Factors, Current Practices, and Possible Role Models. Chevy Chase, MD: National Institute of Mental Health. Burris, S., Kempa, M. & Shearing, C. (2008). Changes in governance. A cross-​disciplinary review of current scholarship. Akron Law Review 41 (1): 1–​66. Castells, M. (1996). The Information Age: Economy, Society, and Culture (Volume 1) The Rise of the Network Society. Oxford, UK: Blackwell.

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Crawford, A. (2009). Governing through anti-​social behaviour. Regulatory challenges to criminal justice. British Journal of Criminology 49(6): 810–​31. Crawford, A. & Hutchinson, S. (2016). Mapping the contours of ‘everyday security’: Time, space and emotion. The British Journal of Criminology 56(6): 1184–​202. Crowe, T.D. (2103). Crime Prevention Through Environmental Design. Waltham, MA: Elsevier. Daems, T. (2020). Electronic Monitoring: Tagging Offenders in a Culture of Surveillance. London, UK: Palgrave Macmillan. Das, A. & Schuilenburg, M. (2018). Predictive policing: waarom bestrijding van criminaliteit op basis van algoritmen vraagt om aanpassing van het strafprocesrecht. Strafblad, Tijdschrift voor wetenschap en praktijk 36 (4): 19–​26. Davis, M. (1992). City of Quartz. Excavating the Future in Los Angeles. London, UK: Vintage. Deleuze, G. (1995). Negotiations 1972–​1990. New York, NY: Columbia University Press. Deleuze, G. & Guattari, F. (1987). A Thousands Plateaus: Capitalism and Schizophrenia. Minneapolis, MN: University of Minnesota Press. Deleuze, G. (2003). Deux régimes de fous: Textes et entretiens, 1975–​1995. Paris, FR: Minuit. Derrida, J. (1992). Given time: I. Counterfeit Money. Chicago, IL: The University of Chicago Press. Dodsworth, F. (2019). The Security Society: History, Patriarchy, Protection. London, UK: Palgrave Macmillan. Ericson, R.V. (2007). Crime in an Insecure World. Cambridge, UK: Polity Press. Ewald, F. (1990). Norms, discipline, and the law. Representations 30: 138–​61. Ewald, F. (2002). The return of Descartes’s malicious demon: An outline of a philosophy of precaution. In T. Baker & J. Simon (eds.) Embracing Risk. The Changing Culture of Insurance and Responsibility. Chicago, IL & London, UK: The University of Chicago Press (pp. 273–​301). Feeley, S. & Simon, J. (1992). The new penology: Notes on the emerging strategy of corrections and its implications. Criminology 30 (4): 449–​74. Ferguson, A.G. (2017). The Rise of Big Data Policing. Surveillance, Race, and the Future of Law Enforcement. New York, NY: New York University Press. Ferrell, J., Hayward, K. & Young, J. (2008). Cultural Criminology: An Invitation. London, UK: Sage.

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Foucault, M. (1977). Discipline and Punish: The Birth of the Prison. Middlesex: Penguin Books. Foucault, M. (1980). Power/​Knowledge. Selected Interviews and Other Writings 1972–​1977 (C. Gordon, ed.). New York, NY: Pantheon Books. Foucault, M. (1998). The Will to Knowledge. The History of Sexuality (Part 1). London, UK: Penguin. Foucault, M. (2003). Abnormal. Lectures at the Collège de France 1974–​ 1975. New York, NY: Picador. Foucault, M. (2008). The Birth of Biopolitics. Lectures at the Collège de France 1978–​1979, New York, NY: Palgrave Macmillan. Foucault, M. (2009). Security, Territory, Population. Lectures at the Collège de France 1977–​1978. New York, NY: Picador. Garland, D. (2001). The Culture of Control: Crime and Social Order in Contemporary Society, Chicago: The University of Chicago Press. Hallsworth, S. & Lea, J. (2011). Reconstructing leviathan: Emerging contours of the security state. Theoretical Criminology 15 (2): 141–​57. Hamilton, J.T. (2013). Security, Politics, Humanity, and the Philology of Care. Princeton, NJ: Princeton University Press. Hobbes, T. (1998). Leviathan. Oxford: Oxford University Press. Hopkins, M. (2014). Ten seasons of the football banning order: Police officer narratives on the operation of banning orders and the impact on the behaviour of ‘risk supporters’. Policing and Society 24 (3): 285–​301. Johnston, L. & Shearing, C. (2003). Governing Security: Explorations in Policing and Justice. Abingdon, UK: Routledge. Johnstone, C. (2016). After the Asbo: Extending control over young people’s use of public space in England and Wales. Critical Social Policy 36 (4): 716–​26. Joseph, I. (1998). La ville sans qualités. La tour d’Aigues. Editions de l’Aube: France. Laurie, E. & Maglione, G. (2019). The electronic monitoring of offenders in context: From policy to political logics. Critical Criminology [online] Available at: https://d​ oi.org/1​ 0.1007/s​ 10612–0​ 19–0​ 9471–7​ Loader, I. & Walker, N. (2007). Civilizing Security. Cambridge, UK: Cambridge University Press. Lofland, L. (1973). A World of Strangers: Order and Action in Public Space. New York, NY: Basic Books. Neocleous, M. (2008). Critique of Security. Edinburgh, UK: Edinburgh University Press. Newman, O. (1972). Defensible Space. New York, NY: Macmillan. Pali, B. & Schuilenburg, M. (2020). Fear and fantasy in the smart city. Critical Criminology 28 (4): 775–​88.

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Palmer, D. & Warren, I. (2014). The pursuit of exclusion through zonal banning. Australian & New Zealand Journal of Criminology 0 (0): 1–​18. Peeters, R. & Schuilenburg, M. (2018). Machine justice: Governing security through the bureaucracy of algorithms. Information Polity 23 (3): 267–​80. Raymen, T. (2016). Designing-​in crime by designing-​out the social? Situational crime prevention and the intensification of harmful subjectivities, The British Journal of Criminology 56 (3): 497–​514. Rienks, R. & Schuilenburg, M. (2020). Wat is er nieuw aan het voorspellen van criminaliteit? Over de ambities en knelpunten bij de implementatie van predictive policing. In Cahiers Politiestudies 54: Informatiegestuurde politie, J. Janssens et al (eds.), (39–​54). Oud-​ Turnhout, BE: Gompel & Svacian. Sadowski, J. (2019). The Captured City [online] Available at: https://​ reallifemag.com/​the-​captured-​city/​. Schuilenburg, M. (2011). The securitization of society. On the rise of quasi-​criminal law and selective exclusion. Social Justice. A Journal of Crime, Conflict, and World Order 38 (1–​2): 71–​86. Schuilenburg, M. (2015a). Behave or be banned? Banning orders and selective exclusion from public space. Crime, Law and Social Change 64 (4–​5): 277–​289. Schuilenburg, M. (2015b). The Securitization of Society. Crime, Risk, and Social Order. New York, NY: New York University Press. Schuilenburg, M., van Steden, R. & Oude Breuil, B. (2014). A critique of security. Towards a positive turn in criminology. In Positive Criminology. Reflections on Care, Belonging and Security, B. Oude Breuil, M. Schuilenburg & R. van Steden (eds.), (9–​16). The Hague: Eleven International Publishing. Sennett, R. (1977). The Fall of Public Man. New York, NY: W.W. Norton & Company. Shearing, C.D. & Stenning, P.C. (1983). Private security: Implications for social control, Social Problems 30 (5): 493–​506. Smith, G.J.D., Bennett Moses, L. & Chan, J. (2018). The challenges of doing criminology in the big data era: Towards a digital and data-​ driven approach. The British Journal of Criminology 57 (2): 259–​74. Stiegler, B. (2006). Within the limits of capitalism, economizing means taking care [online] Available at: http://​arsindustrialis.org/​node/​2922. Stiegler, B. (2010). Taking Care of Youth and the Generations. Stanford, CA: Stanford University Press. Stiegler, B. (2011). The Decadence of Industrial Democracies. Disbelief and Discredit, Volume I. Cambridge, UK: Polity Press.

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Stiegler, B. (2014). The Re-​enchantment of the World. The Value of Spirit Against Industrial Populism. London, UK: Bloomsbury. Stott, C. & Pearson, G. (2006). Football banning orders, proportionality, and public order policing. The Howard Journal of Crime and Justice 45 (3): 241–​54. Van Camp, N. (2012). From biopower to psychopower: Bernard Stiegler’s pharmacology of mnemotechnologies, Ctheory [online] Available at: http://​ctheory.net/​ctheory_​wp/​from-​biopower-​to-​ psychopower/​. Virilio, P. (1986). Speed & Politics: An Essay on Dromology. New York, NY: Semiotext(e). Wakefield, A. (2003). Selling Security. The Private Policing of Public Space. Cullompton, UK: Willan. Waldron, J.J. (2011). Safety and Security. Nebraska Law Review 85 (2): 454–​507. Wood, J. & Shearing, C.D. (2007). Imagining Security. Cullompton, UK: Willan. Yeung, K. (2017). “Hypernudge”: Big Data as a mode of regulation by design. Information, Communication & Society (20) 1: 118-​36. Zedner, L. (2009). On Security. Abingdon, UK: Routledge.

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Pre-​Crime and the ‘Control Society’: Mass Preventive Justice and the Jurisprudence of Safety Pat O’Malley and Gavin J.D. Smith

Control techniques are used not so much to identify a particular individual, but rather to identify a future risk, and to attach this risk to certain kinds of individuals … whereas disciplinary societies constituted the subject as a fixed identity—​defining him according to rigid categories such as normal/​abnormal, sane/​mad—​societies of control seek to define the individual through a series of different, modulated, and overlapping states of risk, with indeterminate and shifting borders. (Newman, 2009, pp. 106–​7)

Risk and dangerousness: pre-​crimes and preventive crimes Robert Castel (1991) famously differentiated between dangerousness and risk, distinguishing between them in terms of dangerousness as a diagnosis based on the analysis of individual symptoms, and risk as involving assignment of a case to a statistical category.1 Individuals are dangerous to the extent that as unique subjects they are manifesting specified symptoms (of sickness, of deviance etc.) that transgress particular thresholds of severity. Castel understood dangerousness as a personal proclivity revealed through symptomology but in itself concealed: hence, dangerousness is always open to second opinions

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and each case is unique. Moreover, it might be considered as an indeterminable and unstable entity, changing in intensity depending on the various circumstances in which the subject is contextually situated. As such, dangerousness is associated with various long-​established forms of preventive detention. However, these relate to the specific subject: to the specific individual known through complex diagnostic records and/​or through the rich description of a case. Risk, on the other hand, is not a property of the individual. Castel argues that ‘the new strategies dissolve the notion of a subject or concrete individual and put in its place a combinatory of factors, the factors of risk.’ (Castel, 1991, p. 281). The need to identify specific individuals however does not disappear in risk. Specific individuals remain available to medicine, psychiatry, criminal justice and so on, and remain their ‘targets’. However, they are known differently: through their belonging in risk pools. Little more need be known about them other than what is required to be known for this mode of risk identification and classification. Gone is the complex case history, the biography, the in-​depth knowledge of the subject, the individualized intervention. Henceforward they are to be known through their risk profile—​which may be as little as a score on a risk schedule or register. Unlike dangerousness, risk varies between somewhere just above zero to somewhere just below certainty—​since virtually nothing is risk-​free or totally certain from a perspective of probability. In such frameworks, hard boundaries such as dangerous/​not dangerous begin to break down even as risk-​identification specificities become ever more precise and inescapable. As Castel points out, ‘the mad’ not only are assigned to increasingly fragmented categories of mental illness, each with its own risks, but at the same time will be identified along a spectrum of madness—​rather than being or not being mad. We are all at risk of becoming mad, and each madness has its specific risk profiles. Consequently, there is no sharp ‘diagnostic’ divide that separates the mad from the sane, the healthy from the sick, the criminal from the non-​criminal. Thus, the way is opened to break down the boundaries that, for example, might prevent us talking of ‘pre-​crimes’, for now there are just different degrees of riskiness. However, at the same time, there is no ‘blurring’ as is popularly spoken of; rather there is increased precision and objectivity. Your degree of riskiness can even be expressed as a numeric, a probability. Increased precision is also obtained because if one were borderline ‘dangerously’ mad, a second opinion would be called in and may challenge the original diagnosis. This is blurring. The identification of a risk factor, however, not only allows a precise risk score to be assigned, but these risk scores are not a matter of

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expert opinion to be challenged or consolidated by another expert opinion. Rather they appear as if objective and factual, because they are based on accumulated statistical data. Blurring is therefore not the right term: rather, there is an open and precise continuity of riskiness. Insofar as conditions like madness, physical health, criminality, and so forth, can be imagined in this way, then it becomes possible and sensible for instance to identify both ‘pre-​crimes’ and ‘post-​crimes’—​ where a kind of circle of riskiness is created. In a risk framework, pre-​crimes exist where the risk factors are identified as requiring some degree of risk-​reduction such as incapacitation or intensified monitoring—​or systematic rearrangement of some milieu. Where this happens, legal license for such action by the state must be issued—​ and thus pre-​crimes gain a statutory existence. Even though all ex-​ offenders carry a heightened risk load, post-​crimes exist where the offender, after completion of the sentence, is classified as too risky to be totally at liberty: being thus subject to some form of risk mitigation such as registration, electronic tracking or extended incarceration. Pre-​crimes and post-​crimes thus merge, since post-​crimes are in effect pre-​crimes whose risk component includes an offense already sanctioned (and many ‘pre-​crimes’ fall into this category in the first place). Both are justified in terms of risk of future offending. Both gain statutory existence, and are subject to some form of incapacitating intervention—​as is commonly the case for sex and violence offenses in many jurisdictions. And of course, ‘crime’ is not some form of discrete slice of meat in the sandwich since each convicted offender is risk-​rated from maximum security downward. In the context of risk, therefore, there is nothing unique about ‘pre-​crime’: it is a temporal phase in a circuit of crime-​r isk management. In some respects, therefore, the term ‘pre-​crime’ makes most sense in the context of dangerousness—​using the term in Castel’s sense. Thus, there are many legally defined pre-​crimes, which are preventive in their nature—​such as what Asp (2013) refers to as ‘non-​consummate offences’. Conspiracy, stalking, grooming and various terrorism offenses would be examples. These are largely ‘pre-​crimes’ defined through individually diagnosed dangerousness and via the category of potentiality. But how should we approach forms of preventive criminal sanction, which criminalize risk categories—​not individuals per se, but actions bearing a statistical risk of generating harms—​including criminal negligence? I have in mind, for example, driving with a blood alcohol level above the permitted limit. This is a strict liability offense that has little or nothing to do with intent: exhibiting the risk factor is the offense. It simultaneously is a crime and pre-​crime

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(and almost automatically sets up a post-​crime by affecting the formal risk-​status of the driver): something that makes perfect sense in light of this commentary on risk. Much the same can be said about speeding offenses. Some of this complexity may be illustrated by a particular case. In the 1960s the British racing car driver Stirling Moss was taken to court for driving over the speed limit in Melbourne. He was able to argue successfully that he was safer driving at 100 mph than most other drivers traveling at half that speed. In other words, he could challenge the ‘pre-​ crime crime’ by diagnosing his specific case as not dangerous. Indeed, in the early part of the 20th century when speeding was legislated as an offense, it was objected that this statute was not required—​as the offense of dangerous driving existed already (O’Malley, 2009). However, changes were in the offing. The ‘democratization’ of driving produced a new phenomenon: the ‘road toll’. While there had always been individual tragedies, as long as motor vehicles were relatively uncommon these remained at the individual level (Plowden, 1971). By the 1960s, however, mass ownership of cars created mass annual deaths and injuries. A new statistic and category was invented dubbed ‘the road toll’. Road traffic accidents and casualties now became a biopolitical issue, affecting the well-​being of the population, not just individuals, and pressure mounted to reduce the toll. Through a series of unanticipated events—​including cuts to speed limits occasioned by the Arab Oil Embargo of the early 1970s—​speeding was identified as a principal factor in the production of road traffic accidents and fatalities. Research demonstrated the increases in vehicle speed correlated with increases in deaths and injury. Speeding now changed its character from a question of individual dangerousness to one of statistical risk (O’Malley, 2009). Like drink driving, not all of the accidents caused could be criminalized but many would be. We could say that drink driving and speeding are crimes because, inter alia, these practices create and intensify the risk of harm and through that, the risk of crime. Stirling Moss would not beat his rap today simply because the case would not be about him and his driving expertise but about the speed-​ risk category into which he fell. (And no doubt to his chagrin and mortification, the racing driver would have a special ‘post-​crime’ risky status attached to his license as a penalty—​in the form of a set number of demerit points or disqualified license.) It is this risk-​categorical basis that gels with the strict liability status of the offenses, rendering the individual case and criminal intent irrelevant. Suppose the case were then to move to a charge of dangerous driving (another pre-​crime that has become a crime with more significant weight than ‘speeding’)?

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Then, but most likely only then, would the case become about concrete individuals and their biography and contextual situatedness in a court of law. Dangerous driving, in other words, is not conceptually about ‘risk’ but about ‘dangerousness’ in Castel’s terms. Thus the bundle of characteristics already alluded to—​the speed-​r isk correlation, the strict liability character, fixed risk-​related penalties— combines with other developments to enable the digitization and virtual administration of such offenses. This is control: a diagram of power associated with digitized risk. But before elaborating on this, we wish to explore in more detail the precise character of risk crimes.

From pre-​crimes to risk crimes It may be objected that the account articulated so far is restricted to ‘marginal’ offenses such as speeding and drink driving. But in no way are we talking about a peripheral or trivial area of criminal law. What we have alluded to earlier are precisely the offenses most likely to bring citizens into the arena of criminal justice; indeed they comprise a considerable bulk of criminal law business (if not necessarily court business); and certainly, they are responsible for large numbers of deaths and injuries and property loss that are legally determined to be criminal (O’Malley, 2013b). Or again, it could be claimed that this is just a ‘diagram’ that is not always adhered to. Challenges do occur and individual details sometimes are made relevant. But this is rare. Of course, elsewhere in justice much of what passes for risk in criminal justice is little better than the informed guesswork of justice officials, notably probation officers, parole boards and so on, for whom statistical evidence is usually only one factor taken into consideration (Kemshall, 2001; Kemshall & Maguire, 2003). Where risk scores are only one of several elements being contemplated, then we are still dealing with the notion of dangerousness, and the concrete, knowable subject. Risk offenses however—​as in speeding and drink driving—​​are defined solely by the risk score made and drawn from the aggregate. Let us examine more closely the identification and prosecution of drunk driving. For many years, alcohol-​impaired driving was based on behavioral evidence such as the discretionary judgment of a police officer sometimes backed up by ‘tests’ such as walking the white line. This is a fairly straightforward example where the police (and courts using police evidence) are making a judgment of individual dangerousness. The specific individual is being diagnosed on the basis of behavioral symptoms—​that is, directly observable phenomena—​held to indicate the inner state of inebriation. Except in fairly extreme cases,

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this procedure or protocol was always available to a second opinion or to the challenge that it was merely a subjective opinion, and not evidentially-​driven proof. We might say, excusing the pun that here is a line that could be and was frequently successfully contested in court (O’Malley, 2009). The advent of portable breathalyzing technologies—​and more direct means of measuring blood alcohol content—​did much to change this. To begin with, the offense now becomes statistically defined and numerically (read ‘objectively’) measurable. That is, the offense will not be drunk driving per se (dangerousness) but rather having a blood alcohol reading that is over the legally prescribed limit. That limit is scientifically derived and statistically set in terms of experimental evidence on impairment and blood alcohol levels—​ not in terms of any visible impairment nor based on the subjective opinion of an enforcement officer. (Of course, the legal limit varies across jurisdictions, depending on how much risk local legislators are prepared to accept.) But three important shifts have occurred. One is that the offense is the existence of the (statistical) risk factor. It is no longer impaired driving per se, but rather the exhibiting of a chemical condition that has been statistically proven to carry more risk of death and injury than will be tolerated. The drivers concerned may be able to walk the line with great precision and to drive impeccably, may claim to be able to hold their drink, but these factors are now irrelevant. It is no longer an opinion to be challenged on the basis of knowledge of the specific offender—​it can only be challenged by contesting the statistical evidence on which the offense and charge is based. In the case of blood alcohol levels, this is now virtually unheard of. The second shift is that of precision, as discussed already. While we may talk of pre-​crime blurring the line between crime and not-​crime, strictly speaking, the line has never been more clearly defined and precise: the crime can usually be defined to within several decimal places. Drivers reading .05 (or whatever the limit is) can drive away, maybe with a finger wagging, but .06 and they are shopped and subject to criminal justice proceedings. Drivers with very high Blood Alcohol Content (BAC) levels, again specific, measurable and exact although varying from one jurisdiction to another, are automatically charged with dangerous driving. This leaves the third shift. The objectification of risk in blood alcohol content has meant that processing cases can be sped up and made more operationally efficient. Breathalyzer tests are usually performed in a matter of seconds, and the tests are rarely challenged in court. Only where the BAC reading is above a very high level do cases automatically

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go to court. It thus becomes possible through the risk-​modeling of this offense—​and the emergence of a corollary technical infrastructure—​for a new kind of justice—​mass preventive justice—​to materialize. Hundreds of motorists can be (randomly) tested in a few hours by a small team of police, and cases do not often need to be heard or contested in court. The number of convictions, as a consequence, increases dramatically (Fox, 1996) as the number of those being routinely monitored (or breathalyzed at the roadside) expands. While in practice only a tiny percentage of those tested prove positive and are charged, the policy argument is that this mass procedure is effective and efficient not only in removing risks from the road. Just as important in the justificatory staging of this policing initiative is the preventive impact of the practice (that is, its deterrence effect), through the widespread awareness that so many drivers can be subject to a random breathalyzer test (RBT)—​or random drug test—​at any moment as they circulate. This is ‘mass preventive justice’ in action (O’Malley, 2013a). But the full implications of this emergent model and practice of justice are only realized when we turn to speeding: for here we move from risk to control.

Control and the emergence of mass preventive justice Thus far, the distinction made between risk and dangerousness appears important, partly because of risk’s ‘objectivity effect’, and partly because of its precise quantification. Inter alia, these allow for eroding the distinctions between pre-​crime, post-​crime and crime by providing a seemingly scientific demonstration of their continuity as risks. However, there perhaps is an even more important potential concerning the transformation of risk into control—​that is, via risk’s progressive digitization, its movement to the virtual realm and capacity to be animated by machinic and algorithmic processes. In Deleuze’s (1995) terms, risk factors attached to specific persons are understood as ‘dividuals’. Dividuals here are mobile and embodied risk factors—​r isk factors attached to specific identifiable bodies that are stripped of other individualizing characteristics. In Deleuze’s diagram of ‘control societies’, these dividuals exist increasingly in digitized systems that will track, price, prevent or permit real or virtual movement according to the risk score attached to them. Driving licenses, credit cards, access cards, club cards, social insurance cards, and so on (or their bar codes scanned on a mobile phone) digitally identify the possessors in terms of their risk—​for all involve some process of risk assessment before issue and during use. In turn, these may allow or prevent access

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to physical or virtual sites, to privileges, and so on. And they leave behind them traces: digitized records of the passage and actions of the dividual. A specific speeding driver detected by a roadside speed camera and processed by an electronic system of justice is just such a ‘dividual’, identified by a car registration number or by the barcode on a driving license. Offending drivers will be algorithmically identified and then dealt with according to the risk they are calculated to re/​present: that is, how fast they were traveling above the speed limit; whether they have demerit points; whether their registration is up-​to-​date; whether they hold special licenses—​such as probationary drivers; and of course, whether their license has (ever) been suspended or cancelled. Each of these statuses has its own unique conditions of permitted speed-​ related riskiness. Drivers not speeding proceed unimpeded, even unaware of the surrounding system of driving enforcement. Even those detected for speeding will, for the most part, not be pulled over. Instead, they will be issued with a notice generated by an algorithm specifying the offense and the penalty, and delivered by post or email. As Foucault (2007) has argued, such assemblages maximize desired flows, especially when compared to disciplinary apparatuses where each case is stopped, examined, and issued or not issued with an offense notice—​which may later involve a court appearance. As well, compared to such arrangements, not only can thousands of cases be monitored and detected each hour (and cameras never sleep)—​and for next to no cost once the apparatus is in place—​but also the caseload on the police and courts declines very substantially. The system maximizes throughput via a series of connected innovations. To begin with, the record of the offense is produced not by a police officer—​whose observational accuracy, competence or disinterestedness may be challenged (they frequently were when the judgment of speed was made by a stopwatch, the mark one eyeball or a trailing police cruiser’s speedometer gauge). Instead, an ‘objective’ photo record with the electronically recorded speed, date and time, vehicle registration and local speed limit is created. Often this is available for inspection by the offender online. While challenges occur, they are proportionally a tiny fraction of detected cases. This partly is an effect of other changes. Inducements are offered to detected offenders not to challenge the notice in court: infringements taken to court for contestation forfeit a monetary ‘discount’ offered for accepting the charge and paying a fine; they run the risk of a conviction being recorded, rather than a mere infringement notice; they may generate court costs to be paid if the case is lost, including perhaps lawyers’ fees; and they take salary-​earning

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time out of the defendant’s life and add stress. Moreover, as money is digitized, fines are payable online (or by mail) rendering the process convenient and—​if so desired—​quite invisible to others to avoid any sense of shame or stigma. Not surprisingly, only a small percentage of speeding infringement notices are challenged (Fox, 1996). Through the combination of risk and digitization—​what Deleuze (1995) refers to as ‘control’—​a new form of justice emerges that transforms an individual pre-​crime (that is, speeding as ‘dangerousness’) into a digitized risk in a control environment (mass preventive justice). In effect, this potentially can morph into a fully developed control apparatus. For Deleuze, control modulates directly in a given domain—​ that is, the digitized code either permits or prevents access to a physical space or virtual site, or effects limits on what may be performed in these sites. Thus, for example, swipe cards or passwords may not only allow or prevent entry but also, depending on the category of the holder, permit certain activities but not others. In the case of speeding, current control apparatuses are only preventive through the pricing of risk (as a fine to be paid or a mobility privilege to be withdrawn in the case of a suspended license), relying on deterrence but mostly not directly or physically preventing repertoires of action. However, deterrence is not the substance of control. Control systems prevent through selective incapacitation. Speed cameras are, therefore, only an incompletely developed apparatus of control. Simple ‘mechanical’ or technical forms of speed limitation already exist of course, as with speed humps, ‘traffic calming’ chicanes and so on. But the technology already exists to control vehicle speeds remotely and virtually. This can be either through roadside bollards or satellites governing vehicle speeds (whose signals can be overridden by emergency vehicles), or simply by adapting already existing satellite navigation systems to prevent speeds above prevailing speed limits. Many new vehicles come equipped with a voluntary version of a speed limiter already. The advent of driverless vehicles would, of course, also eradicate speeding. For all practical purposes, therefore, the technology exists already to render this pre-​crime of speeding all but redundant. The reasons why such steps have not already been taken are likely complex but would certainly include the probability of widespread public opposition. Despite it being normal to justify such a system on the grounds of public safety, public resistance has been significant and pervasive in this field. While little or no public opposition has emerged with respect to preventive driver drug and alcohol testing, in the case of safety cameras (that are used for speeding detection and to detect red light violations) opposition has been considerable, sometimes violent

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and often effective. In order to understand the survival of this ‘pre-​ crime’ or ‘risk-​crime’ of speeding, we need to examine the nature and effectiveness of this public resistance.

Resistance, risk crimes and the domain of control There is a strong sense in what has been written previously and elsewhere (e.g. Ashworth et al, 2013, Wilson & McCulloch, 2015) that there is an almost irresistible incoming tide of pre-​crimes. Certainly, given the shift toward prevention in areas such as policing (Ericson and Haggerty, 1998) and more generally across criminal justice (Kemshall, 2001; Hudson, 2003), this position is more than justifiable. Moreover, it cannot be thought that pre-​crimes are a specific or pioneering trend, when in many respects they are the rather belated move when compared to the long-​term seismic shift toward preventive interventions in fields such as medicine, and even more closely linked areas such as accident and fire prevention (O’Malley and Hutchinson, 2007). Again, while reasons for this tardiness are many and complex, one of these undoubtedly is judicial and public concern with extending the reach of criminal justice to those who have, as yet, committed no crime, nor explicitly planned to commit crime. This most likely explains why, for instance, even though categories such as ‘pre-​delinquency’ have existed since the 1930s (Burgess, 1936), and these have been the basis for crime preventive interventions of a ‘social’ sort, criminal sanctions such as preventive detention have been reserved for a very few categories such as habitual offenders or those suspected of terror plots. The rise of risk-​based justice looked for some time as though it would sweep away such concerns and build a ‘new penology’ or ‘actuarial justice’ (Feeley & Simon, 1992; 1994). However, others—​for example Freiberg (2000) and Simon and Feeley (1995)—​have demonstrated very clearly how the judiciary and the public have resisted risk-​based interventions that violate established principles of justice such as no punishment without a crime, and proportionality of offense and sanction. On this basis, it could be anticipated that public resistance to digitized and machinic speeding enforcement processes would appear. As mentioned earlier, from its beginnings at the turn of the 20th century speeding was resisted partly on the grounds that charges such as ‘furious driving’ or ‘dangerous driving’ already existed and seemed adequately to cover instances where behavior transgressed a moral boundary or harm threshold. It followed, for many, that the existence of these criminal offense categories meant that the stand-​alone act of speeding was not demonstrably dangerous in itself. Car owners, at that time, were mostly

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high status and wealthy elites, and were able to mount considerable resistance to encroachments on their driving practices. Speeding was defined by many as a money-​g rab, especially by local governments, and as a ‘tax on progress’. Indeed, one rationale for the offense in the early years was that speeding cars excessively damaged the unsealed road surfaces of the time. Fines were thereby justified as a road tax even though opponents argued that this was paid already in vehicle registration costs. On this basis, speeding did not exist as what we would now refer to as a ‘pre-​crime’: it was a form of criminalized nuisance that police and justices were often loathe to prosecute, especially given the standing of those being principally effected. Over the ensuing half-​ century, however, as roads were macadamized and cars became more common and capable of greater speeds, media campaigns against ‘road hogs’ gathered momentum (Plowden, 1971). But at the same time, many media portrayals of enforcing speeding laws retained the image of police lurking on empty roads and giving chase to motorists under circumstances where safety was not hinted at as an issue. The idea of speeding as a preventive ‘pre-​crime’ was, at least until the end of the 1950s, still beset by images of meaningless regulation, and sly taxation. As suggested earlier, this began to change with the rise of the statistically derived ‘road toll’ that displaced the specter of individualized ‘road hogs’. This was a time when safety issues became more central in road traffic regulation—​it was the era, too, of the introduction of seat belts, of ‘crumple zones’ and the rise of safety as a marketing feature of vehicles, alongside that of speed and comfort (both of which it would eventually surpass). As statistical data revealed the correlation between speeding and accidents, official justifications for speeding as a preventive offense became prominent. Concern with the public reception of new technologies, such as radar guns and speed cameras, was often associated with extensive signage warning that speed cameras were operating ahead: the reasoning being that this demonstrated an intention to limit speeding and thus reduce unnecessary deaths, injuries and property damage, rather than revenue collection from unsuspecting drivers. This was coupled with extensive media—​and later online—​ information, parables and slogans stressing that safety cameras save lives (see O’Malley, 2013a; Smith & O’Malley, 2017). If the rise of risk-​based approaches to crime has generated public and judicial concern and politics, what happened with the emergence of virtualized systems of control? Here justice becomes digitized in its operation, where drivers are faced with automated detection that picks up even the slightest excess of speed, where contesting electronically monitored offenses in court comes with a risky price tag and extra stress

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loading, and where defendants confront strict liability conditions and a well-​honed jurisprudence of safety. The court, as may be expected from this array of deterrents, has not been the stage where day-​to-​ day contestation has occurred. In practice, just as control operates in a virtual environment, this environment too has been a key site of resistance, where diverse forms of data are gathered, arguments are collaboratively developed and opposition organized. Challenges abound to the use of these models and technologies of government, although not all of these appear to go to the heart of the ‘pre-​crime’ or ‘risk-​crime’ issue. A few claims clearly do—​for example, objections that offenses are criminalized even though particular drivers with local knowledge are better placed to judge speeding risks than are universal rules; and that engineering solutions are superior means to reduce risks associated with speeding than criminal law sanctions. But many appear not to challenge the jurisprudence of safety that is now the foundation of the criminalization of speeding. These include challenges to the accuracy of cameras or their reliability in different weather conditions, challenges to the claims that enforcement through cameras reduces accidents, or claims that cameras are placed in low-​r isk sites. It could be argued that these latter points are not so much challenges to the law and its justification, as to its everyday enforcement. However, it is difficult to untangle enforcement from the more fundamental issues because all of these objections—​including claims that engineering solutions would make criminal law redundant—​are linked directly to a broader claim that speeding laws are not about safety as is claimed by state actors but about revenue raising. Of course, these are objections which date from the early 20th century, but they later assumed a largely subterranean existence—​they may have been widely believed but were not the focus of salient public resistance until comparatively recently. However, the widespread impact of mass preventive justice and the development of the very virtual media infrastructures that make it possible, have brought back to the surface and magnified a resistant micro-​politics. The rise of the Internet has created the means whereby mass opposition can be developed, articulated and mobilized. An abundance of websites, chat rooms, listservs, Twitter accounts and so on have sprung up through which arguments and mediated data may be aired and shared, data may be gathered from public and hacked sites, and protests organized and enacted. Several earlier studies have mapped these issues in detail (e.g. Wells, 2012; O’Malley, 2013a; Wells, 2015; Smith & O’Malley, 2017). As well, the internet and mobile phone networks have been deployed in organizing and staging protests that have included blocking

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motorways, obstructing enforcing officials, publicly shaming contracted speed camera operators and even destroying ‘safety’ cameras (Smith & O’Malley, 2017). The issue here is not to sort out whether these claims are accurate or not—​something that would involve evaluating competing epistemes, claims and evidence—​that would likely prove inconclusive or certainly be contested. Many claims can be accepted at least in part—​such as the superiority of engineering solutions, and the fact that high-​ revenue earning cameras have been placed in low accident risk areas.2 Similarly, other claims can be dismissed, such as those that contend that red light cameras increase fatalities.3 For many others there is no evidential basis for making any conclusion—​such as the argument that local drivers make better judgments about speeding in risk areas than do remote experts who base their assumptions on abstracted, statistical data. Rather, the key question is what social impact they have had on reining-​in the spread of risk crimes in a control environment. Information-​backed campaigns have led to the removal of certain cameras, pauses in network development, the cancellation of many speeding charges and the defunding of camera programs—​not to mention the formation of ‘anti-​enforcement’ driving communities (O’Malley, 2013a). But nowhere have whole systems of enforcement been closed down. At best, there has been a suspension of operations or a scaling back of the system, but in all the cases we have analyzed, this has been a temporary measure. In Sydney Australia, for example, the state government responded to Internet and media challenges about the placement of cameras by holding a review, and then eventually removing 38 high-​revenue cameras that could not be justified on safety grounds—​either because they were in not in proven high-​r isk areas or because they had produced no demonstrable reduction in accidents. (O’Malley, 2013a). However, such changes have, if anything, most likely improved the efficiency of the surveillance apparatus, helping to ensure that more high-​risk sites are monitored. It seems highly unlikely that this form of control apparatus will be wound back, at least unless and until other control arrays already mentioned make speeding impossible. Indeed, it is likely to be just the beginning of a gradual evolution and rolling out of this type of risk-​driven, simulated justice, with new adaptations being designed for use in different domains and contexts of human activity.

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Conclusion In many ways, the rise of traffic regulation has pioneered techniques of governance that are now facilitating the expansion of pre-​crime interventions associated with ‘antisocial’ behaviors—​as in the UK with ASBOs (antisocial behavior order), for example. These include the use of on-​the-​spot infringement notices and the inducements to accept them. As Fox (1996) mapped out some years ago, such techniques were developed in a trial and error fashion as ways of fast-​tracking justice in order to cope with high volumes of traffic infringements. But we should also consider the role of fines as a ‘low impact, low visibility’ sanction. While fines have been the most common sanction in criminal justice since the beginning of the 20th century, traffic control pioneered the fixed fine schedules that allowed automatic calibration of offense and sanction—​and the creation of platforms that could stage both the issuing of a monetary penalty and the ensuing collection of revenue. Indeed, at this point, fines literally become prices: the cost is known beforehand, will apply regardless of the offender, and—​like fines in general—​need not be paid by the wrongdoer. Parents, spouses and employers may all pay fines for offenders. In this way, these kinds of fine literally become a price, a part of day-​to-​day living, something levied for things as trivial as an overdue library book. Thus, they are likely to stir up few of the liberal shibboleths that other sanctions may do.4 As well, traffic control fostered the deployment of ‘quasi-​police’ as enforcers—​such as parking officers initially, and later the widespread use of outsourcing and contracted agents to operate speed cameras. In such ways, risk-​based speeding offenses pioneered the creation of a risk continuum that softened up the ‘leading edge’ of criminalization that is associated with the growth of pre-​crimes. Thus, although speeding offenses are often not thought of as criminal, despite their being so in most jurisdictions, there is a smooth transition that runs from low range speeding that barely raises an eyebrow, to speeding so far over the limit that in many jurisdictions it automatically morphs into the far more serious offense of ‘dangerous driving’. Finally—​b ut in some respects possibly of most long-​term consequence—​it was in the traffic field that the technique of using quantified pre-​crimes as risk markers was developed. Initially, the concern here was that, as others could pay fines for offenders, and because the wealthy could afford to pay fines with ease, this system would not achieve the safety effects intended. The invention of demerit points was planned to deal with this problem. Accumulating with each offense and culminating with license suspension or cancellation, the

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demerit point system really did—​with numerical precision—​‘blur’ the lines of crime and pre-​crime. Accumulating demerit points is not an obvious criminal justice sanction, but it is a sanction delivered by criminal law. As well, it is a sanction that puts the offender into a risk category that heightens the probability of future ‘blurry’ sanctions—​ for license cancellation is not only a ‘regulatory’ sanction, it is also now a widely used sanction in criminal justice. Entering the domain of risk-​based justice now makes it less clear than ever whether we are dealing with crimes, pre-​crimes, post-​crimes or something else altogether: a formalized system of social risk categorization. At this point, the whole problematic of ‘pre-​crimes’ begins to open up into something far more consequential than the issuing of a few fines, or even the issue of traffic safety itself. In the passage cited at the beginning of this chapter, Newman argues that ‘societies of control seek to define the individual through a series of different, modulated and overlapping states of risk, with indeterminate and shifting borders’. What we have been examining in the domain of speeding offenses is exactly this, especially once practices of remote monitoring and digital processing are added into the mix. It extends further than we might suspect even in the traffic domain. Thus, in New South Wales, there has been discussion of using facial recognition technologies within the speed camera enforcement system to identify drivers. This would prevent speeding drivers persuading or paying others to admit to driving an offending vehicle and thereby allowing the driver to avoid the accumulation of demerit points that would lead to license suspension or cancellation (O’Malley, 2013b). From this point, it can readily be seen that the sky is the limit. The ‘Smart Cities’ movement that has worldwide purchase aims at the creation (through building new cities or modifying existing ones) of sensorized, digitized and automated metropolises. Structured around a vision of a ‘fourth industrial revolution’, every aspect of life is to become interconnected through ‘the internet of things’. Whatever benefits may flow from this, and there may be many, it has caused considerable alarm with respect to a dystopian future of universal surveillance. However, in already operating apparatuses—​such as the ‘Switching on Darwin’ program in Australia—​alarm is already being expressed precisely because of its implications for shifting the borders of social control (see O’Malley & Smith, 2019, 2020). In the Darwin project, extensive use of improved LED street lighting and blanket coverage by CCTV cameras enhanced with video analytics are all fed through to police (who have access to facial recognition programs and are negotiating a national facial

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recognition database). This has suggested to critics an arrangement such as the Human Rights Watch (2020), which recently has identified: The social credit system which the Chinese government has instituted in some areas to reward good conduct and punish bad behaviour, such as jaywalking and failure to pay court fees, has now become an ‘off the shelf ’ product available to other states—​opening the door to the proliferation of surveillance states. (Bagshaw, 2020, p. 3) The leading edge of ‘pre-​crimes’ is thus capable of advancing into the interstices of everyday life, and feeding into a ‘demerit’ point system that flags citizens on a risk scale that is vastly diversified, extended and, frankly, indeterminable in scope. We may be far from seeing such a diagram realized in western states. But as the Darwin scheme suggests, only maybe: the diagram of virtual justice that now is commonplace in the governance of traffic ‘pre-​crimes’ was a pipe dream once. Notes 1

2

3

4

It is important to note that many commentators in criminology and elsewhere use the term ‘risk’ much more loosely. For example, Victor Tadros (2013) in a paper that focuses extensively on control orders—​a form of preventive detention deployed in relation to terrorism that has been prominent in UK politics for a decade—​uses the term non-​statistically. This is not problematic in general terms, as it has been rare for criminal justice to resort to statistical probabilities in policy moves or judicial judgments (O’Malley, 2009). However, the wider literature on risk differentiates between (statistical) risk and (estimated) uncertainty. This has important theoretical ramifications, as those familiar with the work of Ulrich Beck (1992) would recognize. As will become clear in this chapter, the shift from uncertainty to statistical risk is vital in consideration of key issues, and throughout risk will be used in the narrower statistical sense. As will later be noted, the NSW government withdrew 38 speed cameras from its Sydney network because they earned high revenues but did not demonstrably reduce risks. Red light cameras have increased certain kinds of accident, principally nose to tail accidents caused when drivers brake hard for a light change. However, they greatly reduce t-​bone accidents (where one car collides head on with the side of another), which are much more likely to cause death and injury (O’Malley, 2013a). This of course is not to trivialize all fines. As discussed earlier, fines may have severe impacts on poor and socially marginalized people, even if this is not recognized by many.

References Ashworth, A., Zedner, L. & Tomlin, P. (eds.) (2013). Prevention and the Limits of the Criminal Law. Oxford, UK: Oxford University Press.

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Bagshaw, E. (2020). China pans ‘unbalanced’ report. The Age 15/​1/​ 2020: 3. Beck, U. (1992). Risk Society: Toward a New Modernity. New York, NY: Sage. Burgess, E. (1936). Protecting the public by parole and parole prediction. Journal of Criminal Law and Criminology 27: 491–​502. Castel, R. (1991). From dangerousness to risk. In G. Burchell, C. Gordon and P. Miller (eds.), The Foucault Effect. Studies in Governmentality. London, UK: Harvester/​Wheatsheaf (pp. 281–​98). Deleuze, G. (1995). Postscript on control societies. Negotiations 1972–​ 1990. New York, NY: Columbia University Press (pp. 177–​82). Ericson, R. & Haggerty, K. (1998). Policing the Risk Society. Toronto, CA: Toronto University Press. Feeley, M. & Simon, J. (1992). The new penology: Notes on the emerging strategy of corrections and its implications. Criminology 30: 449–​7. Feeley, M. & Simon, J. (1994). Actuarial justice. The emerging new criminal law. In D. Nelken (ed.), The Futures of Criminology. New York, NY: Sage. Foucault, M. (2007). Security, Territory, Population. London, UK: Palgrave Macmillan. Fox, R. (1996). Criminal Justice on the Spot. Infringement Penalties in Victoria. Canberra, AU: Australian Institute of Criminology. Freiberg, A. (2000) Guerillas in our midst? Judicial responses to governing the dangerous. In M. Brown & J. Pratt (eds.), Dangerous Offenders. Punishment and Social Order. Abingdon, UK: Routledge (pp. 51–​70). Hudson, B. (2003). Justice in the Risk Society. London, UK: Sage. Human Rights Watch (2020). World Report 2020 [online] Available at: www.hrw.org Kemshall, H. (2001). Understanding Risk in the Criminal Justice System. Milton Keynes, UK: Open University Press. Kemshall, H. & Maguire, M. (2003). Public protection, ‘partnership’ and risk penalty. Punishment and Society 3: 237–​54. Newman, S. (2009). Politics in the age of control. In M. Poster & D. Savat (eds.), Deleuze and New Technology. Edinburgh, UK: Edinburgh University Press (pp. 104–​24). O’Malley, P. (2009). The Currency of Justice. Fines and Damages in Consumer Societies. London, UK: Glasshouse Press. O’Malley, P. (2013a). The Politics of Mass Preventive Justice. In A. Ashworth, L. Zedner & P. Tomlin (eds.) Prevention and the Limits of the Criminal Law. Oxford, UK: Oxford University Press (pp. 273–​95). O’Malley, P. (2013b). Telemetric policing. Encyclopedia of Criminology and Criminal Justice. New York, NY: Springer-​Verlag (pp. 5135–​45).

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O’Malley, P. & Hutchinson, S. (2007). Reinventing prevention. Why did ‘crime prevention’ develop so late? British Journal of Criminology 47: 439–​54. O’Malley, P. & Smith, G. (2019). Disruption as distraction. Darwin’s Smart City Program, public resistance and the racialization of digital governance. Disrupting Data Injustices Roundtable. University of NSW, 2 December. O’Malley, P. & Smith, G.J.D. (2020). ‘Smart’ crime prevention? Digitization and racialized crime control in a smart city. Theoretical Criminology, https://journals.sagepub.com/doi/10.1177/1362480620972703 Plowden, W. (1971). The Motor Car and Politics 1886–​1970. London, UK: The Bodley Head. Simon, J & Feeley, M. (1995). True crime. The new penology and public discourse on crime. In T. Blomberg & S. Cohen (eds.), Law, Punishment and Social Control: Essays in Honor of Sheldon Messinger. New York, NY: Aldine de Gruyter (pp. 147–​80). Smith, G. & O’Malley, P. (2017). Driving politics: Data-​driven governance and resistance. British Journal of Criminology 57: 275–​98. Tadros, V. (2013). ‘Controlling Risk’. In A. Ashworth, L. Zedner & P. Tomlin (eds.), Prevention and the Limits of the Criminal Law. Oxford, UK: Oxford University Press (pp. 133–55). Wells, H. (2012). The Fast and the Furious: Drivers, Speed Cameras and Control in a Risk Society. London, UK: Ashgate. Wells, H. (2015). Getting around and getting on: Self-​interested resistance to technology in law enforcement contexts. Annual Review of Law and Social Science 11: 175–​92. Wilson, D. & McCulloch, J. (2015). Pre-​crime, Pre-​emption, Precaution and the Future (2). Abingdon, UK: Routledge.

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4

The Negation of Innocence: Terrorism and the State of Exception David Polizzi

Introduction In her text, Regarding the Pain of Others, Susan Sontag (2003) explores the phenomenology evoked by the images of the victims of war. She (2003) observes that ‘photographs of the victims of war are themselves a species of rhetoric. They reiterate. They simplify. They agitate. They create the illusion of consensus’ (p. 6). This ‘illusion of consensus’, to which Sontag eludes, is predicated upon the belief that once these images detailing the destructive capacity of war are viewed, the concluding consensus will be that such atrocities must not be allowed to continue. In rejecting such a conclusion1, she offers a simple question: ‘But is it true that these photographs, documenting the slaughter of noncombatants rather than the clash of armies, could only stimulate the repudiation of war? Surely they could foster greater militancy on behalf of the Republic. Isn’t this what they are meant to do?’ (Sontag, 2003, p. 8). Sontag (2003) concludes by observing that such images can only stimulate a repudiation of war, when politics is either dismissed or ignored from this phenomenological process. As such, images of war are rarely viewed as apolitical representations of ‘anonymous generic victims’ (p. 9); rather, they are often employed with the purpose of validating a specific point of view relative to the political narrative these

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images seek to evoke. ‘To those who are sure that right is on one side, oppression and injustice on the other, and that the fighting must go on, what matters is precisely who is killed by whom’ (Sontag, 2003, p. 10). For Sontag, images of war become meaningful from the perspective of the viewer. She argues that the image of a Jewish child killed by a Palestinian suicide bomber or a Palestinian child torn apart by Israeli military ordinance in Gaza is rarely viewed as the murder of an anonymous victim.2 The very fact of these deaths comes to reinforce certain socially constructed beliefs concerning those responsible for these acts.3 From this perspective, these deaths can never be viewed as the murder of anonymous victims, for the simple reason that to do so would also require a reconfiguration of those socially constructed truths, which give these images their specific meaning (Verdery, 1999; Polizzi, 2019).

Who is killing whom in the digital age?4 In the digital age, Sontag’s construction of the ‘Who is Killing Whom’ dynamic, takes on a much more powerful relevance. Though the absence of an anonymous victim is retained in much the same way as it is in the photographs discussed, this lack of anonymity becomes greatly intensified with real-​time video imagery, which seeks to accentuate the social identity of the victim (Polizzi, 2019). In fact, it could be argued that one of the more important aspects of this type of online video footage is to dispel any possibility for such an anonymous victim to be recognized. Anonymity reflects the innocence of the victim killed, which is of course, the exact opposite conclusion these images are trying to evoke. As a result, what becomes one of the more chilling aspects of online video imagery is the way in which the victims of violence become constructed and viewed by the ‘certainty’ of their ‘guilt’ and not by the possibility of their innocence. From this perspective, there is no question concerning the correctness of this verdict. There is only guilt and the punishment to be imposed on those targeted for execution. Within such a phenomenology, all that remains is the point of view of the spectator, who completes the figure of this triangulated relationality. Unlike the photographs described by Sontag, terrorism-​related video images tend to reveal a type of parallel intent, which is focused on the specific task of clarifying the roles or subject positions of both ‘hero’ and ‘villain’. Though it is certainly true that such a process is always present in various types of photographic or digital imagery,5 albeit at

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times indirectly so, this is rarely the case with imagery composed by the perpetrators of domestic or international terrorism or in various examples of mass shooting episodes. In those examples, it is essential that the characterization of protagonist/​antagonist is clearly identifiable to the viewer. Take for example the digital footage offered by IS/​ISIS/​ D.A.E.S.H.6 As German (2019) observes, ‘ISIS has made newsworthy use of social media for a variety of purposes, from soliciting financing to recruiting fighters, establishing legitimacy, and instilling fears in its adversaries’ (p. 129). IS has been particularly successful in establishing fear through their use of horrifically graphic video displays, which could be fairly defined as political snuff films or ‘shorts’. Within this context, it is important to recognize that unlike the manipulation of a random photographic image(s), these video images are carefully composed and choreographed to construct a very specific narrative (German, 2019; Polizzi, 2019). The murder of video freelance reporter James Foley is a tragic example of this process.7 Richey and Edwards (2019) describe the visual scene in the video prior to Foley’s murder in the following way. A shaven and malnourished James Foley, clad in an orange jumpsuit, kneels in the hot desert. On his left flank is an ISIS fighter with his face covered. Foley who is clearly suffering, states, ‘I call on my friends, family, and loved ones to rise up against my real killers, the US government, for what will happen to me is only a result of their complacency and criminality’. (Richey & Edwards, 2019, p. 167) The video image described, powerfully configures both protagonist and antagonist, while also employing a compositional strategy that choreographs the specific meaning of the scene relative to the viewing audiences that it is trying to reach. Unlike the more ‘anonymous’ depictions of various forms of physical violence, these images leave little to the imagination. The compositional strategy employed clearly identifies the main characters in this macabre scene, while also vividly constructing the ‘roles’ that each will ‘play’. As a result, the depiction of James Foley kneeling in an orange jumpsuit next to his executioner holds specific implications for the audience as well. Much like any viewed image, this choreographed scene constructs a specific relationality between hero, villain and spectator that helps to reveal its co-​constituted phenomenology. Within this context, then, the configuration of hero and villain becomes completed by the viewing

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audience. The specific meaning this phenomenology reveals, becomes predicated upon the ways in which the audience relates to these images, which in turn, helps to configure a specific subject position for the viewer as well: does the viewer symbolically place themself in the position of the ‘convicted’ inmate about to be executed or in the subject position of the avenging Holy Warrior? This choreographed meaning-​generating process, which these images seek to impose upon the viewing audience, attempts to configure two different versions of the constructed subject: on the one hand, we see the image of the ‘righteous’ Holy Warrior avenging the crimes against Islam; and on the other, we see the image of the vanquished adversary, now being made to pay the price for those ‘crimes’. When viewed in this way, these images become an apparatus of terrorism, whose function is located within the process of the re-​fabrication of the viewing subject (Polizzi, Draper & Andersen, 2014). It will be recalled that for Agamben (2009), a type of dialogical relationality exists between living being, apparatus and subject: with the subject emerging from the ‘in-​between’ of this clash of being and the apparatus. Within the digital world, various manifestations of the ‘fabricated self ’ are reproduced by the digital machine of terrorism, through this phenomenological engagement with the apparatus.8 The specifics of this re-​fabricated self will depend upon the way in which the viewer is engaged and reconfigured by these images (Flusser, 2000). As a result, the public execution of Foley is not really the end of the narrative depicted by this horrific event; rather, it is simply the opening chapter or scene of a much longer story, whose cinematic intent is to configure the Western viewer as the next criminal subject to be brought to justice. From this ‘cinematic’ point of view, the phenomenology or anticipation of risk or harm becomes perpetual and unresolved. The perceived risk threatened by this radicalized other, cannot be viewed as being exclusively situated within the person of James Foley; rather, it is more focused on who will be its next victim. When configured in this way, the anticipation of risk becomes a type of emotional apparatus, which manufactures subjects of fear and victimization. From this perspective, the possibility of innocence or the recognition of innocence, is negated by the dynamic of who is killing whom; within this context, there are only perpetrators and victims. Potential targets are identified given their ethnic and religious affiliations, a process which is often further clarified by specific localities. Once situated within these localities states of exception emerge identifying targets and nullifying innocence.

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The focus of this chapter will be to explore the various ways by which a state of exception is evoked within the relational dynamics of terrorism. Though this concept is generally recognized as a set of actions performed by a given state, its process can be similarly located within the relational dynamics of various examples of religious and politically motivated violence. Whether evoked by a traditional state actor or by a non-​state organization or group, the contours of the emerging state of exception will be configured by issues of identity and locality, which are clearly situated within the construct of ‘who is killing whom’. We will begin with a discussion of this concept from the perspective offered by Giorgio Agamben (2005).

The state of exception In his text of the same name, Agamben (2005) defines the state of exception in the following way: ‘according to a widely held opinion, the state of exception constitutes a “point of imbalance between public law and political fact” that is situated—​like civil war, insurrection and resistance—​in an “ambiguous, uncertain, borderline fringe, at the intersection of the legal and the political” ’ (p. 1). From this general description, the state of exception becomes a type of political response that emerges during moments of perceived political crisis by the state, or by intentionally manufactured political events that are employed to legitimate the extralegal strategies applied by the state to address the current situation. However, as Agamben (2005) observes, this definition becomes paradoxical insofar as it implies ‘juridical measures that cannot be understood in legal terms’ (p. 1) or suspends the rule of law all together. It is this gray area between the legal and political where Agamben situates his focus. For Agamben, the state of exception exits in the confluence between the political and the legal. As such, this process reflects neither the onset of civil war nor the complete suspension of the law; rather, it creates zones of indifference where extralegal means are allowed, so long as these practices remain confined to specific localities. Though traditionally used to define modern totalitarian states, the state of exception allows: for the physical elimination not only of political adversaries but of entire categories of citizens who for some reason cannot be integrated into the political system. Since then, the voluntary creation of a permanent state of emergency (though perhaps not declared in the technical sense) has

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become one of the essential practices of contemporary states, including so-​called democratic ones. (Agamben, 2005, p. 2) From this perspective, the ‘voluntary creation of a permanent state of emergency’, becomes possible insofar as it is never specifically employed against an entire society. By targeting or physically eliminating certain groups or individuals ‘who for some reason cannot be integrated in the political system’ (Agamben, 2005, p. 2), a permanent state of emergency can be employed given its discriminatory process of identification. Though current immigration practices in the US often employ extralegal strategies by which to curtail certain ethnic groups from entering the country, that practice has not been employed across the board and for the most part has been prominently located on the southern border of the United States or has specifically targeted Latino populations in specific cities across the US. In the aftermath of the 9/​11 attacks, a variety of extralegal strategies were employed to fight the war on terror. Strategies such as extraordinary rendition—​or kidnapping—​were used to remove suspected terrorists from streets with the goal of preventing further attacks (Murray, 2011). Once in custody, some of these same individuals were then subjected to the torture technique of waterboarding to extract potentially actionable intelligence. Perhaps the most profound example of this type of exception was and is witnessed by the detention facility located at Guantanamo Bay, Cuba. Much like the infamous federal penitentiary located on Alcatraz Island in the San Francisco Bay, which operated from 1933–​1963,9 the correctional facility constructed at Guantanamo Bay, Cuba was similarly intended to symbolize through practice how suspected terror suspects would be treated when held in US custody. However, unlike Alcatraz, those prisoners or enemy combatants detained at Guantanamo Bay were denied almost all legal protections given that the US failed to recognize these individuals as protected under the Geneva Convention, while also denying them any access to the US courts.10 It is important to note that most of the detainees held at Guantanamo Bay were never formally charged with any crime, they were not given a date for trial and were refused access to legal counsel.11 Additionally, a number of these individuals were also subjected to waterboarding or other questionable interrogation practices that would have disqualified them from being tried in US courts based on constitutional grounds. It is not surprising, therefore, that many of the supporters of these practices were rather vocal in their opposition to trying any detainee in

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US courts. From this perspective, to do so would grant legal privileges to individuals who are not worthy of such protections, regardless of whether or not such practices actually violated the core beliefs that many of these individuals claim to embrace so strongly. A similar line of ‘logic’ can be recognized between the state of exception described by Sontag and the state of exception employed to rationalize any number of extralegal practices used by the United States in the pursuit of the War on Terror. What is most powerfully present with both of these examples is the negation of any possibility for a ‘pre-​existing innocence’; that is, an understanding of innocence, which is not legitimized or validated by a set of pre-​configured social constructions that has already determined guilt or innocence. However, before a more thorough explanation is provided concerning innocence and the state of exception, it is first necessary to explore this idea within the context of non-​state terrorism.

Non-​state terrorism and the state of exception Within the traditional context of the state of exception, state actors construct zones of indifference, which help to configure specific localities, either domestic or international, where the general practice of the rule of law will be suspended. For non-​state actors, particularly those actively involved with either domestic or global terror organizations, a similar dynamic can be witnessed. However, from the perspective of non-​state actors—​be they, terrorist organizations or individuals working in the service of the same (directly or indirectly) the state of exception becomes a much more fluid process, whose specific configuration will be specific to the group or individual involved. Though this version of the state of exception becomes manifest in similar ways to that of the traditional state, given that it too seeks the physical elimination of those individuals or groups, ‘who for some reason cannot be integrated in the political system’ (Agamben, 2005, p. 2), it often lacks the ability to configure zones of indifference based upon the official suspension of the law. However, as a result, zones of indifference emerge based on the opportunity they present relative to the specific individual or group targeted for physical elimination. Those who have been deemed as ‘unworthy’ to be integrated into the political system are those individuals that then can be targeted for elimination. Take for example the man who murdered two African Americans in a local grocery store in Jeffersontown, Kentucky. The perpetrator, Jeffrey Bush, after failing to enter the First Baptist Church of Jefferson, arrived at the local Kroger grocery store with the intent of killing

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African American shoppers inside. Upon entering the store, he fired multiple rounds at an older African American man before exiting the building; while in the parking lot of that store, he confronted an older African American woman, shooting her multiple times. Bush himself was shot by an armed bystander as he attempted to leave the scene and was subsequently captured by police. Both of Bush’s victims were pronounced dead at the scene. During this episode, he was reportedly confronted by an individual inside the store. Bush is reported to have told this individual that ‘whites don’t kill whites’ and moved on (Zraick & Stevens, 2018). What the case of Jeffrey Bush reveals is the way in which individual presence becomes transformed into a zone of indifference, which seemingly at the moment of this attack, does not extend beyond the persons targeted. When the shooter observes that ‘whites don’t kill whites’, a type of legal prohibition’ is recognized—​albeit only in the mind of the shooter and those who share his position—​that the killer refuses to ignore, even if it would aid him in his own escape. Within this example, the state of exception unfolds as a fluid dynamic that remains exclusively focused on the ‘problem’ that needs to be eliminated. Perhaps what becomes most significant to this version of the state of exception is that it has no specific locality by which to situate this process of suspending the ‘law’.12 With a more traditional state-​driven example of this process, the state of expectation retains certain specifics relative to locality, ethnicity and political and religious affiliations. Whether these more static locations are solitary confinement units in maximum-​security penitentiaries, specifically designated border areas where immigrant children are separated from their families, or specifically targeted neighborhoods, the ‘exceptional’ status of these localities remains more or less unchanged. When placed within the context of non-​state actors, the actual locality of these exceptions become less important, insofar as the focus shifts fundamentally to the individual or group that is being pursued. As a result, the presence of the individual becomes the locality, by which this exception gains its ‘legitimacy’ to act. Once the targeted party has been identified, a zone of indifference is immediately established for the duration of the attack, and then more than likely recedes back into its former identity. Though the possibility of subsequent attacks may still be palpably present, the specific locality does not retain the permanent status of ‘exception’. However, it is important to mention that the earlier discussion is not intended to imply that all non-​state actors fall into this nontraditional configuration of the state of exception. Such a conclusion would not be

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accurate. Any one of the numerous examples of mass shootings in places of worship would suffice as evidence to disprove that possibility. One of the overlapping commonalities of these two types of ‘expectation’ can be recognized by the static nature of the locality in question. Whether the zone of indifference is configured as a place of worship or as a specific portion of a national border, just to name a few possible examples, the locality is generally speaking, static in nature. The targeting of places of worship occur as they do for the obvious reason that if one were interested in killing Jews or Muslims, it is unlikely that the perpetrator would enter a Christian church to achieve their goal. Given this fact, places of worship retain their locality of exception for those individuals or groups, who have constructed a specific religious affiliation as their target.13

State of exception or state of permanence? Agamben’s observation, shown in the following, has chilling implications for the contemporary world: ‘the voluntary creation of a permanent state of emergency (though perhaps not declared in a technical sense) has become one of the essential practice of contemporary states, including so called democratic ones’ (Agamben, 2005, p. 2). The presence of these states of ‘permanent exception’ have come to define the socio-​political and socio-​economic contemporary landscape, which in turn has helped to evoke a tidal wave of marginalized disenfranchised non-​state actors, who have utilized similar strategies of exception by which to identify and confront their adversaries and legitimize their cause. As has been witnessed by the various strategies employed in the War on Terror, emerging ‘necessities’ have been embraced by those targeted by these exceptional means, to rationalize their own equally brutal ends. The rise of Salafist Jihadi organizations in the Middle East and elsewhere and the ‘normalization’ of anti-​Semitism, and various forms of racism and neo-​Nazi attitudes across the US and Europe, has become one of the most troubling consequences of these emerging ‘exceptionalized’ realities. What cannot be forgotten within this context is that permanent states of exception, almost by definition, must continually construct identities that coincide with these zones of indifference. Sontag’s photographs exist as they do because they reside in a permanent state of exception. Once this type of relationality has been established and configured within individual identity, the strength of these calcified social meanings is nearly unbreakable (Griffin, 2012; Moghaddam, 2018; Morris, 2017).

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States of exception and the negation of innocence What seems most recognizable within either configuration of the state of exception is what can be described as the negation of innocence. Whether this construct is viewed through the suspension of the law as reflected by such examples as Guantanamo Bay or by suicide bomber attacks on civilian populations employed by non-​state actors, the result is still the same: the negation of innocence. Whereas with the more traditional configuration(s) of the state of exception, zones of indifference are created and the subjects residing there in are for the most part defined by a presumption of guilt rather than the presumption of innocence. In fact, this specific strategy of subject construction is essential to this process for the simple reason that the exception it evokes and the legitimacy it seeks to enjoy, is fundamentally predicated upon the ‘whom’ of this process. Non-​state actors employing this type of exception take on a much broader configuration and concern. Taken from this perspective, the negation of innocence becomes situated within a meaning-​generating process that configures zones of indifference in a fluid and often unpredictable manner. As such, fluid configurations of sovereignty or the sovereign similarly constitute fluid zones of indifference that no longer require the types of specific locality normally witnessed in the more traditional examples of this construct. Though the suspension of the law is clearly present in these more fluid configurations of exception, particularly those constructed by groups like IS, territorial locality is really no longer necessary, given that the zone of indifference exists anywhere the targeted subject can be found. Within this context, the construct of negation configures those individuals or groups deemed to be in some way in violation of the ‘law’. As such, their elimination from the ‘body politic’ reflects a ‘restoration’ of order and order can only be restored through the elimination of those individuals deemed responsible for this condition (Esposito, 2019). The negation of innocence, therefore, simply extends this more traditional Western philosophical understanding of disorder, without, however, providing an immediate resolution to the issue. Whereas the traditional negation of disorder, helps to evoke a sense of order which emerges from it (Esposito, 2019), the negation of innocence seemingly resolves nothing and at times seems endless in its duration. Whether this ongoing negation is perpetrated by more established states or by the seemingly endless configuration of various secular and religious non-​state actors, this idea of disorder has become, at least for the current historical moment, a consent present.

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Concomitant with this perpetual refiguring of this state of negation, are the continual strategies of resistance employed against this constant threat of disorder.14 It may be argued that the examples of terror attacks or mass shootings are not accurate representations of the state of exception, given that these are obviously not state actors and therefore have no actual set of laws to suspend. However, as the brutally of IS, al-​Qaeda, Boko Harem and any number of alt-​r ight groups in the US and elsewhere clearly attest, the possibility of innocence is only possible after their indictments of guilt have been served. For these examples, zones of indifference suddenly emerge based solely on the determination that those who inhabit these spaces are worthy of punishment. There is no discussion of collateral damage or the unfortunate loss of innocent lives.

Cinematic shock, the aesthetics of violence and real life What is perhaps one of the most telling qualities of the negation of innocence, is the various ways in which it can disrupt or erode the taken for granted relationship between safety and locality. In the absence of innocence, safety becomes less certain and the security of home less capable of diverting the lingering anxiety this uncertainty evokes.15 As such, this new environment becomes transformed and transfixed. What was formerly benign and free of immediate threat becomes eerily uncertain and potentially dangerous at any moment. It is important to include here that such an observation concerning the nature of violence is not simply tautological, not simply stating a rather obvious point: that violence is for the most part always unexpected and unanticipated. Though this is certainly true of most kinds of violence, the violence of terrorism or the violence employed to combat the same, can explode with such unexpected force, and in such unexpected ways that the expectation for safety can be fundamentally disrupted. When this type of negating violence occurs, its explosive force shatters the benign calm of normal daily existence, with a power that both disorientates and terrifies. Whether this shattering is experienced at a place of worship, a high school, a wedding, movie theater, café, crowded city street, or by the lethal violence inflicted by unmanned drone attacks, chaos replaces calm and innocence is no longer possible. In the wake of such events, landscapes and localities are transformed; buildings and streets become something else. If this was a bad horror film, we would be describing what is known as the ‘jump scare’; that almost anticipated moment, when the unanticipated act of horror

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shocks the audience: the only difference being, however, is that terrorism or other types of politically driven violence, are obviously real. It will perhaps be helpful to first explore the phenomenology of the cinematic or jump scare from its original context and then apply that discussion to the aesthetic violence of terrorism. For Hanich (2012), cinematic shock ‘describes the concurrence of an aesthetic strategy designed to create a shocking phenomenological experience with shocked viewers who experience precisely the phenomenological experience aimed at by the aesthetic strategy: Shock—​just as with lust or pain—​cannot exist, after all, without someone to experience it (p. 583). From this encounter with the aesthetic object, two types of aesthetic experience are revealed: one of self-​recognition, which Hanich maintains is situated affectively within the lived-​body and the other, is that of a collective recognition (Hanich, 2012). The initial experience of fear is viscerally evoked in the lived-​body, which is then shared collectively with the others in the audience: an experience which ‘moves from intra-​subjectivity to inter-​subjectivity’ (Hanich, 2012, p. 584). Within this context, a type of intertwinement occurs between viewers, film and the physical surroundings of the theater (Sobchack, 1992). However, this experience of intertwinement is predicated upon varying points of focus, which are fluid in the way they appear and then quickly recede (Hanich, 2012). Central to this process for Hanich is the way in which self-​recognition occurs when ‘confronted’ by the aesthetic object of the film and the intra-​subjective experience it evokes. As my experience of the aesthetic object constructs me through this unfolding of affective recognition, I begin to question my own sense of vulnerability within my own intertwinement with world. The notion of self-​recognition described by Hanich can also be applied to the video images often involved in the process of digital radicalization. Whether this process is focused on imagery related to alt-​right terror groups or those video presentations specific to the Taliban, al-​Qaeda, al-​Shabaab or IS, the notion of self-​recognition becomes an essential aspect of the phenomenology of radicalization. When confronted by the aesthetic object of these types of video presentations, the phenomenology of self-​recognition emerges as this relates to the specific spectator and the perspective they bring. To this point, Hanich (2012) observes that this encounter with the aesthetic object ‘enables us to recognize ourselves’ (p. 586). The author continues by observing, ‘My understanding of recognition as self-​recognition is therefore not inter-​subjective but primarily intra-​subjective. In other words, I am not recognized by an Other, but recognize myself as an embodied being’

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(Hanich, 2012, p. 586). It is through this process of self-​recognition that the phenomenology of radicalization becomes possible in relation to digital reality and existence. The encounter or confrontation with the digital aesthetic objects of extremist websites and social media venues becomes the context from which this phenomenology of radicalization appears. Much like the confrontation with the aesthetic object of the horror film, this apparatus of the terrorism machine evokes for the viewer an image or configuration of the self that he or she would like to be. This emerging self becomes forged from the existing political and social conditions experienced by the viewer within the context of their day-​to-​day existence along with the various ways in which these confronted digital images help to complete this process. As a result, it is important to recognize that the phenomenology of radicalization is not exclusively contingent upon a specific confrontation with this digitally accessible material; rather, it requires that we view the digital world as an extension of individual existence along with the various ways in which social context becomes intertwined with this process.16 However, the process of self-​recognition as described in the experience of cinematic shock is certainly different from this notion of self-​recognition as it is being discussed within the context of the phenomenology of radicalization and the confrontation with the apparatuses of the terrorism machine. With cinematic shock, the experience of the ‘jump scare’ is contained within the structural surround of the movie theater. Though there may be some lingering effects that ‘leak’ into other aspects of our everyday existence, this encounter is for the most part enclosed by the movie going experience. When placed within the context of the phenomenology of radicalization, this process is inverted with often tragic results. Taken from this perspective, the experience of self-​recognition becomes less about vulnerability and more about the transformative ‘possibilities’ that the phenomenology of terrorism offers17 and concomitantly provides—​a different contextual setting for the ‘jump scare’ experience. Once this experience of the aesthetic object reveals to the viewing individual a potential for self not formally embraced or perhaps even formally recognized, the ‘transformative aspects’ of this event are evoked. In fact, it could be argued that two different transformative processes occur that are directly relatable to this experience. The first iteration of this phenomenology of transformative self-​recognition is situated within the intra-​subjective experience of the individual, who is actually viewing this material; while the second iteration becomes situated within the intra-​subjective experiences of those subsequently victimized

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by these violent acts. In each of these examples, the experience of the aesthetic object extends into real time with varying consequences depending upon the specific stance of the individuals involved. However, this process of intra-​subjective experience is not exclusive to these specific individuals; rather, much like the theater experience of the jump scare, a shared collective meaning also emerges for those individuals who are in some way confronted by this material. It has been argued that video presentations of such situations ‘function as cultural screens for multiple enactments, viewings, and interpretations of accepted patterns of themes, and norms (e.g. suicide bombing, martyrdom), while perpetrating the development of shared understandings’ (Chen, 2012 quoted in Aggarwal, 2016, p. 108). From this perspective, these shared ‘recognitions’ flash across these ‘cultural screens’ evoking a plethora of intra-​subjective experiences for those who self-​recognize as either potential perpetrator or potential victim. The construct of self-​recognition introduced by Hanich (2012) within the context of cinematic shock has important implications for the phenomenology of digital radicalization. If the experience of viewing extremist content on the Internet, in turn evokes an intra-​ subjective experience of self-​recognition, then we must conclude that the construct of self-​radicalization offers very little heuristic value.18 Such a conclusion is based on the simple fact that the phenomenology of radicalization is always predicated upon a confrontation with an aesthetic object, be it digital or otherwise, which serves as the apparatus for the terrorism machine. Once so confronted, the possibility for self-​recognition occurs within the mediation of the emerging intra-​ subject experience of the viewer. The self that we recognition will likely become the self that we are.

Conclusion This discussion began with a brief description of the phenomenology, which occurs when viewing the images of war from a specific political or religious point of view. Sontag’s (2003) identification of the ‘who is killing whom’ dynamic of this process, has a similar resonance with Hanich’s (2012) description of self-​recognition. In both of these iterations of this phenomenology, the viewer situates their confrontation with the aesthetic object, and configures a meaning for this experience from the intra-​subjective recognition it provides. As a result, the process of radicalization emerges as an artifact of this intra-​subjective experience, which is only marginally related to the specifics of the aesthetic object. To attempt, to argue otherwise, would by necessity

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require that the totality of this transformative process be situated within the confines of the aesthetic object, which is both philosophically and psychologically untenable. In fact, Hanich’s phenomenological understanding of cinematic shock and the experience of self-​recognition, shares some theoretical similarities with the object oriented ontology of Graham Harman (2016; 2018a, 2018b) and the actor-​network theory of Bruno Latour (2018, 2013). The insistence by Hanich (2012) that the experience of self-​recognition is an intra-​subjective event situated in the individual viewer and not the aesthetic object of the film, has some resonance with Harman’s discussion of the real object and the sensual object and Latour’s notion of network and object translation. It will be recalled that for Harman (2018a), our only access to the real object is through our specific perception of it—​the sensual object—​ which is never reducible to the object itself and never exhausted by the subjective renderings of it (Latour, 2007; Harman, 2018b). With the example of the phenomenology of radicalization and the aesthetic objects of the digital world, the sensual object, aesthetic object, configured by extremist content or extremist imagery, is experienced and becomes what is ‘causally’ related to the process of radicalization that follows. However, this causality is never direct or reducible and can only be recognized indirectly. The process, which Hanich (2012) describes as an intra-​subjective experience, for Harman (2018b) would be viewed as an example of vicarious causality. If the negation of innocence is structured by zones of indifference created by the state of exception, then the emergence of the phenomenology of self-​recognition is the end result that this continually unfolding process of vicarious causality reveals. As such, the negation of innocence is an example of self-​recognition, which overwhelms the individual by the unexpected suddenness of its revealing. Regardless of the specifics from which this intra-​subjective process is realized, the viewing self is transformed leaving us to ask, ‘Who is it that we see?’ Notes 1

Sontag’s discussion is in relation to Virginia Wolfe’s text Three Guineas, which explores the roots of war. In that text, Wolfe concludes that the shock value of such images, ‘cannot fail to unite people of good will’ (Sontag, 2003, p. 6). However, what Wolfe fails to recognize, is how these very same images may indeed help to construct a type of consensus, but not of the kind she envisions or anticipates. This is not to imply that Wolfe’s experience of the images she discusses in Three Guineas is somehow illegitimate; rather, it simply reflects a specific phenomenological process that more than likely does not capture how everyone would construct the meaning of these images.

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3

4

5

6

7

8

9

Sontag does not appear to imply that it is impossible to view the deaths of these children as anonymous victims. However, the political context from which these images emerge and from which they are constructed, makes such a conclusion far less likely. Verdery (1999) observes similarly that ‘A body’s symbolic effectiveness does not depend on its standing for one particular thing, however, for among the most important properties of bodies, especially dead ones, is their ambiguity, multivocality, or polysemy’ (p. 28). The relationality between the state of exception, negation of innocence, and digital existence becomes clearly witnessed through the ways in which the digital age expands the ‘potentiality’ of each of these constructs; this digital material helps to powerfully construct those configured as ‘guilty’ along with various zones of indifference where such targets may be located. Within the context of digital reality, the ‘guilty’ may be located anywhere and everywhere, which in turn evokes a potential sense of vulnerability for those identified by this process. As the IS ‘snuff films’ clearly show, a state of exception is evoked, which in turn negates any possibility of innocence for its victims. It will perhaps be recalled that during the George Zimmerman murder trial of Trayvon Martin, autopsy photos of Martin’s body were provided to the jury by the prosecution in an attempt to humanize the victim. During this moment in the trial, defense counsel intuited that these photos were having a negative influence on his case and responded that it was important for the jurors to remember that the body on the autopsy table was not the individual his client faced on the night Martin was killed (Polizzi, 2013). DAESH, the Arabic term for the Islamic State in Iraq and Syria, can also be defined as ‘to trample or crush’ or ‘bigot’ depending upon how the term is configured in Arabic (Garrity, 2015). It is important to note that the current use of cinematography within the context of Salifist Jihadi terrorism is not new and was first employed by the Afghan mujahidin to document their fight against Soviet forces, which invaded that country in the early 1980s. Stenerson (2017) observes, however, that the videos produced by IS, really do not reflect a new trend in Jihadi cinematography, only that these more polished productions reflect the availability of ready-​to-​use technology that can be easily obtained and which, was simply not available to other some of those jihadi groups which came before them. These created subject positions, which emerge from this clash between living being and apparatus, can be viewed as fabricated versions of the self that may then be constructed in a variety of ways. From the point of view of the state, driven by counterterrorism concerns, these fabricated selves become legitimated targets of government surveillance and suspicion. Once so constructed, the choreographed images displayed in these videos, particularly those of the terrorist, now can be used as a type of blueprint to legitimate a broader employment of surveilling strategies. It will be recalled that one of the symbolic functions of Alcatraz was to represent how the most serious criminal perpetrators would be treated after their arrest (Ward & Werlich, 2003). ‘The symbolic intent of Alcatraz—​a super prison to hold the most publicly notorious gangsters of the day—​evoked the state of exception, which was now exclusively focused on the premise of punishment within this emerging utility of rationalized retribution’ (Polizzi, 2017, p. 40). However, it is also necessary to observe that though Alcatraz did reflect an example of exception as this related to the day-​to-​day practices employed by a correctional administration

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10

11

12

13

in the United States during the opening of that facility, it did not actually violate existing law. Though much of the legislation produced to defend the legal justification of these extralegal strategies of confinement falls well outside the scope of normatively accepted constitutional protections against such obvious abuses, supporters of these activities have ironically enough attempted to employ the US courts to validate these practices. To some degree, this strategy has been effective, particularly in the lower courts. The US Supreme Court, however, has proved to be less willing to abdicate completely its legal authority on this matter, but the Guantanamo Bay facility remains open for business. A variety of court challenges have been pursued, which have ultimately made their way to the US Supreme Court. The central strategy of this legal process has been to contextualize the issue of Guantanamo Bay as a jurisdictional problem, which if upheld, would legally block any attempts to have these cases heard in US courts, and by so doing, prevent any detainee from evoking due process rights under the US Constitution. Though the Supreme Court has for the most part upheld the jurisdictional authority of US courts to hear these cases, the more general question concerning the permissibility of such a facility remains unanswered (Polizzi & Arrigo, 2018, pp. 615–639). Since its opening in 2002 the Guantanamo Bay facility has detained nearly 780 individuals. Of that group, two have been convicted and are awaiting sentencing and seven have been charged and are awaiting trial. Included in the group currently involved in pre-​trail motions, is the 9/​11 architect Khalid Sheikh Mohammad. Khalid Sheikh Mohammad (KSM) was given a trial date of January 11, 2021 in military court; however, that date was postpended due to the COVID-​19 pandemic and has not been rescheduled. if found guilty KSM could be given the death penalty. However, others have not been that ‘lucky’. Moath Hamza Ahmed Al-​Alwi, a detainee arrested in 2001, has yet to be charged with any offense, and yet remains in custody due to his potential dangerousness if released. On August 7, 2018, the United States Court of Appeals for the District of Columbia denied Al-​Alwi’s habeas corpus petition, stating that his detention at Guantanamo Bay was constitutional; subsequently this case was referred to the US Supreme Court, but the Court refused to hear the case, thereby allowing the appellate court ruling to stand. There are currently 40 detainees being held at the Guantanamo Bay facility with 21 from that group being held in ‘indefinite Law-​of-​War Detention and are not currently viewed as being eligible for transfer’. Retrieved 03/​13/​2021 from www.nytimes.com/​interactive/​projects/​guantanamo/​detainees/​current. The use of the ‘law’ in this context is related to the various ways in which ideological structures, be they formal or informal, construct those individuals or groups, who are targeted for possible physical elimination. The ‘legal prohibition’, if it be appropriate to language such a process in this way, becomes recognized within a specific phenomenology of the they-​self, which determines what will be validated and what will not. The absence of any legitimate legal authority, which is suspended by the imposition of this new version of the ‘law’, allows for this new ‘legal authority’ to be unleashed. As will be recalled, Dylann Roof entered the Emanuel African Methodist Episcopal Church in Charlestown, SC, and murdered members of that congregation in the hope of starting a war between the races. Richard Bowers entered the Tree of Life Synagogue in Pittsburgh, PA to murder Jews who he believed were killing his people. These specific terrorist episodes were repeated by a variety of other

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14

15

16

17

18

individuals who were equally intent on killing individuals from a religious group they deemed threatening or dangerous. Strategies of surveillance have taken on their greatest significance and reach in the digital age. Whereas historically, states could identity a specific individual or group as a potential threat, therefore making them ‘legitimate’ targets for ongoing surveillance, the digital age has fundamentally changed this dynamic. Though there is no arguing that these new strategies are far more intrusive in their reach then at any other time in our history, the focus on surveilling the internet, however, is simply one symptom of a far more in-​depth concern. Digital experience, digital existence, represents an ‘expansion’ of human consciousness and relationality that likely requires a more radical reexamination of the meaning of being in the digital age. The traditional notions of disorder and order of which strategies of surveillance are a part, though cause for legitimate concern, are in the end incapable of addressing this more fundamental question for human existence. It is essential that we recognize that the negation of innocence emerges as an apparatus of the aesthetics of violence, and as such, becomes a mechanism by which the construction of the subject(s) is predicated upon the fabrication of ‘appropriate victims’. This appropriation of ‘victimhood’ is the artifact of a consistently shifting process of fabrication, which emerges from the in-​between of perpetrator and victim. When viewed in this way, the negation of innocence cannot be constructed from the exclusive perspective of a specific group or locality, as if only they are capable of this experience of negation; to do so would require that only certain individuals or groups should be allowed the security of place and not others. It also threatens any legitimate claim concerning the loss of innocent lives, given that other localities are similarly inhabited by similar innocents, yet are seemingly denied that same designation. This observation is partly influenced by Latour’s (2019) observation concerning the one-​sided view of the process of globalization where he states, ‘The term is used to mean a single vision, entirely provincial, proposed by a few individuals, representing a very small number of interests, limited to a few measuring instruments, to a few standards and protocols, has been imposed on everyone and spread everywhere’ (p. 13). Within this context, what is ‘imposed on everyone and spread everywhere’, is this experience of negation, which is now also possible in those areas or localities that had been formerly free from this type of violence. Pascarella (2019) observes that too often, the process and definition of radicalization fails to recognize those social conditions or governmental actions that help to contribute to this psychological result. ‘Further, this approach fails to position individuals within the social and political circumstances in which they have come of age as citizens of Western societies’ (Pascarella, 2019, p. 188). Griffin (2012/​2017) describes his construct of heroic doubling as an integrative process of psychological transformation that allows the marginalized individual to embrace another manifestation of self that would be traditionally identified within Jungian theory as a manifestation of the Shadow. However, Griffin correctly observes that this shadow manifestation does not simply reflect the diabolical but includes as Jung himself maintained, a process of integration of shadow material that helps to facilitate a type of psychic healing. It is also important to observe that if the main ‘causal factor’ in this process of radicalization is the event of interaction with this digital material, it would seem to follow that a greater number of violent acts would be witnessed given the large

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amount of traffic, which visits these sites. However, this does not seem to be the case.

References Agamben, G. (2009). What is an Apparatus? And other Essays. D. Kishik & S. Pedatella (Trans.). Stanford, CA: Stanford University Press. Agamben, G. (2005). State of Exception. Chicago, IL: The University of Chicago Press. Aggarwal, N.K. (2016). The Taliban’s Virtual Emirate: The Culture and Psychology of an Online Militant Community. New York, NY: Columbia University Press. Chen, H. (2012). Exploring a Data Mining the Dark Side of the Web. Heidelberg: Springer-​Verlag GmbH. Esposito, R. (2019). Politics and Negation: For an Affirmative Philosophy. Cambridge, UK: Polity Press. Flusser, V. (2000). Towards a Philosophy of Photography. London, UK: Reaktion Books. Garitty, P. (2015). Paris attacks: What does D.A.E.S.H. mean and why does ISIS hate it? NBC News, 15 November, [online] Available at: https://​www.nbcnews.com/​storyline/​isis-​terror/​ paris-​attacks-​what-​does-​daesh-​mean-​why-​does-​isis-​hate-​n463551 German, K. (2019). ‘Video verité’ in the age of ISIS. In M. Krona & R. Pennington (eds.) The Media World of ISIS. Bloomington IN: Indiana University Press (pp. 125–​44). Griffin, R. (2012). Terrorist’s Creed: Fanatical Violence and the Human Need for Meaning. London, UK: Palgrave Macmillan. Griffin, R. (2017). The role of heroic doubling in ideologically motivated state and terrorist violence. International Review of Psychiatry 29: 355–​61. Flusser, V. (2000). Towards a Philosophy of Photography. London, UK: Reaktion Books. Hanich, J. (2012). Cinematic shocks: Recognition, aesthetic experience, and phenomenology. Amerikastudien/​American Studies 57: 581–​602. Harman, G. (2016). Immaterialism. London, UK: Polity. Harman, G. (2018a). Object-​Oriented Ontology: A New Theory of Everything. London, UK: Pelican Books. Harman, G. (2018b). Speculative Realism: An Introduction. London: Polity. Latour, B. (2007). Can we get our materialism back, please? Isis 98: 138–​42. Latour, B. (2013). An Inquiry into Modes of Existence: An Anthology of the Moderns. Cambridge, MA: Harvard University Press.

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Latour, B. (2018). Down to Earth: Politics in the New Climate Regime. Catherine Porter (Trans.). London, UK: Polity. Moghaddam, F. (2018). Mutual Radicalization: How Groups and Nations Drive Each Other to Extremes. Washington, DC: American Psychological Association. Morris, T. (2017). Dark Ideas: How Neo-​Nazi and Violent Jihadi Ideologues Shaped Modern Terrorism. Lanham, MD: Lexington Books. Murray, M.J. (2011). Extraordinary rendition and U.S. counterterrorism policy. Journal of Strategic Security 4: 15–​28. Pascarella, M. (2019). Western millennials explain why they joined the Islamic State. In M. Krona & R. Pennington (eds.), The Media World of ISIS. Bloomington, IN: Indiana University Press (pp. 187–​205). Polizzi, D. (2013). Social presence, visibility, and the eye of the beholder: A phenomenology of social embodiment. In G. Yancy & J. Jones (eds.), Pursuing Trayvon Martin: Historical Contexts and Contemporary Manifestations of Racial Dynamics. Lanham, MD: Lexington Books (pp. 173–​81). Polizzi, D. (2017). Solitary Confinement: Lived Experiences and Ethical Implications. Bristol, UK: Policy Press. Polizzi, D. (2019). The aesthetics of violence. In R. Lippens & E. Murray (eds.), Representing the Experience of War and Atrocity: Interdisciplinary Explorations in Visual Criminology. London, UK & New York, NY: Palgrave Macmillan (pp. 45–​71). Polizzi, D. & Arrigo, B. (2018). Cruel but not unusual: Solitary confinement, the 8th Amendment and Agamben’s State of Exception. New Criminal Law Review 21: 615–​39. Polizzi, D., Draper, M. & Andersen, M. (2014). Fabricated selves and the rehabilitative machine: Toward a phenomenology of the social; construction of the offender. In B. Arrigo & H. Bersot (eds.), The Routledge Handbook of International Crime and Justice Studies. New York, NY: Routledge (pp. 233–​55). Richey, P.G. & Edwards, M. (2019). It’s more than orange: ISIS appropriation of orange prison jumpsuits as rhetorical resistance. In M. Krona & R. Pennington (eds.), The Media World of ISIS. Bloomington, IN: Indiana University Press (pp. 167–​83). Sobchack, V. (1992). The Address of the Eye: A Phenomenology of Film Experience. Princeton, NJ: Princeton University Press. Sontag, S. (2003). Regarding the Pain of Others. New York, NY: Farrar, Straus and Giroux.

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Stenersen, A. (2017). A history of jihadi cinematography. In T. Hegghammer (ed.), Jihadi Culture: The Art and Social Practices of Militant Islamists. Cambridge, UK: Cambridge University Press (pp. 108–​27). Verdery, K. (1999). The Political Lives of Dead Bodies: Reburial and Postsocialist Change. New York, NY: Columbia University Press. Ward, D.A. & Werlich, T.G. (2003). Alcatraz and Marion: Evaluating super-​maximum custody. Punishment & Society 5: 53–​75. Zraick, K. & Stevens, M. (2018). Kroger Shooting suspect tried to enter black church before killing 2 in Kentucky, police say. The New York Times. Available at www.nytimes.com/2018/10/25/us/ louisville-kroger-shooting.html

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PART II

Institutions, Organizations and the Surveillance Industrial Complex

5

Visions of the Pre-​Criminal Student: Reimagining School Digital Surveillance Andrew Hope

Introduction The concept of pre-​crime, which has its origins in a Philip K. Dick short story, extends the temporal limits of criminal law and its associated practices, being ‘directed at monitoring, detaining, disrupting and, in some cases, charging and prosecuting groups and individuals considered to present a future threat’ (McCulloch & Pickering, 2010, p. 32). This highlights that pre-​crime is concerned not only with surveillance but also with intercessions that involve prosecutions for crimes that have not occurred. Problems exist with the contemporary notion of pre-​crime. There is an inherent contradiction in suggesting that something is a crime, while a criminal activity has not occurred. Indeed, ‘future crime is paradoxical. The very act of possessing this data renders it spurious’ (Dick, 2013, p. 257). While legal systems often allow for prosecution of serious crimes where conspiracy or an attempt can be proven, pre-​crime predictions seek to move far beyond such court-​based procedures. Importantly, there also exist clear definitional differences as to how the concept is applied. From a techno-​realist perspective pre-​crime is an evolution of a calculative rationality that has much in common with risk-​based approaches to policing. Here ‘realist’ indicates a view that privileges the existence of a scientific, objective reality, while

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being dismissive of notions of subjectivity, social constructionism and interpretation. This approach uses the latest scientific and digital technologies to find associations that act as indicators of certain criminal intent. It finds embodiment in police departments’ use of predictive analytics for criminal justice purposes and national security agencies counter-​terrorist activities. This viewpoint is strongly evident in the media, public policy and commercial narratives, where pre-​crime is seen as a technological solution to an unknowable but calamitous threat. From a cultural perspective, pre-​crimes are accented to uncertainty rather than risk and involve moving from calculations of probability towards imagined possibilities. Thus ‘[p]‌re-​crime provides a cast, script, stage and venue for performing harms and crimes that have not happened and material for “proving” catastrophic prophecy ranging from the intractable delinquency of marginalized young people to terrorism’ (McCulloch & Wilson, 2016, p. 43). Indeed, McCulloch and Pickering (2010, pp. 2–​3) maintain that pre-​crimes ‘become tangible through countermeasures which become the fire that points to the smoke of pre-​crimes’, suggesting that pre-​emptive action based on imagination and performance may serve to construct the future that it seeks to act against. Thus, rather than offering a technological solution that addresses incalculable catastrophic futures, pre-​crime represents coercive state interventions that threaten individual liberties, persecute minorities and engender self-​fulfilling prophecies. Both of these perspectives will be used to inform discussion, as while they represent differing worldviews they will facilitate a nuanced analysis as to how the concept of pre-​crime is utilized in late modernity. Additionally, in making sense of the commercial influences that promote the consumption and use of pre-​crime surveillance technologies, this work will also draw upon a political economy viewpoint, considering how pre-​crime practices might be driven by the profit motive of private companies, increasing commercialization and burgeoning commodification. In recent years, pre-​crime technology use has increased significantly. There has been a growth not only in terms of the number of agencies utilizing such tools and the varied locations in which such procedures are applied, but also the activities that come under scrutiny. Worryingly as McCulloch and Wilson (2016, p. 83) argue: technologies and science of pre crime are floating downstream from the threat of terrorism and into the local policing spaces of crime and low-​level disorder. Borrowing the tools of data mining and predictive analytics from the

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commercial sector, advocates suggest that there is little difference between a shampoo purchase and the decision to commit armed robbery. Thus, what might constitute a pre-​crime is an expanding category, while from a techno-​realist perspective there is a need to gather ever more information. Significantly, such data is not merely focused on crime related activities, but also everyday interactions. After all, even the most mundane of information might provide a key part of the puzzle, revealing a possible ‘catastrophic future’. Hence, it should come as little surprise that such broad focus also includes gathering data on disruptive schoolchildren and introducing pre-​emptive interventions in schools to combat ‘delinquent tendencies’. Consequently, this chapter examines current and potential relationships between pre-​crime, students and schools. Before exploring the nature of pre-​crime and the school surveillance technologies through which such practices might operate, it is important to consider briefly the connections between crime and schools. After all schools are institutions for educating children and, while social control elements might be present, the direct association with crime should not be accepted without question. Firstly, there is a concern that certain school experiences, such as suspension, might cause behavior labeled as antisocial or violent, resulting in incarceration later in life. Concerns about such associations have resulted in the metaphor of the ‘school-​to-​prison pipeline’, which ‘is best understood as a set of policies and practices in schools that make it more likely that students face criminal involvement with the juvenile courts than attain a quality education’ (Mallet, 2016, p. 15). Secondly, crimes are committed in schools. While criminal activities in schools include theft, vandalism, arson, sexual abuse and illegal drug use, the most notable in terms of impact on the public psyche are incidents of extreme violence, such as school shootings and terrorist activities. Nevertheless, despite highly publicized tragedies schools are statistically safer for children than streets, cars or homes (Monahan & Torres, 2010, p. 2). Thirdly, following the widespread introduction of techno-​security devices into schools, resulting in what Casella (2006) labels as the ‘fortification of schools’, lucrative activities that might be broadly labeled as private policing have crept onto campuses. In examining the links between pre-​crime and schools this chapter will initially focus on the notion of pre-​crime, before exploring the digital surveillance technologies used in schools and considering whether they are, or might be, involved in pre-​crime processes.

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Having ascertained that despite growing technological capacities contemporary school surveillance technologies are not currently involved in such analytics the next section draws upon the notion of neoliberal governmentalities to suggest that there exist commercial pressures for student data to be used in this way. Finally, the notion of the pre-​criminal student is considered.

Pre-​crime The term pre-​crime was first used by author Philip K. Dick in his 1956 science fiction short story The Minority Report. The main premise of this story is that within a future society three ‘precogs’, who have the ability to see the future, foresee all crime before its occurrence. Their vision-​inspired utterances are analyzed and interpreted by a punch card computer, with the data then used by a criminal justice agency called Pre-​crime to remove those who will commit these crimes in the future. The title of this short story derives from the possible outcome where one of the three ‘precogs’ predictions conflicts with the other two, creating an alternative version of events and a minority report. In the conclusion of the narrative, the protagonist realizes that all three reports were ‘minority’ as they each described different situations, suggesting that the technology is inherently flawed. Filmmaker Steven Spielberg loosely adapted this short story for his 2002 blockbuster movie Minority Report. Despite the enduring appeal of the original short story, it is the film that has become the main cultural reference point for the notion of pre-​crime, particularly in media coverage of predictive police data analytics and security surveillance assemblages. A number of key points can be drawn from the short story and its cinematic interpretation that will help inform subsequent analysis. Firstly, notwithstanding the central importance of the three ‘precogs’, the system is presented as a surveillance technology, involving wires, disks, files and duplicate cards. A focus on digital surveillance technologies, often utilizing big data sets, is key in much of the discussion about pre-​crime approaches in contemporary society. Thus, Ferguson (2017) notes that the Chicago Police Department is in the vanguard of using digital data analytics to combat crime through predictive policing, while Mor (2014) reports that crime prevention apps, such as RTM Dx, which maps geolocation and crime data, are in use by police departments in Colorado, Texas, Missouri, New Jersey, Arizona and Illinois. This current tendency to use predictive analytics in policing emerged from epidemiological and environmental studies (Ferguson, 2017) suggesting that such techniques already operate in

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broader society. Indeed, discussions of pre-​crime data analytics can be linked to the notion that in many economically developed countries ‘surveillance societies’ have emerged (Lyon, 1994), with some arguing that ‘surveillance capitalism’ is now a dominant market form (Zuboff, 2019). Regardless of the validity of such arguments, it is inescapable that modern life is highly monitored, from marketing to health and entertainment, the scope is ever widening, as increasing amounts of data are harvested and warehoused. This is also true of schooling, where driven by a deregulation of state markets and the availability of a vast array of new technologies, the scope and reach of school surveillance has increased exponentially. Consequently, commentators have suggested the emergence of a ‘surveillance curriculum’ (Monahan, 2006; Hope, 2010) the ‘surveillance school’ (Taylor, 2012) ‘surveillance 2.0’ in educational institutions (Kuehn, 2008, Hope, 2016) and the ‘database school’ (Hope, 2013). In this context, it is vitally important to consider whether school surveillance technologies are being used or have the potential to be used as instruments of pre-​crime. This is a question that will be further examined when the focus shifts to an analysis of the surveillance technologies currently operating in schools. Secondly, Gad and Hansen (2013) note that with regard to the film the Pre-​crime Department’s name derives not only from the focus on future crimes but also from the phrase ‘prevent crime’. While this process is clearly concerned with ‘revealing’ crimes and intervening, the question arises as to the particular nature of the crimes. In the short story envisioned pre-​crimes include ‘petty crimes’ such as theft, income tax evasion, assault and extortion, although in the film they are limited to murder. In academic research, a critical interpretation of pre-​crime has become strongly associated with radicalization and terrorism. Oleson (2016, p. 302) notes ‘[t]‌he logic of pre-​crime is most evident in the context of terrorism—​where the precautionary principle is employed to legitimise coercive state interventions’. Given practices such as risk profiling for ‘terrorist indicators’, prolonged detention without charge and extraordinary rendition, it is hardly surprising that the notion of pre-​crime has become strongly associated with de-​radicalization and counterterrorism strategies. Nevertheless, these practices have spilled out into other spaces, with Zedner (2007) positing an emerging ‘pre-​crime society’, and McCulloch and Wilson (2016, p. 77) warning that ‘with a surfeit of threats and uncertainties ever imminent, the market for pre-​crime science and technology is all but guaranteed to perpetually expand’. Furthermore, it is also worth considering that mission creep (Wall, 2010) might occur, where citizens caught in the digital surveillance network are arrested for lesser

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crimes. Consequently, although the notion of pre-​crime has a strong connection with terrorism, it is also associated with other violent crimes, including murder, as well as a range of lesser crimes. With regard to schooling it could be asked what might ‘pre-​crime offences’ entail. As will be subsequently discussed, interventionist policies already exist in schools to address radicalization of students and potential violent extremism, while private companies are employed to monitor student social media for indicators of suicidal or violent tendencies. Thirdly, despite some serious doubts about the effectiveness of pre-​crime technologies, the approach is often presented, from a techno-​realist viewpoint, as a highly effective crime reduction strategy, leading many to accept the predictions with ‘absolute, overwhelming conviction’ (Dick, 2013, p. 227). Data manufactured through surveillance technologies are often proffered as objective measures, interpreted in a scientific manner. Yet, in reality, there are strong social components, in how such technologies are constructed and utilized. Despite this, there is often a powerful narrative of the reliability of the data and the related processes, which is promoted by state organizations and private companies. Indeed the coercive nature of police and state interventions surrounding the use of these predictive data analytics suggests that such strategies are as much about social control as crime prevention per se. In the context of schooling, where issues of social control are far more prevalent than those relating to crime, it is possible that any tendency towards the introduction of pre-​crime technologies and procedures might mask attempts to increase social control. After all, schools have a long history of operating as institutions of social control, using ‘unremitting surveillance’ (Hall, 2003, p. 50). Finally, while Minority Report contains themes concerning invasive surveillance and free will, it can also be interpreted as a tale of political economy, involving the struggle for resources and the retention of power. Although it is recognized that pre-​crime practices may encompass ‘substantial and continuing coercive police or state action without a legally required link to criminal charge, prosecution, or conviction’ (McCulloch & Pickering, 2010, p. 32), less is written about the role of commercial organizations in this process. Technologies with pre-​crime capabilities used in schools are likely to be provided by the private sector. Surveillance in schools is a billion dollar industry, offering vast markets for private companies intent on selling the latest protection software, surveillance technologies and social sorting protocols. As Casella (2010, p. 74) notes ‘the installation of security equipment in schools is foremost a corporate transaction led … by business people’. In this context, it might be expected that commercial pressures will

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drive any expansion of pre-​crime technologies into schools. This is not to dismiss the importance of promises of greater security, more efficient performance and effortless compliance, but as will be subsequently argued the exploitation of neoliberal governmentalities by private companies needs to be considered.

Techno-​realist transactions: digital surveillance technologies, schools and pre-​crime Within the last two decades, there has been a revolution in the provision and use of surveillance devices in schools. Thus technologies such as closed-​circuit television (CCTV) cameras, automated fingerprint identification systems (AFIS), facial recognition software, iris/​vein scanners, metal detectors, radio frequency identification (RFID) microchips, body cameras, drones, pedometers, safety management services, classroom management software and networked databases have all been introduced into educational institutions. These devices are introduced for a variety of reasons, including combating crime, promoting well-​being and safety, improving educational processes and facilitating social control (Hope, 2018a). They are also installed in schools because of the successful exploitation of newly emerging markets by private companies (Casella, 2006, 2010). While there is a plethora of monitoring devices now operating within schools, few focus upon potential criminal activities. In focusing upon data analytics, the following discussion will eschew technologies such as metal detectors or drug tests, both of which are not associated with data sets, and which are intended to detect rather than predict criminal violations in schools. Similarly, policy interventions in schools to combat delinquency, which are not associated with predictive analytics and datasets, will not be considered. Consequently, analysis will focus on dataveillance, which is ‘the systematic use of personal data systems in the investigation or monitoring of the actions or communications of one or more persons’ (Clarke, 1988, p. 499). In particular, discussion will center on safety management services, classroom management software, corporate/​government databases, the Internet of Things (IoT) and surveillance cameras. In describing the school-​based technologies that fall within each of these categories it will be considered whether these devices currently engage in pre-​crime analytics and, if not, the potential for this to occur. Before discussing such devices, it is worth noting that ‘technological systems themselves are neither the cause nor the sum of what surveillance is today. We cannot simply read surveillance consequences

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off the capacities of each new system’ (Ball et al, 2006, pp. 9–​10). In other words, merely because a surveillance technology is introduced for a declared use does not mean that it will end up being utilized in this manner. Thus, there is the possibility of surveillance slack, which is the difference between the potential full utility of a monitoring technology and its actual lesser use (Marx 2002, p. 23). Yet, such thoughts also allow for the prospect of surveillance creep, wherein new observational technologies might be used in ways not initially intended when introduced (Hope, 2018b). Partly as a reaction to school shootings in the US the use of third-​ party safety management services in schools has grown substantially. The services offered differ somewhat although they generally involve monitoring of school learning systems, work files, email accounts and, upon occasion, social media. For example Gaggle, which claims to monitor 4.5 million students across 1,400 school districts, surveils student use of Google G Suite and Microsoft’s Office 365, but can also process notifications from Facebook, Twitter and Instagram where the accounts are linked to a school email address (Haskins, 2019). Bark, another safety management company, claims to work with at least 1,400 school districts, monitoring correspondence from school email addresses, Gmail chat, items stored in Google Drive folders and posts in Google classroom (Beckett, 2019). Securely, the self-​labeled ‘Student Safety Company’, whose products are reportedly used by 10 million students, offers similar services including internet filtering, monitoring of Gmail as well as school mobile device management. Some companies such as GoGuardian specialize in monitoring student email searches, while others including Snaptrends, Digital Fly and Ascham surveil postings on social media sites such as Facebook, Twitter, Instagram and Youtube (Vaas, 2015; Abramsky, 2016). Despite a diversity of digital focus, these companies have two things in common. Firstly, they have the same declared aim, scrutinizing student online work and behavior for signs of violence, suicidal tendencies, drug use, mental health crisis, profanity and sexual content. Indeed, such companies strongly promote the value of their services based on unverifiable statistics about lives saved through suicide interventions and the number of violent incidents averted. Secondly, such organizations use a combination of Artificial Intelligence (AI) powered filtering systems and human moderators who intervene when a risk is identified. In this regard, there is a trace of pre-​crime analytics about how these services are operated, with extensive harvesting of student digital data that is analyzed through algorithmic processes. While interventions might result from a reported event

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or an imminent action, there is also a predictive capability in such systems. Thus, Gaggle provides a safety management dashboard for school administrators, which includes a ‘Top Concerns’ graph, displaying a ranked table of students who have violated Gaggle’s rules. Such dataveillance products are not overly dissimilar from predicative policing ones. Yet there are differences. The production of data means little in itself if it does not result in a labeling or intervention process. Additionally, while some of the monitored activities could result in criminal prosecutions, it is unlikely that the vast majority will do so. Rather assistance or school disciplinary actions are more likely. Of course, there are exceptions. For example, where ‘student-​produced pornography’ is identified Gaggle automatically sends the file to the National Center for Missing and Exploited Children. There is also a greater association with school surveillance technologies and criminal procedures in relation to terrorism. In the UK there is a legal obligation that schools prevent students from being drawn into terrorism under the Counter-​terrorism and Security Act (UK Government, 2015). Impero, a UK education software company, has adapted filtering software to flag keywords associated with radicalization, such as ‘jihobbyist’, ‘jihadi bride’ and YODO (you only die once) (Taylor, 2015). Given the coercive nature of anti-​radicalization interventions in UK schools, it could be argued that software that monitors and flags the use of such language is engaging in a very early form of pre-​crime intervention, where it is assumed that failure to re-​educate ‘at-​r isk’ students will result in a violent crime. Before considering classroom management software, it is worth noting that distinctions between these services and safety management ones are not always clear with some educational companies such as Impero also offering security products. Nevertheless, these technologies should be analyzed separately as they aim to achieve somewhat different goals. The use of classroom management software is widespread in schools, with one report claiming that 72 per cent of English and Welsh secondary schools use such technology (Big Brother Watch, 2016, p. 3). These programs include functions such as the monitoring of student screens, internet activity, filtering software and keyboard strokes, with alerts created for certain flagged words. Some of these functions are responses to legal requirements. For example, in the US e-​Rate funded schools must block and filter website content in order to comply with the Children’s Internet Protection Act (CIPA) (Federal Communications Commission, 2015). Yet, such controls are largely concerned with guarding the well-​being of minors and ensuring that

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discipline is maintained in schools rather the predicting or curtailing criminal activity. While classroom monitoring software is primarily a learning support tool, the data harvested and the subsequent supervisory reach has grown notably, stretching far beyond the school day and the classroom. Thus, the Queensland State Government supplied laptops to students with software installed that monitored their use, even outside of school with screenshots emerging of students’ Skype conversations and movie snapshots at home (Chillcott & Tin, 2012). Indeed Big Brother Watch (2016, p. 8) reports that as a consequence of Bring Your Own Device schemes in UK schools ‘over 1400 pupils’ personal devices have been installed with Classroom Management Software’, co-​opting them into the school surveillance assemblage. While there is potential for such software to capture students’ engaging in illegal activities much of this software is largely reactive, responding to an event that has occurred rather than predictive. Furthermore, these activities are more likely to relate to school disciplinary offenses rather than criminal ones. Yet, if such data is harvested and warehoused, it could subsequently be used as part of big data analytics. Such programs might amalgamate data to create algorithms, which could flag certain online or digitally recorded behavior as being associated with crime. Yet, such worrying possibilities have not yet been realized. There exists a host of external state bodies who are required to gather information from schools in order to meet and enforce statutory requirements, constructing government databases in the process. For example, in the UK, schools are required to provide information for the National Pupil Database (a school census) and a range of other surveys tied to social care or youth justice. The US Youth Risk Behavior Surveillance System (YRBSS) surveils a wide range of health-​risk behaviors, including data on violence, bullying, sexual activity, weapon possession and suicide. Such data are collected every two years within schools and used to produce a database focusing on the risky behavior of students in grades 9–​12. Currently such government databases predominantly inform policy, rather than predict personal behavior or trigger individual interventions. While such databases can be large, far more data is gathered through the online school-​based activities of companies such as Facebook (co-​founder of the Summit Basecamp educational initiative) and Google (providers of G Suite for Education). Such initiatives are primarily concerned with promoting learning and currently have no connection to criminal justice systems. Nevertheless, China’s Social Credit System may hint at a future where connections can be made between schools, commercial activities and disciplinary

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or legal processes (The Economist, 2016). Ultimately, while corporate/​ government databases generated through schools could be used in predictive policing and pre-​crime practices they currently are not. The IoT includes a dizzying array of networked technologies such as car navigation systems, health devices, smart domestic appliances and motion-​control gaming. While it was estimated that the IoT will consist of around 30 billion devices by 2020 (Nordrum, 2016), Augur (2015) argues that its integration into education is slower and more nuanced, potentially involving school weather stations and interactive boards. Arguably far more prevalent in schools is what Rich and Miah (2009) term prosthetic surveillance through IoT devices such as pedometers, fitness video games and high-​tech sensors that measure food intake. Indeed as governments increasingly introduce programs, such as ‘Finnish Schools on the Move’, which provide money for the purchase of pedometers to encourage physical exercise (UUTISET News, 2017), it is likely that more of this type of data will be generated in schools. Nevertheless, while the IoT features increasingly in policing, with conversations recorded by smart televisions and smart fridges used as evidence in criminal trials and smartphones utilized as tracking devices, it is unlikely that IoT data harvested in schools will find its way into pre-​crime strategies. Indeed, it is far more likely that data from prosthetic surveillance will be used to instigate health interventions. Surveillance cameras are widespread in many schools. Back in 2012, Big Brother Watch (2012) reported that 90 per cent of the English, Welsh and Scottish secondary schools had closed-​circuit television cameras installed, while webcams and video-​style surveillance elements of classroom management software were also widespread (Hope, 2018a). In addition to pervasive smartphones with integrated cameras, other new visual technologies are creeping into educational establishments including body-​worn cameras (Walker, 2017), aerial drones (Hiatt, 2018) and facial recognition cameras in vending machines (Lee, 2018). While Zuboff (2015, p. 78) suggests that ‘flows from private and public surveillance cameras, including everything from smartphones to satellite, Street View to Google Earth’ could feed into big data sets, the reality in schools is somewhat different. With the exception of students posting material recorded using their smartphone on social media websites, video surveillance data in schools is predominantly held on local networks. Nevertheless, this situation may change with some schools starting to use visual facial data to monitor student emotions and engagement in lessons (Lee, 2018). Despite the potential to use such devices in criminal justice processes, there appears little will to link these devices and use them to construct predictive systems within schools.

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Ultimately, it might appear that pre-​crime predictive analytics have little association with schools. Indeed, with the possible exception of aspects of safety management services there is little evidence to suggest that the masses of online data generated by students will be used to predict future criminal tendencies or activities. This should hardly be surprising as schools are not criminal justice institutions. Nevertheless, worryingly there is potential for such information to be co-​opted into a predictive policing process. Drawing upon Gane’s (2012) discussion of neoliberal governmentalities the next section will consider the commercial pressures that could result in the growth of pre-​crime technologies in schools.

The political economy of possible futures: neoliberal governmentality and pre-​crime surveillance in schools Drawing upon Foucault’s notion of governmentality Gane (2012) explores the interplay of state and market in contemporary surveillance practices. Central to his argument is a typology he develops of surveillance as discipline, as control, as a mechanism for promoting competition and as interactivity (Gane, 2012, p. 611). According to Gane these four types may operate simultaneously. In order to understand how pre-​crime practices might become more common in schools it will be helpful to consider these types. In ‘governmentality through discipline’ Gane (2012) argues the state, and related agencies, monitor people in an overt manner. Here he draws upon Foucault’s discussion of Bentham’s Panopticon prison design, wherein people believing that they could be the object of constant surveillance start to self-​police their behavior. Such a dynamic is crucial to certain predictive policing practices, where the police remind individuals who have been labeled as ‘high risk’ that they are being monitored. Similar processes also occur in schools, yet are concerned with discipline rather than crime. Ultimately, this type of governmentality offers few insights into pre-​crime and future market activities. Drawing upon Deleuze’s discussion of ‘societies of control’, governmentality through control ‘is where state institutions are not the only ones doing the watching’ (Gane, 2012, p. 630). Surveillance technologies are devolved from the state to new market-​fostered organizations who track and tag mobile individuals. In the US, digital surveillance is part of a $3 billion-​a-​year school security industry (Beckett, 2019). Given such possible financial rewards, it seems

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appropriate to consider whether private companies will operate in the public interest. Worryingly, Zuboff (2015) suggests that digital data extraction by commercial companies is a one-​way process that engenders a corporate ‘formal indifference’. She explains that ‘formal indifference’ involves private company ‘incursions into legally and socially undefended territory until resistance is encountered. Its practices appear designed to be undetectable or at least obscure’ (Zuboff, 2015, p. 79). This suggests that the law, or other formal guidelines, are not a barrier to invasive surveillance practices, unless utilized by those seeking to resist. This raises the question of whether commercial organizations can be trusted to refrain from co-​opting data that they harvest from schools into predictive, pre-​crime analytics. Furthermore, it is far from evident how corporations are actually using the data that they harvest. Shade and Singh (2016) draw attention to privacy prevarication, where digital surveillance companies operating in schools use language in their privacy policies that obscure or hedge possible future uses. This means that schools and educational authorities are currently employing private companies to ostensibly safeguard student well-​being, but with little or no notion of how these organizations may use the data that is extracted and analyzed. Tied to the devolution of state markets is governmentality to promote competition, where ‘the market now penetrates all aspects of both state and society’ (Gane, 2012, p. 632). While the state is ‘rolled back’ within the education sector as security activities are devolved to commercial companies, a ‘rolling out’ has also occurred of market principles into public sector schooling. As ‘the market introduces new audits and measures into the state [schooling] that in turn are used to justify its legitimacy and value’ (Gane, 2012, p. 632), the resultant actuarial turn allows penetration of market principles and practices into the educational environment. Competition and profit become key drivers in educational surveillance as an astonishing array of intrusive monitoring devices are introduced into schools. It is curious that invasive technologies such as RFID, AFIS, palm vein/​iris scanning devices and facial recognition software have been introduced into schools merely to speed up registration. It might be suggested that overly encroaching, over-​engineered solutions to minor problems have seemingly become a norm in many schools without due consideration of students’ rights or the long-​term consequences of such heavy handed approaches. In this light, it might be asked how long it will be before school safety management services also offer pre-​crime products. Driven by the desire to increase profits it may only be a matter of time

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until the emerging shoots of pre-​crime technologies evident in safety management software take firmer hold. Using the concept of the synopticon (Mathiesen, 1997), where the many watch the few, Gane (2012) proposes that governmentality through interactivity operates via the viewer society, as the masses watch and are influenced by the behavior of the few, looking to the mass communications market rather than the state for guidance. Thus, Mathiesen (1997, p. 226) suggests that ‘[m]‌edia personalities and commentators … actively filter and shape the news … all of this is performed within the context of a broader hidden agenda of political or economic interests’. Yet, in a viewer society, not only does the source of influence change, but as a consequence of the proliferation of new media, people also become far more surveillance tolerant, with some being ever more desirous of the public gaze. From this viewpoint, governmentality through interactivity can be seen as facilitating the spread of intrusive surveillance technologies. Hence, students entering US and UK schools will become socialized into thinking that invasive surveillance is normal as they unquestioningly accept the monitoring technologies surrounding them, while being seduced by the entertainment value of mass surveillance. While resistance and opposition to school surveillance is possible, for example CCTV cameras were removed from toilets in a UK school after students petitioned senior management (MailOnline, 2008), such invasive technologies have nevertheless become normalized. If, in a viewer society, student digital data was used to construct pre-​ crime technologies it is uncertain what level of concern might be generated. ‘Engaging in data creep, data exhaust and data warehousing commercial organizations are increasingly gathering information from students’ online activities’ (Hope, 2018b, p. 67) begging the question of how resistant people are to this seemingly inevitable encroachment. Furthermore, the viewer society is a highly commodified one, as those using online media pay for these services, sometimes with money, often with their data.

Envisioning the pre-​criminal student It might be asked why focus on the pre-​criminal student, as opposed to the pre-​criminal child or youth. In other words, what is the relevance of schooling in the pre-​crime equation? As discussed earlier in this chapter there are associations between crime and schools. Thus, the occurrence of crimes within schools, a concern with the ‘school-​to-​ prison pipeline’ and the burgeoning school surveillance market all

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indicate the importance of focusing on students in particular. How each of these issues are interpreted will depend on the particular perspective adopted, as techno-​realist, cultural and political economy approaches differ in their underlying assumptions and focus. In exploring these differences, the distinction between the phrases pre-​crime and pre-​ criminal will also be considered. From a techno-​realist viewpoint, it is assumed that pre-​crime technologies and related surveillance tools are scientific, an evolution of risk-​based crime approaches, which facilitate valid measurement and reliable predictive processes. Although issues might arise with regard to accuracy, this is likely to be seen as an issue of calibration rather than an inherently flawed approach. From this perspective, pre-​ crime technologies in schools could facilitate the prediction of future crimes. Such crimes might range from illegal drug use and vandalism to more catastrophic harms, such as school shootings and terrorist activities. An argument may be posited that pre-​crime technologies will work because they stop future crime, safeguarding students and staff, although much like the claims of school safety management services there is unlikely to be rigorous evidence to support these claims about a fabulated future. Given what Suskind (2006) terms the ‘one per cent doctrine’, wherein a one percent chance of a catastrophe occurring is treated as a certainty, as well as the somewhat Draconian measures introduced into schools in some countries with the declared aim of combating terrorism, there appears to be some willingness to make use of such technological measures in educational institutions. If stopping ‘future crimes’ through data analytics and predictive software is prioritized, then there will be a need to harvest the data that will inform such calculations. While much information could be gathered through students’ social media use and broader digital interactions, schools are also immense surveillance hubs, generating vast amounts of data that could feed into such predictive engines. Introducing the term ‘pre-​criminal student’ raises the question of whether techno-​realist predictions are likely to focus on a future incident or if there might be a blurring of boundaries as the identity of the student is privileged. McCulloch and Wilson (2016, p. 8) note that a ‘key pre-​crime trait is a focus on identity as the primary grounds for coercive interventions … suspect identities become proxies for the guilty mind element of pre-​crime offenses’. Lacking actual evidence, analysis of criminal intent might shift towards the ‘delinquent personality’ of students. For those who uncritically believe in the existence of a ‘school-​to-​prison pipeline’, the concept of a pre-​criminal student could reflect a necessary broadening in focus from crime events to ‘criminal personalities’.

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Consequently, the term is significant insofar as it might serve to expose processes of mission creep that could occur in schools, wherein the notion of pre-​crime is applied in a broader manner, moving beyond events to identities. From a cultural perspective, the techno-​realist narratives of pre-​crime and the pre-​criminal student are highly problematic. Simply put, the pre-​criminal student is someone who is identified as undertaking a harmful and illegal activity, which will happen in the future. Clearly, such a statement involves the contradictions at the heart of pre-​crime, a hypothetical judgment treated as a reality. Indeed, as McCulloch and Wilson (2016, p. 11) note ‘precrime countermeasures amount to performances that “preconstruct” hypothetical crimes and “pre-​enact” catastrophic futures’. Thus, the very notion of the pre-​criminal student is a social construct, one created from imagined futures and used in a coercive manner. From this viewpoint, pre-​crime processes are not primarily concerned with prediction but rather with labeling. Negative labels can be seen as problematic insofar as they influence not only how others see an individual but also self-​identity. The label of ‘pre-​criminal student’ is particularly problematic insofar as it can never relate to an action that has occurred, referring only to a simulation. There is little positive that can arise from the labeling of a student as pre-​criminal. It is not just that no actual crimes are averted, but that as part of a self-​ fulfilling prophecy, students who accept the pre-​criminal label may subsequently engage in deviance and crime, where they previously lacked the motivation. In this context, pre-​crime and its associated labels could ultimately create the criminal activity that it claims to stop. Since analyzing pre-​crime from a cultural perspective reveals grave problems with the notion and its practices, it might be asked why the techno-​realist viewpoint remains so powerful. This is not merely because of the seductiveness of the claims about scientifically eradicating future crimes but also because of commercial pressures. Drawing upon the discussion of neoliberal governmentalities and adopting a political economy approach, it can be argued that pre-​crime is a commercial endeavor. The devolution of state markets and the promotion of competition in many education systems have resulted in the emergence of a surveillance industrial complex within this sector. As Casella (2010, p. 75) notes ‘[s]‌chool administrators enter into deals with vendors and take away a product designed to provide safety but geared to making customers want to buy more and better technologies … it is about private enterprise, the opening up of the public school market to businesses’. In this context, the products and services associated with pre-​crime and the pre-​criminal student can be seen simply as

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commodities, goods to be consumed. As private companies seek to sell new security products as ‘life accessories’ and essential ‘professional tools’ there is often cultural capital in having the latest technological devices (Casella, 2010). Consequently, the actual efficiency and effectiveness of such devices might not be the primary concern. Yet, the education sector is not the only consumer of such goods. Given the need to harvest increasing amounts of information students themselves may be co-​opted into these commercial transactions, paying with data. Alongside broader social processes, this may generate student indifference towards invasive monitoring practices within schools. Indeed, as ‘quietly, subtly schools become experimental labs and then junkyards for our surveillance futures’, (Hope, 2015, p. 855) it is likely that the use of surveillance technologies will continue to grow within educational institutions. Driven by commercial pressures, the desire to exploit new markets and the acceptance of invasive surveillance practices as a norm within schools, part of this growth could be the emergence of devices that purport to identify the pre-​criminal student.

Conclusion In conclusion, connections exist between pre-​crime processes and digital school surveillance technologies. Not in terms of current school practices, but rather with reference to the potentialities and the socio-​economic conditions necessary for such applications to occur. There exists a rich array of digital surveillance technologies that currently operate in schools, some of which could be co-​opted into pre-​crime technologies. Within neoliberal governmentalities, state activities are increasingly devolved to private companies, with the market penetrating all aspects of everyday life, while the viewer society appears unconcerned about ever encroaching surveillance. All of these elements suggest an expanding and increasingly invasive role for surveillance technologies, one in which pre-​crime practices and predictive policing might spread outside of contemporary criminal justice settings. Furthermore, the problematic notion of the pre-​ criminal student might emerge from techno-​realist narratives that promise to stop future crime. Despite the destructiveness of such a label, commercial pressures could nevertheless result in both a growth of invasive technologies within schools and the notion of the pre-​criminal student. While it could be hoped that corporate ethics or privacy laws might prevent such an occurrence, Zuboff’s (2015, 2019) discussion of surveillance capitalism and ‘formal indifference’ raises serious doubts about the reliability of such safeguards.

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The consequences of such imagined possibilities are daunting. Schools may function less effectively as institutions of learning as trust is undermined through new coercive policing practices. Students might be punished for disciplinary offenses, or even crimes that they have not committed. The rights of children will be further eroded as they are socialized into being ever more surveillance tolerant. Schooling becomes increasingly subject to commercial pressures, as the surveillance industrial complex seeks new ways to monetize their involvement with educational institutions. In truth, these are imagined futures. Yet, the same can be said of pre-​crime. Ultimately, there needs to be far more consideration of the broader social cost of such technologies, particular as they seep into other environments, such as schools. References Abramsky, S. (2016). The school security industry is cashing in big on public fears of mass shootings. The Nation, [online] Available at: https://​www.thenation.com/a​ rticle/t​ he-​school-​security-​industry-​ is-​cashing-​in-​big-​on-​public-​fears-​of-​mass-​shootings/​ Augur, H. (2015). IoT in education: The Internet of School Things. Dataconomy, [online] Available at: http://d​ ataconomy.com/2​ 015/1​ 2/​ iot-​in-​education-​the-​internet-​of-​school-​things/​ Ball, K., Lyon, D., Wood, D., Norris, C. & Rabb, C. (2006). A Report on the Surveillance Society. London: Information Commissioner’s Office. Available at: https://​ico.org.uk/​media/​about-​the-​ico/​documents/​ 1042390/​surveillancesociety-​full-​report-​2006.pdf Beckett, L. (2019). Under digital surveillance: How American schools spy on millions of kids. The Guardian, [online] Available at: https:// ​ w ww.theguardian.com/ ​ w orld/ ​ 2 019/ ​ o ct/ ​ 2 2/​ school-​student-​surveillance-​bark-​gaggle Big Brother Watch (2012). Class of 1984: The Extent of CCTV in Secondary Schools and Academies, [online] Available at: http://​www. bigbrotherwatch.org.uk/​home/​2012/​09/​the-​class-​of-​1984.html Big Brother Watch (2016). Classroom Management Software—​Another Brick in the Wall? How Schools Use Software to Monitor Pupils, [online] Available at: https://​www.bigbrotherwatch.org.uk/​wp-​content/​ uploads/​2016/​11/​Classroom-​Management-​Software-​Another-​ Brick-​in-​the-​Wall.pdf Casella, R. (2006). Selling Us The Fortress: The Promotion of Techno-​ Security Equipment for Schools. New York, NY: Taylor and Francis.

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Casella, R. (2010). Safety or social control? The security fortification of schools in a capitalist society. In T. Monahan & R. Torres (eds.) Schools Under Surveillance: Cultures of Control in Public Education. New York, NY: Rutgers University Press (pp. 73–​86). Chillcott, T. & Tin, J. (2012). Screen spy keeps watch on school students’ home laptop activity. The Courier Mail, [online] Available at: http://​www.couriermail.com.au/​news/​queensland/​screen-​spy-​ keeps-​watch-​on-​students/​story-​e6freoof-​1226358220320 Clarke, R. (1988). Information technology and dataveillance. Communications of the ACM 31 (5): 498–​512. Dick, P.K. (2013). Selected Stories of Philip K. Dick. New York, NY: Houghton Mifflin Harcourt. The Economist (2016). China invents the digital totalitarian state. The Economist, 17.12.2016, [online] Available at: https://​www.economist. com/​briefing/​2016/​12/​17/​china-​invents-​the-​digital- t​ otalitarian-​state Fe d e r a l C o m mu n i c a t i o n s C o m m i s s i o n ( F C C ) ( 2 0 1 5 ) . Universal Service Program for Schools and Libraries (E-​R ate), [online] Available at: https://​www.fcc.gov/g​ eneral/u ​ niversal-s​ ervice-​ program-​schools-​and-​libraries-​e-​rate Ferguson, A.G. (2017). Policing predictive policing. Washington University Law Review 94 (5): 1109–​189. Gad, C. & Hansen, L. (2013). A closed-​circuit technological vision: On minority report, event detection and enabling technologies. Surveillance & Society 11(1/​2): 148–​62. Gane, N. (2012). The governmentalities of neoliberalism: Panopticism, post-​panopticism and beyond. The Sociological Review 60 (4): 611–​34. Hall, N. (2003). The role of the slate in Lancastrian schools as evidenced by their manuals and handbooks. Paradigm 2 (7): 46–​54. Haskins, C. (2019). Gaggle knows everything about teens and kids in school. Buzzfeed.News, 01.11.2019, [online] Available at: https://​ w ww.buzzfeednews.com/​ a rticle/​ c arolinehaskins1/​ gaggle-​school-​surveillance-​technology-​education Hiatt, B. (2018). Drones used to inspect WA school buildings. The West Australian, 04.01.2018, [online] Available at: https://​ thewest.com.au/ ​ n ews/ ​ wa/ ​ d rones- ​ u sed- ​ t o- ​ i nspect- ​ wa- ​ s chool-​ buildings-​ng-​b88704995z Hope, A. (2010). Student resistance to the surveillance curriculum. International Studies in Sociology of Education 20 (4): 319–​34. Hope, A. (2013). ‘Clouds’ that reign over: learning to be surveilled in the ‘database school’. Learning with New Media Research Group, Monash University, [online] Available at: http://​newmediaresearch. educ.monash.edu.au/​lnmrg/​blog/​learning-​to-​be-​surveilled

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Hope, A. (2015). Governmentality and the ‘selling’ of school surveillance devices. The Sociological Review 63 (4): 840–​57. Hope, A. (2016) Biopower and school surveillance technologies 2.0. The British Journal of Sociology of Education 37 (7): 885–​904. Hope, A. (2018a). Unsocial media: School surveillance of student internet use. In J. Deakin, E. Taylor & A. Kupchik (eds.) The Palgrave International Handbook of School Discipline, Surveillance and Social Control. London, UK: Palgrave macMillan (pp. 425–​44). Hope, A. (2018b). Creep: The growing surveillance of students’ online activities. Education and Society 36 (1): 55–​72. Kuehn, L. (2008). Surveillance 2.0: The ‘information panopticon’ and education. Our Schools, Our Selves Summer 2008: 81–​91. Lee, D. (2018). At this Chinese school, Big Brother was watching students—​and charting every smile or frown. LA Times, 30.06.2018, [online] Available at: http://​www.latimes.com/​world/​la-​fg-​china-​ face-​surveillance-​2018-​story.html# Lyon, D. (1994). The Electronic Eye: The Rise of Surveillance Society. Cambridge, UK: Polity Press. MailOnline (2008). School removes CCTV cameras from children’s toilets after furious protest from parents. Mail Online, 21.02.2008, [online] Available at: http://​www.dailymail.co.uk/​news/​article-​ 517250/​School-​removes-​CCTV-​cameras-​childrens-​toilets-​furious-​ protest-​parents.html Mallett, C.A. (2016). The school-​to-​prison pipeline: A critical review of the punitive paradigm shift. Child and Adolescent Social Work Journal 33 (1): 15–​24. Marx, G. (2002). What’s new about the ‘new surveillance’? Classifying for change and continuity. Surveillance & Society 1 (1): 9–​29. Mathiesen, T. (1997). The viewer society: Michel Foucault’s ‘panopticon’ revisited. Theoretical Criminology 1 (2): 215–​33. McCulloch, J. & Pickering, S. (2010). Future threat: Pre-​crime, state terror, and dystopia in the 21st century. Criminal Justice Matters 81 (1): 32–​3. McCulloch, J. & Wilson, D. (2016). Pre-​crime: Pre-​emption, Precaution and the Future. Abingdon, UK: Routledge. Monahan, T. (2006). The surveillance curriculum: Risk management and social control in the neoliberal school. In T. Monahan (ed.) Surveillance and Security: Technological Politics and Power in Everyday Life. New York, NY: Routledge (pp.109–​24). Monahan, T. & Torres, R. (2010). Introduction. In T. Monahan & R. Torres (eds.) Schools under Surveillance: Cultures of Control in Public Education. New York, NY: Rutgers University Press (pp. 1–​18).

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Mor, Y. (2014). Big data and law enforcement: Was ‘minority report’ right? Wired, 5 March 2014, [online] Available at: https://​www.wired.com/​ insights/​2014/​03/​big-​data-​law-​enforcement-​minority-​report-​r ight/​ Nordrum, A. (2016). Popular internet of things forecast of 50 billion devices by 2020 is outdated. IEEE Spectrum, 18.08.2016, [online] Available at: https://​spectrum.ieee.org/​tech-​talk/​telecom/​internet/​ popular-​internet-​of-​things-​forecast-​of-​50-b​ illion-d​ evices-b​ y-2​ 020-​ is-​outdated Oleson, J. (2016). Review of McCulloch J. and Wilson D. (2016) Pre-​crime: Pre-​emption, precaution and the future. Australian and New Zealand Journal of Criminology 49 (2): 301–​3. Rich, E. & Miah, A. (2009). Prosthetic surveillance: The medical governance of healthy bodies in cyberspace. Surveillance & Society 6 (2): 163–​77. Shade, L. & Singh, R. (2016). ‘Honestly, we’re not spying on kids’: School surveillance of young people’s social media. Social Media + Society 2 (4): 1–​12. Suskind, R. (2006). The One Percent Doctrine: Deep Inside America’s Pursuit of Its Enemies since 9/​11. New York, NY: Simon and Schuster. Taylor, D. (2015). Schools monitoring pupils’ web use with ‘anti-​radicalisation software’. The Guardian, [online] Available at: https:// ​ w ww.theguardian.com/ ​ u knews/ ​ 2 015/ ​ j un/ ​ 1 0/​ schools-​trial-​anti-​radicalisation-​software-​pupils-​internet Taylor, E. (2012). The rise of the surveillance school. In K. Ball, K. Haggerty & D. Lyon (eds.) Handbook of Surveillance Studies. Abingdon, UK: Routledge (pp. 225–​32). UK Government (2015). Counter Terrorism and Security Act 2015, [online] Available at: http://​www.legislation.gov.uk/​ukpga/​2015/​ 6/​contents/​enacted UUTISET News (2017). Tangible steps towards fitness: Finnish school invests in pedometers. UUTISET, 01.10.2017, [online] Available at: https://​yle.fi/u ​ utiset/o ​ sasto/n ​ ews/t​ angible_s​ teps_t​ owards_fi ​ tness_​ finnish_​school_​invests_​in_​pedometers/​9861025 Vaas, L. (2015). How one school district is monitoring social media of students and teachers. Naked Security, [online] Available at: https://​ nakedsecurity.sophos.com/2​ 015/0​ 7/3​ 1/h ​ ow-​one-​school-​district-​is-​ monitoring-​social-​media-​of-​students-​and-​teachers/​ Walker, P. (2017). Two UK schools trial use of police-​style bodycams for teachers. The Guardian, 08.02.2017, [online] Available at: https:// ​ w ww.theguardian.com/ ​ e ducation/ ​ 2 017/ ​ f eb/ ​ 0 8/​ two-​uk-​schools-​trial-​use-​of-​police-​style-​bodycams-​for-​teachers

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Wall, J. (2010). From post-​crime to pre-​crime: Preventing tomorrow’s crimes today. Criminal Justice Matters 81: 22–​3. Zedner, L. (2007). Pre-​crime and post-​criminology? Theoretical Criminology 11 (2): 261–​81 Zuboff, S. (2015). Big other: Surveillance capitalism and the prospects of an information civilization. Journal of Information Technology 30 (1): 75–​89. Zuboff, S. (2019). The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. New York, NY: Hachette Book Group.

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Commodification of Suffering Matthew Draper, Brett Breton and Lisa Petot

Introduction One of the authors, Dr Matthew Draper, worked as a mental health professional in correctional settings and currently works as a clinical director of an addictions rehabilitation outpatient center (rehab), in which he daily treats those bound up in these two processes. In his field, one of the major links between those formerly incarcerated and those suffering from addiction is mental illness (Smith et al, 2017), and it seems that mental illness keeps many patients ‘stuck’ between rehab and incarceration. Upon close examination, it is not mental illness itself, or addiction itself, that perpetuates the cycle between rehab and incarceration, or even their comorbidity. Rather, it is a lack of adequate and affordable treatment and the way vested financial interests serve as a barrier to treatment for the poor and middle class. For example, Dr Draper submitted an assessment and treatment plan to an insurance company with the diagnosis of borderline personality disorder and opioid dependence (severe) for a patient recently released from jail. The insurance company denied the claim, leaving Draper to decide whether to treat the patient pro-​bono. His peers at other facilities advised him to change the diagnosis to ‘mood disorder’ rather than a personality disorder. Insurance companies prefer mood disorders diagnoses because medication and brief psychotherapy seem to readily ameliorate them, whereas personality disorders (like borderline personality disorder) are not as readily treated with medication, require long-​term intensive psychotherapy, and intensive training for the psychotherapist, which is far more expensive (Kersting, 2004). Practitioners’ commonly shared

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wisdom says that insurance companies tacitly ‘required’ diagnoses that fell under Axis I (clinical disorders—​including mood disorders) of the DSM-​IV-​TR for the treatment to qualify for payment. Likewise, the unwritten understanding was that disorders formerly falling under ‘Axis II’ (i.e. personality disorders and intellectual disability) were, at best, questionable for third-​party payment. It is not clear that the new structure of the DSM 5 has ameliorated this dynamic (Frances, 2012). Curious, Draper inquired among colleagues, who told him that such deliberate misdiagnoses were very common, and they justified the practice as ‘necessary’ to provide at least some treatment to those suffering. Instead of borderline personality disorder, they suggested a diagnosis of bipolar disorder. Simultaneously, a patient must receive treatment for the diagnosis, including appropriate medications and psychotherapy, or the insurance companies deny the claims. He found that the argument ‘it is better to give clients some treatment rather than none, even if you have to misdiagnose them’ problematic with his patient because ‘no medication has been shown to be an adequate primary treatment agent, that borderline personality disorder is distinct from bipolar disorder, and that placebo may be an effective treatment when delivered in the context of good clinical management’ (Gunderson & Choi-​Kain, 2018). Although such deliberate misdiagnosing is clearly contrary to the ethics of the American Psychological Association, National Association of Social Workers and the American Counseling Association, the practice is growing more prevalent, exposing an ethical contradiction in the training of mental health practitioners, who for example, are taught that competent and effective treatment requires diagnosing ethically and accurately, developing relevant treatment plans (Pope & Vasquez, 2016). Yet, practitioners also learn that providing care to those that need it sometimes requires a deliberate misdiagnosis (Loue, 2018). Consequently, the ensuing treatment can constitute malpractice. This ethical contradiction puts mental health practitioners in a very difficult position. This aforementioned dynamic is so prevalent that it is not a ‘dirty secret’, but an openly discussed fact. The common metaphor is that the ‘tail’ of insurance reimbursement ‘wags the dog’ of psychotherapy practice, so much so that for a practice to remain financially viable, personnel must conform to the demands of insurance reimbursement. Such problematic conformity, however, arises out of a certain set of cultural values, and how those values have unfolded over time. In this chapter, we outline how mental health problems became a market commodity; how those mental health problems are surveilled; and

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how these issues relate to a crisis in psychotherapy practice generally, the issue of mental illness, and the American rates of incarceration. We begin with a brief history of the complicated ethics involved.

Cultural assumptions and commodification The tension between providing for the need of others and the tendency to seek profit has a lengthy history in American culture, although the origin predates the United States. A full exploration of these issues exceeds the space limitations of a short chapter, but a brief outline suffices. A commodity, according to Webster’s is ‘an article of trade or commerce, especially a product as distinguished from a service’ (2019). Interestingly, US culture has transformed much of our world into a commodity, including ourselves. For example, we hear ‘You really have to sell yourself ’ and ‘You have to make it clear what it is you offer’, during a job interview, as though the self is an object on the open market, a mere article of commerce. This objectification, and hence commodification, of the self is the outcome of millennia of our shared social imaginary. Taylor (2007) defines ‘social imaginary’ as a commonly shared, pre-​theoretical cultural assumption. These assumptions change and unfold over time and facilitate communication within cultural and language groups. That is not to say that those who share assumptions agree; instead, it implies the existence of foundational understandings that allow varying degrees of agreement and disagreement. Tracing this history of ideas, we note that philosophy (a very theoretical understanding) can grow pre-​theoretical as it becomes increasingly common and shared within culture. This objectification of Being, insofar as historians can trace it, started with the ancient Greeks, like Herodotus, who saw the nature of humans as part of the natural cycle of the seasons, from which some of the various human health and sufferings also arise (Robinson, 1995; Thomas, 2002). Furthermore, this led to viewing humans and the human condition as natural objects in the natural world. This became a foundational assumption of natural philosophy, and by the 19th century, of ‘natural science’ (Robinson, 1995). An important assumption of natural science is the importance of reductionism and atomism (Slife, Reber & Richardson, 2005). Atomism reflects the assumption that to know the ‘truth’ of an object, scientists must reduce a complex system, like a human being, into its smallest discernable and researchable units, or ‘atoms’. This assumption, once discussed and argued in the halls of philosophers, found its way into

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our social imaginary. One of Draper’s clients, for example, came into treatment describing the symptoms of a major depressive episode. After she did, she said earnestly, “I may need to get on antidepressants; there’s clearly something wrong with my dopamine. I hope my insurance covers them.” Interestingly, this same client felt trapped in an emotionally abusive relationship with a partner upon whom she was financially dependent and religiously obligated to remain married to. Although antidepressants might help a little in such cases, she voiced the atomistic tendency common in our culture to look for the simplest (atomized) explanation of her suffering. This social imaginary of atomism perpetuates the cultural tendency to look for atomized solutions to atomic problems, such as reaching for medication. In light of such tendency, Eli Lilly, for example, originally developed the drug LY110141, the medication that became Fluoxetine and later Prozac, to treat blood pressure. When it had no effect, they tried it as an anti-​obesity agent—​again unsuccessfully. Later, they administered it to patients hospitalized with depression, particularly those with severe symptoms, but many patients continued to deteriorate. Finally, they tested the drug on five people suffering from mild depression, and all five of the recruits reported an amelioration of depression symptomology (Breggin & Breggin, 1995). Eli Lilly introduced Prozac to the market in 1987, and by 1999 earned just over $2.5 billion per year on this drug alone (Moore, 2007). This social imaginary of atomism combined with the development of psycho-​reactive medications influenced how Americans relate to their suffering, offering a chemical solution to what they assume is merely a chemical problem. This social imaginary, however, is not the only factor informing the issue of commodification of suffering, so do individualism and egoism. Individualism is the assumption that human beings are self-​contained monads. Their essential nature is internal to themselves, and nothing fundamentally connects them to others or the outside world. Every person has their own experience of events, of others, of themselves and even of moral truth. The two manifestations of the individualism social imaginary are expressive individualism and liberal individualism. Expressive individualism holds that everyone has a personal, internal nature, who they ‘truly’ are, and that they need to express their selves to others. So, we hear things like ‘I need to live my truth’ or ‘I just gotta be me’. Problematically, one person living their ‘truth’ can interfere with others’ well-​being. Tempering the expressive extreme, liberal individualism asserts that everyone is free to be their own autonomous selves but only insofar as it does not interfere with the autonomy of others (Slife, Reber & Richardson, 2005). This liberal

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individualism can be seen through American history, and even appears in the Declaration of Independence; all men have the right to ‘life, liberty, and the pursuit of happiness’. The Western social imaginary portrays humans as natural objects caused by natural forces, subject to natural law, beholden only to their own internal truths. Included in the common ‘individual’ experience are pleasure and suffering. Early psychologists such as Freud, Watson, and Skinner noted that organisms (including humans), tend to seek after pleasure and to avoid pain—​Freud called it the ‘pleasure principle’ (Robinson, 1995). Given that their imaginary presumes that humans are disconnected from other sources of meaning, they look within for what is needful, like meeting the needs and urges that provide pleasure. As isolated monads disconnected from the world and others, the sources of pleasure are personal and relative to the individual. Likewise, the causes and nature of individual suffering are also internal. If someone chronically suffers, something is wrong with them individually and/​or internally. We commonly hear such assumptions in psychotherapy practice, which focuses on individual thinking and behaving, not on ameliorating social problems like the relational disconnections perpetuated by technologism and modernity, the socio-​economic injustices that keep many in poverty, and the socio-​political strife arising from disconnection from a sense of civic duty or community connection (Fowers, Guignon & Richardson, 1999). This assumption is evident as clients adopt ideas like ‘Only you can make you happy’ or ‘I deserve happiness’ or ‘I need to change my thinking so I can be happy’. Happiness has become a moral good, existing within us individually and arising from our chemistry or personal attitude. This attitude perpetuates the ethic of egoism, that the pursuit of individual self-​interest is the best course of action. This idea is so ingrained, that Taylor (2007) observes that the point of human existence is happiness, or at least the pursuit thereof. This attitude is reflected in the mental health field. Happiness, or at least contentment, is ‘healthy’ and sorrow and suffering are ‘unhealthy’, especially when they are acute or chronic enough to interfere with ‘social and occupational functioning’ (DSM 5). Therefore, when people experience mental health symptoms, the assumption is that something is wrong with them, and they are motivated to remove the symptoms because of a moral obligation to ‘be happy’. In addition, egoism leads people to perceive unwanted feelings or experiences as problems to be fixed promptly and pharmaceutically. Draper reports a common interaction with his patients that occurs in the evenings in the mental health clinic

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where he works. Patients, with energy drink in hand, ask to see the physician for a prescription for sedatives to help them sleep at night. When he expresses concern that they are asking for a sedative while drinking an energy drink at night, they are surprised, and inform him that they ‘should’ be alert when they want to be alert, and they ‘should’ be asleep at night, and that it is wrong of him to suggest otherwise. Under the individualistic social imaginary, symptoms are automatically detached from broader social dynamics that may inform and even give rise to them. Instead, symptoms can be studied in isolation and their amelioration likewise estimated, marketed and profited from: ‘Once the creatures that surround us lose the significance that accrued to their place in the chain of being, they are open to being treated as raw materials or instruments for our projects’ (Taylor, 1991, p. 5).

Suffering as commodity Mental health issues have largely become a commodity with an associated service—​treatment. Although ‘health outcomes’ are carefully tracked and measured by government agencies, insurance companies and providers alike, the commodity surveilled is not health, but sickness, especially in the case of mental health issues, which are often portrayed as common, chronic or recurring (Soussia et al, 2017). Ironically, the rate of disease also indicates the possibility of profit. Developing treatments for rare diseases is unprofitable, while those for common ones are very lucrative (Carey & Gebeloff, 2018). For instance, depression is often referred to as the ‘common cold’ of mental disorders (Kandahakatla, Yarra, Pallepati & Patra, 2018). Interestingly, the relevant section of the DSM-​IV reads: The duration of a Major Depressive Episode is also variable. An untreated episode typically lasts 6 months or longer, regardless of age of onset. In a majority of cases, there is complete remission of symptoms, and functioning returns to the premorbid level … In some individuals (5%–​10%), the full criteria for a Major Depressive Episode continue to be met for 2 or more years (in which case the specifier Chronic may be noted. (APA, DSM-​IV, 1994, p. 325, emphasis added) The verbiage is almost identical in the DSM-​IV TR (APA, 2000). In the DSM 5, however, this same section seems ambiguous and may lead to different interpretations, with different implications:

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The course of a major depressive disorder is quite variable, such that some individuals rarely, if ever, experience remission … while others experience many years with few or no symptoms between discrete episodes … Chronicity of depressive symptoms substantially increases the likelihood of underlying personality, anxiety, and substance use disorders and decreases the likelihood that treatment will be followed by full symptom resolution. (APA, DSM 5, 2013, p. 165) Whether the nature of the disorder has significantly changed or whether such changes in prevalence and prognosis come from other factors is not quite clear. One interpretation of the earlier versions of the DSM is that for most people even untreated episodes go away on their own (even if the duration is six months or more). The latest version reverses the statement and the text may be interpreted as suggesting that the prevalence and duration of the disorder is more widespread and pervasive that previously thought. In addition, it seems that once depression is diagnosed, medication is not only the treatment of choice (given its ostensible fast action and symptom reduction) but also that patients should take the medication for prolonged periods, perhaps even for life. Moreover, according to TV advertisements, when one medication is not doing the full job, sufferers should take an additional one to complete the treatment. Incidentally, almost hidden just a few lines below the section from the DSM 5 previously quoted, it reads: ‘many individuals who have been depressed only for several months can be expected to recover spontaneously. Features associated with lower recovery rates, other than current episode duration, include psychotic features, prominent anxiety, personality disorders, and symptom severity’ (APA, DSM 5, 2013, p. 165). While the last text initially seems amenable to spontaneous recovery, it quickly lists additional factors that can exacerbate the disorder, suggesting that chronicity may be more prevalent and more likely to require continuous medication. The development of alleviating suffering as a commodity rather than a right unfolded slowly in the United States over the past century. Historically, in Western Europe and the United States, health care practitioners were often offered (or requested) reimbursement for services to patients. Unfortunately, the fees physicians could demand sometimes exceeded the ability of lower-​socio-​economic groups to pay. In much of Europe, countries systemized and nationalized healthcare, seeing it as a fundamental right. In the United States,

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however, the question of whether healthcare is a right or a for-​ fee service is unresolved. For example, in 1929 a group of Dallas teachers (members of the lower-​middle class by income) asked the Baylor medical system to provide them with 21 inpatient days for a monthly payment of 50 cents (The US Care Non-​System, 2008). Many physicians expressed concern about a monthly payment to an organization to guarantee access to treatment, fearing that such a system would decrease their incomes and therefore their standard of living. Increased scrutiny, accreditation demands and the intensification (and expense) of physician training over the previous two decades also contributed to the physicians’ concern. Simultaneously, with advances in medical technologies, the American public regarded doctors’ skills as more legitimate, which increased the amount of money physicians could demand for their services (The US Care Non-​System, 2008). From around 1929, the cost of healthcare exceeded the ability of many Americans to pay, especially if they suffered from a catastrophic injury or illness. Today this problem has increased to the point that 65 per cent of Americans who declare bankruptcy do so because of issues related to health care costs (lost wages and medical bills, specifically) (Konish, 2019). Again, the problem of unaffordable care is not secret, and is oft discussed in both government and business arenas. American citizens and politicians have made two national efforts to address this issue—​the Health Maintenance Organization (HMO) act of 1973 and the Patient Protection and Affordable Care Act (ACA) of 2010—​and both demonstrate the schizophrenia of healthcare being both a profit-​driven enterprise and a citizen’s right. The HMO act, for example, authorized hundreds of millions of dollars in grants and contracts to encourage the development of Health Maintenance Organizations (HMOs), prepaid plans and group practices, as an alternative to traditional fee-​for-​service and solo practitioners as a method to manage costs. It also amended the Fair Labor Standards Act, requiring employers to include HMO options in their health benefit offerings. These sections of the Act reflect the ‘healthcare as a right’ ethic. However, the fact that the Act provided hundreds of millions of dollars to enterprising businesses and specified the community-​rating methodology for determining premiums, reflects the view that suffering is the commodity and healthcare is the for-​ profit solution. The community-​rating method for establishing premiums involved contemplating the cost of the healthcare system providing the services but also the income of those enrolled; setting up a maximum-​value-​for-​cost dynamic that still exists today.

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The Patient Protection and Affordable Care Act (ACA) of 2010 expresses contradictory positions: healthcare is both a commodity and a right. The commodity argument posits that the marketplace should govern demand, supply and costs of care. On one hand, this Act establishes state insurance exchanges, an open marketplace where the customers (American citizens) purchase health care coverage from a listed provider. At the same time, the Act also implies that healthcare is a right, a fundamental human need, not a luxury. Thus, the authors of the act included mental health and substance use disorder treatment specifically. The authors also recognized the tendency of for-​profit systems to maximize profit by reducing expenses. Therefore, it required government regulators to establish and assess standards of healthcare to forestall or prevent insurers from compromising care quality and minimizing benefits for customers while maximize their own profits (Aggarwal, Rowe & Sernyak, 2010). Given that mental illnesses are usually treated based on the medical model (Anckarsäter, Radovic, Svennerlind, Höglund & Radovic, 2009), often involving medications, the increase in prescription drug use and pricing is a highly debated issue. During one of the 2020 Democratic debates, several would-​be presidential candidates ‘demonized’ both current trends in health care and the pharmaceutical industry for ‘commodifying the suffering’ of those experiencing health issues, including mental illness (Facher, 2019). During one of the debates, Elizabeth Warren (D-​MA) reproached giant drug companies for ‘rigging’ the American economy in favor of corporate interests. Several Democratic candidates commented on the abysmal disconnect between the current health care system and the ‘ideal’ system that would establish health care as a right, rather than a commodity. The authors of both HMO and ACA Acts recommended government regulators’ surveillance of the health of Americans and the healthcare industry. Researchers from the American Psychiatric Association, as well as various state and federal governments, measure the rates of mental illness in various states and the nation as a whole using three primary methodologies. First, they examine suicide rates and hospitalization rates for mental health concerns, requesting cause-​of-​ death data, diagnoses warranting inpatient hospitalization, and discharge data from hospitals and medical examiners’ offices. Second, they surveil utilization rates per capita by examining the number of mental health practitioners in each population as well as the number of psychiatric beds available. Third, they surveil the population directly employing surveys and face-​to-​face questioning of a representative sample of the population (Tannenbaum et al, 2009).

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Mental health surveillance In 2015, the Council of State and Territorial Epidemiologists (CSTE) developed and defined surveillance indicators to guide local and state health departments in monitoring mental health disorders to compare their occurrence among various jurisdictions using uniform methodology (Hopkins, 2018). The CSTE stated that these surveillance indicators would make it ‘easier for disease control program managers to design and evaluate prevention and control programs’. To prevent and control mental health disorders CSTE advised that public health agencies ‘must have high-​quality, timely information on their incidence, prevalence, risk factors, and consequences’. The council recommended the same methods to obtain mental health surveillance data. To conduct surveillance effectively, the CSTE asked public health agencies to reach an agreement that included these public health surveillance practices when surveilling mental health disorders: • the condition is important to put under surveillance; • federal, state, local, territorial and tribal public health agencies should establish surveillance for that condition using specified data sources, time intervals, ways of subdividing the population and definitions of events to be counted; • agencies should share the collected data with CDC with summaries of the data made public on a regular schedule. (Hopkins, 2018) The American Psychiatric Association (APA) includes prevalence rates of mental illnesses in the Diagnostic and Statistical Manual of Mental Disorders (DSM-​5). According to APA research, for example, the prevalence rate of Antisocial Personality Disorder (a characterological disturbance in an individual’s capacity to follow rules and laws) averages at around 5 per cent of men and just under 1 percent of women (APA, 2013). These estimates give practitioners a sense of the rarity or commonality of the symptoms of their patients. In addition, state departments of health also surveil the health of the state’s citizens ostensibly to better meet health needs by employing methodologies to track the prevalence of diseases (Hopkins, Landen & Toe, 2018). Some diseases, like substance use disorders, are difficult to track because those suffering from the illnesses are less likely to respond to surveys, maintain a fixed address, or both. Both the APA and state departments of health track illness ‘trend’ data over time. Tracking these trends has illuminated, for example, the notion that immediately after a drug is invented to ‘treat’ a

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mental illness, the rates of diagnosis of that illness greatly increase. For instance, shortly after the invention of the first monoamine-​oxidase-​ inhibitors, theorized to play a role in depressive symptoms, the rates of depression diagnoses skyrocketed, as did prescriptions for this medication, significantly increasing the ensuing profitability (Horwitz, 2010; Hillhouse & Porter, 2015). Interestingly, diagnoses for Attention Deficit Hyperactivity Disorder (ADHD) suddenly surged from around 1995 even though the common treatment for it, amphetamine methylphenidate, was invented in 1955. However, in the mid-​90s the corporation CIBA marketed the drug to treat short attention span in young boys (Rasmussen, 2008). This strategy proved successful, and the rates of amphetamine consumption (such as methylphenidate) have quintupled. The correlation between drug availability and diagnoses could be seen as a ‘good’, because more people are receiving treatment (López-​ Muñoz & Alamo, 2009). Nevertheless, other researchers question this conclusion, due to the abrupt rise in diagnosis prevalence after a drug enters the market (Shorter, 2014). Investigations by journalists, as to whether the pharmacy industry is pathologizing normative suffering to increase their profits, has made the issue public domain (Haberman, 2014). Meta-​analytic research on the effectiveness of antidepressant medication only exacerbates these concerns. Researchers find that 75–​80 per cent of prescriptions for these medications are given to patients suffering from mild to moderate symptoms of depression. For these patients, however, the drugs’ effectiveness is questionable at best, because they relieve symptoms no better than a placebo. Moreover, researchers find that patients typically continue to take only five of the available 21 most commonly prescribed drugs after two months because subjects report that ‘they don’t work’ (Cipriani, Furukawa & Slanti, 2018). Despite such outcomes, pharmaceutical companies continue to market all 21 medications even knowing that 16 do not work, and five work only for the most severely depressed (Cipriani, Furukawa & Slanti, 2018). Apparently, an advantage of depression is its profitability for pharmaceutical companies. Few people enjoy suffering, and many will pay for amelioration of their symptoms. Although major depressive disorder costs the economy $210.5 billion annually (Greenberg, Fournier, Sisitsky, Pike & Kessler, 2015), one of the largest costs is presenteeism: those suffering from symptoms still go to work, receive health insurance benefits and receive a paycheck but perform at lower levels. As mentioned, depression is very profitable to those who promise remission or minimization of symptoms because sufferers, on average,

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are employed and can pay for treatment. Many pay for longer periods than necessary. The symptomology for depression indicates that symptoms remit after 14 weeks for 31 per cent of patients and 16 weeks for 65 per cent of patients (NIMH, 2008). However, the National Center for Health Statistics reports that almost 50 per cent of patients continue to take medication for significantly longer periods of time (CDC, 2017) given strong recommendation from healthcare providers and popular health websites like WebMD (Conaway, 2010). Why continue paying after the symptoms resolve? For two primary reasons: prevention of relapse and/​or discontinuation syndrome. Psychiatric researchers note that 20 per cent of patients experience a recurrence of symptoms within the first six months after remission (Solomon, 2000; Fife, Reps, Cepeda, Stang, Blacketer & Singh, 2018). Therefore, psychiatrists commonly encourage patients to continue with the medication for six months to a year. In addition, 20 per cent of patients experience discontinuation syndrome, with flu-​like symptoms and mood issues. The syndrome typically lasts two weeks, prompting some patients to resume their medications to ameliorate the symptoms (Rolston, 2018). Interestingly, the pharmacy industry claims that these medications are not habit forming (a common belief that also appears on WebMD) even though 20 per cent of patients experience withdrawal syndrome, and it is dangerous to stop taking the medications without titration (Bhandari, 2019). Regardless, the majority of patients take medication that provides no benefit over placebo, and many continue to take the medication for months or years after the symptoms would have naturally remitted, yielding a large profit for those manufacturing and selling the medications. (To be fair, according to this research, about 25 per cent of patients demonstrate a consistent and positive response to these medications and continue to take them for a long period of time; the concern arises from the 75 per cent that provide raw profit for the drug companies with no real benefit.) Another factor is the emergence of quality measures of medical diagnosis and treatment (created by CMS-​Centers for Medicare and Medicaid Services), which are driven by prevalence/​surveillance data, and cost-​saving measures. These represent ‘best practices’ that claim to provide the ‘best outcome’ for more people and less money, and inform treatment policy, spending projections and payment rates. Insurance companies employ this data and use Pay-​for-​Performance tactics, persuading practitioners to use them with a certain percentage of their patients. Pay-​for-​performance is ostensibly intended to improve

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the quality and value of health care in the US, and its rates are derived from CMS’s quality measures. Medicare, Medicaid, and insurance companies all use pay-​for-​performance methodology. Here are some examples of pay-​for-​performance incentives. • Community Care Behavioral Health Organization incentivizes their network drug and alcohol detox providers in Allegheny County with a 5 per cent increase in reimbursement if they demonstrate a 20 per cent increase from their baseline measurement in the number of persons engaged and retained in treatment. • PacifiCare Behavioral Health incentivizes their network outpatient psychotherapists with plaques ($1,000 payments were discontinued) for participating in the ALERT (Algorithms for Effective Reporting and Treatment) Program. ALERT is based on a member-​reported treatment-​outcomes questionnaire. • Health Partners incentivizes all provider groups in the nine-​county greater Minneapolis Health Partners network with a $100,000–​ $300,000 bonus pool. If 60 per cent of patients in the group meet the criterion for depression treatments, the provider gets a one quarter payout. If 65 per cent of patients meet criteria, the provider gets the total amount. Treatment criteria for depression includes documentation of symptom monitoring within three months, and that the patients remain on an antidepressant for at least six months (Bremer, 2008, p. 4). The problem with Pay-​for-​Performance practices is two-​fold: 1. Using pay-​for-​performance methodology standardizes patient care, turning patients, treatments and outcomes into variables in an algorithmic equation instead of giving providers the ability to treat patients within their context. 2. As patient care becomes an algorithm-​driven assembly line, healthcare becomes less about healing and more about outcomes, reducing the provider, the patient and the treatment to commodities. On an assembly line, each ‘part’ moving down the line is treated identically. Likewise, each worker is interchangeable with anyone having the same qualifications. Mental health workers (psychiatrist, nurse, counselor, therapist) are interchangeable as well. The only thing left is for the marketplace to set the price of the commodity transaction. With an ever-​expanding diagnostic manual and a pharmaceutical, electronic or scripted cure for every ill, psychiatry

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speeds toward a future where the patient’s experience and perception no longer matter; only the presence of a measurable symptom does. Contrasting depression with schizophrenia reveals a sharp difference. The National Institute of Mental Health estimates that 3.2 million Americans suffer from schizophrenia, and that only 15 per cent of them are currently employed (CDC, 2020). Compare this with depression sufferers: although depression can prevent some from working, around 85 per cent are gainfully employed (NIMH, 2020). Although medications can prove helpful to the well-​being of some depressed patients, antipsychotic medication is vital to the basic life functioning of many who suffer from schizophrenia (Percudani, Barbui & Tansella, 2004). Because schizophrenia patients struggle to obtain employment, and may not be healthy enough to work, this market is much less profitable. Consequently, the pharmacy industry seeks new markets for drugs originally developed for an unprofitable group. For example, Quetiapine (better known by its market name Seroquel) an antipsychotic medication designed to treat schizophrenia with fewer toxic side effects is also approved for the treatment of the mania of bipolar I disorder (Riedel, Müller, Strassnig, Spellmann, Severus & Möller, 2007). However, due to the rarity of these diagnoses and the patients’ lack of income, the profitability of both markets is quite small. Thus, psychiatrists commonly prescribe Quetiapine ‘off-​label’ to those suffering from insomnia because of its sedative effects (Anderson & Vande Griend, 2014). Given that insomnia is a common side effect of depression, AstraZeneca pushed for its approval as a supplement medication for major depressive disorder. It was approved, despite limited evidence that atypical antipsychotics are effective for these symptoms (Komossa, Depping, Gaudchau, Kissling & Leucht, 2010). This increased the medication’s profitability markedly; AstraZeneca made $5.3 billion on Seroquel alone in 2010, despite the lack of clarity about the long-​term effects of antipsychotic medications for non-​psychotic patients (Allgov, 2020). Patients with psychotic symptoms, on the other hand, struggle to pay because they are not employed, and often turn to (or are directed to) government-​funded insurance programs like Medicaid. The issue of cost, for mental health services, is the subject of extensive debate and has significant impact on many who suffer from mental health difficulties (Rowan, McAlpine & Blewett, 2013). ‘Although access to specialty care remained relatively stable for people with mental illness, cost barriers to care increased among the uninsured and the privately insured who had serious mental illness’ (Rowan, McAlpine

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& Blewett, 2013, p. 1723)—​and the barriers are larger for sufferers with no insurance or other resources. The latter are effectively left to fend for themselves, and many finding themselves without recourse, may end up homeless or incarcerated.

Mental health deinstitutionalization and incarceration According to some research (e.g. Stoddard-​Dare, Mallett & Boitel, 2011), individuals processed in the legal system for delinquent behaviors suffer from bipolar disorder more than other populations: ‘[a]‌majority of youth in the U.S. who have perpetrated violent crimes and are placed in detention have mental health related issues’ (Stoddard-​Dare, Mallett & Boitel, 2011, p. 208). Another study (Sugie & Turney, 2017) suggested that the very action of processing individuals in the criminal justice system has deleterious consequences for future mental health. Apparently, any type of criminal justice processing—​not only incarceration but also arrests—​correlates with mental health, perhaps even causally. Research suggests a strong, positive correlation between mental illness and crime: Attributing causes to complex behaviours such as crimes is not an unbiased process, and mental disorders will attract disproportionate attention when it comes to explanations of behaviours that we wish to distance ourselves from … Thus, psychiatry was a central player in the expansion of the ‘triumphalistic’ medical paradigm, which saw modern medicine as the royal road to the understanding and alleviation of man’s ailments and sufferings. (Anckarsäter et al, 2009, p. 1) Deinstitutionalization may exacerbate the criminal justice system/​mental illness revolving door. In general terms, deinstitutionalization refers to the government policy that moved mental health patients out of mental institutions (‘insane asylums’) into federally funded mental health centers. In the times of ancient Greece and Rome, the word ‘asylum’ was synonymous with a sanctuary, a place of refuge for debtors, criminals, mistreated slaves or others afflicted with difficult life circumstance (Phillipson, 1911). The modern connotation of ‘asylum’ is an inversion of its original meaning. Mental hospitals have been the subject of government scrutiny and public suspicion for decades, and the public

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perception of mental hospitals often is of a cursed place where the mentally ill are locked away from society and subjected to mistreatment and abuse. Films and books like One Flew over the Cuckoo’s Nest (1975) only confirmed the popular view. In 1946, Congress passed the National Mental Health Act, and called for the establishment of the National Institute of Mental Health (Pan, 2017), which allowed for government management of mental health treatment facilitates. In 1963, John F. Kennedy signed the Community Mental Health Act, which provided federal financial support to construct improved community-​based preventive care and treatment facilitates, to deinstitutionalize mental health patients out of state-​run ‘insane asylums’ and into federally funded community mental health centers. However, the policy failed as economic conditions changed and the program received inadequate funding (Marks, 1990). According to Criminalizing the Seriously Mentally Ill: The Abuse of Jails as Mental Hospitals (Torrey, 1992), while agencies implemented deinstitutionalization with good intentions, this provided no alternate treatment avenues for those with serious mental illnesses. The Kennedy-​ sanctioned community mental health centers focused resources on individuals with less severe conditions, and, while limited federal funds for training mental health professionals yielded many psychiatrists in wealthy areas, it did so at a much lower rate in low-​income areas. Thus, the Community Mental Health Act unintentionally incentivized discharging patients without follow-​up care (Torrey, 1992).

Outcomes Government policy and funding make it increasingly difficult for people with severe mental illness to find appropriate care and shelter. The authors consider schizophrenia, bipolar disorder or major depressive disorder as ‘serious mental illnesses’. The National Institute of Mental Health (NIMH), defined ‘severe mental illness’ as longstanding mental illnesses, typically psychosis and those that cause moderate-​to-​severe disability of prolonged duration (Goldman, 1981), and found that 6.3 per cent of the population suffers from severe mental illness (Kessler, 2005). Given that the number of adults 18 and over in the US was estimated at roughly 234,564,000 (US Census, 2010), approximately 14.8 million people had severe mental illness that year alone. The Treatment Advocacy Center polled experts who estimated that about 50 beds per 100,000 people would meet needs for acute and long-​term care, but in some states the number of available beds is as low as five per 100,000 (Torrey, 2008). In 1965,

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the treatment capability of mental health institutions in the US was available for approximately 451,000 people. By 1985, this number declined to about 177,000 (McCorkle, 1995). Using Department of Health and Human Services data, researchers determined there was one psychiatric bed for every 3,000 Americans in 2010, compared to one for every 300 in 1955 (Torrey, 2010). The study also reported an increasing percentage of mentally ill people in prisons throughout the 1970s and 1980s (Torrey, 2010). The previous study concluded that in the United States there are currently three times more seriously mentally ill persons incarcerated than in hospitals. In some states, like Arizona and Nevada, the ratio is nearly ten to one. More glaring is a 1991 survey through the National Alliance for the Mentally Ill, concluding that 40 per cent of mentally ill individuals experience incarceration (Torrey, 2010). A 2017 report from the US Bureau of Justice Statistics gathered self-​ reported survey data to assess the prevalence of mental health issues among inmates. They found that 14 per cent of prisoners and 25 per cent of jail inmates had serious psychological distress in the previous 30 days, compared to 5 per cent of the US general population. More striking was the 37 per cent of prisoners and 44 per cent of jail inmates reporting a history of a mental health problems (Bronson, 2017). With the research indicating an almost 20 per cent increase in mental illness among the incarcerated and the correlation of this increase with deinstitutionalization-​supporting policy, it is difficult to ignore the desperate situation of America’s severely mentally ill population (Torrey, Entsminger, Geller, Stanley & Jaffe, 2008). Diminished treatment options can lead these populations to engage in activities that could land them in insane asylums under a different name—​prison (Lamb & Weinberger, 2005). Research makes it easy to presume that the people who should be getting serious mental help are simply being put into correctional facilities because that is the easiest accommodation (Glaze & Heberman, 2013). In this regard, Crocker, Martin, Leclair, Nicholls and Seto (2017) explain: [t]‌he criminal justice system has become a common gateway to mental health care for individuals with serious mental illness (SMIs) … Both forensic and civil psychiatric services provide care to growing numbers of individuals with SMI who have come into conflict with the law … The variability in mental health and criminogenic needs in this evolving population has direct implications for the organization

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of services in terms of intensity and breadth of services, resource allocation, as well as safety and security of patients, care providers and the community. (p. 84) This report represents another effort to surveil mental illness, particularly in relation to criminology, ostensibly to seek for amelioration—​or to pursue avenues for profit, as in privately run prisons. In a private prison, more inmates mean more profits. The government decided in 1997 to outsource incarcerations to private prisons. In 2010, news anchor Dan Rather reported that the federal government spends billions of tax dollars on private prisons. Some inmates, such as Jesus Galindo, an epileptic who died in a Reeves, Texas prison, lack necessary medical attention. Jesus, of course, had no access to outside resources, but treatment was even less accessible inside the prison. And, as Rather reported, there is no transparency and very little, if any, accountability for companies running these prisons (Rather, 2010). In fact, privately operated detention centers or prisons ‘are not required to disclose how they operate despite the fact that it is American taxpayers who are footing the bill’ (Crocker, Martin, Leclair, Nicholls & Seto, 2017). Many individuals who suffer from mental illnesses, and who lack the financial resources to pay for treatment, end up in prisons, public or private. Others become homeless, and many engage in socially undesirable activities, due to illness and/​or illicit attempts to get the essentials of living. The reason for the behaviors is not the focal point; it is that they are in the streets fending for themselves with little or no resources. This is another legacy of deinstitutionalization. A research project (Roots, Bjerkeset & Steinsbekk, 2018), indicated that ‘transferring patients ready for discharge from mental hospital to community residential aftercare can have the potential to reduce total consumption of health services and costs without increased hospital admissions’ (p. 1). However, because of their economic status and the severity of their illnesses, many do not qualify as good candidates for community centers. For various reasons, particularly financial ones, many state mental hospitals closed, which effectively decreased the availability of long-​term, inpatient care facilities. The lack of facilities leaves many individuals with mental illness in dire circumstances. In or outside of the prison system, the proportion of individuals with exclusively psychotic disorders is decreasing, while the proportion with comorbid issues, such as substance use and personality disorders is rising (Crocker et al, 2017). Research exploring psychiatric treatment for individuals presenting comorbidity with substance abuse (Dickey & Azeni, 1996) indicates that

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Psychiatric disabled substance abusers had psychiatric treatment costs that were almost 60% higher than those of non-​abusers … although the public health and financial costs of high rates of comorbidity are obvious, the solutions to the problems are not. Numerous bureaucratic and social obstacles must be overcome before programs for those with dual diagnoses can be tested for clinical effectiveness. (p. 973) The upshot is that individuals suffering from severe mental illnesses that are not readily treatable require longer treatment and more financial resources. Many of the mentally ill try to feel better by engaging in undesirable behaviors and/​or unhealthy coping mechanisms (‘self-​ medicate’), such as using alcohol and illicit substances (Lagoni, Crawford & Huss, 2011). Attempts to obtain illegal substances can logically lead to involvement with the criminal justice system.

Conclusion The inevitability of suffering leads to an adamant quest for its alleviation. This search presents opportunities for service, and in our modern western societies, an opportunity for profit. As mentioned, this holds especially true in the realm of mental health. Again, more often than not, the ‘tail’ of insurance reimbursement ‘wags the dog’ of psychotherapy practice. An important ethical contradiction between patient care and sustainability of service often puts mental health practitioners in a very difficult dilemma; remaining financially viable and conforming to the demands of insurance reimbursement. This project has illuminated the tension between providing for the need of others and the tendency to seek profit. Again, there is evidence to argue that US culture has transformed many of its components into commodities, including ourselves. Part of the common Western individual experience, or social imaginary, is the pursuit of pleasure, and by the same token, the avoidance of suffering, so much so that it could be argued that the main point of human existence is happiness, or at least the pursuit thereof. Happiness, or at least contentment, constitutes a ‘healthy’ life, and sorrows and suffering an ‘unhealthy’ existence, especially when the latter is perceived as acute or chronic enough to interfere with ‘social and occupational functioning’ (DSM 5). In this sense, the social imaginary of atomism combined with the development of psycho-​reactive medications has greatly influenced

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how Americans relate to their suffering or attempt to ameliorate it in the pursuit of true happiness. The argument that mental health issues have largely become a commodity with an associated service—​treatment is illustrated with notions such as that of the interpretation of earlier versions of the DSM, from which it could be understood that for most people even untreated episodes of depression usually go away on their own. The latest version turns that statement on its head, implying that prevalence and duration of the disorder is more widespread and pervasive than previously thought. Although ‘health outcomes’ are carefully tracked and measured by government agencies, insurance companies and providers are not measuring health, but sickness, especially in the case of mental health issues which are often portrayed as chronic. Ironically, the rate of disease emerges as an important indicator of the possibility of profit. Ostensibly, to prevent and control mental health disorders, public health agencies have been advised to have information on incidence, prevalence, risk factors and consequences of mental illness problems within their given jurisdictions. The APA and state departments of health surveil data over time establishing ‘trends’ in illnesses. Another effort of surveillance is the emergence of quality measures of medical diagnosis and treatment. Quality measures claim to offer providers with guidance as to how to give better care for less money, and led to the implementation of provider ay-​for-​performance methodology. The reality is that using pay-​for-​performance standardizes patient care, turning patients, treatments and outcomes into variables in an algorithmic equation (objectification) instead of giving providers the ability to treat patients within their context. Healthcare becomes less about healing and more about outcomes, reducing the provider, the patient and the treatment to commodities. The illustration provided here, shows that schizophrenia patients struggle to obtain employment and may not be healthy enough to work, therefore this market is much less profitable than that of those patients suffering from depression, a large percentage who have some form of gainful employment. The latter, then, represent a more profitable commodity. Many of the severely mentally ill tend to ‘self-​medicate’ in an effort to alleviate their suffering, and in such effort may engage in undesirable behaviors and/​or unhealthy coping mechanisms, such as using alcohol and illicit substances. Instead of finding amelioration in socially-​supported institutions, there is a void in treatment for many

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of those who suffer from mental illnesses, due to legislation of the mid-​19th century, which led to the deinstitutionalizing of America. Such movement has left hundreds of thousands of severely mentally ill individuals stranded on the streets with little or no resources. Indeed, the modern cultural ideologies, based on assumptions of market analyses and surveillance trends, have fueled the commodification of suffering, particularly in regard to mental health issues, although not limited to these, turning human suffering into a market commodity. Meaningful repercussions are felt and discussed within an ensuing crisis in psychotherapy practice generally. In closing, it is argued here that the issue of mental illness, the tragedy of deinstitutionalization, and the American rates of incarceration carry very important correlations. Further scholarly efforts present with the opportunity for exploration of how changes in individual paradigms and social policies can alter the current course of this mental health treatment model. If suffering continues to be surveilled as a commodity, there will always exist the risk of exploitation, rather than increasing efforts toward contextual and genuine amelioration. References Aggarwal, N.K., Rowe, M. & Sernyak, M.A. (2010). Is health care a right or a commodity? Implementing mental health reform in a recession. Psychiatric Services 61 (11): 1144–​5. Allgov.com (2020). Seroquel Is So Profitable, AstraZeneca Is Glad to Pay Millions in Penalties [online] n.d., Available at: http://​www.allgov. com/​news/​controversies/​seroquel-​is-​ so-​profitable-​astrazeneca-​is-​ glad-​to-​pay-​millions-​in-​penalties?news=842383 American Psychiatric Association (1994). Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition. Washington, DC. American Psychiatric Association (2000). Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition Text Revision. Washington, DC. American Psychiatric Association (2013). Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition. Arlington, VA. Anckarsäter, H., Radovic, S., Svennerlind, C., Höglund, P. & Radovic, F. (2009). Mental disorder is the cause of crime: The cornerstone of forensic psychiatry. International Journal of Law and Psychiatry 32: 342–​47.

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NIMH (2008). Sequenced Treatment Alternatives to Relieve Depression (STAR*D) Study [online] Available at: https://​www.nimh.nih.gov/​ funding/​clinical-​research/​practical/​stard/​index.shtml NIMH (2020). Major Depression [online] Available at: https://​www. nimh.nih.gov/​health/​statistics/​major-​depression.shtml One flew over the CUCKOO’S NEST [Motion picture]. (1975). UA/​ Fantasy Films. Pan, D. (2017). TIMELINE: Deinstitutionalization and Its Consequences [online] June, Available at: https://​www.motherjones.com/​politics/​ 2013/​04/​timeline-​mental-​health-​america/​ Percudani, M., Barbui, C. & Tansella, M. (2004). Effect of second-​ generation antipsychotics on employment and productivity in individuals with schizophrenia. PharmacoEconomics 22 (11): 701–​18. Phillipson, C. (1911). The International Law and Custom of Ancient Greece and Rome (Vol. 1). London, UK: Macmillan. Pope, K.S. & Vasquez, M.J.T. (2016). Ethics in Psychotherapy and Counseling: A Practical Guide. Hoboken, NJ: Wiley. Rasmussen, N. (2008). On speed: The many lives of amphetamine. Choice Reviews Online 46 (4). DOI: 10.5860/​choice.46-​2125 Rather, D. (2010). Private Prisons: What’s Happening Inside Reeves?—​Dan Rather Reports [Video file] Available at: https://​fod.infobase.com/​ PortalPlaylists.aspx?wID=114324&xtid=114519. Riedel, M., Müller, N., Strassnig, M., Spellmann, I., Severus, E. & Möller, H.J. (2007). Quetiapine in the treatment of schizophrenia and related disorders. Neuropsychiatric Disease and Treatment 3 (2): 219–​35. Robinson, D.N. (1995). An Intellectual History of Psychology. London, UK: Arnold. Rolston, C. (2018). Antidepressant Discontinuation Syndrome. Encyclopedia of Clinical Neuropsychology 279–​280. DOI: 10.1007/​ 978–​3-​319–​57111–​9_​9175. Roots, E., Bjerkeset, O. & Steinsbekk, A. (2018). Health care utilization and cost after discharge from a mental hospital: An RCT comparing community residential aftercare and treatment as usual. BMC Psychiatry 18 (363): 1–​13. Rowan, K., McAlpine, D. & Blewett, L. (2013). Access and costs barriers to mental health care by insurance status, 1999 to 2010. National Institute of Health 32: 1723–​30. Shorter, E. (2014). The 25th anniversary of the launch of PROZAC gives pause for thought: Where did we go wrong? British Journal of Psychiatry 204 (5): 331–2.

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Slife, B.D., Reber, J.S. & Richardson, F.C. (2005). Critical Thinking about Psychology: Hidden Assumptions and Plausible Alternatives. Washington, DC: American Psychological Association. Smith, L.L., Yan, F., Charles, M., Mohiuddin, K., Tyus, D., Adekeye, O. & Holden, K.B. (2017). Exploring the link between substance use and mental health status: What can we learn from the Self-​ medication Theory? Journal of Health Care for the Poor and Underserved 28 (2S): 113–​31. Solomon, D.A. (2000). Multiple recurrences of Major Depressive Disorder. American Journal of Psychiatry 157 (2): 229–​33. Soussia, R.B., Khouadja, S., Marrag, I., Younes, S. & Nasr, M. (2017). Major depressive disorder: Recurrence risk factors. European Psychiatry 41. DOI: 10.1016/​j.eurpsy.2017.01.1974 Stoddards-​Dare, P., Mallett, C.A. & Boitel, C. (2011). Association between mental health disorders and juveniles’ detention for a personal crime. Child and Adolescent Mental Health 16: 208–​13. Sugie, N.F. & Turney, K. (2017). Beyond incarceration: Criminal justice contact and mental health. American Sociological Review 82: 719–​43. Tannenbaum, C., Lexchin, J., Tamblyn, R. & Romans, S. (2009). Indicators for measuring mental health: Towards better surveillance. Healthcare Policy | Politiques De Santé 5 (2) DOI: 10.12927/​ hcpol.2013.21180 Taylor, C. (1991). The Ethics of Authenticity. Cambridge, MA: Harvard University Press. Taylor, C. (2007). The Secular Age. Cambridge, MA: Harvard University Press. Thomas, R. (2002). Herodotus in Context: Ethnography, Science and the Art of Persuasion. New York, NY: Cambridge University Press. Torrey, E.F. (1992). Criminalizing the Seriously Mentally Ill: The Abuse of Jails as Mental Hospitals. Washington, DC: Public Citizens Health Research Group, Arlington, VA. Torrey E.F., Entsminger K., Geller J., Stanley J. & Jaffe D.J. (2008). The Shortage of Public Beds for Mentally Ill Persons: A Report of the Treatment Advocacy Center [online] Available at: www. treatmentadvocacycenter.org/​storage/​documents/​the_​shortage_​ of_​publichospital_​beds.pdf. Torrey, E.F., Kennard, A.D., Eslinger, D., Lamb, R. & Pavle, J. (2010). More Mentally Ill Persons Are in Jails and Prisons than Hospitals: A Survey of the States. Arlington, VA: Treatment Advocacy Center.

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US Census Bureau, Population Division. (2010). Table 1: Intercensal Estimates of the Resident Population by Sex and Age for the United States: April 1, 2000 to July 1, 2010. https://​www.census. gov/​data/​tables/​time-​series/​demo/​popest/​intercensal-​2000-​2010-​ national.html

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Surveillance, Substance Misuse and the Drug Use Industry Aaron Pycroft

Introduction A hermeneutical narrative will be used in this chapter to enable both a critical appreciation of the dynamics of the drug use industry in ultramodern1 democracies and also solutions to its inherent and real institutional violence. A hermeneutical narrative ‘seeks to bring new resources to our criminological perspective through occupying liminal spaces … and seek(s) to engage with diverse thinkers and traditions who have the potential to offer significant insights to criminology and the practices of justice’ (Pycroft & Bartollas, 2018, p. 234). In particular, an examination of the relationship between the practices of justice and theology will provide a focus of suspicion. This approach will reveal that the ultramodern rationalizations that enshrine the utilitarian calculus and the forms that they take in the technologies of new public management, (e.g. outcome monitoring, drug testing and risk profiling2) that pre-​criminalize drug users are theological in nature and an ultramodern concealment of sacred scapegoat mechanisms that arise from our anthropological heritage. The rationality of these mechanisms effectively ‘lock in’ the punitive practices that are ontotheological in nature but hidden in plain sight and that justify transcendental violence through the metaphysics argued to be foundational to social order. The hermeneutical narrative, as unconcealment (aleithia) will seek to apprehend the ding an sich (‘the thing in itself ’3) of institutional violence that is locked in to the criminal justice system. With respect to the

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drug use industry, our critical suspicion is enabled through arguing for recovery as an example of the non-​places that have come to define super modernity. In this non-​place the drug dependent person is always in transit but can never arrive, precisely because of the conflation of the sacred and economic value (anthropological place) that their suffering and dependence provides to state and society. Recovery is at the very least concerned with Platonic myths of purity and return and as such is a metaphysical (ontotheological) concept. Aside from the fact that much of the drug misuse industry is underpinned by the explicit theology of 12 Step Programs (particularly in the US), which are a major contribution of Protestant evangelical theology to modernity, criminal justice as practiced in the UK and US is also a theological enterprise. This leads to an antinomy of justifying harsh punishments and rehabilitation with both being grounded in retributive interpretations of the Judeo-​Christian scriptures as a basis for atonement (see Gorringe, 1996, 2020). Having outlined suspicions, the chapter will then seek a hermeneutic of affirmation to identify new theoretical and practical resources. It will be argued for the development of new dynamical states through a process of discovery rather than recovery with respect to humanity that seeks distance from a repressive state apparatus, or repressive systems of thought. To achieve this the concept of poetic space in the thought of Gaston Bachelard will be utilized as a criminological framework to explore a process of becoming. Bachelard’s work encourages us to ‘unlearn’ rationalism and scientific enquiry so as to be receptive to a poetic imagination that is independent of causality (see Ayiter, 2019). For Bachelard, the encounter between two persons is a special synthesis of event and eternity that has a mutual questioning and surprise, based upon a phenomenology4 of the instant (see Kearney, 2008). To unlearn, and to discover this new way of being, then it is necessary to engage in a hermeneutic process to reveal what emerges from the intersection of non-​places, anthropological places and poetic spaces. While the focus of hermeneutics in the work of—​for example, Paul Ricoeur, has been on identity, act and potentiality rather than substance (see Pellauer & Dauenhauer, 2016), I will argue for the significance of the latter in addressing the realities of suffering in the criminal justice system. This journey evolves out my reading of the critical tradition in criminology, within the context of having been a practitioner, and now an academic directly involved in researching with and educating practitioners and service users. This approach of necessity involves an ongoing critique of that tradition to avoid the risks of idolatry (expressed as ‘will to power’). Recent developments in the so-​called

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‘religious turn’ in continental philosophy (see e.g. Kearney, 2016) and theological thought enable us to reappraise intellectual developments in response to Nietzsche’s proclamation of the death of God and an appraisal of what it now means to act. As Marx states in his 11th thesis on Feuerbach ‘philosophers have only interpreted the world in various ways; the point is, to change it’ (Bernstein, 1969, p. 13, emphasis in the original). Likewise, he argues in his eighth thesis that any theory that leads to mysticism must be resolved through human, sensuous praxis (rational practice and comprehension of that practice). That sensuous practice (praxis), I argue, reveals new and non-​idolatrous names for God (see Richard Kearney’s concept of Anatheism (Kearney, 2011)) through philosophical and theological analysis.5 Increasingly, these approaches are being used to inform developments in criminology (see Millie, 2020, in press; Pycroft & Bartollas, forthcoming 2022, and this chapter is a contribution to those debates).

The death of the God of metaphysics The task of giving a name to the God who is dead is undertaken by Nietzsche who identifies the Judeo-​Christian God of metaphysics. In recent theological work on the ‘the death of God’ debate it has been argued that the god of metaphysics is an idol whose death is necessary (Marion, 2002a). From a criminological perspective, this God is the god of punishment and retribution who has become the idol of the nation-​state and out of necessity has lived on in concealed form in the criminal justice system (see Gorringe, 1996, 2020; Pycroft & Bartollas, 2018; Pycroft, 2020). This all seeing, all knowing, all judging, all condemning (conditionally forgiving) God of Platonic and Aristotelian elitism and purity (and a host of other idolatrous names that have yet to be encountered) provides metaphysical justification for all punishments.6 Nietzsche in pronouncing the death of the god of metaphysics (and Greek purity) is doing no more than acting upon the fact that God already is dead in the hearts of his contemporaries (Camus, 2000). This death and disenchantment as a defining feature of modernity would appear to build upon a transvaluation that is stated by Freud on the basis of three revelations grounded in rationality and science: Humanity has in the course of time had to endure from the hands of science two great outrages upon its naive self-​love. The first was when it realized that our earth was not the center of the universe, but only a tiny speck in a

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world-​system of a magnitude hardly conceivable; this is associated in our minds with the name of Copernicus … The second was when biological research robbed man of his peculiar privilege of having been specially created, and relegated him to a descent from the animal world … this transvaluation has been accomplished in our own time upon the instigation of Charles Darwin, Wallace, and their predecessors … But man’s craving for grandiosity is now suffering the third and most bitter blow from present-​day psychological research which is endeavoring to prove to the ‘ego’ of each one of us that he is not even master in his own house. (Strachey, 2001, pp. 284–5) Nietzsche’s leap to action, in the absence of a god, to all intents and purposes for ‘the people yet to be’ (a new metaphysical and teleological enterprise) has been seen particularly in the US as part of the existential tradition (see Cotkin, 2005) and also features significantly in Lippens’ and Crewe’s (2009) excellent edited collection on existentialist criminology. In this book, Lippens argues a positive list of do’s and don’ts from Nietzsche that focuses on individual creativity. Likewise, Lyng, Matthews and Miller (2002) in the same volume argue that Nietzsche is not only proclaiming the death of God but the death of all transcendental values and principles. The suspicions of Nietzsche, Marx, Freud and Darwin are well justified, but the risk of the actions that follow is nihilistic self-​ promotion, with the will to power simply reinstating a metaphysical aristocracy of the egotistical ubermensch and always at the expense of the untermensch. These risks have been exacerbated in subsequent thought, as is argued by Nuechterlein (2002): It is sometimes said that the post-​modern age is the post-​ Holocaust age—​the age of humanity trying to comprehend the horrific depths of its own violence. Or is it? The post-​ modern age is also one that might be said to have become preoccupied with texts—​to the point of analysing them down to the letters, the signs, of which they are constituted. If we can no longer get beyond texts to ‘reality’, then post-​modernism might instead be a clever way to avoid being confronted with our violence once again. We can seemingly find violence in our texts, but we cannot get to a better understanding of ‘real’ violence in the ‘real’ world, of human beings doing violence. A wholistic kind of learning

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to not do violence tends to be narrowed down to learning how to purge our language of its violence. (Emphasis in the original) The hermeneutical narrative by necessity reveals the failures of criminology to address the will to power and a deep conservatism and elitism inherent in the philosophical genealogies of the critical tradition. This genealogy includes the thought of the Marquis de Sade (who would only kill for pleasure rather than in the name of justice (Marquis de Sade, 1966)), Nietzsche (who places cruelty at the heart of his genealogy (see e.g. Nietzsche, 20037)), Heidegger (who was a Nazi (Mitchell & Trawny, 2017)) and Foucault (for whom judicial murder is an admirable form of power (Miller, 1994) and the ways in which they obscure our own complicity in judicial (and other forms of) violence). The critical tradition and the development of postmodern thought has provided us with frameworks of action (see Milovanovic, 2019) following the death of God, but this genealogy does not provide us with a way out of our violence, other than seeing self-​cruelty as a supreme expression of agency (Parmer, 2017) and acquiescence to the soul now trapping the body (Foucault, 1977). While providing a powerful critique these systems of thought collapse into forms of reductionist individualism that reifies the individual ego and thus cannot transform the criminal justice system through providing a necessary, critical and loving inter-​subjectivity (see Quinney, 1991 and DeValve, 2015). Any critical criminology thus has to be a peacemaking criminology rooted in marginality and powerlessness (see Pycroft, 2020) that is able to become conscious of its own will to power. It is only possible to become conscious in the light of the other, but only if I can truly see the face of the other, rather than seeing the other as a reflection of my own selfish desire (see Pycroft, 2020, in press). This alludes to Žižek’s (2009) critique of Levinas and the failure to take into account the problem of the otherness of the human being when reduced to the non-​human. We fail to see the other’s violence and my own complicity in it (see Girard, 1978), because, phenomenologically I always come between myself and that which I apprehend.

Recovery as ontotheology Recovery (from the Latin ‘recuperare’ meaning ‘to get again’) and its cognates (re-​habilitation, re-​storation, re-​integration) are central to an ontotheological conceptualization of drug misuse in ultramodern societies. Both Kant and Heidegger use the term ‘ontotheology’ in ways

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that are independent from each other but nonetheless have some loose connections (see Haltemann, 1998). In Kantian rationalism (namely, the sovereignty of reason, and metaphysics as the domain of that reason) ontotheology represents knowledge of the existence of God8 through reason alone without recourse to natural revelation or scripture (e.g. we hold the truths of the pursuit of life, liberty and happiness to be self-​evident). Kant’s ethical (practical reason) rather than theological (falling outside the remit of practical reason) arguments are focused on personal autonomy and intent of the individual to will the universal good (categorical imperative) through imposing her own limits rather than allowing others (including God) to impose those limits (forming the basis of liberalism, the reification of la différence and versions of postmodern thought). In this respect Kant is responding to the new physics of the enlightenment (see Rohlf, 2016), which saw nature and matter as mechanistic (deterministic) and the Cartesian dualism of separating structure and agency. In contrast, Heidegger uses the term ‘ontotheology’ to critique the general approach to Western philosophy that had followed Plato who had sought a metaphysical mastery of reality. This mastery is an essentialism that explains the existence of individuality through the imposition of universal ontological forms, which in turn emanate from a theological conceptualization of the Good that is the source of everything. The contemporary philosopher and theologian Jean-​Luc Marion (2002a) argues that the problem with ontotheology is that the nature of being and the way in which it is represented takes precedence over the very being itself. Marion finds the origins of ontotheology in Descartes, who had shifted philosophy from the ontological orientation of medieval scholasticism to that of epistemology (see Scruton, 2003). Foundational to enlightenment and subsequent thought is the rejection of haecceity (thisness, see e.g. Porter (2005) for an analysis of scholastic approaches to natural law), whereby we could now only describe rather than engage with the thing in itself. In applying this logic to the use of psychoactive substances we can see how the imposition of labels such as ‘addict’, ‘junky’, ‘pisshead’ or ‘mentally disordered offender’, uses an epistemology of agency to determine a metaphysical structure to the person, without engaging with the truth in itself of that person or their circumstances. The humanity or the personness of the person are lost but a new reality (judgment) of that person is created, based upon what is epistemologically valid according to my own frame of reference. This epistemic (mechanical and disjunctive) turn was further reinforced by Kant’s practical reason and leads to consciousness of (separate from) rather than in (connected to) something. This situation

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remained until the work of Henri Bergson9 whose philosophy was an attempt to overcome Kantian antinomies by asserting the possibility of absolute knowledge, and has now been reinforced by developments in hermeneutical phenomenology, quantum mechanics and complexity theory, which have revealed the dynamic nature of reality that we are constitutive of (see Pycroft, 2018).

The uses of psychoactive substances The use of psychoactive substances and the indisputable pleasures and pains that the uses of those substances can bring reveals the limits of normative (philosophical) ethics and the challenge of how or whether it is possible to reconcile the good, its ends and purposes (teloi) with a sense of what is necessary or dutiful (deon). The attempt to achieve this reconciliation is found in the work of Paul Ricoeur (see Wall, 2001), which itself is grounded in a transvaluation of the Judeo-​Christian tradition following the Holocaust. He argues that sacred texts transgress and rupture ordinary human understanding and reveal the limits of philosophy. This is demonstrated in articulating and realizing a determination of what an appropriate moral and legal response should be to the use of psychoactive substances. We can all cite examples of what we see as a bad law and agree that it is a bad law but not necessarily for the same reasons—​for example, the use of prison sentences for possessing relatively small amounts of illicit drugs. Non-​malicious retributivists (deontologists) might highlight the inconsistencies that arise in practice, for example drugs such as crack and crack cocaine being pharmacologically identical but the latter being dealt with more harshly than the former (the punishment is not proportionate). A utilitarian might point out that as a consequence of seeking to maintain a deterrent effect that too many people are being sent to prison (especially Black people who are more likely to use crack rather than White people who tend to use cocaine), leading to institutional racism, overcrowding, a loss of effective rehabilitation and therefore not being cost effective. A virtue ethicist might argue that the uses of either crack or cocaine and the brutalizing effects of prison do little to enable people (prisoners of criminal justice staff) to acquire the characteristics necessary to lead a good life. At times, these positions come very close together and help, politically, to bring often disparate groups of people together to make arguments for change and to build hegemonic momentum for change. There is a challenge though to developing a collective language because the causes and consequences of the use of psychoactive substances

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are fundamentally uncertain. There are no simple and direct causal relationships between biology, psychology and social context with respect to pathways into use, problematic use and dependent use (see Pycroft, 2010, 2015). Likewise, there is no certainty (agreement) about recovery, the nature of non-​harmful use, cessation of use or the meaning of relapse. Trying to make certain (i.e. through legal and medical categorization) that which is fundamentally uncertain is part of a Cartesian mathematical compulsion seeking application to all aspects of human life (Danisch (2013) calls this ‘ironic mathematics’). This is described by Heidegger (cited by Schrijvers, 2010, p. 220) as the necessity of precluding any uncertainty with respect to being and the process of ‘tranquilisation’ brought about by such aspirations. In modern liberal democracies the solution to the antinomies inherent in these situations is always a utilitarian trade off (described as ‘practical, democratic reason’), but with someone always having to suffer for the ‘greater good’. The process of tranquilization is revealed in Girard’s great insight that while we can always identify people who are being scapegoated, we cannot identify our own practices of scapegoating. It works precisely because it is unconscious (this is a form of Freudian transference) (Girard, 1978). Girard (1978) argues that religion evolves precisely to contain violence in societies (anthropological and sacred places), thus bringing about social order and culture. This is necessary because of the reality of mimetic rivalry that culminates in the war of all against all, and an escalation to extremes. In times of crisis, a scapegoat (usually an outsider on the basis of gender, race and ability) is randomly chosen to be excluded or killed. The sacrifice appears to resolve the crisis and period of peace commences, so much so that that the person sacrificed appears to have magical powers and is often deified. As Girard argues, this is the process whereby we create our gods. What disrupts (or more accurately irrupts) (apropos Paul Ricoeur’s hermeneutics) is that the Judeo-​Christian gospel narratives are written from the perspective of the innocent victims. These were the victims scapegoated to resolve a political and religious crisis in Jerusalem (the trial and execution of Jesus of Nazareth) and the events following that execution (the repression of his disciples and the religious stoning to death of Stephen). In these accounts of violence both Jesus and Stephen forgive their persecutors and refuse to use violence (either from themselves or God) to change their situation. From this narrative it follows that Christianity is not a religion but an organizing principle that deconstructs the archaic religious and the sacred sacrificial. It demonstrates that violence always comes from people and not from God, and that God reveals to us our own violence as the cause of

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apocalypse (Coronavirus, genocide, global warming, poverty etc.). We punish ourselves through our own blindness. Reductionist sacrifice is at best an interim and anthropic trade off in an entropic universe of our own imagining. The revelation of the scapegoat mechanism leads to modernity’s process of disenchantment with religion (it no longer works because we know the scapegoated victim is innocent), and consequently, Girard argues (2008) that we are more concerned with the victim than at any other time in human history. The innocent victim then becomes the object of our desire, which leads to harsher punishments in the name of the victim and of philosophical (normative) justice. With the decline of church and religious rituals, justice is the only public ritual that we have left (Dupuy, 2013) and becomes the place where our anger is focused on necessary scapegoats (see Gorringe, 1996, 2002, 2020) who become a perpetual sacrifice. This sacrifice is a reality in which real people are really suffering through being sacrificed for the greater good whether conceived of as the ‘unfinished project of the enlightenment’ (see Žižek, 2009) or of ‘the people yet to be’ (in the Nietzschean sense).

Recovery as non-​place The critical perspective unconceals the key mechanisms of scapegoating and the ultramodern enshrinement of (onto-​theological) purity codes in the concept of recovery through the principles of less eligibility, and risk management (see Pycroft & Green, 2016; Pycroft, 2018). Less eligibility is directly linked with the use of deterrence as one of the aims of punishment within criminal justice. It is a powerful ideological concept that stems from the work of the utilitarian philosopher Jeremy Bentham. It was foundational to the English Poor Laws and states that: ‘If the condition of persons maintained without property by the labour of others were rendered more eligible, than that of persons maintained by their own labour then … individuals destitute of property would be continually withdrawing themselves from the class of persons maintained by the labour others’ (Bentham cited in Sieh, 1989). It is important to consider the contemporaneous nature and re-​emergence of less eligibility in an age of austerity and financial cuts10 with a dominant discourse of the deserving and undeserving of help. It is argued by Sieh (1989, pp. 169–​170) that the concept is both vague and flexible and allows for the exercise of discretion in criminal justice, but that, Any reform which ignores the concept of less eligibility is doomed from the start. Divergent sentiments on the

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treatment of inmates become manifest and slow progress when a change occurs in the handling of an inmate. Bureaucrats view innovation as troublesome and see any reform … as troublesome because of the difficulties associated with implementation. Less eligibility combined with risk assessment removes the resources that enable people to access new dynamical states and circulates them through the non-​places of the drug use industry. It is argued by Marc Augé (1995) that ‘non-​places’ are a defining feature of super modernity. For Augé the transitory non-​places in which we spend so much of our time (railway stations, airports, motorways, superstores etc.) are places of circulation, consumption and communication that are always transitory, anodyne and anonymous. Augé contrasts these non-​places where relations, history and identity are erased with anthropological places where there are symbolic sites such as churches/​temples, altars, memorials, which are steeped in memory and belonging. The rationalizations of super modernity render recovery via the criminal justice system as a non-​place, where the addict is always in transit and never arrives but whose circular trajectory is defined by and delineated by the Foucauldian gaze and the soul trapping the body through governance and bureaucratic functions of case management, referrals, assessments, waiting lists, budgets, risk reviews, court reviews, drug testing, probation reporting and so on. These pre-​crime control mechanisms in an age of big data take a number of bureaucratic and algorithmic forms that are inherently discriminatory. For those people serving community sentences then reporting to the supervising probation officer becomes an end in itself, rather than the therapeutic encounter with that officer, so that simply phoning in to the office or other forms of communication at distance is sufficient to meet the requirements of the order. A consequence of this is firstly, the decontextualizing of the probation officer from their probationer’s local environments as they spend the majority of their time in front of a computer screen completing bureaucratic tasks. This mitigates against knowledge of local resources, which is essential in assisting those being supervised by the probation services to build social and human capital. Secondly, tasks such as actuarial risk assessment and risk profiling, which are claimed to be objective, actually reflect the inherent bias and discrimination in societies. It is, for example demonstrated by Ugwudike (2020) that such technologies over predict the risk of recidivism especially to Black people. Further, actuarial assessments that design sentence plans both deskill the practitioners (a

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form of trained incapacity (see Pycroft, 2019)) and also up tariff service users. This happens through prison and probations staff ‘gaming the system’ and inflating risk scores to secure an alcohol or drug treatment for people on their caseload, which would not otherwise be available to them (see Jennings & Pycroft, 2012). These processes ensure that addiction is maintained as a chronic relapsing condition, thus becoming more a Sisyphean torture than a self-​fulfilling (self-​inflicted) prophecy. This aporia is at the heart of the suffering of people with substance dependence. The UK Ministry of Justice (2016) clearly states that As a group, offenders in custody suffer from multiple and complex health issues at rates in excess of those observed in the general population. These may include mental health problems, learning difficulties, substance misuse, risk of suicide and self-​inflicted harm. Moreover, many people in prison, particularly women, have pre-​existing mental health or wellbeing issues and some may have received psychiatric help prior to incarceration. These underlying health issues are also often exacerbated by difficulties in accessing the full range of health and social care services in the local community prior to custody, including access to accommodation, employment and steady income. But rather than bringing about meaningful change this understanding represents the utilitarian use of social and economic disadvantage as economic advantage with prison building, the outsourcing of functions for surveillance and the delivery of rehabilitation services being used to stimulate local economies. Current approaches to statistically based ‘frequentist’ risk management approaches further contribute to the locking in of retribution and the failures of rehabilitation precisely because these approaches mean that for an individual who has committed a crime the slate cannot be wiped clean because of what they might do in the future requiring information to remain on file. It is essential, then, for the drug use industry and the wider penal-​ industrial complex that recovery and rehabilitation do not succeed. This is clearly demonstrated in the UK11 where Scotland, England and Wales have the highest imprisonment rates in Western Europe, rising by 69 per cent in the last 30 years, with there being no link between the prison population and levels of crime. Reconviction rates for those serving prison sentences of less than 12 months is 63 per cent, those on community orders is 56 per cent and suspended sentence orders

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is 54 per cent. To address this issue of the revolving door of crime, in England and Wales anyone spending more than two days in prison is now subject to 12 months supervision from the probation services, but leading (in 2018) to 8,927 people being recalled to prison (a significant proportion of whom were women). It is argued by Bacon and Seddon (2020) that the sites of drug treatment are representative of wider practices of penal power rooted in a hybrid of punishment and power that is used to control the poor. They also demonstrate that there is a significant overlap between drug treatment and the criminal justice system with populations characterized by high levels of unemployment, low incomes and other socio-​economic disadvantages. It is clear that less eligibility then extends beyond the criminal justice system into wider control practices. In practice the discourse of/​on recovery within this governance of corrections is a further example of an onto-​theological antinomy. In the requirement for drug users to become drug free (sobriety is argued to be the key virtue) the arguments about the best way to achieve this (in the UK and US) have focused on abstinence versus harm reduction and their relative merits but within a pure body thesis (see Bourgois, 2000)12 as the categorical imperative. In the UK, since the 1997 we have had at differing times a clear focus on both approaches from different governments. Between 1997 and 2010 the New Labour governments committed to a harm reduction approach, and the incoming coalition and subsequent governments since 2010 have committed to a recovery (abstinence) agenda (it was the Scottish government in 2008 that pioneered a move away from the harm reduction approach). The failings from both of these totalizing (in the sense that Levinas (1969) would argue about people who are satisfied with themselves and the systems that they can organize and control) are instructive.

Harm reduction Between 1997 and 2010, the New Labour Governments in the UK undertook a massive investment in harm reduction strategies (substitute prescribing, needle exchange etc.) to tackle the problem of approximately 250,000 dependent drug users. At the same time there was a huge investment in drug testing and treatment orders through criminal justice interventions (for alcohol, illicit drugs and mental health problems) and an expansion of a legal requirements for health, welfare and criminal justice agencies to work together (see Pycroft & Gough, 2010). The quantitative and biomedical benefits of harm reduction are well established (see Shea, 2015) with respect to

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reductions in injecting drug use, death from overdose, communicable diseases (HIV, Hepatitis A, B and C) in illicit drug use, and criminal activity. In the UK, the use of methadone as a cheaply produced drug enabled the New Labour governments to realize their target of increasing the number of people in drug treatment by 100 per cent over a ten-​year period. While it has been argued that harm reduction was seen by some as no more than a trojan horse for the legalization of illicit and harmful drugs, it has been clear that within clinical communities the emphasis had initially been on reducing the script and achieving abstinence. At the heart of substitute prescribing is the negotiation of the script and the issues of what is an appropriate level of medication relative to the street drugs that are being replaced, whether that dosage should be maintained, reduced and if the latter at what pace? Problems of going too fast can lead to people ‘topping up’ with illicit drugs and consuming more alcohol, which is a combination that can lead to an increased risk of overdose and death (see Senbanjo et al, 2006). As Bacon and Seddon (2020) argue, despite the convergence of health issues and criminal justice, little work has been done on the disciplinary nature of drug treatment. It is argued by Bourgois (2000) that methadone maintenance as drug treatment is Foucauldian bio-​power at work through medical and judicial categorization declaring some forms of opiates to be medicines and other forms as illegal. He argues (2000, p. 168) that Concretely, in the case of methadone, competing scientific, political and populist discourses mobilize an avalanche of objective, technical and rigorously quantified data that render them oblivious to their embroilment in a Calvinist-​Puritanical project of managing immoral pursuits of pleasure and of promoting personal self-​control in a manner that is consonant with economic productivity and social conformity. In the UK, the National Health Service is responsible for the provision of health services in prisons, and prisoners should expect the same level of and access to health services as people outside the criminal justice system. In practice, due to less eligibility this does not happen as the multiplicity of actors within these settings exercises a range of influences and powers through governance (see Gough, 2019). In my own work to develop harm reduction services in prison to try and ensure this equality of access and provision (e.g. continuity of script when imprisoned and

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discharged, access to assessment for a script on the development of drug dependence in prison) the prisoners have expressed concerns. Firstly, the lack of confidentiality between health care and prison staff and the conflation of rehabilitative (voluntary drug testing, VDT) and disciplinary (mandatory drug testing, MDT) measures. In the UK prison system, VDT is used for people who want to address their drug problems and so volunteer to be tested to build motivation and engage with programs and cannot be used for disciplinary reasons. In contrast, MDT is supposed to be random, to check for drug use in prisons and is directly linked to further punishment. Prisoners that I interviewed were very clear of the risks of testing positive for a VDT, as you could expect not soon after to be required to carry out an MDT. Secondly, anecdotal evidence from my conversations with probation officers working within prisons suggests occasions where prison governors have become involved in negotiations over the script for disciplinary reasons, which would constitute a clear breach of medical ethics and human rights. These examples demonstrate Bourgois’ (2000, p. 167) argument that methadone ‘represents the state’s attempt to inculcate moral discipline into the hearts, minds and bodies of deviants who reject sobriety and economic productivity’.

Recovery (abstinence) However, the real challenge to the Puritan ontotheological concept of the pure body was that government funding mechanisms linked to targets to increase both treatment and engagement with treatment led to people being ‘parked’ on methadone scripts, and given no choice about reduction, and often over long periods of time (10–​15 years). This use of the ‘liquid cosh’ is otherness itself being reduced to the radically inhuman and is akin to Žižek’s (2009) discussion of Agamben’s Musselman, the ‘living dead’ in concentration camps. The key analogy is that of the person being parked on a script and experiencing the full horror of not having any choice or power to change the situation and is unable to bear witness to that situation—​complete powerlessness.13 In 2008, the new Scottish nationalist government in Scotland implemented a new drug strategy that rejected the centralized approach to harm reduction. In 2010, the UK coalition government followed suit with an emphasis on recovery in their new drug policy linked to the acquisition of recovery capital. In this ‘new’ approach scapegoats continue to be essential to the structures of governing through crime (Simon, 2007), and apropos Galbraith’s ‘Culture of Contentment’ (Galbraith, 1992) those with sufficient cultural capital (the minority)

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will not so much benefit from punishment and mandated treatment but have the resources not be to be too disadvantaged by it. This is demonstrated by the work of Granfield and Cloud (1996) in their research into the recovery of middle-​class alcohol and drug addicts who often managed to resolve their problem without resorting to treatment), which challenged prevailing ideas about the nature of recovery and the necessity of treatment. Their first major paper on recovery capital (Granfield & Cloud, 2001) used Bourdieu’s concept of social capital, defined as ‘the sum of the resources, actual or virtual, that accrue to an individual or a group by virtue of possessing a durable network of more or less institutionalized relationships of mutual acquaintance and recognition’ to explain how people advantaged in this way were able to use these resources to enable a secure and fruitful exit from their addictions. They pointed out the implications for helping less advantaged addicted people: that treatment should aim at the enhancement of social capital (Granfield & Cloud, 1996, 2001), and that the individualized, de-​socialized understanding of addiction problems embedded in traditional models of treatment was doing a disservice to those lacking such social resources. Despite the policy on recovery, this proved to be no more than rhetoric as in the wake of the 2008 global financial crisis, the Coalition Government made a political choice to engage in a process of austerity funding, with explicit statements based on less eligibility, namely that the ‘feckless poor’ who refused to help themselves should not be entitled to the same benefits and resources from society as those who do (see Pycroft, 2019). Funding to the public sector was decimated, meaning that the kinds of social networks that drug users would depend on to build recovery capital was not there, coupled with a loss of harm reduction services. As a consequence, there have been a record number of drug related deaths with the Office for National Statistics (2019) demonstrating that recorded deaths from drug poisoning in 2018 increased by the highest ever level (16 per cent) since records began in 1993. A key part of these statistics is that over two thirds of the deaths were from people with existing substance misuse problems and involved an increasingly wider range of drugs including cocaine, new psychoactive substances as well as opiates. Death rates were highest in the poorest parts of the country with the stark realities of the links between drug dependence and socio-​economic disadvantage being revealed. The dynamic of less eligibility ensures that individuals are required (coerced into treatment) to ‘make good’ in desisting from crime and drug use but are not provided with the resources (social and human capital) to enable that to happen.

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Discovery as poetic space Given this enduring context it is not surprising that Pilgrim (2009, p. 112) argues that recovery ‘For professionals … is about successful treatment or rehabilitation but for critical service users, it is about survival and emancipation.’ Likewise, Roberts and Wolfson (2004, p. 37) state that: Recovery is usually taken as broadly equivalent to ‘getting back to normal’ or ‘cure’, and by these standards few people with severe mental illness recover. At the heart of the growing interest in recovery is a radical redefinition of what recovery means to those with severe mental health problems. Redefinition of recovery as a process of personal discovery, of how to live (and live well) with enduring symptoms and vulnerabilities opens the possibility of recovery to all. The ‘recovery movement’ argues that this reconceptualisation is personally empowering, raising realistic hope for a better life alongside what remains of illness and vulnerability. This discovery process is akin to poetic space, which for Bachelard (1969) opens the way to creative imagination requiring active participation with the other and for which there can be no passive phenomenology. He argues that this creativity is independent of causality and rationality. I would argue that there is a clear intersection between non-​places (exclusionary) and anthropological (sacrificial) places, and that poetic space is an example of emergence from these interactions that allows for an irruption of the person in themselves, in both being and becoming (expressed as a truth, or series of truth events—​see Badiou, 2003). This is to be understood neither as return in the Platonic ontotheological sense or an imposition of self as Nietzsche’s eternal recurrence of the same, and neither is it dialectical whereby the thesis and antithesis dissolve into some new synthetic reality where the past is forgotten. Poetic space allows for the development of new dynamical states that are immanent14 (see Pycroft & Bartollas, forthcoming 2022) that is accepting of the person as they are in themselves, in the here and now. This approach does not look back to the past as a basis for retribution, or to the future to determine the person that they could become (the binaries of modern criminal justice). This, in the philosophy of Vladimir Jankélévitch (Looney, 2015, p. 20) means that ‘Necessity and truth are installed as eternally already there and as unengendered

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self-​evidence (cela-​va-​de-​soi). But that which posits truth is not itself truth; that which makes the truth the truth is prior to and beyond the dichotomy of true and false’ (emphasis in the original). With the death of the God of Metaphysics, Marion (2002a) gives the new and non-​ idolatrous name of ‘Charity’ (agape) to a God, who is a God beyond being and absolutely free of all determinations that metaphysical ontotheology might ascribe to Him (sic). This understanding then opens up the possibilities of a genuine phenomenology of givenness whereby we truly understand that the person that we apprehend is first given to us (Marion, 2002b). This is anathema to the surveillance, risk and pre-​crime society. This approach requires different ways of working, and which is to be found in many peer led communities. Pushing Change is such a community in Portsmouth, UK, which works with a discovery rather than a recovery model, arguing that the past has made us who we (and as a place of trauma is not somewhere to return to) are but not necessarily who we are to become. This work does not fit into traditional and professionalized ways of working, as it is only through the acceptance of the individual as and where they are, and free from bureaucratic referral, assessment and funding processes that the discovery of the self of becoming is possible. This also means that the fragmentation in service delivery that separates out alcohol, illicit drugs and mental health on the basis of key performance indicators and funding based on outcome measures can be overcome. It is these processes that increase the risk of relapse and perpetuate pre-​criminalization.

Conclusion In this chapter I have argued for a process of unconcealment that demonstrates the significance of theological, philosophical and anthropological processes to our criminological imaginations in exploring the pre-​crime society. In the creation of a hermeneutical narrative to explore suspicions and to find affirmations, we always need to be conscious of our own will to power and tendency to conservatism and elitism. The critical tradition in criminology is not exempt from that risk and I argue that the introduction of new theological and philosophical resources following the Death of God discourse provides us with a necessary corrective in finding solutions to the problems of pre-​criminalization. This approach, I argue is consistent with criminology as peacemaking and a clear reason why criminology should not seek to distance itself from wisdom and doxastic traditions (see Pycroft, 2020). It is these approaches that genuinely irrupt into

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the rationalisms of crime and punishment to expose both the limits of those rationalisms and that also allows for a genuine phenomenology of the immanent. Notes 1

2

3

4

5

6

7

8

9 10

11 12 13

This chapter makes no distinction between ultramodern, super-​modern or hyper-​ modern. As will be discussed, the defining theme will be the rationalizations of bureaucratic modes of governance that follow from the disenchantment of modernity. Each of these reinforces the other and creates an organizational path dependence that is deterministic and locks in failure. In addiction relapse this is the norm rather than the exception, but in the processes of justice this is inverted, so what is normal is treated as abnormal and therefore requiring further punishment. On the basis of positive drug tests judgments are made about individual motivation,capacity for change and implications for public protection. We set people up to fail. Kantian philosophy argues the impossibility of apprehending the thing in itself. His approach to practical reason and epistemology leads ultimately to a breakdown in coherent thought structure and consequently an inability to speak a common language in addressing these issues (see Hall & Winlow, 2015; Pycroft, 2020; Pycroft & Bartollas, forthcoming 2022). Without a coherent thought structure and common language there can be no real identification of the problems let alone remedy. Kearney (2008) shows that while poetry was Bachelard’s preferred literary genre, phenomenology was his preferred philosophical one. Interestingly Rabbinic Judaism describes seven names for God that are so holy that once they have been written they should not be erased. See Gorringe (1996) for a discussion of the influence of Greek philosophical thought on the Christian theology of atonement and how this links to the criminal justice system. Further the publication of his unfinished works (Nachlass) reveals his contempt for emancipatory movements in 19th-​century Europe, and his disdain for women, slave workers and the ‘sick and corrupt’ (see Ruehl, 2018). Kant considers God to be the unconditioned principle that is necessary for the moral life to exist through practical reason. His thinking contains both a concept of natural law and social contract as a consequence of that law. Natural law as an expression of divine law had been articulated by the medieval scholastics in Christianity, Islam and Judaism, but Kantian thought forms the basis for a philosophical rather than theological interpretation. A notable exception was in the poetry of Gerard Manley Hopkins. At the time of writing we are in the midst of the COVID-​19 pandemic from which economic hardship will follow. The scapegoating process has already started with President Donald Trump seeking to deflect attention from his own deficiencies in addressing the virus by blaming the World Health Organization for being pro Chinese and therefore seeking to withdraw their funding. The figures that follow are from the Prison Reform Trust (2019). I am indebted to Bacon and Seddon (2020) for highlighting this work. My own experiences of setting up a residential detox program for people to come off methadone demonstrated to me just how difficult this process was for service users physically, psychologically and socially.

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This also links to Bergson’s concept of la durée as an expression of time and consciousness.

References Augé, M. (1995). Non-​places: An Introduction to Supermodernity. London, UK: Verso. Ayiter, E. (2019). Spatial poetics, place, non-​place and storyworlds: Intimate spaces for metaverse avatars. Technoetic Arts: A Journal of Speculative Research 17 (1&2): 155–​69. Bachelard, G. (1969). The Poetics of Reverie: Childhood, Language and Cosmos. Boston, MA: Beacon Press. Bacon, M. & Seddon, T. (2020). Controlling drug users: Forms of power and behavioural regulation in drug treatment services. British Journal of Criminology 60: 403–​21. Badiou, A. (2003). Saint Paul: The Foundation of Universalism. Stanford, CA: Stanford University Press. Bernstein, R. (1969). Praxis and Action. Philadelphia, PA: University of Pennsylvania Press. Bourgois, P. (2000). Disciplining addictions: The bio-​politics of methadone and heroin in the United States. Culture, Medicine and Psychiatry 24: 165–​95. Camus, A. (2000). The Rebel. London, UK: Penguin Books. Cotkin, G. (2005). Existential America. Baltimore, MD: Johns Hopkins University Press. Danisch, R. (2013). Risk assessment as rhetorical practice: The ironic mathematics behind terrorism, banking, and public policy. Public Understanding of Science 22 (2): 236–​519. DeValve, M. (2015). A Different Justice: Love and the Future of Criminal Justice. Durham, NC: Carolina Academic Press. Dupuy, J.P. (2013). The Mark of the Sacred. Stanford, CA: Stanford University Press. Foucault, M. (1977). Discipline and Punish. London, UK: Penguin Books. Galbraith, K. (1992). The Culture of Contentment. New York, NY: Sinclair-​Stevenson Ltd. Girard, R. (1978). Thing Hidden since the Foundation of the World. Paris, FR: Grasset and Fasquelle. Gorringe, T. (1996). God’s Just Vengeance. Cambridge, UK: Cambridge University Press. Gorringe, T. (2002). The prisoner as scapegoat: Some sceptical remarks on present penal policy. Journal of Offender Rehabilitation 35 (3/​4): 243–​51.

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Marquis de Sade (1966). The One Hundred and Twenty Days of Sodom. London, UK: Arrow Books. Miller, J. (1994). The Passion of Michel Foucault. London, UK: Flamingo Books. Millie, A. (ed.) (2021). Public Theology and Criminology: On Mercy, Hope and Restoration. Bristol, UK: Bristol University Press. Milovanovic, D. (2019). Postmodern Criminology. London, UK: Routledge. Ministry of Justice (2016). Health and Justice Annual Review 2015/​16 [online] Available at: https://​www.gov.uk/g​ overnment/p​ ublications/​ prison-​health-​health-​and-​justice-​annual-​report. Mitchell, A. & Trawny, P. (eds.) (2017). Heidegger’s Black Notebooks: Responses to Anti-​Semitism. New York, NY: Columbia University Press. Nietzsche, F. (2003). Twilight of the Idols and the Anti-​Christ. London, UK: Penguin Books. Nuechterlein, P. (2002). Rene Girard: The Anthropology of the Cross as Alternative to Post-​Modern Literary Criticism [online] Available at: Girardianlectionary.net. Office for National Statistics (2019). Deaths Related to Drug Poisoning in England and Wales: 2018 Registrations. London: Office for National Statistics. Parmer, W.J. (2017). Nietzsche and the art of cruelty. The Journal of Nietzsche Studies 48 (3): 402–​29. Pellauer, D. & Dauenhauer, B. (2016). Paul Ricoeur. In Stanford Encyclopedia of Philosophy [online] Available at: https://​plato.stanford. edu/​entries/​r icoeur/​. Pilgrim, D. (2009). Key Concepts in Mental Health. London: Sage. Porter, J. (2005). Nature as Reason: A Thomistic Theory of the Natural Law. Grand Rapids: Eerdmans. Pycroft, A. (2010). Understanding and Working with Substance Misusers. London, UK: Sage. Pycroft, A. (ed.) (2015). Key Concepts in Substance Misuse. London: Sage. Pycroft, A. (2018). Consciousness in rather than of: Advancing modest claims for the development of phenomenologically informed approaches to complexity theory in criminology. Journal of Theoretical and Philosophical Criminology 10: 1–​20. Pycroft, A. (2019). From a trained incapacity to professional resistance in criminal justice In A. Pycroft & D. Gough (eds.) Multi-​agency Working in Criminal Justice: Theory, Policy and Practice. Bristol: Policy Press (pp. 25–​40).

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Pycroft, A. (2020). Between Athens and Jerusalem in peacemaking criminology: The importance of weak and marginal positions. Journal of Theoretical and Philosophical Criminology 12: 188–​99. Pycroft, A. & Gough, D. (2010). (eds.) Multi-​agency Working in Criminal Justice: Care and Control in Contemporary Correctional Practice. Bristol, UK: Policy Press. Pycroft, A. & Green, A. (2016). Challenging the cultural determinants of dual diagnosis in the criminal justice system. In Winstone, J. (ed.) Mental Health, Crime and Criminal Justice: Responses and Reforms. London, UK: Palgrave Macmillan (pp. 147–​66). Pycroft, A. & Bartollas, C. (2018). Forgiveness as potentiality in criminal justice. Critical Criminology 26: 233–​49. Pycroft, A. & Bartollas, C. (forthcoming 2022). Redemptive Criminology. Bristol, UK: Bristol University Press. Quinney, R. (1991). The way of peace: On crime, suffering and service. In H. Pepinsky & R. Quinney (eds.) Criminology as Peacemaking. Bloomington, IN: Indiana University Press (pp. 3–​13). Roberts, G. & Wolfson, P. (2004). The rediscovery of recovery: Open to all. Advances in Psychiatric Treatment 10 (1): 37–​48. Rohlf, M. (2016). Immanuel Kant. In Stanford Encyclopaedia of Philosophy [online] Available at https://​plato.stanford.edu/​entries/​ kant/​. Ruehl, M. (2018). In defence of slavery: Nietzsche’s dangerous thinking. The Independent 2 January. Schrijvers, J. (2010). Marion, Levinasa and Heidegger on the question concerning ontotheology. Continental Philosophical Review 43: 207–​39. Scruton, R. (2003). A Short History of Modern Philosophy. London, UK. Routledge Shea, T. (2015). Harm reduction In A. Pycroft (ed.) Key Concepts in Substance Misuse. London, UK: Sage (pp. 92–​100). Sieh, E. (1989). Less eligibility: The upper limits of penal policy. Criminal Justice Policy Review 3: 159–​83. Simon, J. (2007). Governing Through Crime: How the War on Crime Transformed American Democracy and Created a Culture of Fear. Oxford, UK: Oxford University Press. Strachey, J. (ed.) (2001) The Standard Edition of the Complete Psychological Works of Sigmund Freud Volume XVI (1916–1917): Introductory Lectures on Psycho-Analysis (Part 111). London, UK: Vintage.

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8

The Politics of Actuarial Justice and Risk Assessment Andrew Day and Armon Tamatea

Introduction There is probably more than a grain of truth in Van de Steene and Knight’s (2017) observation that ‘the inevitability of digital transformation is set to shape the way justice is done and experienced’ (p. 256). New technologies are being introduced into criminal justice systems across Europe, Australasia and North America at a rate that has been described as astonishing, with Morris and Graham (2019) noting that the range of available services and programs now includes electronic monitoring, apps for mobiles and other digital devices, kiosks, in-​cell technologies, digital storytelling, virtual reality, video conferencing, social media, and websites and online portals. Increasingly these new technologies are being used to supplement, augment and, at times, even replace other modes of service delivery. In Aotearoa/​New Zealand, for instance, many major public services now use algorithms as part of core operations that range from identifying fraud, passport facial recognition, anticipated tax refunds, resolving fines and even tracking clients who require additional assistance for their recovery from physical or psychological injury to re-​enter the workforce (Stats NZ, 2018). Generally, it seems that correctional practitioners, prisoners and offenders have reacted positively to these new ways of ‘doing business’, with Morris and Graham (2019) suggesting that those who fail to embrace the new digital technologies can be categorized as falling within one of two camps: those who feel dystopia, or who associate

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technology ‘with surveillance, dehumanised and distant practices set in Orwellian visions of the future’, and those who feel retrotopia, or who have ‘a retrospective nostalgic yearning for (perceivably) less complicated and more human, benevolent rehabilitative practices past’ (p. 4). Proponents of technological innovation point to the improvement in efficiency, reliability and accuracy that automation can bring, as well as more fundamentally, arguing that the adoption of the scientific methodology will inevitably lead to better professional decision-​making (see Ross, 2018). The focus of this chapter is on the specific application of technology to those risk assessments used by correctional services in the Western world. Olver and Wong (2019) have recently observed that risk assessments are now routinely used to inform a wide range of criminal justice decision-​making processes, including those relating to bail and remand, sentencing and preventative detention. While correctional practice has tended to rely on the face-​to-​face administration, scoring and interpretation of assessments, algorithmic tools that are scored electronically—​without the personal involvement of either the person being assessed or the criminal justice professional—​are increasingly being introduced. As with other technological innovations, it has been suggested that actuarial and automated algorithmic approaches hold considerable promise in so far as they allow for more accurate, consistent, cost-​effective and timely decision-​making in ways that also diminish the possibility of improper motivations or bad faith of assessors, resulting in decisions that lack validity (Hogan-​Doran, 2017). However, in this chapter we argue that the introduction of this form of digital justice in the correctional setting is neither morally or politically neutral, nor can it necessarily be assumed to be ethical. Specifically, we draw attention to the possibility that the increased application of technology to risk assessment in correctional settings may disproportionately and adversely impact upon those from cultural minority groups such as Indigenous offenders from Australia and Aotearoa/​New Zealand. We suggest that this specific application of digital technology is inevitably associated with an increased danger of providing services that reflect narrow cultural interests and that may not be in the best interests of all sections of the correctional population, with those from Indigenous and other minority communities—​many of whom are disproportionately present in criminal justice systems around the Western world—​particularly disadvantaged. This in turn, raises questions about the political context in which risk assessment occurs, which go beyond the pragmatism and economic justifications that have underpinned their introduction. We start, however, by

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providing a brief overview of what have been termed ‘digital justice’ approaches to risk assessment in correctional settings.

Correctional risk assessment It is important to note that, in a correctional context, the term ‘risk’ is typically used in an actuarial sense to refer to the probability of a future event occurring, specifically reoffending (or some proxy measure such as ‘return to correctional services’). Over 20 years now, Bonta (1996) differentiated unstructured clinical judgments about risk that rely solely on the subjective integration of data from actuarial risk assessments that aggregate variables selected solely on the basis of their correlation with reoffending to determine an overall categorization. Bonta, and a number of his colleagues from correctional services in Canada, have argued strongly that actuarial approaches are more reliable and more accurate in predicting future offending in known offenders and, as such, should be routinely employed to guide sentence management and rehabilitation programming. The associated idea that services and interventions should be commensurate with the assessed level of risk (colloquially known as ‘the risk principle’) was one that quickly attracted the attention of both correctional managers and policy makers around the Western world, as evidence accumulated that risk-​ matched interventions have the largest impact on reoffending rates, as well as some studies showing that intervening with low-​r isk prisoners and offenders actually increased risk despite the best intentions of service providers (e.g. Lowenkamp & Latessa, 2004). These days most jurisdictions base service delivery on some form of front-​end assessment of actuarial risk, with more than 300 different risk assessment tools of this type currently available (Singh et al, 2014); many of which are heavily marketed and sold commercially. An actuarial risk assessment adopts a nomothetic approach whereby estimates of future offending are provided within a given time frame, contingent on base rates (see Tully, Chou & Browne, 2013). This involves the use of an explicit coding scheme in which those factors shown to be empirically related to the prediction of recidivism are scored as either ‘present’ or ‘absent’. Total scores are then summed and converted (via experience tables) to probabilistic estimates of recidivism occurring, which are then transformed to categorical risk groups (e.g. ‘low’, ‘medium’, ‘high’), which are linked to the relative frequency of the event over specified follow-​up periods (see Hanson & Morton-​ Bourgon, 2009; Mossman, 2013). This actuarial approach is, in theory, subject to regular update with empirically-​based revisions and the

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expansion of normative samples in order to maintain the validity of the assessment (e.g. Harris & Hanson, 2010), although the statistical and psychometric evidence supporting the use of many current assessment tools remains limited (see Risk Management Authority, 2019). The actuarial approach to risk assessment is employed by correctional services around the Western world (but less so in other parts of the world, see Morgan & Morgan, 2018) to predict general offending, as well as for specific populations such as sexual and violent offenders. Assessment tools predominantly utilize static risk factors, such as age at first conviction, victim characteristics (e.g. male, unrelated, stranger), developmental factors (e.g. juvenile offender), offense history (e.g. prior sexual and criminal offenses, history of violence, non-​contact offenses), along with some clinical factors (e.g. evidence of psychopathy; see Craig, Browne, Stringer & Beech, 2005) to determine the probability of further offending. Not all of the available instruments include every known predictor; nor, for that matter, are they always consistent in terms of which variables are included; however, validation studies have consistently reported the predictive validity of these measures across both samples and jurisdictions to be ‘adequate’, if not ‘good’ (see Tully et al, 2013). Thus, despite some of the tools (such as the Correctional Offender Management Profile for Alternative Sanctions; COMPAS) taking up to one hour to complete, the simplicity of the approach along with the ease of administration and scoring have served to maintain their popularity for over two decades (Singh, Grann & Fazel, 2011). It might be expected that further improvements to both the administration and the accuracy of actuarial risk assessment tools will occur with the introduction of new technology that allows automated administration and scoring. VanNostrand and Keebler (2009), for example, have described how this works in relation to assessing the risk of bail failure. They showed, for example, that a combination of nine weighted variables1 can be combined into an algorithm that is then used to automatically identify those defendants who are less likely to appear in court and/​or more likely to commit further offenses while on bail. In New Zealand/​Aotearoa, a risk of conviction and imprisonment algorithm (RoC*RoI) is now used across correctional services that only requires information from administrative files and is computer scored to classify all new prisoners and determine their eligibility for different services. On the surface then these might seem to be elegant and efficient approaches that lead to significant savings of professional resources and time allocated to offender assessment. However, a number of methodological and ethical problems with the

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use of actuarial risk assessment tools have been identified (e.g. Hart, Michie & Cooke, 2007; Cooke & Michie, 2010; Fazel, 2019) and, we suggest, the increased application of technology in this area may only serve to compound rather than ameliorate these. The most notable limitation of actuarial tools is a statistical problem associated with deviation from known base rates. As Mossman (2015) has pointed out, the assumption underpinning the development of these tools is that the normative data used to translate scores to probabilities of recidivism are constant across all subgroups of offenders—​even though research findings simply do not support this. For example, actuarial sex offender risk assessments typically fail to discriminate between extra-​familial child molesters who have consistently been found to have higher reoffense rates than incest offenders, and child molesters with male victims have consistently shown higher reoffense rates than child molesters with exclusively female victims (Harris & Hanson, 2010). This is not a particular issue when ranking individuals from different populations, but differences in probabilities associated with each score will inevitably result from different population base rates (see Mossman, 2000; Singh, 2013). In other words, questions arise about the validity of the approach as it applies to particular subgroups in the correctional population, especially when automation creates the circumstance in which within-​ group differences are not explicitly considered. Another potential problem is the unreliability of applying group-​ based risk evaluation to the assessment of risk in individual cases (e.g. Berlin, Galbreath, Geary & McGlone, 2003; Hart, Michie & Cooke, 2007). For example, a sex offender scoring 6 on the Static-​99 (one of the most widely used actuarial tools) would be considered to belong to the ‘high-​risk’ category, with 52 per cent of the original sample known to reoffend over the 15-​year follow-​up. What the instrument cannot specify, however, is whether the ‘high’ risk offender being assessed belongs to the 52 per cent who sexually reoffended or to the 48 percent who did not (Berlin et al, 2003). Consequently, an individual score on an actuarial tool is not considered to be a particularly reliable guide to the specific risk of reoffending, simply because actuarial methods are designed to assign levels of risk to groups rather than to individuals (Mullen & Ogloff, 2012). Thus, there is a need to interpret the extent to which actuarial data applies to a particular person or set of circumstances, which again, is less likely when the assessment is automatically scored. Other potential problems with the actuarial approach arise from the emergence of risk assessment tools from a largely atheoretical approach

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where scale construction is based solely on correlations with recidivism (Craig & Beech, 2010; Rossegger, Gerth, Seewald, Urbaniok, Singh & Endrass, 2013). In addition, and in response to the need to assess offenders in ways that explicitly inform risk management efforts (rather than simply classify offenders), structured professional judgment (SPJ) risk assessment tools have now been developed that simply use total scores as an aide-​memoire to guide an overall risk judgment (e.g. ‘low’, ‘moderate’, or ‘high’) with case-​specific information about the person being evaluated also included (see Rettenberger, Boer & Eher, 2011). Although Doyle et al (2011) have argued that these two approaches are valid and complementary, as actuarial assessments can be used to ‘anchor’ the risk assessment with the professional judgment method incorporating dynamic and idiographic risk information to inform risk management, the use of automation inevitably reduces the opportunity to incorporate contextual information into any final judgment of risk. It is, for example, considered much too difficult to ascertain an estimate of recidivism risk based on a careful analysis of a particular individual’s relevant characteristics when there are no opportunities for direct examination (Mullen & Ogloff, 2012). Of particular interest to those who live and work in post-​colonial societies is the understanding that offending behavior occurs in a cultural context. Yet, the offender risk assessment literature has been largely silent on the issue of culture. Culture, in contrast to ‘race’ and ‘ethnicity’,2 is a less exact term that reflects the interaction between the social world and people’s ideas about it (López & Guarnaccia, 2000) and is something that is learned and shared among a group of people. It includes intangible ideas by which an individual interprets his or her environment and events, recognizes and decides what is valued and ideal and which activities should be pursued or avoided (Evans, 2005), as well as determining problem definition and problem solving (Kleinman, 1988). In this regard, culture is best appreciated in a context of relationships to be recognized rather than as a ‘thing’ to be reified and measured. Reoffending, then, is likely to be better understood in ways that can guide the most effective correctional responses when the cultural context in which it occurs is considered. Clearly actuarial and algorithmic measures have not been designed for this purpose.

The ethics and politics of risk assessment Notwithstanding the statistical limitations of current risk assessment tools (see Fazel, 2019 for a fuller discussion of these), concerns have also

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been expressed about their political use and, in particular, the extent to which associated ethical concerns arise in relation to the use of risk classifications and labels. These concerns relate primarily to the question of who decides how these are defined, with Monahan and Steadman (1996) asking a series of questions, over 20 years ago now, about who actually determines the number of risk categories and category labels that are used, as well as the prescriptions for information-​gathering and risk management that accompany each category: In light of legitimate concerns … that categorical risk assessment conflates scientific questions (i.e. probability estimates) with questions of social values (i.e. the choice of cut-​off scores distinguishing categories), we believe that it is essential that the ultimate users of risk communications about violence (e.g. judges and other policymakers) be centrally involved from the beginning in developing any categorical risk communication scheme. (p. 935) Their primary concern here relates to the lack of involvement of any ‘stakeholder’ or ‘end user’ in the use of actuarial risk assessments, although we would suggest that stakeholders extend beyond the judges and other policy makers referred to in the earlier quote to include those who are being assessed and the families and communities from which they come, and will return. To put this another way, there is a range of people who can offer a level of insight into why or how a particular individual might be at risk or, indeed, the available options for eliminating or moderating risk that is simply unavailable from actuarial data. This, of course, is even less possible when risk assessments are scored automatically and electronically, when there is no scope to apply professional judgment or override statistically derived classifications. An additional concern relates to the issue of consent. Face-​to-​ face assessment inevitably requires that client consent is sought, based on full knowledge regarding the nature of the assessment, the purposes to which it may be used, and any limitations with respect to confidentiality. Not only does risk assessment based on file data and algorithmic scores obviate the need to obtain consent, but Rudin and Ustin (2018) have also noted that those who are being assessed are not allowed the opportunity to inspect and critique the algorithms or underlying data. Thus, it can be argued that automation leads to a lack of transparency and accountability in ways that can have severe consequences for those being assessed. To illustrate this, Rudin and Ustin refer to a 2015 case in California (People v. Chubbs) in which

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a man was imprisoned on the basis of a risk assessment derived from software developed by a private company. The company refused to reveal how the software worked, arguing that this information was commercial in confidence, with the appeals court ruling in their favor. One of the most contested aspects of actuarial assessments is the assumption that criminal history data offers a reliable and culturally neutral measure of underlying criminal activity. A recent statement, signed by a group of 27 prominent researchers from MIT, Harvard, Princeton, NYU, UC Berkeley and Columbia, argues that this is simply not the case. They point to evidence from the US that communities of color have been arrested at higher rates than their White counterparts, even for crimes that both groups engage in at comparable rates (Barabas et al, 2019). Similarly, these researchers argue that, compared to similarly situated White people, African Americans are more likely to be convicted and more likely to be sentenced to prison in the US. Their conclusion is that risk assessments that utilize this ‘distorted’ data will produce distorted results and that ‘there are no technical fixes for these distortions’ (p. 4). There is certainly evidence that actuarial risk prediction is more accurate for ‘White’ offenders than for those from various ethnic minority/​Indigenous groups (Singh et al, 2011), with Konikoff and Owusa-​Bempas (2019) pointing to studies that have shown, for both the LSI-​R and COMPAS risk assessment tools, that ‘Black’ offenders are more likely to be ‘overclassified’ (i.e. predicted to be rearrested when they actually were not) than those who were classified as either ‘White’ or ‘Hispanic’. They argue that this gives the court ‘permission’ to treat ‘Black’ offenders more harshly than others. Similar issues have been identified in studies conducted in other countries where actuarial risk assessments are routinely used (e.g. Hart, 2016). In Australia, for example, Fitzgerald and Graham (2016) have used administrative data to identify those factors that were associated with new incidents of domestic violence in known perpetrators. They then developed a statistical model that predicted future offending with reasonable accuracy, before concluding that their model was racially biased; Indigenous3 individuals were more than twice as likely to be predicted as reoffenders (29.4 per cent) compared to the observed rate (13.7 per cent), whereas non-​Indigenous individuals were less than half as likely to be predicted as reoffenders (2.3 per cent) compared to the observed rate (6.1 per cent). For McNamara et al (2018) these studies highlight a basic issue of fairness in algorithmic decision-​making, especially as computerized risk assessment tools become more widely used. In their view, fairness should involve parity (i.e. predictions should be similar for different

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groups), independence (i.e. predictions should be independent of group membership) and causality (i.e. predictions should not be caused by group membership). This resonates with Fazel’s (2019) view that risk assessment tools should be able to discriminate (i.e. distinguish between those who have offended and those who have not by assigning a higher risk score or category to those who offend, and be tested by reporting sensitivity, specificity, positive predictive value and negative predictive value) and calibrate (i.e. demonstrate how the tool’s predicted risk matches the observed risk). Importantly, Fazel notes that calibration data is almost never reported, with validation studies only typically reporting the ability to discriminate. In other words, issues of fairness are not considered as researchers rely on reporting accurate statistics. A more fundamental consideration is the way in which current risk assessment approaches can impose limits on the purpose, scope and form of practice. As a set of procedures that ultimately derive from a quasi-​medical perspective (i.e. ‘risk factors’ for violence as akin to risk factors for diabetes or heart disease), the current paradigm for actuarial risk assessment clearly reflects a cultural practice that has its roots in Western empirical traditions and that are shaped by varying definitions and conceptual thresholds of behavior. For instance, sexual offenses are defined in legislation and subsequently are linked with controlled vocabularies and classification schemes that impose a special interpretive system that frames discussions about risk (e.g. ‘high-​r isk’, ‘dangerous’, ‘sexual predator’, ‘public protection’) in ways that rely on a detached language of risk that is not particularly accessible to a relatively unsophisticated public who stand to benefit from this knowledge or, indeed, be sufficiently informed to respond to its limitations (Tamatea & Boer, 2016). Reducing complexity is clearly a central function of algorithmic and actuarial tools, with the in-​built coding rules allowing for a systematic approach that holds promise for more ‘elegant’ approaches to practice that are amenable to standardization and reliable comparisons over time and across populations. However, the inclusion of items is based on statistical (i.e. correlative) models, and the behaviors themselves are informed by legally defined categories of behavior and do not reflect naturalistic accounts of human activity. In addition, actuarial risk assessment tools assume an atomistic understanding of persons that places primacy on individual agency or on individuals as a totality in themselves. However, such a view artificially extracts an individual from his or her relationships, essentially decontextualizing people from their communities and culture. The role of psychologists and allied practitioners then becomes impacted by limits that are imposed (e.g. by legislative requirements, government policy, etc.) on the manner in

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which they can define a complex and multifaceted problem, inevitably resulting in overly simplistic categorizations and conclusions. In this way, reality is over-​simplified, and the likelihood of statistical error is increased. The consequences of such influences on risk assessment research and practice include the privileging of certain knowledges, valuing predetermined outcomes and prioritizing practices. Practitioners who administer risk assessments are, for example, forced to reduce and define complex and multifaceted problems in a simplistic manner, with legislation influencing their knowledge, practice and outcomes in the following ways (Tamatea & Boer, 2016).

Privileging scientific knowledge over Indigenous knowledge For instance, Western empirical approaches are more likely to be valued as evidenced by State-​sponsored research and development than are other ‘exotic’ ideas that are not derived from an empirical basis. This bias against the development of Indigenous or minority-​led research may reflect what Sue (1999) has referred to as the selective reinforcement of scientific principles and can be reflected in poor research opportunities for Indigenous-​led research or lack of an unambiguous outcome with non-​dominant research methodologies. Furthermore, Mittelstadt et al (2016) argue that appeals to so-​called objectivity are unrealistic because algorithmic measures simply reflect the intent and purposes of the original designers. The method assumes an atheoretical, objective (and presumably impersonal and culture-​ neutral) basis that relies on ‘factual’ information (such as that derived from official criminal records) rather than data derived from more subjective approaches.

Prioritizing statistical accuracy over real world salience Actuarial tools are commonly regarded as essential to risk assessment ‘best practice’ and reflect Quinsey, Harris, Rice and Cormier’s (1998) conclusion that actuarial methods are ‘too good and clinical judgement too poor to risk contaminating the former with the latter’ (p. 171). Similarly, Lin, Jung, Goel and Skeem (2020) have reported that algorithms outperform human raters on risk estimate simulations, even when the available offender data were enriched. However, despite the reported predictive accuracy of some of these measures, it is noted that the data itself are decontextualized. Culture, on the other hand, is context-​specific and hence incongruent with pure actuarial approaches to accounting for behavioral outcomes.

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Valuing safety over healing The reduction of recidivism is a near-​universal outcome that is valued across jurisdictions. However, ‘improved well-​being’, although not unrelated or necessarily independent, is a goal typically sought by Indigenous communities that does not superimpose neatly onto current risk management frameworks. A reframe to a ‘healing’ focus speaks to relational accountability (Kirkness & Barnhardt, 1991) in ways that privilege meaningful and non-​exploitative knowledge-​sharing engagements with a given community and pave the way for the co-​ design of mutually acceptable outcomes. In summary, the prioritization of predictive validity and universality of automated actuarial risk assessment tools offer the benefits of conceptual simplicity, statistical ‘accuracy’ and economy of use but also relies on a disaggregated schema of persons who exist in decontextualized spaces in a detached way. Actuarial approaches of this type are also too imprecise to be used for any given individual and demonstrate substantial variations in predictive accuracy. A more culturally responsive approach would permit of relevance to the person in a context-​friendly and ‘meaningful’ way but also introduce complex relationships and fuzzy concepts that are difficult to elucidate and validate in a scientifically meaningful way. In Indigenous communities where holistic and relational knowledge can offer richer and nuanced explanations of the behavior, the factorial lens is at variance with the complexities of community life. This is where we turn to next.

Understanding risk from an indigenous perspective In our work, which has largely focused on understanding the ways in which correctional services respond to the needs of Indigenous peoples in prison in both Australia and Aotearoa/​New Zealand, we have sought to articulate the potential benefits of understanding risk from the perspective of people in their social and relationship contexts. It is important to note here that the very term ‘Indigenous’ is ambiguous and not widely agreed upon and so, for the sake of convenience, we refer respectfully to Indigenous peoples as those who are typically a non-​dominant group that has an acknowledged claim to be the original inhabitants of a given land. Our focus here is on the Aboriginal and Torres Strait Island peoples of Australia and the various iwi4 that comprise the Maori of Aotearoa/​New Zealand. Elsewhere (e.g. Tamatea, 2016; Day, Tamatea & Geia, 2018), we have proposed that the starting point for any understanding of reoffending

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risk in a post-​colonial context is to view offenders as embodying their culture by actively making choices and creating meaning in their lives, within inevitable bodily, material, social and ideological constraints. This approach recognizes that emotional distress and troubled or troubling behaviors are intelligible responses to a person’s history and circumstances and, by doing so, increases the possibility for change by acknowledging the link between distress and social injustice, as well as increasing access to power and resources and promoting social action and psychological change. We have drawn on the work of Gillies (2013), who critiques the use of approaches developed for dominant culture members either whose connection to cultural institutions is implicitly understood (or who are now separated from their pre-​ existing cultural institutions by migration), as well as arguing that there is a fundamental problem with privileging propositional knowledge, which is formal, explicit and concerned with generalizability, rather than focusing on the importance of prudential values that define cultural experience. We have suggested then, that rather than rely solely on actuarial data it is also important to collect and legitimate non-​propositional knowledge that is informal, implicit and derived primarily through experience. As Gillies describes it, the adoption of a culturally neutral position inadvertently continues a colonization dynamic whereby this type of culturally relevant data is suppressed during any assessment (in the name of science), labeling this either as institutional racism, or ‘unintentional racism resulting from inadequate resource development and practitioners having no alternatives but to adopt an assimilationist stance’ (p. 15). In essence then, the popularity of risk assessment instruments across international jurisdictions reflects the value that such tools have in facilitating offender management solutions. Instruments such as the Static-​99 have enjoyed routine use beyond their country of development and have surfaced in distant countries such as Australia and Aotearoa/​New Zealand where only limited validation data are available. Although a measure may demonstrate an acceptable level of validity during construction, it does not necessarily follow that it will also be valid in these countries. Accordingly, practitioners are cautioned about the wholesale adoption of risk assessment tools that are used in jurisdictions and with cultural groups where these measures were not developed.

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Some observations and an invitation Our discussion of risk assessment as a key example of emerging approaches to digital justice has, thus far, focused on the technological accuracy of offender management practice as well as reflecting on how this has increased the disconnection that exists with Indigenous cultural perspectives about crime and criminal justice. A much broader issue here, however, extends beyond concerns about both the practicality and validity of algorithmic risk assessment to more fundamental concerns about how difference and identity are understood in an increasingly interconnected global society. Brown (2018) has recently described this in terms of an understanding of crime and society that is coded to the histories, cultures and societies of the criminology of what he refers to as the ‘global North’ (Europe and North America). Brown suggests that in the US, for example, readers are generally encouraged to think about cultures in essentialist terms, in the ethnographic present; ‘to see colonialism and nationalism as cultural phenomena and to distance academic work from partisan politics’ (p. 101). For Brown this separation typically serves to strengthen academic credibility, whereas in post-​colonial countries he suggests that scholars are more likely to embrace politics in one form or another as a professional responsibility of citizenship. Brown’s argument here is that there is a place for thinking beyond the simple application of ‘Northern’ cultural models of criminal justice using comparative methodologies. This resonates strongly with our review of risk assessment practices in this chapter, as does his suggestion that there is a place for thinking differently about the structure of criminology’s Enlightenment-​derived thinking to fundamentally change the whole discipline and articulate what he refers to as the ‘conditions of possibility’ for an alternative vision of crime and society. The key point here is that colonial administrators typically frame their thinking about crime, and by extension the concept of ‘risk’, to reflect the unique historical, cultural, religious, social, economic and environmental conditions from which it emerges. In order to understand the politics of risk assessment there is a need to do more than simply add observations from countries populated by Indigenous groups to test or revise existing theory but also to think through possibilities for knowledge, ways of being and knowing that do not rely or constantly fall back upon Western cognitive structures. For Connell (2007) this involves viewing cultural knowledge as a source of theory, rather than a source of data; and yet it is one thing to challenge the risk paradigm from a cultural position (and, as we have done, lament some of the limitations and perhaps harmful implications

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of the approach to post-​colonial prison populations) and another to think about how the concept of risk and broader systems of crime and justice might be imagined differently. It is also the case that many of those involved in the industry of risk assessment would want to identify with these ideas and would have neither the interest nor inclination to rework radically what correctional practice currently looks like. As Brown (2018) also points out, we need to recognize that while we may talk of Southern criminology as if it had some essence, it can and will be different things to different people. Ultimately, these are epistemological questions that have potentially far-​reaching implications for professional practice. It is apparent to us, for example, that approaches to understanding risk that draw on Western scientific (positivist) approaches are more likely to be viewed as legitimate than alternative ‘exotic’ ideas that are not derived from an empirical basis. The introduction of technology, such as in the use of computer-​scored algorithms, further positions the knowledge that results from risk assessments as both scientific and legitimate. It might also be argued that this structural bias against the development of indigenous (or minority-​led) research reflects the selective reinforcement of scientific principles and is reflected in poor research opportunities for Indigenous-​led research or the lack of any unambiguous outcomes from non-​dominant research methodologies (Sue, 1999). Indeed, the development of risk assessment measures has always been the privilege of the test designers (who, in some cases, may also be service providers with an inherent belief in the ‘nobility’ of the assessment process) rather than of those end users who ‘consume’ the outcomes. This includes decision-​makers (e.g. parole boards), persons with criminal convictions and the broader community—​most of whom are likely to be generally unlearned in the specialized area of test design, construction and interpretation. Consequently, actuarial risk measures can be considered to be ‘practitioner-​oriented’ as they are administered, scored and interpreted by practitioners and not by the individual who is the subject of the assessment. It might similarly be argued that a ‘top-​down’ approach to assessing risk promotes a mythic ideal, where a belief exists in a single ‘best’ and ‘right’ way of doing things. Such an ideal is often couched in terms of being correctional ‘best practice’. However, this serves to simply reinforce a perception that there is only one way that risk assessment can be practiced and dismisses alternative viewpoints. Finally, the purpose of risk assessment (i.e. to support practices that lead to a reduction in recidivism) is a near-​ universal outcome that is valued by correctional agencies, but which neglects other outcomes such as improved well-​being, which are also

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sought by Indigenous communities. For us this is exemplified in the area of risk assessment technology where the task has been typically conceptualized in terms of collecting more specific predictive validity data about recidivism with cultural cohorts (e.g. Shepherd, 2015). However, the 2007 UN Declaration on the Rights of Indigenous Peoples, which secures the collective and cultural rights of Indigenous groups clearly establishes that rights extend beyond those that inhere solely in the free individual and obligations to flow solely out of the contracts that such individuals make (i.e. the notion of ‘the social contract’; see Brown, 2018). Through this discussion we invite readers to consider questions of ‘who we are’ and ‘what we are becoming’ in an era in which actuarial justice and computational risk assessment have come to inform choice and dictate action. Should we, for example, view those who become engaged with the justice system as what Ward and Stewart (2003) famously described as ‘disembodied bearers of risk’ who should be classified and managed according to algorithms that determine their future. Or are there opportunities to view them as members of families and communities in ways that contextualize risk as something that is culturally determined and requires a more socially focused response? And what are the implications, not only for those who are the subject of a risk assessment but also those who conduct the assessments, are custodians of the data, and who are responsible for decision–​making? Questions such as these quickly lead us into a broader discussion about the purpose and value of contemporary prisons and the role that prisons serve for the wider community. Currently, prisons remain what Goffman (1961) called total institutions, or ‘24-​hour settings where residents have no control over egress and are infantilized by the fact that they must depend on the staff for almost everything that is vital to their existence, including food, clothing, shelter, and contact with the outside’ (Wener, 2012, p. 5), and where many prisoners remain in crowded or isolated conditions, with little movement for days, weeks, months and years. Although there is no reason to think that the end of imprisonment is as imminent as some might hope, these remain important questions for all of those who are interested in correctional practice.

Conclusion In drawing together some of the themes from this chapter, we return to the work of Bonta (1996) who argued that useful and effective risk assessment measures are quantitative, structured and empirically-​linked

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to a relevant criterion as expressed by discrete events such as recidivism or parole failure. In short, the benefits of quantitative methodologies serve to: (1) reduce the complexity of data and increase empirical rigor; (2) demand structured protocols that reduce human error (and presumably bias) by means of strict scoring rules and systematic data collection strategies; and (3) rely on specific criteria that reduce the range and type of outcomes of concern. Together, these aspects of instrument development reflect an increased focus on risk management as defined by specified results and also occlude related—​ but competing—​interests that concern Indigenous communities such as improving well-​being or eliciting offender redemption narratives. Actuarial tools are used to privilege large data and apparent ‘facts’, or uncritically received information that is uninformed by knowledge and that results from regional inequities. In this sense, expert knowledge (‘top-​down’) takes precedence over local knowledge (‘bottom up’) as valuable or ‘expert’ in its own right. Risk assessments of this type might be considered to be somewhat anti-​democratic in that they are devised as a result of differential access to data and technology (hardware, software, ‘humanware’ and data) that communities typically have no ownership of. Public dialogue about the ethical and responsible uses of these tools is also limited—​especially in relation to sentencing and sentence-​related decisions that are made on the basis of these assessments. In our view, there is a need for a forum where issues, information, alternative perspectives and decisions can be discussed in an open dialogue with a relevant public. One way ahead might involve revisiting risk assessment tool design principles and actively consulting with community experts, especially those who hold knowledge of another worldview (this would also mean an acceptance of complexity) and co-​design measures with all relevant stakeholders. Combining factorial, systemic/​relational and narrative data might provide a more holistic and ultimately more accurate ‘picture’ legitimate of risk. In its own way, this chapter speaks of broader questions of personhood in the light of the ‘technocratization’ of social problems, and at what point there is a trade off between pragmatism, efficiency (expediency?) and what is justifiable (or even just?). Actuarial tools have become the sine qua non of risk assessment practice, despite the data itself being inevitably decontextualized—​revealing some important ‘trees’ but no ‘forest’. Culture, on the other hand, is incongruent with pure actuarial approaches because culture is meaningless in the absence of context. Our central suggestion then is that actuarial risk assessment approaches are not only culturally bound but also deliberately and conspicuously ignorant of the social context in which risk emerges.

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And in this chapter, we have suggested that these deficiencies will become even more apparent as automation increases through the application of digital justice approaches. The solution, however, is not likely to be particularly palatable for correctional administrations, as it requires considering the centrality of family, acculturation strain, religiosity, gender role expectation and other factors when assessing risk and identifying appropriate mitigation strategies. This can, of course, only occur when there is a strong understanding of the communities from which offenders come (and will inevitably return) and when judgments of risk involve authentic consultations with those who fully understand these issues. We hope that our cautiousness about the use of digital justice in correctional risk assessment reflects neither dystopia nor retrotopia. Indeed, we would argue that we should embrace technological advances that can help corrections professionals to deliver better quality services. However, it is by no means clear to us that pursuing an automated, algorithmic approach to risk assessment will achieve this, and that alternative approaches are needed if minority cultural groups are to be treated fairly. Notes 1

2

3

4

The nine predictors are: (1) whether there were other charges pending against the defendant at the time of the arrest; (2) the number of prior misdemeanour arrests, (3) the number of prior felony arrests; (4) the number of prior failures to appear; (5) whether the defendant was unemployed at the time of the arrest; (6) the defendant’s residency status; (7) whether the defendant suffered from substance abuse problems; (8) the nature of the primary charge; and (9) whether the primary charge was a misdemeanour or a felony (VanNostrand & Keebler, 2009). For the purposes of this chapter, race—​a somewhat outmoded term with socio-​ political dimensions—​represents an imposed classification based on phenotypy (e.g. genetically determined characteristics such as skin color), whereas ethnicity includes race in addition to a broader range of characteristics such as shared ancestry and history (e.g. African American, Chinese) (Atkinson, Morten & Sue, 1998). Both race and ethnicity are organizing principles and provide a convenient demarcation strategy to describe a sample. A term often used to describe those who self-​identify as from Aboriginal and/​or Torres Strait Islander cultural backgrounds, see what follows. Major Maori tribal groups in Aotearoa/​New Zealand.

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Berlin, F.S., Galbreath, N.W., Geary, B. & McGlone, G. (2003). The use of actuarials at civil commitment hearings to predict the likelihood of future sexual violence. Sexual Abuse: A Journal of Research and Treatment 15 (4): 377–​82. Bonta, J. (1996). Risk-​needs assessment and treatment. In A.T. Harland (ed.) Choosing Correctional Options that Work: Defining the Demand and Evaluating the Supply (pp. 18–​32). Sage Publications, Inc. Brown, M. (2018). Southern criminology in the post-​colony: More than a ‘derivative discourse’? In K. Carrington, R. Hogg, J. Scott & M. Sozzo (eds.) The Palgrave Handbook of Criminology and the Global South (pp. 83–​104). London, UK: Palgrave Macmillan. Connell, R. (2007). Southern Theory: The Global Dynamics of Knowledge in Social Science. Crows Nest, NSW: Allen and Unwin. Cooke, D.J. & Michie, C. (2010). Limitations of diagnostic precision and predictive utility in the individual case: A challenge for forensic practice. Law and Human Behavior 34 (4): 259–​74. Craig, L.A. & Beech, A.R. (2010). Towards a guide to best practice in conducting actuarial risk assessments with sex offenders. Aggression and Violent Behavior 15 (4): 248–​93. Craig, L.A., Browne, K.D., Stringer, I. & Beech, A. (2005). Sexual recidivism: A review of static, dynamic and actuarial predictors. Journal of Sexual Aggression 11 (1): DOI: 10.1080/​13552600410001667733 Day, A., Tamatea, A. & Geia, L (2018). Scientific inquiry and offender rehabilitation: The importance of epistemic and prudential values. Psychology, Crime and Law. DOI: 10.1080/​1068316X.2018.1543422 Doyle, D.J., Ogloff, J. & Thomas, S. (2011). Designated as dangerous: Characteristics of sex offenders subject to post-​sentence orders in Australia. Australian Psychologist 46 (1): 41–​8. Evans, I.M. (2005). Behavior therapy: Regulation by self, by others, and by the physical world. In C.R. O’Donnell & L.A. Yamauchi (eds.) Culture & Context in Human Behavior Change: Theory, Research, and Applications (pp. 13–39). New York, NY: Peter Lang Fazel, S. (2019). The Scientific Validity of Current Approaches to Violence and Criminal Risk Assessment [online] Available at: https://​www. researchgate.net/​publication/​333491817. Fitzgerald, R. & Graham, T. (2016). Assessing the Risk of Domestic Violence Recidivism. Crime and Justice Bulletin No. 189. Sydney: NSW. Gillies, C. (2013). Establishing the United Nations’ Declaration on the Rights of Indigenous Peoples as the minimum standard for all forensic practice with Australian Indigenous peoples. Australian Psychologist 48: 14–​27.

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Goffman, E. (1961). Asylums. New York, NY: Anchor. Hanson, R.K. & Morton-​Bourgon, K.E. (2009). The accuracy of recidivism risk assessments for sexual offenders: A meta-​analysis of 118 prediction studies. Psychological Assessment 21 : 1–​21. Harris, A.J.R. & Hanson, R.K. (2010). Clinical, actuarial and dynamic risk assessment of sexual offenders: Why do things keep changing? Journal of Sexual Aggression 16: 296–​310. Hart, S.D. (2016). Culture and violence risk assessment: The case of Ewert v. Canada. Journal of Threat Assessment and Management 3: 76–​96. Hart, S.D., Michie, C. & Cooke, D.J. (2007). Precision of actuarial risk assessment instruments: Evaluating the ‘margins of error’ of group v. individual predictions of violence. The British Journal of Psychiatry 190: s60–​s65. DOI:10.1192/​bjp.190.5.s60 Hogan-​Doran, D. (2017). Computer says ‘no’: Automation, algorithms and artificial intelligence in Government decision-​making. Journal of the Judicial Commission of New South Wales 13 (3): 345–​82. Kirkness, V.J. & Barnhardt, R. (1991). The Four R’s—​Respect, Relevance, Reciprocity, Responsibility. Journal of American Indian Education 30 (3): 1–​15. Kleinman, A. (1988). Rethinking Psychiatry: From Cultural Category to Personal Experience. New York, NY: Free Press. Konikoff, D. & Owusu-​Bempah, K. (2019). Big Data and Criminal Justice—​W hat Canadians Should Know. Toronto: Centre for Criminology and Sociolegal Studies University of Toronto. Lin, Z., Jung, J., Goel, S. & Skeem, J. (2020). The limits of human predictions of recidivism. Science Advances 6 (7): 1–​8. L ó p e z , S. R . & G u a r n a c c i a , P. J. J. ( 2 0 0 0 ) . C u l t u r a l psychopathology: Uncover ing the social world of mental illness. Annual Review of Psychology 51: 571–​98. Lowenkamp, C.T. & Latessa, E.J. (2004).Understanding the Risk Principle: How and why correctional interventions can harm low-​ risk offenders. Topics in Community Corrections [online] Available at: https://​www.correctiveservices.justice.nsw.gov.au/​Documents/​ Risk-​principal—​accessible-​442577.pdf. McNamara, T., Graham, E.B. & Cheng, S.O. (2018). Trade-​offs in algorithmic risk assessment: An Australian domestic violence case study. In A. Daly, M. Mann & S.K. Devitt (eds.) Good Data (Theory on Demand, 29) (pp. 96–​116). Institute of Network Cultures, The Netherlands. Mittelstadt, B., Allo, P., Taddeo, M., Wachter, S. & Floridi, L. (2016). The ethics of algorithms: Mapping the debate. Big Data & Society 3 (2): 1–​21.

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Monahan, J. & Steadman, H. (1996). Violent storms and violent people: How meteorology can inform risk communication in mental health law. American Psychologist 51: 931–​8. Morris, J. & Graham, H. (2019). Using technology and digitally enabled approaches to support desistance. In P. Ugwudike, H. Graham, F. McNeill, F. Taxman & C. Trotter (eds.) The Routledge Companion to Rehabilitative Work in Criminal Justice, London, UK: Routledge. Mullen, P.E. & Ogloff, J.R.P. (2012). Assessing and managing the risks of violence towards others. In M. Gelder, N. Andreasen, J. Lopez-​Ibor & J. Geddes (eds.) New Oxford Textbook of Psychiatry (2nd ed.). Oxford, UK: Oxford University Press. Morgan, I. & Morgan, N. (2018). Conference Report 2018. 38th Asian and Pacific Conference of Correctional Administrators. 2–​7 Sept, Melaka, Malaysia. Mossman, D. (2000). Assessing the risk of violence: Are ‘accurate’ predictions useful? The Journal of the American Academy of Psychiatry and the Law 28: 272–​81. Mossman, D. (2013). Evaluating risk assessments using receiver operating characteristic (ROC) analysis: Rationale, advantages, insights, and limitations. Behavioral Sciences and the Law 31: 23–​39. Mossman, D. (2015). From group data to useful probabilities: The relevance of actuarial risk assessment in individual instances. The Journal of the American Academy of Psychiatry and the Law 43: 93–​102. Available at: http://​www.jaapl.org/​content/​43/​1/​93.full.pdf. Olver, M.E. & Wong, S.C.P. (2019). Offender risk and need assessment: Theory, research and application. In D.P.P. Polaschek, A. Day & C.R. Hollin (eds.) The International Handbook of Correctional Psychology. Chichester, UK: Wiley (pp. 461–​75). Quinsey, V.L., Harris, G.T., Rice, M.E. & Cormier, C.A. (1998). Violent Offenders: Appraising and Managing Risk. Washington, DC: American Psychological Association. Rettenberger, M., Boer, D. & Eher, L. (2011). The predictive accuracy of risk factors in the Sexual Violence Risk-​20 (Svr-​20). Criminal Justice and Behavior 38: 1009–​27. Risk Management Authority (2019). RATED: Risk Assessment Tools Evaluation Directory [online] Available at: https://​www.rma.scot/​ research/​rated/​ Ross, S. (2018). Policy, practice and regulatory issues in mobile technology treatment for forensic clients. European Journal of Probation 10: 44–​8.

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Rossegger, A., Gerth, J., Seewald, K., Urbaniok, F., Singh, J. P. & Endrass, J. (2013). Current obstacles in replicating risk assessment findings: A systematic review of commonly used actuarial instruments. Behavioral Sciences and the Law 31: 154–​64. Rudin, C. & Ustun, B. (2018) Optimized scoring systems: Toward trust in machine learning for healthcare and criminal justice. Journal on Applied Analytics 48: 449–​66. Shepherd, S.M. (2015). Criminal engagement and Australian culturally and linguistically diverse populations: Challenges and implications for forensic risk assessment. Psychiatry, Psychology and Law 23: 256–​74. Singh, J.P. (2013). Predictive validity performance indicators in violence risk assessment: A methodological primer. Behavioral Sciences & the Law 31 (1): 8–​22. Singh, J.P., Grann, M. & Fazel, S. (2011). A comparative study of violence risk assessment tools: A systematic review and metaregression analysis of 68 studies involving 25,980 participants. Clinical Psychology Review 31 (3): 499–​513. Singh, J.P., Desmarais, S.L., Hurducas, C., Arbach-​Lucioni, K., Condemarin, C., Dean, K., Doyle, M., Folino, J.O., Godoy-​Cervera, V., Grann, M., Ho, R.M.Y., Large, M.M., Nielsen, L.H., Pham, T.H., Rebocho, M.F., Reeves, K.A., Rettenberger, M., de Ruiter, C., Seewald, K. & Otto, R.K. (2014). International perspectives on the practical application of violence risk assessment: A global survey of 44 countries. International Journal of Forensic Mental Health 13 (3): 193–​206. Sue, S. (1999). Science, ethnicity, and bias: Where have we gone wrong? American Psychologist 54 (12): 1070–​7. Stats NZ (2018). Algorithm Assessment Report [online] Available at: https://​ www.data.govt.nz/​ assets/​Uploads/​Algorithm-​Assessment-​Report-​ Oct-​2018.pdf Tamatea, A. (2016). Culture is our business: Issues and challenges for forensic and correctional psychologists. Australian Journal of Forensic Sciences 49 (5): 564–78. Tamatea, A.J. & Boer, D.P. (2016). Sex offender risk assessment and culture: Issues for research and practice. In L. Craig & M. Rettenberger (eds.) The Wiley-​Blackwell Handbook on the Assessment, Treatment and Theories of Sexual Offending (Volume: Assessment). New York, NY: Wiley (pp. 1181–​200). Tully, R.J., Chou, S. & Browne, K.D. (2013). A systematic review on the effectiveness of sex offender risk assessment tools in predicting sexual recidivism of adult male sex offenders. Clinical Psychology Review 33: 287–​316.

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Van der Steene, S. & Knight, V. (2017). Digital transformation for prisons. Probation Journal 64: 256–​68. VanNostrand, M. & Keebler, G. (2009). Pretrial Risk Assessment in the Federal Court. Report for the Office of the Federal Detention Trustee (OFDT), Washington, DC. Ward, T. & Stewart, C.A. (2003). The treatment of sex offenders: Risk management and good lives. Professional Psychology: Research and Practice 34: 353–​60. Wener, R.E. (2012). The Environmental Psychology of Prisons and Jails: Creating Humane Spaces in Secure Settings. Cambridge, UK: Cambridge University Press.

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PART III

Dataveillance, Governance and Policing Control Societies

9

Cameras and Police Dataveillance: A New Era in Policing Janne E. Gaub and Marthinus C. Koen

Big data tools create the potential for big data policing. The combination of new data sources, better algorithms, expanding systems of shared networks, and the possibility of proactively finding hidden insights and clues about crimes has led to a new age of potential surveillance. (Ferguson, 2017b, p. 19)

Introduction The word surveillance was first used in 1792, following the French Revolution, in the name for the Comité de Surveillance (Committee of Surveillance), which was tasked with monitoring suspicious people (generally strangers) and recommending arrest (Hanson, 2004). In the three centuries since, the word has retained its original meaning, as it still entails the gathering of information about groups and/​or individuals for the purpose of monitoring, usually by the government (Clarke, 1988). Within the context of information technology, Clarke (1988) describes a subset of surveillance known as dataveillance, or ‘the systematic use of personal data systems in the investigation or monitoring of the actions or communications of one or more persons’ (p. 499). Esposti (2014) expands this definition to include regulation of behavior, and both public and private entities engage in dataveillance

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(Clarke, 1988, 1994; Amoore & De Goede, 2005; Ashworth & Free, 2006; Van Dijck, 2014). A well-​known example of government dataveillance is the case of whistleblower Edward Snowden, who accused the National Security Agency (NSA) of spying on Americans. Snowden revealed Project PRISM, a classified initiative that involved the collecting and intercepting of private data related to phone calls, social media communications and online behavior recorded by companies like Verizon, Facebook and Google (Van Dijck, 2014). Project PRISM permits the NSA to require these companies to turn over data that match approved parameters considered to be ‘criminal’ or ‘dangerous’, as defined by the US Foreign Intelligence Surveillance Court. Snowden alleged that the NSA violated these protocols by illegally surveilling domestic targets, but then-​President Obama and many large tech firms insisted the NSA’s practices were an implicit transaction. The public cannot expect that the data they generate online will not be used by other parties, especially when using free services such as Facebook or Google (Van Dijck, 2014). Nonetheless, this sparked intense debate about the extent to which third parties should have access to personal communications. The concept of dataveillance has predominantly been discussed as we describe here—​outside entities monitoring data generated digitally by individuals to understand their movements and communications, typically within the context of national governments or large companies (Clarke, 1988, 1994; Ashworth & Free, 2006; Van Dijck, 2014). However, little scholarly discourse has sought to apply the concept of dataveillance at the local level, particularly among law enforcement. This lack of discussion is troublesome, as most people are likely to be the subject of local law enforcement dataveillance without ever knowing it. In fact, this has been a facet of local policing in America since its inception, and improved technology has only solidified its use. We assert that within the context of local law enforcement, the increased use and reliance upon video data and associated technologies (e.g. artificial intelligence) is at the heart of localized dataveillance. Moreover, we suggest that such dataveillance will become such an integral part of local law enforcement that we have entered a new era of policing—​the dataveillance era. To demonstrate this, we first explain the historical context of American policing using the three-​era framework developed by Kelling and Moore (1988). We then explain the proliferation and evidence base of popular surveillance technologies upon which local law enforcement agencies rely, asserting that the mass

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adoption of body-​worn cameras (BWCs) has solidified our current age as the dataveillance era of policing.

Historical context What led police departments to use—​and rely on—​cameras for the use of surveillance and control? To understand this, we must first understand the history of policing as we know it in the United States. American policing is rooted in the English tradition. Indeed, the word sheriff comes from the old English ‘shire reeves’, tasked with protecting the land and property of British noblemen, and the London Metropolitan Police Department—​established in 1829 by Sir Robert Peele—​was the template for the first modern American police departments beginning in the 1840s (Kelling & Moore, 1988). Kelling and Moore (1988) divide the history of policing into three eras: the political, professional and community problem-​solving eras. Hooper (2014) introduces a fourth era, that of the information era. Others include an era prior to the political era, during the colonial period and the decades of the early American republic (Cole, Smith & DeJong, 2015). During this time, the night watchman system flourished in the North and slave patrols operated in the South, but neither constituted an organized institution of law enforcement in the traditional sense. In both systems, the primary purpose was to protect the property of landed whites (Byfield, 2019; see also Reichel, 1988; Hawkins & Thomas, 1991). In this way, a key function of police has always been to control the masses, especially those outside the ruling class (Bass, 2001). In fact, Manning (2008) describes the police as: [A]‌rather quaint kind of rational-​legal organization built over a tradition of core values and practices—​namely, visible patrol, ‘working the streets’, and investigating class-​ based, nineteenth century street crimes. That is, the focus has always been upon regulating simple crimes of stealth and violence committed on the streets by those with few options and choices. (p. 23)

Three eras of policing For the sake of ease, we use Kelling and Moore’s historical framework of policing because they begin at the formation of modern, organized law enforcement agencies as one would recognize them today. The foundation of the political era, lasting from the 1840s until roughly the

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1920s, is that all government institutions—​including policing—​was entrenched in local politics. Police departments were staffed with individuals chosen by local ruling elites according to ethnic or religious connections. During this time, police departments provided essential social services, functioning as soup kitchens and orphanages as well as law enforcement. Officers walked neighborhood beats and used street justice to maintain order (Kelling & Moore, 1988). This era also coincides with the end of the Civil War, the abolition of slavery, and the Great Migration of over one million former slaves into Northern cities and various areas in the Midwest and West. Socially, newly-​ freed Blacks and recently-​migrated European whites competed for resources, and the police were used to control the racialized ‘others’, often through police-​based violence (Byfield, 2019). Above all else, the police were tasked with ensuring that crime and disorder never reached the doorsteps of the elite (Kelling & Moore, 1988). Beginning in the 1920s, police reformers like August Vollmer, O.W. Wilson and J. Edgar Hoover gained traction (Kelling & Moore, 1988). In the professional era (1920s–​1970s), the goal was to transform policing from a job based on cronyism to a standardized profession. They instituted the civil service and police academy so that officers met a consistent set of standards. The advent of the automobile, radio and telephone (and accompanying 911 system) permitted specialization and uniformity—​hallmarks of bureaucracy and scientific management (Taylor, 1916/​1978; Weber, 1946/​1978). Additional technological advances permitted innovations such as handwriting and fingerprint analysis (Cole et al, 2015). Patrol activities transition from officers on foot to officers in vehicles, increasing social distance between the police and their communities. Instead of social services, officers focused on crime-​fighting. The community was expected to passively assist the police in doing their job by calling for police services when needed and being good witnesses. It is during this era that police officers develop a demeanor that is often perceived as detached or aloof, which persists even to this day (Kelling & Moore, 1988). However, ‘professionalization of policing [also] meant a hyper-​ policing of Black communities’ (Byfield, 2019, p. 94). The end of this era was characterized by over 150 uprisings stemming from continued racial discrimination and violence by police. The Kerner Commission, created by President Johnson to study the civil unrest, ‘reported that white racism and its manifestation in police violence against blacks were the central cause of the uprisings’ (Byfield, 2019, p. 94; see also National Advisory Commission on Civil Disorders, 1968). Walker explains that this era of professionalization led law enforcement agencies to become

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‘closed bureaucracies, isolated to the public, and unresponsive to the demands of racial justice’ (Walker, 2016, p. 539). The community problem-​solving era begins in the 1980s. During this era, there was a concerted shift away from the fact-​finding and crime-​ fighting mentality of the professional era towards a more holistic understanding of the role of policing. Drawing on research from the 1970s and 1980s, police executives revived policing practices and strategies such as foot patrol, community-​oriented policing and problem-​solving (Kelling & Moore, 1988). In some ways, the shift back to community authorization was reminiscent of the political era, but professional-​era reforms like the civil service, unionization and bureaucratization created a ‘counterbalance’ (Kelling & Moore, 1988, p. 11). Policing was decentralized, with the rank-​and-​file being encouraged to take ownership of initiatives through the creation of task forces. Ultimately, the foundational component of this era is ‘an intimate relationship between police and citizens’ (Kelling & Moore, 1988, p. 12). Citizens were encouraged to bring problems directly to their local beat officer or precinct, and officers were expected to devise and implement solutions. Many of these problems focused on issues related not to enforcement of laws but to reduction of fear, maintaining order, resolving conflicts and improving overall quality of life. To achieve these goals, many departments adopted broken windows policing, which is predicated on the belief that aggressive enforcement of lower-​level offenses—​nuisance crimes, quality-​of-​life offenses and disorder—​will reduce more serious offenses. The 1980s was marked by an all-​ time high crime rate across the country, the war on drugs and mass incarceration. And longstanding racial tensions continued: decades of police brutality and abuse of authority culminated in a congressional hearing in 1983 investigating 98 cases, with only one case resulting in criminal charges (and ultimately, acquittal; Byfield, 2019). It is important to note that Kelling and Moore wrote this history of policing prior to several important milestones in policing. The great American crime decline, along with the widespread use of broken windows policing, in the 1990s led to many changes in how the police do business. Broken windows policing (Wilson & Kelling, 1982), sometimes referred to as order maintenance policing, has taken many forms. Perhaps its staunchest supporter is William Bratton, first the commissioner of the New York Transit Police and then Commissioner of the New York City Police Department (NYPD) in the 1990s. He first adopted broken windows policing to address disorder in the New York City subway system, but eventually deployed it citywide

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(McKee, 2020). The strategy was used to target quality-​of-​life offenses like prostitution, aggressive panhandling and the notorious ‘squeegee men’, and was later expanded to include the controversial, systematic use of Stop, Question, and Frisk (or SQF; Byfield, 2019). Studies have found the tactic (i.e. a Terry stop) to be used disproportionately against people of color, with low ‘hit rates’ for drugs, weapons or other contraband (Fratello, Rengifo & Trone, 2013; White & Fradella, 2016). In 2013, a federal judge found the NYPD inappropriately wielded Terry stops in a racially discriminatory fashion, and the use of SQF has substantially decreased in subsequent years (White & Fradella, 2016). In fact, many ‘scholars have argued that one of the most harmful elements of aggressive policing strategies is their disproportionate targeting of both minority citizens and poor minority communities’ (Brunson & Miller, 2006, p. 616; see also, e.g. Bass, 2001). Community policing and problem-​oriented policing also continued to be quite popular. The federal government instituted a grant program (the Smart Policing Initiative, later renamed Strategies for Policing Innovation) in 2009 to fund innovative problem-​solving projects, wherein law enforcement agencies partner with external evaluators (Bureau of Justice Assistance, 2009). Important for our discussion, however, is the fact that data collection and monitoring is a core component of the policing strategies used during the community problem-​solving era. Problem-​oriented policing, for example, is founded on the principle of identifying problems, devising solutions and evaluating the outcomes (Goldstein, 1979). Data plays an essential role in this process, including forms of dataveillance such as video footage, SQF or traffic stop reporting cards, or criminal histories and follow-​up records. Even police strategies like foot patrol can rely on dataveillance, as officers compile information about the people and places within their beats to better understand community problems and norms—​or for more nefarious purposes, like knowing and enforcing who ‘belongs’. Over a decade after Kelling and Moore outlined their historical framework of policing, the terrorist attacks of September 11, 2001—​ and the counterterrorism focus that followed—​forever changed the function of police and their role in the counterintelligence apparatus. Computerized databases like the Combined DNA Index System (CODIS) and the Automated Fingerprint Identification System (AFIS) were already in use, but the network of information-​sharing and dataveillance was cemented post-​9/​11, as Ferguson (2017b) explains: After the terrorist attacks of September 11, 2001, federal and state officials joined forces to establish a national intelligence

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strategy to improve criminal justice data collection and information sharing. A vast array of law enforcement organizations now shares personal data about suspects, crimes, and crime patterns. These organizations include state, local, tribal, and territorial agencies, the Department of Justice, the Department of Homeland Security, the Federal Bureau of Investigation, the Drug Enforcement Administration, and the Bureau of Alcohol, Tobacco, and Firearms. (p. 15) As such, this ‘rapid expansion of police surveillance capabilities in a post-​9/​11, intra-​PATRIOT Act era presents a number of justice and privacy concerns regarding what aspects of public life are subject to state-​sanctioned surveillance’ (Hood, 2020, p. 161; see also Bloss, 2007). As the war on terrorism continued, police use of dataveillance expanded, now with dueling roles of ‘improv[ing] public safety and promot[ing] police accountability’ (Chavis, 2016, p. 986). Combined with the increased reliance of local law enforcement on video and other surveillance, we have now reached an era of policing characterized by dataveillance.

Populating databases through dataveillance While policing has a reputation of being resistant to change, technology has been one area where law enforcement has largely embraced advancement. There are several explanations for this. Some scholars argue that technology aligns with the standard model of policing, particularly the cultural emphasis on secrecy and the ‘us v. them’ mentality (Manning, 2008; Sanders & Henderson, 2013; Sanders, Weston & Schott, 2015). Others view technology as a method of stimulating crime-​reducing innovation or as a bulwark of efficiency and effectiveness (Lum, Koper & Willis, 2017). Regardless, technology in policing is not new. Police cars and radios first became standard issue during the professional era of policing in order for officers to quickly respond to 911 calls (Kelling & Moore, 1988; Lum et al, 2017). More recent additions include computerized records management systems and biometrics (e.g. iris or fingerprint scans, facial recognition; Esposti, 2014; Lum et al, 2017). But currently, the overriding emphasis of police dataveillance has been on video surveillance in the form of closed-​circuit television (CCTV), in-​vehicle cameras (IVCs), license plate readers (LPRs), and body-​worn cameras (BWCs) (Reaves, 2015; Lum et al, 2016, 2017; Koen & Willis, 2017; Hyland, 2018; Lum,

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Stoltz, Koper & Scherer, 2019; White & Malm, 2020; Piza, in press). Moreover, each of these technologies has afforded the police with different opportunities to surveil the public and control the narrative of police action. In this section, we briefly discuss these technologies, how police have used them, and the evidence base related to outcomes and processes.

Closed-​circuit television Closed-circuit television (CCTV) has been used in the United States since the early 1940s and is now a common source of video surveillance across the world (Caplan, Kennedy & Petrossian, 2011; Keenan, 2014; Welsh, Piza, Thomas & Farrington, 2020; Piza, in press). Unlike broadcast television, which openly transmits video data to a multitude of viewers, CCTV uses only a ‘closed’ set of monitors. CCTV has particularly become a popular policing tool in the United Kingdom (Norris & McCahill, 2006). A survey conducted by the British Security Industry Association (2013) estimates that there were approximately 4.9 million to 5.9 million CCTV cameras in the UK in 2013, translating to one camera per 11 people. In contrast, CCTV use in the US is typically reserved for metropolitan jurisdictions containing more than 250,000 citizens (Reaves, 2015; Piza, in press). However, CCTV is also popular among private businesses and households, which the police could access through either consent or a search warrant. The first empirical evaluations of CCTV were conducted in the late 1970s, though the research base has significantly expanded (Welsh & Farrington, 2003, 2004, 2009; LaVigne, Lowry, Markman & Dwyer, 2011; Salvemini, Piza, Carter, Grommon & Merritt, 2015; Piza, Welsh, Farrington & Thomas, 2019; Welsh et al, 2020). Law enforcement use of CCTV—​a nd resulting research—​is primarily rooted in one of two outcomes: Crime deterrence or suspect apprehension (Welsh & Farrington, 2008, 2009; Piza, in press). Research has been modestly supportive of the effectiveness of CCTV to deter crime in general (Welsh & Farrington, 2008, 2009; LaVigne et al, 2011; Piza et al, 2019). However, the effect is dependent on crime type, the location of the CCTV system and how the technology is leveraged. While a handful of studies have found some reductions in violent crimes, the lion’s share of the evidence base demonstrates that CCTV has an overall greater impact on property crime and disorder (Welsh & Farrington, 2003, 2004, 2008, 2009; Piza et al, 2019; Welsh et al, 2020), such as reducing disruptive fans at soccer matches (Priks, 2015) and public heroin injections (Scott et al, 2016). Research also

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suggests that CCTV works better as a deterrent when focusing on micro-​places (like parking areas, bars/​nightclubs and private residences) to target specific crimes (like auto theft, violent crime and robbery or burglary, respectively) (Caplan et al, 2011; Piza, Caplan & Kennedy, 2014; Lim & Wilcox, 2017). CCTV is also used to facilitate the apprehension of individuals suspected of criminal wrongdoing (Piza, in press). While generally less rigorous, these studies have found that CCTV footage provides valuable evidence in open criminal investigations (Gill & Spriggs, 2005), but is generally less useful for retroactive investigations (King, Mulligan & Raphael, 2008; LaVigne et al, 2011). Officers noted that CCTV often does not capture enough relevant information due to camera positioning, incomplete videos or poor quality footage (King et al, 2008; LaVigne et al, 2011). Nonetheless, the police tend to perceive CCTV as an important exploratory investigative tool, even if the footage itself is not evidence (LaVigne et al, 2011).

License plate readers Similar to CCTV, license plate readers (LPRs) were first adopted by police agencies in the United Kingdom in 2006 (Lum et al, 2016). LPRs use video to scan alphanumeric data from license plates and cross-​references it with existing databases. The technology has quickly diffused in the United States and abroad—​from 19 per cent of agencies in 2007 to roughly 70 per cent in 2013—​despite scant evidence of their effectiveness (Reaves, 2010, 2015; Lum, Hibdon, Cave, Koper & Merola, 2011; Merola & Lum, 2012; Lum et al, 2016). This rapid diffusion has been attributed to the availability of federal funds and by the presumed ability of LPRs to make certain police processes more efficient (Lum et al, 2011, 2016). However, the technology suffers from a lack of public support. Community members tend to voice concerns related to privacy rights, especially when LPRs are used indiscriminately (e.g. continuously scanning and recording all vehicles on the road) rather than being targeted towards those for whom some level of reasonable suspicion or probable cause exists (Merola & Lum, 2014). LPRs continuously operate, collecting data through video cameras and comparing it against existing databases. Depending on the parameters set by the police officer or agency (e.g. auto theft, parking violations/​citations, outstanding warrants or persons of interest), the system will notify officers of license plates that are associated with vehicles of interest (Lum et al, 2011, 2016; Damak, Kriaa, Baccar, Ayed

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& Masmoudi, 2020). The majority of LPR units have been mounted on police vehicles or in fixed areas such as traffic lights, toll booths or street corners (Merola et al, 2012; Lum et al, 2016). Because LPR systems store both metadata (e.g. time, location, date) and recorded data, their primary use has been in investigations and crime prevention (Taylor, Koper & Woods, 2011; Lum et al, 2011, 2016; Koper, Taylor & Woods, 2013; Willis, Koper & Lum, 2018). However, the research on the effectiveness of LPRs is limited to a handful of studies that ultimately rendered mixed results. One study in the context of investigations found that investigators found LPRs invaluable in their ability to assist with rapid response to open and evolving cases, suspect and crime pattern identification, and verification of alibis (Willis et al, 2018). Two randomized controlled trials focused on crime hot spots but came to opposing conclusions; one found reductions in auto-​related and drug crime calls for service (Koper et al, 2013; Taylor et al, 2011) while the other found no significant differences (Lum, Merola, Willis & Cave, 2010; Lum et al, 2011). However, these studies were conducted in 2010, during the initial stage of proliferation, and were limited by small LPR databases, low treatment usage, and different patrol styles of officers driving LPR vehicles (Lum et al, 2011, 2010; Taylor et al, 2011; Koper et al, 2013).

In-​vehicle cameras In the context of policing, in-vehicle cameras (IVCs; also called ‘dashboard cameras’ or ‘dashcams’) are audiovisual recording devices that attach to the dashboards or windscreens of patrol vehicles to capture police encounters, typically from a distance (Turner et al, 2019). IVCs were first introduced to police agencies in the 1960s, but it was not until the 1990s and early 2000s that the technology rapidly diffused across the country as funding, technological advances and public support converged (Hickman & Reaves, 2003; International Association of Chiefs of Police [IACP], 2005; Reaves, 2015; Hyland, 2018). Data from the Law Enforcement Management and Administrative Statistics (LEMAS) survey shows that the use of IVCs among local police departments increased from 37 per cent to 55 per cent between 2000 and 2003, and to 69 per cent by 2016 (Hickman & Reaves, 2003; Reaves, 2015; Hyland, 2018). In the 1980s, Mothers Against Drunk Driving vocalized concern about lax enforcement and prosecution of drunk drivers (IACP, 2005). IVCs were a logical solution because they could record field sobriety tests, thereby providing better evidence in drunk driving cases (IACP,

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2003; Koen, 2016). The motivation behind their use altered during the 1990s, as complaints of excessive use of force and discriminatory profiling—​and assaults on officers—​increased, particularly among state agencies responsible for highway patrol and traffic stops. In response, the COPS Office provided funding for 47 highway patrol and state police agencies in 2000 (IACP, 2003). Proponents of IVCs argue that they lead to better evidence, increased transparency and accountability, and improved perceptions of safety among officers, but rigorous evaluations testing these claims are virtually non-​existent. Only one evaluation—​conducted by the IACP in 2002 and 2003—​comprises the entirety of the evidence base. Relying on quantitative and qualitative survey data from police officers, prosecutors, and the public, the IACP study found that respondents generally had favorable views of IVCs (IACP, 2003). Police and prosecutors alike believed IVCs to be valuable because footage aided in successful prosecution, and some police agencies reported a modest (8 per cent) reduction in sustainable citizen complaints and a shortened complaint investigative timeframe (IACP, 2003).

Body-​worn cameras As with CCTV and LPRs, body-worn cameras (BWCs) were first used in the UK before making their way to the United States in the late 2000s (Goodall, 2007; White, 2014). Proponents of the technology argue that the technology leads to increased accountability and transparency, reduction in police use of force and citizen complaints, and positive court outcomes (Miller, Toliver & Police Executive Research Forum, 2014; White, 2014). While the research base has largely supported the contention of reduced citizen complaints (White, Gaub & Padilla, 2019a), the story is far less clear regarding use of force. Early studies found substantial reductions in use of force, but more recent research has found that BWCs have little to no effect on use of force, leading to increasingly mixed results (White, Gaub & Padilla, 2019b). The small body of research addressing court impacts has found some modest impacts, particularly in cases related to domestic violence or intimate partner violence, wherein BWC footage can serve as a stand-​in for victim testimony (Owens, Mann, & Mckenna, 2014; Morrow, Katz & Choate, 2016). Additionally, police BWCs enjoy broad support from a range of stakeholders, including officers, command staff, court actors, users of police services and the general public (Gaub, Choate, Todak, Katz & White, 2016; Smykla, Crow, Crichlow & Snyder, 2016; Todak, Gaub & White, 2017; Kerrison,

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Cobbina & Bender, 2018; Lee, Taylor & Willis, 2018; Gaub, Naoroz & Malm, 2019; Koen & Willis, 2019; McKay & Lee, 2019; Miethe, Lieberman, Heen & Sousa, 2019). And yet, critics have noted the immense monetary cost of BWCs, concerns related to camera point-​of-​view, the complexities associated with public access to footage, and privacy concerns for both officers and citizens. The true cost of a BWC program is not the purchase of the cameras themselves, but the storage of footage, which can be prohibitively expensive and is the reason some agencies have actually stopped using BWCs altogether (Kindy, 2019). Additionally, some argue that mounting the camera on an officer actually removes a good deal of the accountability potential because the officer is not visible. Adams and Mastracci (2017) explain that ‘the subject of BWC surveillance is purportedly the police officer’, when in reality ‘the officer is a tool of surveillance who reminds others that their actions are recorded by the state’ (p. 320).

Video recording as police dataveillance Taken together, CCTV, LPRs, IVCs and BWCs compose an impressive array of police video surveillance capability. CCTV captures people’s movements from fixed positions of high-​crime hot spots including: parking garages and lots; nightlife venues like bars, nightclubs and restaurants; and residential areas, especially multi-​housing units. LPRs capture people’s vehicular movements (when used in motion) and track places people frequent (when used in parking lots). IVCs and BWCs capture people’s interactions with police, including passersby who may be entirely uninvolved in the incident of interest. When combined with other capabilities, like facial recognition, the possibilities become even more invasive. In the name of public safety, people’s everyday movements and interactions are captured, stored and analyzed, without any suspicion that they have actually committed any crime. While this potential was exacerbated by the introduction of BWCs, Adams and Mastracci (2017) explain that this was not a new phenomenon: BWCs were not born as a new technology so much as they represent a streamlined, modern addition to the state’s use of technology to enhance its surveillant capabilities, inserting the state into our most private spaces in our most vulnerable times. BWCs are just one piece of the state’s surveillant technology. (p. 324)

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In fact, Brown (2016) notes that ‘the pervasiveness of cameras throughout Western societies “is changing the dynamics of policing on the ground” ’ (Haggerty & Sandhu, 2014, p. 11, quoted on p. 295). The integration of these cameras—​particularly CCTV and BWCs—​with facial recognition and livestream capabilities only further cements their use in police dataveillance (Ferguson, 2017b; Hood, 2020). But the adoption of BWCs specifically has presented its own set of challenges, far more problematic than with CCTV, LPRs and IVCs. Unlike the other three, BWCs do not remain solely in the public domain, as officers routinely answer calls in private spaces like businesses, homes and medical facilities (Chavis, 2016). Groups like the National Association for the Advancement of Colored People Legal Defense Fund, the National Urban League, the Lawyers Committee for Civil Rights, and the American Civil Liberties Union have found themselves in a quandary, as BWCs simultaneously promote accountability and invade privacy (Stanley, 2013; Chavis, 2016). And privacy concerns are only exacerbated by public release of footage as private spaces and moments become public record (Chavis, 2016; Fan, 2016; Hartzog, 2018).

Moving forward Over the last few decades, federal and state law enforcement agencies have been the predominant players in compiling a number of databases documenting everything from biometrics (like DNA, fingerprints and iris scans) to tattoos, which are then made available to local agencies. The USA PATRIOT Act in 2001, which created a formalized network of data sharing, only solidified those relationships (Ferguson, 2017a). But ‘data available in real time only helps if the information is accurate’ (Ferguson, 2017b, p. 86). One of the key concerns related to police dataveillance is the accuracy of information being generated. Facial recognition software provides a good example, as it has historically suffered from racial bias. As Hood (2020) explains: The strength of a facial recognition algorithm—​its ability to correctly verify/​identify faces—​depends on, among other factors, the size and diversity of its training set, a database of photographs used to ‘teach’ a model how to perform its job. If the training set overrepresents one demographic, such as white male faces, the algorithm will be more adept at identifying white male faces, creating opportunities for

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the misidentification of other demographics. Factors such as eyeglasses, lighting, make-​up, skin tone, environment, and angle can reduce success rates of facial recognition algorithms. (p. 163) In other words, an algorithm built on biased or faulty datasets will provide biased or faulty outputs. The inherent risk here becomes obvious: As police agencies increasingly rely on dataveillance, the potential for biased policing also increases. This concern has been raised in other instances when police use algorithms to direct their practices (e.g. predictive policing; Ferguson, 2017b; Santos, 2019). In fact, research on police technology tends to show that, for the most part, police use technology in accordance with existing structures and practices, and which tend to reflect a few minor adjustments rather than substantial changes to police operations (Willis, Mastrofski & Weisburd, 2007; Mastrofski & Willis, 2010; Lum et al, 2017; Koen & Mathna, 2019; Koen & Willis, 2019). Deep learning—​a subset of machine learning—​allows computers to be able to identify and categorize data with limited (or no) human input or intervention through what are known as ‘neural networks’ (Schmidhuber, 2015). This process is the basis of LPR technology and many facial recognition systems, and is used in a number of capacities by law enforcement (Joh, 2016; Ferguson, 2017a, 2017b; Damak et al, 2020). Amazon’s ‘Rekognition’ facial recognition software, for example, was specifically marketed to federal law enforcement (US Customs and Border Protection), but it is also increasingly used by local law enforcement (Levy & Hirsch, 2020). When deep learning processes are fully integrated with CCTV, LPR, IVC and/​or BWC technology, the results can be exceptionally useful for police. For example, when paired with metadata (e.g. location, date and time), investigators would be able to gain a deeper, more nuanced understanding of people’s movements. Similarly, officers conducting traffic stops would be able to obtain a wealth of information to better inform their discretionary options (Joh, 2016; Ferguson, 2017a, 2017b).

Conclusion The benefits of dataveillance in the context of law enforcement are arguably ‘smarter policing, faster investigation, predictive deterrence and the ability to visualize crime problems in new ways’ (Ferguson, 2017b, p. 503). Proponents of increased use of police technology—​ especially video surveillance—​argue that the accountability and

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transparency benefits far outweigh any purported concerns. But dataveillance often operates in shades of opacity. Unmanned aerial drones, for example, have started making inroads in local law enforcement (Heen, Lieberman & Miethe, 2018). They, like BWCs, encroach on areas that have historically been considered private and sacrosanct, free from government and police intrusion. The era of dataveillance also brings with it concerns about infringement on free speech and assembly. While police have long used video surveillance to maintain public safety in large crowds, the use of extensive dataveillance mechanisms and coordination between federal and local law enforcement can have chilling effects on peaceful protests (e.g. Walby & Monaghan, 2011). The hacking group Anonymous claimed credit for stealing tens of thousands of police records in June 2020 following the mass demonstrations across the United States protesting against police brutality of minority citizens. These records, dubbed BlueLeaks, laid bare the use of law enforcement surveillance during Black Lives Matter protests, wherein the Federal Bureau of Investigation coordinated with local law enforcement agencies to track social media activity (e.g. Twitter) and report individuals to local law enforcement (Anonymous, 2020; Daniel, 2020). As such, the era of dataveillance pits ‘two revered democratic values of transparency and privacy’ against each other (Fan, 2016, p. 401). References Adams, I. & Mastracci, S. (2017). Visibility is a trap: The ethics of police body-​worn cameras and control. Administrative Theory & Praxis 39 (4): 313–​28. Amoore, L. & De Goede, M. (2005). Governance, risk and dataveillance in the war on terror. Law & Social Change 43 (2–​3): 149–​73. Anonymous [@YourAnonNews] (2020, June 23). Inside #BlueLeaks—​ a trove of hacked police documents released by Anonymous [Tweet; thumbnail link to article]. Twitter. Available at: https://​twitter.com/​ YourAnonNews/​status/​1275435207693225986. Ashworth, L. & Free, C. (2006). Marketing dataveillance and digital privacy: Using theories of justice to understand consumers’ online privacy concerns. Journal of Business Ethics 67 (2): 107–​23. Bass, S. (2001). Policing space, policing race: Social control imperatives and police discretionary decisions. Social Justice 28 (1): 156–​77. Bloss, W. (2007). Escalating US police surveillance after 9/​11: An examination of causes and effects. Surveillance & Society 4 (3): 208–​28. British Security Industry Association (2013). The Picture Is Not Clear: How Many CCTV Surveillance Cameras in the UK? London.

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Theorizing Surveillance in the Pre-​Crime Society Michael McCahill

Introduction This chapter interweaves ‘surveillance theory’, ‘policing studies’ and ‘field theory’ (Bourdieu, 1984) to examine the politics of ‘pre-​crime’ in the UK ‘field of policing’.1 The theoretical literature on policing and new surveillance technologies often describes these developments in terms of epochal shifts or societal transformations, such as the emergence of the ‘control society’ (Deleuze, 1992) or the ‘pre-​crime society’ (Zedner, 2007). However, these abstract narratives of change often fail to explore how wider global trends or social forces, such as neoliberalism or bio-​power, are refracted through the crime control field in different national jurisdictions. In contrast, the questions posed in this chapter are more modest. They include questions such as what is pre-​crime? What is surveillance? What is the connection between surveillance and pre-​crime? Why has there been an apparent shift in crime control policy from the penal-​welfare strategy towards pre-​crime and surveillance? To what extent are pre-​crime mentalities and new surveillance technologies being incorporated into police practice? These questions in turn lead to further questions, such as who are the ‘police’, what is ‘policing’ and which ‘policing’ organizations are adopting new surveillance technologies that facilitate the ‘pre-​ emptive turn’? To address these questions, we situate the emergence of new surveillance technologies within ‘fields of struggle’, defined ‘as a structured space of positions in which the positions and their

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interrelations are determined by the distribution of different kinds of resources or “capital” ’ (Thompson, 1991, p. 14). For Bourdieu, ‘fields of struggle’ are relatively autonomous social spaces ‘that cannot be collapsed under an overall societal logic’ (Bourdieu & Wacquant, 1992, p. 17) such as ‘modernity’ or ‘post-​modernity’, or, we might add, the ‘pre-​crime’ society. We use this approach to examine the use of new surveillance technologies by a diverse network of agencies that make up the ‘field of policing’. At the same time, we try to avoid giving the impression of an all-​encompassing ‘police network’ that underplays the existence of hierarchies, lines of confrontation or ‘the distinction between central and peripheral actors’ (Bonelli & Bigo, 2005, p. 8). We begin, however, by defining the key concepts (‘surveillance’, ‘pre-​ crime’ and ‘policing’) and explaining how they are related.

Background and context: surveillance, pre-​crime and policing Let us begin with surveillance defined as the ‘collection and analysis of information about populations in order to govern their activities’ (Haggerty & Ericson, 2006, p. 3). This has always been a central feature of policing and criminal justice. This includes the ‘direct supervision’ of subject populations by uniformed officers on the beat and the accumulation of ‘coded information’ (Giddens, 1985) by other agents, which began in the 19th century when fingerprints, photographs and files were collated by criminal justice practitioners to aid in the prevention of future crimes. Over the last two decades, the advent of computer databases, surveillance cameras and other technological advances are said to have given rise to a ‘new surveillance’ (Marx, 2002) that monitors whole groups and populations, geographical locations and time periods rather than individual suspects. More recently, the pre-​emptive turn is said have accelerated with the emergence of ‘big data’ which refers to the collection of large volumes of data from a diverse range of sources that can be combined with software tools to search for patterns or trends for the purposes of law enforcement, order maintenance or security. Recent examples used by the police include ‘bulk communications data surveillance’ (e.g. ‘network composition’, ‘pattern identification’, ‘smart phone location data’ and ‘social media intelligence’) (Murray & Fussey, 2019) and ‘predictive analytics’ (Ferguson, 2017), which draws on a diverse range of law enforcement data sources ‘to predict and intervene before behaviors, events, and processes are set in train’ (Lyon, 2014, p. 4).

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Drawing upon the prescient vision of science fiction writer Philip K. Dick, Zedner (2007) describes these developments as the emergence of a ‘pre-​crime society’ characterized by an emphasis on ‘calculation, risk and uncertainty, surveillance, precaution, prudentialism, moral hazard, prevention and, arching over all these, there is the pursuit of security’ (Zedner, 2007, p. 262). The rise of new surveillance technologies would appear to fit neatly with these developments because risk is a statistical attribute of populations, which makes it necessary to collate information on whole groups and populations rather than individual suspects (Norris & McCahill, 2006). Predictive policing also ‘shifts the temporal perspective to anticipate and forestall that which has not yet occurred and may never do so’ (Zedner, 2010, p. 24). Pre-​crime surveillance is also facilitated by the introduction of new laws such as the UK government’s Prevent strategy, which requires public sector workers to look for signs of ‘radicalization’ and intervene before any of their charges are drawn into terrorism. However, just because new laws or new surveillance technologies are available does not mean that they will be implemented or that they will be incorporated into everyday police practice. To begin with ‘the police’ consists of a diverse range of agencies including public police departments (uniformed officers, criminal investigation, operational and administrative support), domestic security and intelligence services, border police, private security and a transnational field of security professionals (Brodeur, 2010, pp. 23–​7). While ‘calculation’, ‘risk management’, ‘security’ and ‘surveillance’ may be central to the work of some of these agencies (e.g. investigation departments and intelligence services), pre-​crime mentalities may not be so important in work conducted by other agencies, including for example, rank-​and-​file uniformed officers who are often described as engaging in problem-​oriented policing rather than law enforcement (Goldstein, 1979). Another way to think about the relationship between pre-​crime, surveillance and policing, is to move from a ‘police-​centered’ focus (which is often restricted by a focus on the public police working in uniforms) to a ‘policing-​centered’ theory which is ‘based on the recognition that policing is a plural enterprise in which many agents can be involved’ (Brodeur, 2010, p. 21). As a number of writers have argued, the balance between ‘public’ and ‘private’ provision has shifted to the extent that a ‘pluralized, fragmented and differentiated patchwork has replaced the idea of the police as the monopolistic guardians of public order’ (Crawford, 2003, p. 136). For Johnston and Shearing (2003), these changes are part of a paradigm shift in policing

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and social control signified by the move away from a ‘punishment’ mentality towards a ‘risk’ mentality. In the former paradigm, the central state exercises its security responsibilities through the employment of specialized professionals, such as police officers, whose main concern is the apprehension and punishment of suspected wrongdoers (Johnston & Shearing, 2003, p. 14). Under the ‘risk’ paradigm, on the other hand, security is exercised under plural auspices beyond the central state and is characterized by a ‘corporate’ mentality that emphasizes proactive prevention rather than reactive punishment, and actuarial calculation rather than conventional moral prescription. From this perspective, Foucauldian theories on ‘governmentality’ (Foucault, 1991) or ‘nodal governance’ (Johnston & Shearing, 2003), are said to be the most suitable for understanding the emergence of ‘surveillant assemblages’ (Haggerty & Ericson, 2000) that operate beyond the confines of the state. Nonetheless, while the move towards a ‘policing-​ centered’ theory encourages us to expand the focus of our attention beyond uniformed police personnel, it also makes it ‘progressively more difficult to find a common thread binding them all together’ (Brodeur, 2010, p. 7) The literature on ‘governmentality’ does little to resolve this issue because it tends to focus on ‘rationalities’ or ‘mentalities of liberal governance’, rather than on ‘the ways that politicians, officials, professional agents and other citizens interpret and apply them in their everyday practices and the contexts in which they operate’ (Stenson, 2012, p. 47). For instance, how is ‘risk’, ‘actuarial thinking’, ‘predictive analytics’ and ‘loss prevention’ mediated by police managers, police officers, intelligence analysts, private security officers and citizens going about their business in police stations, CCTV control rooms, welfare offices, shopping malls and airports? Perhaps instead of searching for a ‘common thread’ that unites a diverse range of policing agents, it may be better to view the ‘field of policing’ as a contested space structured by a general competition over the legitimate definition of ‘policing’ (e.g. law enforcement, order maintenance, crime prevention, security, governance) and over competing views on the role that new surveillance technologies should play in the field (intelligence logic, criminal justice logic, productivity/​efficiency logic). In this respect, the field of policing refers not to ‘an archipelago of networks of bureaucracies’ but a ‘field of force’ that ‘polarizes around the specific stakes of the agents involved’ and as a ‘field of struggle’ ‘that is able to understand the “colonizing” activities of various agents, the defensive retreats of others, and the various kinds of tactical algorithms that organize bureaucratic struggles’ (Bonelli & Bigo, 2005, pp. 3–​5).

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The politics of pre-​crime in the field of policing The field of policing, like any field of practice, is not governed solely by its own internal laws and must therefore be positioned ‘inside a larger political and social space’ (Bonelli & Bigo, 2005, p. 3). Thus, any theory of contemporary penal change must begin by considering the wider transformation of the ‘field of power’ ushered in by the demise of the Keynesian Welfare State (KWS) and the emergence of neoliberalism. In his writing on ‘the state’, Pierre Bourdieu (1984) explains how the neoliberal period has been characterized by a series of internal divisions and struggles within the ‘bureaucratic field’. 2 This includes the internal struggle between the ‘higher state nobility’ (policymakers promoting market-​oriented reforms) and ‘lower state nobility’ (those wedded to the traditional missions of government) (Bourdieu, 1984). The second includes the distinction between the ‘left hand’ of the state (e.g. education, health, social assistance) and the ‘right hand’ of the state (those charged with enforcing economic discipline, deregulation and budget cuts) (Bourdieu, 1998, p. 2).3 These internecine struggles in the wider political and social space have led to a number of changes that we would argue are related to the emergence of pre-​crime mentalities within the ‘field of policing’. The demise of the penal-​welfare strategy, for instance, has witnessed the fusion of penal policy and welfare policy to manage the problem populations generated by neoliberal economic policies (Wacquant, 2009). As Wacquant (2009) argues, this includes the ‘deployment of punitive and proactive law-​enforcement policies’ and ‘an insatiable craving for bureaucratic innovations and technological gadgets’ such as databases, mapping of offenses, surveillance cameras, criminal profiling and electronic monitoring (Wacquant, 2009, pp. 1–​2). As we mentioned previously, the neoliberal period has empowered a ‘higher state nobility’ (Bourdieu, 2014) intent on imposing market discipline and the promotion of policies such as privatization, outsourcing and deregulation. This has witnessed the emergence of a technological field of expertise that has boosted the position of security companies providing biometrics, data bases and profiling (Bonelli & Bigo, 2005). The emergence of new surveillance technologies and predictive analytics reinforces these developments by introducing databases which serve ‘to tame the unruliness of local discretion and idiosyncratic practices through standards, forms, rules, tick boxes, procedures, reporting requirements and so on’ (Ruppert, 2012, p. 118). In this respect, the emergence of ‘predictive analytics’ and

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‘bulk communications data surveillance’ (Murray & Fussey, 2019) are part of a drive for efficiency within public constabularies. At the same time, these developments are said to shift the police focus from law enforcement to predictive policing. Thus, while historically police surveillance referred to the focused attention given by state agencies to individuals suspected of committing past crimes, pre-​crime surveillance consists of the collection of bulk data aggregated from both state and non-​state sources where ‘the target becomes the hidden patterns in the data, rather than particular individuals or events’ (Andrejevic & Gates, 2014, p. 190). For all that, it is important to recognize that pre-​crime mentalities and new surveillance technologies are refracted through a field occupied by police managers, police officers, computer analysts and intelligence officers with different levels of seniority, technical expertise and subjective visions on digital policing and surveillance. Next, we examine empirical research on policing and digital surveillance to explore how the temporal shift to ‘pre-​crime’, ‘actuarialism’, ‘risk management’ and ‘loss prevention’ is refracted through ‘fields of practice’ and mediated by a field-​specific ‘habitus’ that refers to ‘an internal set of dispositions that shape perception, appreciation, and action’ (Page, 2013, p. 152). One of the central features of ‘pre-​crime’ is the shift towards ‘actuarial thinking’ and ‘risk management’. Thus, ‘while the logic of criminal justice focuses on individuals, the intelligence logic of anticipation focuses on groups’ (Bonelli & Bigo, 2005, p. 37). Over the last two decades, police datasets have grown exponentially with the introduction of the Police National Computer (PNC) (which in May 2017 contained more than 12.2 million personal records, 62.6 million vehicle records and 58.5 million driver records) and the Police National Database (PND), which since 2011 has allowed ‘police officers to search across the 220 different databases operated by individual police forces in the UK’ (Babuta, 2017, p. 9). If we add to this the Automatic Number Plate Recognition (ANPR) network—​which consists of very large datasets (volume), from multiple sources (variety) and the use of algorithms to automatically identify vehicles of interest (velocity)—​then one can see how the three V’s of big data might facilitate pre-​crime policing and surveillance. Be that as it may, a recent review of the field (including interviews with 25 serving British police officers and technological experts) revealed that ‘the use of big data technology for policing has so far been limited … despite the police collecting a vast amount of digital data on a daily basis’ (Babuta, 2017, p. vii). The reasons for this included the existence of multiple fragmented databases that are not mutually compatible; a lack of the advanced analytical tools required

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for making sense of unstructured data; and financial cuts that have led to centralization and the divorce of analytical and operational processes (Babuta, 2017). Perhaps the central feature of ‘pre-​crime’ is that it ‘shifts the temporal perspective to anticipate and forestall that which has not yet occurred and may never do so’ (Zedner, 2010, p. 24). For Brodeur (2010), these developments mean that the distinction between ‘low’ policing (everyday policing concerned with traffic control, property crimes or domestic disputes) and ‘high’ policing (intelligence-​led policing that aims to protect the national interest from internal threats) is becoming increasingly blurred to the extent that ‘high’ policing mentalities (loss prevention, risk management and surveillance) are beginning to pervade the entire ‘policing web’ (Shearing, 2011). Nonetheless, in his research on the New York Police Force, McQuade (2016, p. 15) has spoken of the ‘technological drama’ currently taking place in US police forces as new surveillance technologies introduced by the ‘higher state nobility’ are shaped by the existing organizational and occupational concerns of the ‘lower-​state nobility’ (e.g. police managers and front-​ line officers). Thus, despite the pressure to adopt pre-​crime mentalities, intelligence-​led policing and crime mapping, one New York Police chief remained committed to community policing because ‘technology-​ driven forms of intelligence analysis were distracting police from their core functions’ (McQuade, 2016, p. 10). Similar findings have been reported in Australia where interviews with law enforcement officers, intelligence officers and computer technologists revealed that there was a general focus on individuals rather than aggregates. Here police officers (and police managers) reported ‘the importance of using data for case-​by-​case, investigative or disruptive purposes, rather than for identification of trends, predictions or strategic analysis’ (Chan & Bennett Moses, 2017, p. 306). One of the most widely cited forms of predictive policing is PredPol, which uses a proprietary algorithm to generate 500 x 500 feet boxes that indicate times and places where crimes are likely to occur (Babuta, 2017). An operational review carried out by Kent Police in 2014 on a similar model of ‘predictive policing’ found that the introduction of new software to predict where crimes were likely to take place produced an impressive hit rate of 11 per cent. However, police officers chose to ignore this intelligence with ‘only 25% of boxes generated by the software’ being visited by police officers (Babuta, 2017, p. 15). Research on social media intelligence (SOCMINT) by UK police officers meanwhile reported how social media was used for the ‘post-​crime’ functions of law enforcement and arrest. This includes #ShopaLooter campaigns and the use of

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dedicated websites with images of people thought to be involved in looting deigned to encourage citizens to inform on those involved in the UK summer riots of 2011 (Bartlett et al, 2013). Another key feature of ‘pre-​crime’, is the shift towards ‘prudentialism’ and ‘loss prevention’ said to be a particular characteristic of ‘private’ security officers who have little concern with the post-​crime functions of law enforcement (Zedner, 2007, p. 263). All the same, empirical research on the operation of CCTV surveillance systems (considered by some as an exemplar of actuarial technology) shows that private security officers often work alongside public police officers to enforce the criminal law and pursue criminal investigations. CCTV control rooms, we should remember, are not separate or discrete systems but part of wider surveillance assemblages (Haggerty & Ericson, 2000) that connect a diverse range of plural policing agents working together (albeit on an ad hoc basis) in the ‘field of policing’.4 Research on the use of CCTV surveillance cameras by corporate actors in shopping malls, for instance, has shown how these technologies are used to target ‘known criminals’, ‘suspected drug addicts’, and those ‘wanted’ for the breach of bail conditions (McCahill, 2002; Wakefield, 2003). In one case study, it was reported how the CCTV control room situated in a shopping mall on a deprived council estate in the north of England came to act as an intelligence-​base for the state police (McCahill, 2002). On this site, the majority of the security officers were local people with extensive knowledge of the area and its inhabitants. This localized knowledge was very useful for the police who, with the help of the security officers, used the control room as an intelligence-​base to monitor suspected drug dealers. Some uses of the system included, Criminal Investigations Department (CID) officers sitting in the control room and using the cameras to zoom in on a local public phone booth to watch the telephone numbers dialed by suspected drug dealers or clients; the local beat officer sitting in the control room and watching the screens to put names to faces and faces to names; policing officers asking the CCTV operators to film the registration number of cars driven by suspected drug dealers; and CCTV operators ringing the local beat officer on his mobile telephone to let him know when any ‘wanted’ persons enter the shopping center (McCahill, 2002).

Responsibilization and pre-​crime policing In his writings on the ‘bureaucratic field’, Bourdieu (2014) constructs ‘a model of the state as a process of concentration of different species of capital (physical, economic, cultural and symbolic), leading to the

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emergence of a kind of “meta capital” capable of exercising power over the other species of capital’ (2014, p. 375). This reconceptualization of the state as the central ‘bank of symbolic capital guaranteeing all acts of authority’ (Wacquant, 2005), reminds us that neoliberal strategies of privatization, deregulation, outsourcing and public-​private partnerships are instigated by national governments and do not therefore represent a simple retreat of the state but rather a reconfiguration of the wider field of power. As Wacquant (2009) points out, neoliberal policies include not only ‘market rule’ and the fusion of the ‘penal-​welfare state’ but also ‘the cultural trope of individual responsibility’ (Wacquant, 2010, p. 197). Thus, alongside the emergence of ‘plural policing’ and the ‘commodification of security’, there have been ‘attempts by the state to make social actors of all kinds—​individuals, corporations, communities—​responsible for a greater involvement in their own security’ (Abrahamsen & Williams, 2011, p. 63). In this respect, the ‘field of policing’ can be situated in the wider ‘crime control field’ defined by David Garland as ‘the formal controls exercised by the state’s criminal justice agencies and the informal social controls that are embedded in everyday activities and interactions in civil society’ (2001, p. 5). This more expansive conception of the crime control field allows us to examine the emergence of pre-​crime mentalities and new surveillance technologies in both the penal sector of the bureaucratic field (e.g. probation and policing) and in the wider society, which has seen pre-​crime mentalities and new surveillance measures adopted in the context of education, housing, welfare, shopping malls, airports and so forth (Simon, 2007). In the context of probation, for example, this includes the widespread use of standardized assessment tools that are used to classify and ‘separate the more from the less dangerous’ (Feeley & Simon, 1992, p. 452). These include the Offender Assessment System (OASys) that is used to classify adult offenders (Bullock, 2011) and Asset, an assessment tool used in the context of youth justice (Moore, 2005). These developments have facilitated the introduction of intensive supervision and surveillance programs directed at ‘prolific’ or ‘persistent’ offenders, which utilize an array of new surveillance technologies and practices including compulsory drug testing, criminal profiling, electronic monitoring and police databases. Similar developments can be found in the context of ‘bureaucratic welfare’ regimes where a plethora of new surveillance technologies have been introduced to monitor the welfare poor (Gilliom, 2001; Wacquant, 2009). Welfare claimants in the UK and US are surrounded by a range of surveillance technologies and programs that intimately oversee their eligibility for work, leisure patterns and family

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status. In the United States, for instance, it has become increasingly difficult to distinguish the welfare office from the probation office. Welfare offices have borrowed the stock-​and-​trade techniques of the correctional institution: a behaviorist philosophy of action à la Skinner, constant close-​up monitoring, strict spatial assignments and time constraints, intensive record keeping and case management, periodic interrogation and reporting, and a rigid system of graduated sanctions for failing to perform properly. (Wacquant, 2009, p. 102) There has also been a swathe of state-​initiated responsibilization strategies designed to encourage (or compel by law) a whole range of private companies and other state organizations to engage in pre-​ crime surveillance on behalf of the state. For example, the Proceeds of Crime Act 2002 and the Terrorism Act 2000 required a number of organizations to submit appropriate Suspicious Activity Reports (SARs) to the National Crime Agency (NCA). This included the Anti Money Laundering/​Counter Terrorism Financing (AML/​CFT), which required banks and building societies to monitor customer transactions and report any suspicious activity to the Serious Organized Crime Agency (now replaced by the NCA) and the former e-​Borders program, which compelled airlines to collect passport data in advance of travel and transfer it to the Border Agency for screening against watch-​lists (Ball et al, 2015, p. 21). In the pre-​crime literature, it is often argued that the major driver behind new pre-​crime measures is ‘global terrorism’ and the events of 9/​11 in the US and 7/​7 London bombings in particular (Zedner, 2007; McCulloch & Pickering, 2009). Nonetheless, we would argue that the emergence of new pre-​crime surveillance measures is best viewed as a ‘field effect’ where a multiplicity of interacting factors is involved (Bonelli & Bigo, 2005). For instance, many of the surveillance related measures introduced as part of the so-​called ‘war on terror’ (e.g. wiretapping, widening government access to data held by internet service providers etc.) were recycled from earlier legislative efforts that were said to be essential for the international ‘war on drugs’ or ‘money laundering’ (Haggerty & Gazso, 2005).5 Thus, while international terrorism and security are clearly important drivers of the pre-​crime society, the ‘preventative turn’ is also connected to much earlier efforts designed to control the problem populations generated by neoliberal economic policies (Wacquant, 2009). Bourdieu’s (2014) notion of the ‘bureaucratic field’ allows us to critically engage with theories of ‘governmentality’ and ‘societies

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of control’ that often underestimate how neoliberal strategies of deregulation, privatization and outsourcing can serve to strengthen the position of political elites (Scott, 2013). It is now ‘absolutely clear for example that earlier characterizations of neoliberalism as simply the “retreat of the state” were wide of the mark’ (Squires & Lea, 2012, p. 1). The most striking example of recent years to support this view, are the revelations of former National Security Agency (NSA) employee Edward Snowden, which made it clear that state intelligence agencies were engaging in mass surveillance of their own citizens. The revelations revealed that the British Government Communications Headquarters (GCHQ) had used intercepts on the fiber optic cables that make up the backbone of the Internet to gain access to large amounts of information on Internet users’ personal data. As we have seen, state-​initiated responsibilization strategies have also compelled by law the private sector (financial institutions, internet giants, travel agents etc.) to collect large volumes of information on their customers and conduct surveillance on the state’s behalf. Thus, while concepts such as ‘plural policing’, ‘surveillance assemblage’ or ‘networked governance’ may capture some of the complex connections between police, private security, technology companies, and software designers, ‘the Bourdieuian perspective allows us to retain an appreciation of the continued power, both materially and symbolically, of state security and its varied relations to private actors’ (Abrahamsen & Williams, 2011, p. 16). Once again state-​initiated responsibilization measures are refracted through ‘fields of practice’ and mediated by a field-​specific ‘habitus’. Empirical research in a range of settings has shown that despite the decline of the penal-​welfare model, those working within the ‘left hand’ of the state have often opposed the measures introduced by the ‘right hand’ of the state (Bourdieu, 1998, p. 2). In Australia, for example, practitioners working within ‘welfarist’ working cultures obstructed the introduction of public space surveillance cameras (Sutton & Wilson, 2004). Similarly, research has shown how ‘welfare agency staff assisted clients in bettering the surveillance system’ through the use of ‘head nods (yes) or shakes (no) as the client responded to questions during intake interviews that were logging data into the system’ (Gilliom & Monahan, 2012, p. 408). At the micro-​level of probation practice, meanwhile, it has been shown that the ‘right hand’ of the state is not always aware of what the ‘left hand’ is doing as ‘risk-​based’ discourses are filtered through the occupational concerns of front-​line practitioners who continue to be guided by the old ‘welfare’ mentality rather than the ‘risk’ mentality (Kemshall & Maguire, 2001). Similarly, state-​initiated responsibilization strategies designed to mobilize those

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working in health and education have been contested. This includes those academics opposed to the Government’s Prevent strategy designed to engage with people believed to be at risk of radicalization. One group of academics claimed that the Extremism Risk Guidance 22+ underpinning the program is based on ‘flawed science’ and does not even ‘factor political grievance into the modelling’ (The Guardian, 2016). Thus, while internal divisions within the bureaucratic field may have given rise to new forms of pre-​emptive surveillance in a range of different settings, pre-​crime mentalities have not fully taken root in ‘the heads and habitus of penal agents’ (Page, 2013, p. 158) working in the crime control field, or in the heads of those working in the left hand of the state who ‘have an interest in defending the state, particularly its social aspect’ (Bourdieu, 1998, p. 41).

Data politics and the technological field of expertise A central theme in Bourdieu’s (2014) writings on ‘fields of practice’ is ‘the importance of the symbolic, or cultural, dimension in the struggle for power’ (Albert & Kleinman, 2011, p. 266). The ‘field of policing’ (like all fields) is characterized by the appearance of a specialized elite who come to monopolize socially recognized forms of expertise of which they are the exclusive holders. Historically the police have been able to command substantial economic capital (in terms of budget, technological and human capacities); social/​political capital (derived from their proximity to agents in the political or bureaucratic field); cultural capital (including unique expertise on crime prevention and law enforcement); and symbolic capital through the various mechanisms that confer legitimacy to the organization (Dupont, 2004). However, as we have seen, this dominant position has been challenged by a number of developments, including the emergence of a technological field of expertise that has boosted the position of security companies providing biometrics, databases and profiling (Bonelli & Bigo, 2005). The connection of ‘myriad distributed people (software designers, data handlers, intelligence officers) and technologies (computers, devices, software, algorithms)’ (Ruppert et al, 2017, p. 3) raises a number of issues that require further research. One approach would be to provide an examination of the informal networks and cross-​overs that exist between police, security and technology experts and the role played by private companies that may act as software or hardware consultants to the police or assist in requirements mapping and training. Based on her observations of interactions between law enforcement officers

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and software representatives at surveillance industry conferences, Sarah Brayne (2017, p. 996) has argued that ‘instead of filling analytic gaps or technical voids identified by law enforcement’, the tech companies and their representatives are creating ‘new kinds of institutional demand’ (Brayne, 2017, p. 996) by encouraging police organizations to purchase new technological systems and software solutions. Further research might want to explore how the adoption of these new software platforms shapes police practice. It has already been reported that police use of social media software leads police officers to adopt the terminology used in the ‘field of marketing’ (e.g. ‘sentiment’ and ‘influencers’) as customer relations management (CRM) techniques and language becomes embedded in ‘law enforcement’ (Dencik et al, 2017, p. 13). Another approach would be to combine some of the insights of science and technology studies and critical data studies (Kitchin, 2017) with their focus on materiality, technology, human/​non-​human relations and the ‘symbolic power of algorithms’ (Beer, 2017), with field theory, which allows us to examine which agents in the ‘network’ have power (i.e. capitals). As Ruppert et al have argued: ‘Data does not happen through unstructured social practices but through structured and structuring fields in and through which various agents and their interests generate forms of expertise, interpretation, concepts, and methods that collectively function as fields of power and knowledge’ (Ruppert, Isin & Bigo, 2017, p. 3). The emphasis placed on ‘materiality’ and ‘technology’ in science, technology, and society (STS) has been taken up by surveillance theorists who are keen to draw attention to some of the political and ethical issues surrounding the construction of socio-​technical surveillance systems that often remain opaque and hidden from public scrutiny. David Lyon (2014), for example, points out that while much of the talk surrounding big data and surveillance describes these processes in terms of ‘clouds’ and ‘data streams’, there is, as the Snowden revelations made clear, a materiality and geography to big data surveillance. This includes the data warehouses and fiber optic cables that placed the US and UK intelligence agencies in an advantageous position and enabled those agencies to collect data upstream. At a more mundane and local level, we need to know how technology companies, software designers and coders work with the police to provide the information infrastructure required for the purpose of pre-​crime surveillance and how this might be shaping police practice. For instance, to what extent are the principles of accountability and transparency undermined when ‘the algorithms used for predictive policing remain obscure to both police

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and the public’ (Dencick, Hintz & Carey, 2017, p. 13). It is partly due to this invisibility that the authorities are able to present ‘algorithmic’ systems as a form of scientific and value neutral information that offers ‘a more rational, impartial, reliable and legitimate way of decision-​ making’ (Mayor-​Schonberger & Cukier, 2013, in Dencik, Hintz & Carey, 2017, p. 3). Further research is required to explore how ‘human interventions may insert pre-​existing biases and agendas into predictive policing’ (Dencik, Hintz & Carey, 2017, p. 14). It might be useful to explore these issues by combining ‘critical algorithm studies’ (Seaver, 2017) with ‘dynamic nominalism’ (Hacking, 2006). Ian Hacking has ‘long been interested in classifications of people, in how they affect the people classified, and how the effects on the people in turn change the classifications’ (Hacking, 2006, p. 2). But how is this ‘looping effect’ (i.e. ‘the way in which a classification may interact with the people classified’) likely to play out in a socio-​ technical environment where algorithmic decision-​making meets police discretionary powers? For instance, the information entered into new software systems for predictive analytics is often the product of hidden police discretion. If this information on arrests is used ‘to focus police resources, this can lead to further discretionary arrest patterns against the same neighbourhoods and people’ (Joh, 2016, pp. 30–​1). In this respect, predictive models are performative, ‘creating a feedback loop in which they not only predict events such as crime or police contact, but also contribute to their future occurrence’ (Brayne, 2017, p. 998). The use of algorithms to classify suspects as ‘high-​r isk’ means that ‘prolific’ offenders are likely to receive further attention from the police in the form of police deployment, stop and search or home visits (see McCahill & Finn, 2014). This extra attention from the authorities may result in an alteration to the original classification of the classified. Finally, this alteration to the original classification may have further consequences or impacts on those who are classified. However, once all of this is ‘transformed into data, this information can appear neutral and objective, even though they are the products of individual discretionary decisions’ (Joh, 2016, pp. 30–​1).

Conclusion A central theme in the literature on surveillance and pre-​crime is that predictive policing ‘shifts the temporal perspective to anticipate and forestall that which has not yet occurred and may never do so’ (Zedner, 2010, p. 24). There is no doubt that the pre-​emptive turn has accelerated in recent years with the emergence of big data flows

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that emerge out of everyday activities as people interact with social networks and mobile devices that produce data that can be combined with software or algorithms and used by the police to search for patterns or trends for the purposes of governance, policing and security. A recent review of the field in the UK has shown that ‘the use of big data technology for policing has so far been limited’ (Babuta, 2017, p. vii). Nonetheless, the report goes on to state that ‘as sophisticated technologies become available at increasingly low cost, the effective use of big data will become a top priority for the police and other law enforcement agencies’ (Babuta, 2017, p. 1). This is supported by the National Police Chiefs Council’s (NPCC) commitment to improve digital intelligence and evidence gathering and by the announcement of one billion of increased funding for policing, including £175 million to drive police transformation through digital and technological projects (NPCC, 2018). However, as we have shown in this chapter, new surveillance technologies and digital solutions ‘are integrated into social worlds and into everyday practices only if they are seen by actors as helping them in their power struggles’ (Bigo & Bonelli, 2019, p. 108). Thus, rather beginning with abstract statements on the emergence of ‘societies of control’ (Deleuze, 1992) or the ‘pre-​crime society’ (Zedner, 2007), we began with ‘those little questions that big theorists abandon’ (Bourdieu, 2014, p. 109). By approaching the problem in this way, we discovered ‘a space of competing agents’ (Bourdieu, 2014, p. 111) within the ‘field of policing’, some with technical expertise on the operation of pre-​crime surveillance technologies, some with knowledge of organizational and legal frameworks, some committed to the new pre-​crime mentalities, others committed to the old ‘community policing’ methods, some with operational competence and some with informational competence (Bigo et al, 2007). From this complex balance of forces, a diverse group of actors working within the field of policing compete over forms of capital (economic, social, cultural and symbolic) that act as key resources in determining who has the power to develop, enforce, shape or evade crime control policies and strategies (Bourdieu, 2014, p. 111). Thus, rather than begin with abstract statements on the ‘pre-​crime society’, the chapter calls for police researchers to examine surveillance in practice and then work back up to the ‘pre-​crime society’ or ‘surveillance state’ to explore the ‘big’ questions that grand theorists outline at the outset. A second question for police researchers to explore is the issue of whether ‘digital technologies professionals’ are beginning to ‘impose their own interests and professional values’ (Bigo & Bonelli, 2019, p. 120) on a field previously dominated by law enforcement officers.

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While some have attempted to promote the technologies underpinning pre-​crime (e.g. ‘machine learning’ and ‘algorithms’) as ‘visions of calculative objectivity’ (Beer, 2017, p. 1), critical data studies writers are quick to point out that new forms of predictive analytics are used to ‘search, collate, sort, categorize, group, match, analyse, profile, model, simulate, visualize and regulate people, processes and places’ (Kitchin, 2017, p. 18). Researching these issues however is not straightforward because algorithms are formulated in private settings and many companies use nondisclosure agreements to prevent the police from disclosing any information relating to surveillance equipment to third parties (Joh, 2016, p. 39). All the same, as Seaver (2017, p. 7) points out, ‘if our interest is not in the specific configuration of a particular algorithm at one moment in time, but in the more persistent worlds algorithms are part of, then useful evidence is not bound by corporate secrecy’. This could include the use of technology company documents, industry material, case studies, promotional online videos and attendance at surveillance industry conferences to examine the ‘symbolic’ power of ‘machine learning’ and ‘algorithms’. In other words, ‘the discourses surrounding and promoting them, and how they are understood by those that create and promote them’ (Kitchin, 2017, p. 25). This could be accompanied by interviews with representatives of technology companies (e.g. technology experts, software designers and coders) to examine the role played by private companies that may act as software or hardware consultants to the police or assist in requirements mapping, training, the disclosure of data types, sources and storage so that the most suitable technology can be recommended. There is one final aspect of the ‘politics of pre-​crime’ that we think has been neglected by those researching pre-​crime policing. This concerns the question of how data subjects experience and respond to being monitored by new surveillance technologies. The pre-​crime literature as we have seen tends to talk about ‘statistics’, ‘algorithmic predictions’, ‘profiles’ and ‘populations’ with no mention of ‘pre-​ crime subjects’. Here surveillance subjects are presented as ‘dividuals’ or ‘monads’, ‘beings beyond human perception’ that require database devices ‘to mediate and make them visible’ (Ruppert, 2012, p. 126). All the same, we should not assume that surveillance subjects are completely unaware of big data surveillance and pre-​emptive policing strategies. In another context, Bourdieu (1990) has referred to the ‘lucidity of the excluded’ to illustrate how the exclusion of marginalized groups from certain realms of privilege can often accord them a certain critical insight into the structures that oppress them (see McNay, 2000). This

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principle applies equally to how marginalized groups might experience pre-​crime policing and surveillance. As Ball et al (2016) have argued, while big data surveillance processes are difficult to identify, they ‘can also have a sudden, non-​negotiable and destabilizing presence if attention is drawn to it’. ‘Those moments of noticing—​however momentary they are—​ become moments of connection, as the individual realizes their place in a much larger infrastructure and notices the identity category to which they are assigned’ (Ball et al, 2016, p. 73). These moments of noticing pre-​emptive surveillance may occur when police officers, deployed by CCTV operators, suddenly arrive ‘out of the blue’ to intervene before the suspects have committed any wrongdoing (McCahill & Finn, 2014), or when ‘prolific offenders’ read the details on ‘multi-​agency’ information-​sharing agreements on the consent forms that they are required to sign (McCahill & Finn, 2014). Some moments of noticing come too late when, for instance, information exchange between welfare offices and criminal justice facilitates the introduction of ‘sting operations’ in food stamp offices. Here it has been reported that ‘individuals with outstanding warrants would receive a phone call indicating there was a problem with their benefits’ only to find, upon arrival, that ‘an officer from the sheriff’s department would serve them an arrest warrant’ (Brayne, 2014, p. 371). As many criminologists have shown, one of the crucial processes involved in ‘desistance’ from crime are the ‘subjective’ changes that take place among offenders and, in particular, the ability to develop ‘a new perspective on the self ’ (Shover, 1985). In the pre-​crime society, many suspects have to find a way of leaving behind not only the ‘old’ self but also the ‘digital self ’ that is generated by the use of ‘new surveillance’ technologies and shared among diverse agencies. As Brayne (2014) has shown, individuals who have had contact with the criminal justice system (e.g. have been stopped by police, arrested, convicted, or incarcerated) are less likely (than those who have not had contact with criminal justice institutions) to interact with other surveilling institutions that collect big data such as medical, financial, labor market and educational institutions. In this respect, the fusion of penal-​welfare systems and the integration of discrete databases may serve simply to reinforce existing social divisions as those on the receiving end of ‘pre-​ crime’ mentalities avoid those institutions (health, education, finance and welfare) that are pivotal for desistance and reintegration. If this is the case, it may be that rather than ‘forestall that which has not yet occurred’ (Zedner, 2010, p. 24), pre-​crime policing and surveillance may simply result in further crimes.

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Notes 1

2

3

4

5

The chapter focuses mainly on the UK but also draws upon empirical studies on policing and new surveillance conducted in other neoliberal countries including the USA, Canada and Australia. The bureaucratic field is defined as ‘a splintered space of forces, vying over the definition and distribution of public goods’ (Wacquant, 2010, p. 200). Loic Wacquant (2009) fills a gap in Bourdieu’s writing on the ‘bureaucratic field’ by including policing and criminal justice institutions as core constituents of the ‘right hand’ of the state. In one south London shopping mall, private security officers had the facility to pull down the images displayed by council-​operated public space CCTV cameras (Norris & McCahill, 2006), while in public space CCTV control rooms, retail radio network connect police officers and private security officers working in a range of different public and private settings (Norris & Armstrong, 1999). McCulloch and Pickering (2009, p. 62) point out that ‘pre-​crime counter-​terrorism measures can be traced through a number of interlinking historical trajectories including the wars on crime and drugs, criminalization and, more fundamentally, in colonial strategiesof domination, control and repression’.

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Dataveillance and the Dividuated Self: The Everyday Digital Surveillance of Young People Clare Southerton and Emmeline Taylor

Introduction ‘Data is the new currency’ has become a deceptively simple mantra of the past decade; it is the oil of the digital era, the hitherto untapped gold mine of the 21st century. If we take the metaphor a little further and think of the phrase ‘to have currency’ (meaning something has a lot of value), is it then to suggest that those who produce more data should be considered to be more active and engaged citizens, and those who do not produce data—​or produce less of it—​are of less value? Furthermore, if data is as valuable a commodity as the metaphors suggest, it might follow that there would be significant regulation and safeguards about how, when and why it is harvested from the individuals that generate it. In this chapter, we seek to explore the multiple ways in which young people experience everyday monitoring and dataveillance. The chapter is divided into three main sections. Firstly, we explore the concept of dataveillance, paying special attention to the way that it can be instructive and shape behavior. There is a pervasive presumption, similar to the excavation of oil, that data can be extracted from people and actions with little impact upon them. We seek to trouble this notion by exploring the way in which data and its uses are mutually transformative, shaping the future decisions and actions

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of data subjects. Framing the emergence of dataveillance with the Deleuzian concept of ‘dividuation’, we examine how the datafication industry has real consequences for young people. In a field in which empirical data is scarce, in the second section we draw upon findings from a study with young people themselves. In particular, there is a lack of research that gives young people the opportunity to define and identify the forms of surveillance they feel and experience. The findings are structured by a broad taxonomy of surveillance devices; visual, biometric, spatial and algorithmic in order to explicate the multiple ways in which the self becomes fragmented—​dividuated—​across data-​ harvesting technologies. The third and final section presents the key ethical concerns regarding the surveillance of young people. We argue that an approach that is oriented towards dividuals allows a rich and nuanced understanding of data ethics. We contend that this approach avoids neoliberal logics of ‘personal responsibility’ based on consent/​ non-​consent (Papathanassopoulos et al, 2016; Marwick et al, 2017) and provides a more complex account of the conditions under which data is collected.

Dataveillance, the dividuated self and young people More than 30 years ago, Roger Clarke (1988, p. 498) originally developed the concept of dataveillance, defining it as ‘the systematic use of personal data systems in the investigation or monitoring of the actions or communications of one or more persons’. Yet since this early conceptualizing, the scope of dataveillance has expanded considerably as data continues at pace to shape our everyday lives. Degli Esposti (2014, p. 210) argues that ‘dataveillance specifically indicates the ability of reorienting, or nudging, individuals’ future behavior by means of four classes of actions: “recorded observation”; “identification and tracking”; “analytical intervention”; and “behavioral manipulation” ’. It is precisely this ability of dataveillance to enlist data users and shape their future actions by means of multiple and overlapping modes of data collection that this chapter is concerned with. We can situate the emergence of dataveillance within broader trends of datafication, in which subjects, objects and practices are increasingly transformed into digital data. Datafication is a term that has been used to describe the process by which more and more aspects of social life are rendered machine-​readable, quantifiable by virtue of the fact that more of social life plays out in digital spaces (Mayer-​Schönberger & Cukier, 2013; van Dijck, 2014). This datafication also facilitates greater

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dataveillance, through which data is aggregated and analyzed. Alongside this process is the logic of datafication, which views subjects and objects and their interactions potential data sources that can be ‘mined’ for correlations or sold. Media scholar José van Dijck (2014) uses the term ‘dataism’ to describes the pervasive ideology of datafication, which takes as a given the insights of aggregated data as truth. What could be called the ‘datafication of social life’—that is the data-​traces that online interactions generate—makes this dataveillance possible. Given the central role social media platforms have come to play in the formation and maintenance of social connections, these connections are now able to be collected as pieces of data in the form of comments, likes, shares and clicks. Digital daily life also involves a range of other data-​r ich activities including online shopping, web browsing and digital content streaming (Lupton, 2019). Smartphones, now used by nine out of ten Australians (Deloitte, 2019) and 81% of people in the United States (Pew Research Center, 2019), with their geo-​locative capacities, now facilitate richer data as users move about during the day. Thus, a young person’s commute to school, university or work now generates data that could be combined with the social media browsing history from their device as they waited for the train, their google maps search for a nearby coffee shop—​with many transit systems too now using trackable tap-​on-​and-​off card systems that also generate data (Galdon-​Clavell, 2013; Wigan & Clarke, 2006; Kitchin, 2014b). The very routines of daily life are now rich sources of digitized information. Indeed, it is precisely because this dataveillance operates through habitual practices that it largely goes unnoticed (Southerton & Taylor, 2020). Young people are particularly impacted by this datafication of social life and growing dataveillance, as they are the most likely to use social media platforms (Miller-​Bakewell et al, 2015; Perrin, 2015). Existing scholarship also emphasizes that online spaces can be important sources of peer support and play a role in the development of a young person’s identity (Hanckel et al, 2019; McCann & Southerton, 2019). Datafication also extends into the lives of young people far beyond social media and earlier than their teen years, as children are increasingly monitored in schools by Radio-​frequency identification (RFID) tags in uniforms, facial recognition enabled CCTV and online monitoring of classwork (Taylor, 2013). Dataveillance has also impacted childhood beyond education, as scholars have highlighted, through child tracking devices and apps (Taylor & Michael, 2016; Hasinoff, 2017). Young people have largely been characterized as ignorant of or indifferent to surveillance or privacy concerns—​especially given the

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rise of social media and digital culture (Barnes, 2006; Taddicken, 2014). However, recent studies have suggested that young peoples’ ambivalence around the concept of privacy may have more to do with confronting the impossibility of managing digital privacy at an individual level, rather than an overall rejection of privacy as a right or something desirable (boyd & Hargittai, 2010; Tufekci, 2012; Marwick & boyd, 2014; Hargittai & Marwick, 2016; De Wolf, 2019). Young people also engage in a range of privacy protective strategies (boyd & Hargittai, 2010; Marwick et al, 2017; Quinn & Papacharissi, 2018; Zillich & Müller, 2019); a nationally representative survey in the UK of 2000 participants found that young people are the most likely to have checked privacy settings on social media (Blank et al, 2014). However, as Marwick and boyd (2014, p. 1064) explain, these strategies cannot address the widespread structural failures of platforms: ‘The privacy practices and strategies that teenagers engage in do not necessarily ‘solve’ the problem of privacy, but they do reveal how the technical affordances of networked publics are insufficient to protect privacy.’ Choi et al (2018, p. 42) have coined the term ‘privacy fatigue’ to describe the ‘emotional exhaustion and cynicism’ that characterizes social media users’ relationships to privacy following futile attempts to control their data, especially given that almost every platform they use requires they give it up. Given that existing research within critical youth studies urges for the accounts of young people to be prioritized (Allen, 2008; Best, 2007; Clark-I​ báñez, 2007), and a dearth of empirical studies that respond to this, we wish to foreground the voices of young people in tracing the different surveillant modes in their everyday experience using a photo elicitation method. Participants took photographs that captured their experience of surveillance and we allowed their interpretation of surveillance to direct the images.1 Consequently, the findings that form the basis of this chapter reveal the ways that different modes or expressions of surveillance emerge, interact and are interconnected over the course of a week in a young person’s life. Our participants traced moments of ordinary surveillance and data collection, the kind of routine surveillant modulation that philosopher Gilles Deleuze describes in the essay Postscript on the Societies of Control (1992). Deleuze attempts to move beyond Michel Foucault’s historical understanding of ‘disciplinary societies’ in which society is bounded by and exercised within clearly defined institutions, towards ‘societies of control’. According to Deleuze, the ‘environments of enclosure’ (schools, hospitals, the factory and so on) in which disciplinary power is exercised have been displaced by a kind of ‘free-​floating control’

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that is no longer confined to these institutions; control is all around rather than confined to specific times and locations. Deleuze rejects the notion of a universal subject and takes this notion further, arguing that subjects are never stable but rather in a perpetual state of metastability. ‘The numerical language of control is made of codes that mark access to information, or reject it. We no longer find ourselves dealing with the mass/​individual pair. Individuals have become “dividuals”, and masses, samples, data, markets, or “banks” ’ (Deleuze, 1992, p. 5). Power is individualizing but there is never a final individual, rather a ‘dividual’ who is inseparable from the relations in which they form and reform. Surveillance, then, is oriented not towards the subject but towards dividuals, which are made up of extracted pieces of information that can be connected to each other (Cameron, 2004). The modulation of control is both impersonal and intimate in the sense that these systems are largely disinterested in the whole person; but the data harvested is detailed, specific and extends into almost every aspect of their lives. As Heather Cameron (2004, p. 140) explains, ‘Societies of Control are not interested as much in the soul or what sins people have committed, but in behaviour and what future actions can be predicted.’ It would be a mistake to suggest that the data aggregated represents an accurate capture of a young person’s life. Indeed, it is important not to allow the marketed predictive capacity and objective capture of big data analytics to be taken at face value. As Rob Kitchin (2014a) argues, data sets are always framed through a particular lens and big data sets are no exception to this. Bringing together large datasets can establish correlations between seemingly disparate variables, for example comparing the words entered into search engines with hospital admissions numbers from digitized hospital records. However, when being presented as proof of a causal relationship, this can produce misleading results that are presented as insight (Kitchin, 2014a). Despite its questionable insight, this data is intimately entangled with a user’s access to a wide range of daily practices. In many ways, the societies of control can feel like they provide greater freedom because the exercise of power is no longer always visible—​there is no longer a guard in the watchtower or a factory manager overseeing conduct. Power and control become hidden—​embedded in codes and algorithms, which makes it very difficult to pinpoint and articulate the constraints that dictate, shape and bound behavior (Cheney-​ Lippold, 2011). We argue that Deleuze’s concept of the dividuation and conceptualization of surveillance as modulation offers a productive way to examine the multiple surveillant technologies encountered by our participants. We draw on the concept of dividuation, in particular,

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because it has significant implications for thinking through the question of choice—​which has become an important part of debates around privacy and young people’s data sharing practices. If we challenge an understanding of surveillance as a form of power exercised over rational subjects, who ought to seek their freedom, and instead understand it as operating through the modulation of capacities, the implications are significant. To limit our understanding of surveillance to this framework reduces individuals to oppressed subjects who are always already manipulated. To conceptualize young people in this manner is, in particular, to contribute to an already well-​established patronizing narrative. In contrast, if we acknowledge surveillance as deeply embedded in enabling systems, how might we think about who ought to be held to account when it comes to the use and misuse of personal information? In the following analysis, we focus on four modes of surveillance that our participants described and photographed: visual, biometric, spatial and algorithmic.

Visual Participants in our study recounted and depicted with their images the ways visual surveillance emerged as part of their everyday routines. They often reflected on realizing a CCTV camera was positioned in a place they regularly frequented and they had not noticed it until tasked with completing the photo diary. One participant, Jacob (19 years old), took a photo of a surveillance camera in his university accommodation. The photograph depicts a round camera attached to a beige ceiling lined with ceiling tiles, with white-​framed windows visible in the bottom left of the frame. In the interview, Jacob describes the prevalence of these cameras in different parts of his accommodation and across the university campus, with the photograph attempting to capture this: ‘Sort of, like, how in all aspects of our days we’re always being watched. I’m, like, making dinner, making lunch I’m always being watched. And it’s usually … hidden away, like, not really hidden but it’s … whenever you try to look up … that we’re being surveilled and the surveillance is happening … Because just, like, the main base behind most of these things is that any point in time someone could be watching me.’ In his retelling of the encounter with the CCTV camera, Jacob is focused on the location and on the activities he is undertaking

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there—​making dinner or lunch. Jacob’s description of the camera also emphasizes its always-​on capacity to observe him. Similarly, another participant, Chistopher (21 years old) described being under CCTV in his workplace and captured a photograph of the screens in the room where the CCTV footage could be viewed. Christopher similarly emphasizes the location, activity and time as central to this form of surveillance, as he lists the areas of his workplace that have cameras and explains what impacts his comfort with the cameras: ‘‘I think it’s reasonable, because if there’s an incident they would want to record that and have that as backup. Say a customer gets rowdy and wants to raise an issue with the club, the club can say ‘here’s the evidence’.” Both participants emphasize the potential of the CCTV, to be watching in case something happens or possibly watching them at any moment in time. Furthermore, the emphasis on events and moments in time (cooking dinner, a potential altercation) suggests the orientation of the camera is towards not necessarily individuals, as we might think of them, but selecting out relevant incidents from all the data it has collected. We can see the kind of ‘nudging’ that Esposti (2014) described as one key ability of dataveillance. Both Jacob and Christopher describe their encounters with CCTV as more about an awareness or potentiality, which may not directly instruct them towards a specific action but rather incline them towards or away from behavior that they may feel uncomfortable having recorded. What we see here also offers an important point of reflection on how our participants are constituted as fragments of data through these surveillant practices. In the instances described previously, the focus is not on the actualization of an event but rather on its potential, a kind of continuous modulation of the capacities of the spaces in which the CCTV is installed. Drawing on a Deleuzian framework, what this mode of surveillance is oriented towards is not purely a disciplinary model under which criminality is punished, but rather this system is both enabling and constraining. Christopher explains that he feels safer because the CCTV allows him to prove his work behavior is appropriate if challenged, it eases some parts of his work because some security measures are reduced knowing the recording is available. On the other hand, Jacob describes the way the potential recording acts to modulate his capacities: ‘‘I dunno if I’ve been watched and where I’m being watched. Umm … and just the scare factor.’’ In referring to the ‘scare factor’ Jacob gestures to the kind of subtle affective atmospheric modulation of CCTV. We can observe from these narratives that these layers of surveillance are oriented not towards the individual but rather towards measurable units of time and target the level of the capacity to do something

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(Deleuze, 1992). As Cameron (2004, p. 141) argues, ‘the development of CCTV as a surveillance technology fits into the model of power offered by Foucault and improved by Deleuze of dividing groups into measurable units and then reassembling them for various purposes’. Both Jacob and Christopher are captured in CCTV in fragmentations, in frames of video that can be stored as information—​valuable for their potential use and for their management of risk, rather than necessarily what they afford in the moment.

Biometric and wearable technologies Wearable technologies and their analytic algorithms have the ability to redefine the way that children (and adults) understand and experience their bodies. Vander Schee (2009, p. 558) asserts that surveillance apparatus broadcast particular ‘knowledges and truths about the ways in which individuals should conduct their lives for the betterment of self and society’. The ‘algorithmic skin’ (Williamson, 2015) worn by children in education shapes their subjectivity and exerts a tremendous influence on their being. The ‘quantified child’ knows that they are the subject of continuous monitoring, and that the interpretation of their biophysical data will furnish particular decisions about them or invite action based on their health, well-​being and intellect. For our participants, there were a few forms of surveillance that they made reference to with their photo diary that were associated with the use of biometrics. Though these tended to be less ‘ordinary’ events—​more often than not they referred to moments the participant was traveling—​but nonetheless they facilitated conversation about how these sensors felt for the participant and what they considered to be acceptable or not acceptable. Emily (19 years old) captured an image that referenced going to the airport recently, for the first time since facial recognition had been introduced as part of the immigration process: ‘everything is automated so instead of seeing a person it’s … you put your passport in a, like a face recognition thing and it just takes photo of you and it, like, recognizes your face and you just go through. And I thought that was kind of … really odd and kind of scary at the same time. Like, this isn’t a person and … they’ve got my face, like, total face … facial recognition. And it was, like, really out of this world kind of thing … I dunno it’s kind of, like, a trust thing. Like it kind of freaks me out that they’re able to do

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that and that they put so much trust in that machine to be able to do it correctly.’ While Emily describes being somewhat uncomfortable, her encounter with the new technology was also an enthusiastic one as she explains that ‘‘[i]‌t was kind of exciting to be taking part in that kind of new age technology but also scary’’. She describes the process by which she is confronted by herself reconstituted as data, with her passport being associated with digitally enhanced photograph that enabled facial recognition. The process is an account of her encounter with a checkpoint through which the dividual of Emily’s biometric information is constituted through a range of physical and digital objects, facilitating her travel and the tracking of her movement. At the same time, the newness and unfamiliarity of the process means that it is perceptible to her as a process of fragmentation, which may, with time, become familiar and routine. The biometric passport or e-​passport embodies the identification and tracking capabilities of dataveillance (Esposti, 2014) Though it is assigned to an individual citizen, the value of these passports lies in their operation as part of access-​control systems that modulate the flow of people through national border checkpoints using automated checking mechanisms. They are part of the micro-​level operations of power through controlling access to these thresholds (Massumi, 2002). Deleuze (1992) argues that in control societies, code becomes the central language and it is through code that dividuals are constituted. Further, Cameron (2004, p. 140) describes dividuals as ‘composites of various codes and group identifiers which can be structured and localized based on a particular piece of structuring information—​e.g. the postal code which indicates where one lives’. The corporeal body is thus fragmented into units of data and coded information that are used as a proxy measure for the whole.

Spatial Our participants often described moments where their awareness was drawn to forms of location-​based surveillance, where their movements were recorded or accessible information. There was a wide variation in how participants felt about whether their location was personal information or not. One participant, Madhavi (19 years old), described discomfort around being uncertain about who has access to the information about where she has swiped into on campus with her ID card:

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‘So essentially for all the buildings if you tap your ID it’s on record what time you got in to the building and what time you got out. So … (laughs) … cameras … and that’s what I mean … cameras is something like an obviously thing with you being recording but now with IDs and [bus cards], you know, our own IDs, I feel it’s that … I’m known, like you know, kind of like … little sneaky hidden way of keeping an eye on you if someone wants to.’ For Madhavi, the sense that her movements and location can be traced, makes her feel exposed—​in her own words she feels ‘known’ (emphasis added) and this is uncomfortable. However, she considers the boundaries of what is acceptable and what is not acceptable, conceding that she finds it okay for the government to have this information but not give it to third parties. ‘I’m not special, if they want to keep an eye on which bus I go to and which ATM I get out of that’s okay’. Her encounters with these systems cultivate, at the same time as they are uncomfortable to her, a sense of their mundanity and her own mundanity in them. This renders them more acceptable. We can see a similar normalizing of location awareness in a different setting when Emily (19 years old) describes the ways that displaying and sharing her location with others can be part of the pleasures of digital social life—​though she has a very different reaction to her location being known to Madhavi. In the interview, she presented a screenshot she had taken of her iPhone that depicted her ‘location settings’, which determinine which apps could access the geolocation information her smartphone collects. She reflected on how she felt about her location information being used by different apps: ‘Like, I actually, on Facebook, have my location, like, I’m pretty sure that anyone can just see where I am at any point (laughs). I kind of think that’s a bit cool. Like I just don’t really think anyone would … like if someone went to the lengths of actually wanting to know where I am and, like, because only my friends can see that, it’d be like kind of like ‘‘Cool! Someone wants to know where I am!’ ’’ Emily describes a feeling of excitement at the idea that one of her Facebook friends could find out her location, using the information she shares on the site. Her account is punctuated by laughter, perhaps an indicator that the statement ‘anyone can see where I am at any

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point’ is somewhat playful. However, her account suggests she feels that having her location known is not only not invasive but also normal and desirable. Other participants echoed these sentiments, with another participant, Olivia (19 years old) capturing a photo using a location-​ specific filter on the photo sharing app Snapchat as part of her photo diary. She described the use of the filter and its location information as something that emphasizes social status, that displaying access to certain locations in your image was desirable rather than invasive. She describes it as ‘‘kinda like … powerful to be able to tag yourself in these cool places’’. At the same time, Olivia acknowledges that the capacity of the smartphone to collect the data does not enter into this evaluation of tagging yourself in the location, as she explains ‘‘you don’t really think about how your phone has just … you know, known where you are at that exact point in time to allow you to do that’’. When it comes to ‘opting out’ of apps like Snapchat that collect your location data or even not using a smartphone it is very clear that the access they grant young people to vital social connections is far too important. Olivia explains this clearly, when she discusses her lack of engagement with privacy agreements on social media platforms: ‘And I think even if I had read [the privacy agreement] and they say ‘‘by the way, we get to keep all your photos and we own them now’’, people would probably still sign up to it just because without Snapchat … you are left out of a … massive part of, like, a social … like your social circle. So … people don’t look at the terms and conditions but I think even if they did it’d still, you’d still maybe click yes because it’s such an important part of life anyway.’ From Olivia’s description here, we can begin to trace the central role an app like Snapchat plays in young people’s social interactions. Returning to Deleuze’s (1992) conceptualization of a control society here, the complexity of the so-​called choice young people are presented with is clearer. Such privacy agreements cannot offer the conditions of any meaningful consent when we consider that the location data collected by ID cards and bus cards—​in Madhavi’s example—​are access mechanisms that modulate capacities through withholding and granting access to specific functions or spaces. Furthermore, for many young people social media platforms like Snapchat and Facebook—​as Olivia and Emily described—​provide just as essential a service as accessing a bus or entering a room on the university campus. They cannot

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withhold their data from these services without facing repercussions for the ease of their physical movement and social interactions.

Algorithmic A significant number of our participants took photographs that made reference to the ways they experienced surveillance that was largely algorithmic—​that is surveillance that is undertaken on the basis of reducing their activities to data that can be analyzed computationally or what Esposti (2014) terms ‘analytical intervention’. Targeted advertisements were a readily recognizably way that participants saw their digital data presented back to them. Participants reflected in their interviews about how they felt when they encountered a targeted advertisement and the associated collection of data from their online browsing practices that made the advertisement possible. Sarah (19 years old) took a photograph of a targeted ad on her Facebook feed and reflected on how she felt the advertisement might have categorized her according to her demographics: ‘Everyone’s just like ‘‘Oh it’s just Facebook, it’s just ads’’ but they’re actually going through so much of your data and your searches and things. Tailor everything to you … It makes me feel like Facebook has an idea, like an image of who I am. And they’re like ‘‘Oh she’s a girl, she likes to shop’’ or something (laughs) … Because they just know you so well from all your previous searches. Because I feel like it is that kind of categorizing process. If I’m looking at Peter Alexander pyjamas and then I’m looking at dresses that I like online clothes shopping. And then I get put into that group to be advertised with clothes and products and things.’ Sarah begins to say here that Facebook’s data collection has revealed a lot about her, as she states that they have so much her data and feels that the platform knows her from her search history. But she goes on to discuss that she feels like their knowledge of her is limited, an empty kind of categorization based on a stereotype that she is a girl and therefore her interests are shopping—​a kind of cartoonish image of her. We can see that her encounters with the targeted advertisements, with the reflections of her data back at her have left her feeling that Facebook does not necessarily have the whole picture of her. This echoes Ruckenstein and Grandroth’s (2020, p. 18) study on targeted advertising that negative reactions were triggered by advertisments in

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which ‘[i]‌nstead of subtly guiding consumers, classification schemes become visible as crude sorting mechanisms’. Although Sarah describes the significant extent of the information Facebook collects on her and the process of categorization, when she is asked in the interview how she feels about this process of categorization she is somewhat ambivalent. She reasons that ‘‘just to put advertisements on the side of my Facebook wall, so I don’t think that’s hurting anyone’’. As discussed earlier, the tension between discomfort with data surveillance or seeking to preserve privacy and the desire for access to the services that are obtained through exchanging one’s data for the service was present in many of our interviews. Participants felt they could not give up access to social media platforms like Facebook or services that used their personal data, like Spotify, because they were entangled within these systems and accessing their functions was integral to their daily practices. As Olivia (19 years old) explains: ‘‘I mean … I could stop using Facebook but then I would lose like half my connection to my friends. I could stop using Spotify but then I couldn’t listen to my music so … umm … yeah I definitely think there’s no way out.” Beyond the collection of their personal data through social media and online browsing practices, the young people we interviewed also took photographs that reflected the ways they were subject to forms of surveillance through which they felt more readily that they were being seen through a computational lens. Several participants took photographs of the text-​matching anti-​plagiarism software Turnitin, commonly used in Australian universities, and described their feelings when encountering the program in routine university life. Jacob (19 years old) said that the software made him ‘‘really stressed’’, and Sarah (19 years old) felt that a perceived lack of human contextualization of the ‘originality score’ generated by the software made her more worried about how the system was evaluating her: ‘It’s kind of … an automated process that evaluates your work and decides whether or not you have plagiarized. And I feel like it’s another aspect where the personal element has been taken out of it. Because like obviously the lecturer still reads it and if Turnitin picks up something and it obviously isn’t plagiarism they can disregard that. Ummm … but it still flags things that the lecturer will look. And it does that whole process. And maybe the lecturer doesn’t look at anything it hasn’t flagged, so it’s completely reliant on this

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process, I guess. Like, in this one I got 11% and that was completely my reference list. So it’s like I haven’t plagiarized, it’s actually evidence that I haven’t plagiarized (laughs). It’s … but it’s saying that I have plagiarized. Removes a bit of the … like … emotional connection. it makes me feel very … like … investigated, I guess. (Laughs). Like, because when Turnitin brings up little things like … it’ll be like ‘‘in’’ … ‘‘the’’ … ‘‘but’’ … and those words. And it’s like ‘‘what have you done?’’, this is like 20% of all these, like, little things. And it’s like what are you saying? I haven’t done anything wrong and it’s like 20% plagiarism or whatever. Ummm … so it is a bit. I never plagiarize and I still always worry about my Turnitin score.’ Participants were eager to assert they had never violated the rules or plagiarized but still felt significant anxiety and sometimes even guilt while using the Turnitin system. They felt the stakes were high and the possibility of error was strong. As Christopher (19 years old) put it ‘‘[t]‌his could put a permanent black mark on my record’’. This sense that of the system’s indifference to the individual and orientation instead towards the ‘truth’ of the data was central to their anxiety that subjectivity would be lost. It was identifiable in the analysis that participants had real concerns about automated decision-​making, in this context, in which they presumed everyone to be a potential wrongdoer and so worthy of scrutiny. This challenges the most tedious leitmotifs relating to surveillance: ‘if you have nothing to hide you have nothing to fear’. Within these algorithmically-​enabled sorting systems, everyone is under suspicion of plagiarism or other kinds of wrongdoing until evaluated as beneath the threshold of committing the crime. The participants in this study clearly did feel they had something to fear within this system, despite identifying themselves as innocent of plagiarizing. Importantly, the interviews and photo diary exercise identified the process of screening itself that caused them discomfort. They felt that the universal application of surveillance meant that everyone was presumed to be a potential wrongdoer. We can connect their accounts of the notion of the ‘quantified child’ (Smith, 2017) who knows that they are the subject of continuous monitoring, and that the interpretation of their biophysical data will elicit judgments about their character, abilities, intellect, health or well-​being. Ben Williamson (2015) argues that the ‘algorithmic skin’ worn by children in education shapes their subjectivity and exerts a

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tremendous influence on their being. Like a standardized school test ‘valorizes some kinds of knowledge skills and renders other kinds invisible’ (Bowker & Star, 1999, p. 6) we can see how the Turnitin software offers its own inference about desirable and appropriate behavior, modulating students behavior. Indeed, as Lupton (2013, p. 14–​15) asserts ‘data themselves and the algorithms that interpret them and make predictions based on them are social actants’ and these actants can have a ‘profound impact on how individuals view themselves and the world’. We can see this impact in the way our participants grapple with anxieties around their sense of themselves as ‘good’ students who do not plagiarize while encountering Turnitin originality scores that challenge this knowledge.

Conclusion Our entanglement with technology has never been more noticeable; but philosophers have been reflecting on our co-​constitution with our material long before social media and smartphones. In the 1950s French philosopher Georges Canguilhem (1952, p. 143) identified how tools and machines become extensions of living organisms. Distinctions between ‘what is inside and what is outside the human body’ (Amoore, 2014, p. 96) at times dissolve and are reconstituted. In the age of dataveillance, Calguilhem’s theorizing can be reframed in a new light thinking about the dividuated self or a ‘data double’ relating to ‘the formation and coalescence of a new type of body, a form of becoming which transcends human corporeality and reduces flesh to pure information’ (Haggerty & Ericson, 2000, p. 610). Our participants’ accounts trace moments of their own encounters with their data, dataveillance and data doubles. Dataveillance and its analytic algorithms have the ability to redefine the way that young people understand and experience their bodies and their capacities. The very conditions of possibility are modulated and constrained through this dataveillance. Carolyn Vander Schee (2009, p. 558) explains that surveillance mechanisms cultivate ‘knowledges and truths about the ways in which individuals should conduct their lives for the betterment of self and society’—​the kind of ‘nudging’ and gentle behavior modification we observed in our participants through subtle mechanisms like discomfort. We have traced four key categories of dataveillance apparatus: visual, biometric, spatial and algorithmic, recognizing that the boundaries are blurred between them. It is through these apparatus that young peoples’ everyday lives are constituted and modulated. We have argued that their accounts of dataveillance add

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further evidence to suggest that these apparatus are not oriented towards individuals—​towards knowing them but towards dividuals, fragmentations that can be measured and aggregated. Our findings suggest that this fragmentation is an organizing practice that is felt in their encounters with these systems as they struggle with fluctuating discomfort and comfort, with feeling known and yet invisible. Note 1

Participants, aged between 19 and 24, were recruited from undergraduate courses at an Australian university located in Canberra in late 2016. We provided the students with a digital camera, or some elected to use their smartphone instead, and they were instructed to take photographs that reflected the broad theme of surveillance over a period of one week. After a week they returned for an unstructured interview during which they discussed ten images they had taken, images they selected themselves. Some participants also chose to include screenshots taken using their personal devices (e.g. laptops, smartphones or tablets) as part of their photo diary. See Southerton and Taylor (2020) for an in-​depth discussion of the method.

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The Bad Guys Are Everywhere; the Good Guys Are Somewhere John E. Deukmedjian

Introduction Following World War II, modern national security intelligence agencies in English-​speaking countries had a simple mandate: to prevent another Pearl Harbor. Implementation was not so simple during the height of the Cold War. National security agencies partnered with federal/​ national law enforcement and started looking inward for potential threats. The problem was that state actors could not legally peer into the lives of ordinary citizens, absent probable cause as determined by the judiciary. Senator Frank Church rightfully recommended a targeted approach to minimize further violations of the freedoms and rights of the American population (see United States Senate Select Committee to Study Governmental Operations with Respect to Intelligence Activities 1976 a.k.a. Church Committee). ‘Targeted’ national security surveillance proceeded in the next two decades. Nevertheless, following 9/​11 widespread mass security surveillance of global populations became entrenched under the auspices of the global war on terror (GWT). Terrorism discursively and globally juxtaposed violent crime and the spectacle of mass kinetic attack guided by ideology, politics or religion. This helped create the conditions for our present-​day pre-​crime mentality. Pre-​crime stems from futuristic dystopian fiction, specifically Steven Spielberg’s 2002 adaptation of Philip K. Dick’s 1957 (see Dick 1987/​ 1991) short story, The Minority Report, wherein specialized pre-​crime

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police are tasked with arresting and charging those who have been determined by ‘Precogs’ to be murderers, though the murder suspects who are charged have yet to commit (nor have attempted to commit) murder (Dick, 1987/​1991). This said, the idea of preventing and/​ or pre-​empting crime prior to its materialization is per se a modern governmental preoccupation. Loosely speaking, classical thinkers such as Colquhoun, Beccaria and Bentham problematized crime within the broader mindscape of creating the conditions for a well-​regulated and self-​ disciplined population. The state would ideally enable self-​governance through the formation (or reformation) of apparatuses of utilitarian discipline and deterrence (such as the modern police, rationalized law, and the prison). Classical reformers were proponents of preventing crime rather than pre-​empting it. From the mid-​nineteenth century (and until perhaps the interwar period), crime became increasingly viewed as a biopolitical problem of controlling dangerous and/​or habitually criminal individuals (Foucault, 1978; Garland, 1985). While not representative of the majority of police practice, nevertheless identifying and pre-​ empting the most dangerous and/​or habitual offender increasingly became a cornerstone of detective work. In the 20th century, crime was viewed as a problem of social structure. Prevention depended on social intervention and programming. Criminological ideas from the Chicago School, in addition to strain, differential association and labeling became ingrained, aligning nicely with post-​war welfarism and Keynesianism. In the late 1960s, the President’s Commission on Law Enforcement (1967) along with Becker’s (1968) ‘Economics of Crime’, represented the birth of yet another layer: crime needed to be managed. The question of how became an actuarial one (Feeley, 1992). Criminal justice needed to allocate capital investments for maximal economic benefit within a burgeoning neoliberal state. The securitization of society followed (see Ericson & Haggerty, 1997)—​mostly absent questions of criminogenesis. The risks posed by crime and beyond required practices of security surveillance along with situational resilience, disruption, containment, displacement or elimination—​in short, risks (and the risks associated with risks) needed to be managed and distributed so as to not manifest (Beck, 2009). While a rationality of prevention often asks: ‘why do (some) people commit (certain types of) crime?’ the pre-​crime mentality that developed in the latter decades of the 20th century would culminate with the repeated question: ‘why was the crime permitted to occur in the first place?’ With respect to homicides of children (both those living at home and those in protective care by the state) a colleague and I traced this question in the United Kingdom and Canada by

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considering reports of various commissions of inquiry in the latter half of the 20th century. While the specifics of each of the incidents leading to a government inquiry were relatively unique, all reports expressed a belief of a common failing by social workers and police: the lack of effective interagency cooperation and sharing of vital information (see Deukmedjian & Cradock, 2009). From roughly the 1990s, and accelerating in the post-​9/​11 era, advancements in computational technology and the Internet, combined with a strong political will for greater interagency cooperation and information–​sharing, led to developments in policing and national security intelligence including ‘intelligence-​led policing’, and ‘total information awareness’ approaches to managing risks before they progress or even materialize. This chapter interrogates some of the ways in which the development of a fusion between national security intelligence and law enforcement govern populations through the latest iterations of pre-​crime. It is important to understand that the fields of national security and policing of crime are extremely vast. There would be no way of approaching the fusion of these contexts in any exhaustive sense within this chapter. As such, the analysis may seem uneven in the sense of time and space. My goal is to highlight patterns primarily within the UK, US and Canadian space rather than to suggest some exact series and importance of events (i.e. there are important texts which will not be analyzed for the simple reason that one example may seem to exemplify a general sense of progressions and problematizations discussed herein). Ultimately, the distinguishing feature of present-​day pre-​crime is the de facto presumption that everyone poses potential risks however politically defined in any given time and space. Pre-​crime might have originated in a fictional depiction of a dystopian future. Depending on one’s worldview, pre-​crime may or may not be dystopian, but rather than being fictional, this chapter shows how pre-​crime is currently functional through a national security lens. I ask the reader to consider a world in which a few (mainly secretive) organizations have the ability to intimately ‘know’ the conduct of everyone, every group and every organization in real-​time—​limited only by resources and political will. Such is a world not of conspiracy theory nor science fiction but one in which we currently find ourselves.

Early problematizations of national security and high policing Modern liberal democracies (though not necessarily contemporary ones) have sought to separate apparatuses of national security from

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apparatuses for policing domestic crime. This political and discursive will may have stemmed from the ‘tyranny v. liberty’ binary of the enlightenment (cf. Locke & Laslett, 1966). While the binary has a complex philosophical and legal genesis from the 17th century, it is notable that overcoming tyranny and injustice became a key problem for many classical thinkers including Beccaria (2004). Indulging in caricature for a moment, the binary discourse of tyranny v. liberty often contrasts where we find ourselves today (in a time and place governed through rule of law and premised upon civil and human rights and freedoms), with where we once found ourselves and where some still find themselves (ruled by ‘emperors’, ‘tyrants’ and ‘dictators’). In lands characterized by liberty, the public largely governs itself, assisted by a state elected by the population, and through highly regulated, professional and visible police tasked with protecting the public’s rights. Alternatively, tyrants and dictators regularly deploy secretive agents, informants and often the military to repress their subjects. Perhaps Western democracies have always functioned in a political space somewhere in-​between, though it is easy to see a progression of discourses and practices away from the liberty ideal.

Human intelligence and counterintelligence Histories of modern policing in English-​speaking countries have often (and perhaps over-​) emphasized how apprehension against the potential for tyranny from a police force intertwined the nearly 80-​ year history of English police reform, culminating with the passage of the Metropolitan Police Act and the deployment of the ‘new police’ in 1829 (Payley, 1989). Of note, Sir Robert Peel had emphasized the largely reactive and preventive (i.e. visible deterrence) role of the ‘new police’ in his infamous speech to Parliament in 1828 (see Peel, 1853, p. 556–​64). We can loosely designate such policing as ‘low policing’. Pre-​empting crime that had not been committed (yet) had no place under rational rule of law and neither did the Metropolitan Police have any mandate for national security counterintelligence operations which, by the very nature of countering (rather than simply gathering, analyzing and reporting), too often led (and leads) to practices of setting up targets (among others) for a variety of (potentially unlawful) interventions. For Brodeur (2010, p. 226), ‘[h]‌igh policing is an exercise in covering up, carried to its ultimate consequences’. Such practices appear to have been precisely what the Metropolitan Police were engaged in three years after their inception. Sometime in March of 1822, Sergeant William S. Popay infiltrated a ‘class’ (or

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chapter) of the National Political Union of the Working Classes under the guise of an impoverished artist to not only spy on the group but also in some cases, to incite violence against members of the British government. When his activities came to light in 1833, members of this group petitioned the House of Commons and William Cobbett MP successfully argued for the formation of a House committee. That committee found 49 reports by Popay to his superior, Superintendent M’Leau, and in turn, to both Commissioners Mayne and Rowan, and ultimately the Secretary of State for the Home Department (Cobbett, 1833). Popay was not a lone Metropolitan Police spy. As many as 20 of his colleagues were at some time or another under M’Leau’s command as spies and agent-​provocateurs (Hansard, 1833, p. cc834–​9). The House of Commons did not find fault with either commissioners or the secretary but did find the activities of both Popay and M’Leau to be abhorrent to the sensibilities of the public. Both were dismissed from the police (Hansard, 1833). Half a century on, the Metropolitan Police’s Special Irish Branch was established. The Branch was originally tasked with gathering intelligence and countering the Irish Republican Brotherhood (Porter, 1987). Nevertheless, their remit quickly expanded to include a growing anarchist and communist threat, and the SIB simply became the Special Branch that dealt strictly with threats to the national security of the United Kingdom. More recent research by Cook (2004) shows that the Special Branch was (and still is) a counterintelligence outfit through-​and-​through. As alluded to earlier, one way in which a future crime can be pre-​empted is if the police (or other government service/​agency) invent a criminal plot and entice targets to participate in it. Of course, since the police are managing the script, they know exactly when their targets will execute the plot, and hence exactly when to arrest the targets they have set up. All levels of policing, including (and perhaps especially) national security/​high policing (see Brodeur, 2010) continue to resort to this time-​tested method for achieving pre-​crime ‘success’. For example, in 1892, William Melville of the Special Branch was lauded for foiling the Walsall bomb plot. However, according to Cook (2004), Melville ordered a subordinate, Auguste Coulon, to act as an agent-​provocateur to fit-​up the Walsall bombers (with fake bombs).1 We can go into much more recent examples, such as the apparent set-​up by the Royal Canadian Mounted Police (RCMP) of John Nuttall and Amanda Korody in 2013, who were at the time dubbed the ‘B.C. Bombers’, as the plot involved detonating pressure-​cooker bombs at the legislature on Canada Day. In 2016, British Columbia Supreme Court Justice

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Catherine Bruce said the RCMP ‘used trickery, deceit, and veiled threats to engineer the terrorist acts for which Nuttall and Korody were arrested. … Ultimately, their role in carrying out the plan was miniscule compared to what the police had to do … it was the police who were the leaders of the plot’ (Omand, 2016). The RCMP had targeted the pair with what is known as a ‘Mr. Big’ sting operation. Mr. Big operations, while very costly, have been a mainstay RCMP high policing tactic since the 1980s (Keenan & Brockman, 2010). By 1895, after almost a half-​century of development of its detective branch, the Metropolitan Police established the Criminal Investigations Department (CID) consisting of 472 officers (Lee, 1901). In the context of this chapter, the CID engaged in a type of pre-​crime we still see today. I mention their approach (which was initially described by Pike in 1873) to show two things. Firstly, even day-​to-​day detective work often entailed (and entails) some form of pre-​emptive policing. For example, Pike (1873) stated that detectives secretively identified, ranked and ultimately contained (i.e. arrested) ‘habitual criminals’—​or those we would view today as prolific and repeat offenders. Detectives operated similarly in the United States (see for example Flinn, 1887; Costello 1892). Secondly, and more importantly, during the interwar and post-​war periods, this approach to detective work was problematized by highly regarded reformers August Vollmer (1936) and his student, O.W. Wilson (1950). Among other things, Vollmer and Wilson had both been police chiefs and appointed professors during their careers. They promoted scientific reforms in support of reactive forensic investigations, rather than pre-​emptive approaches, such as rounding-u​ p the usual suspects. They both envisioned detective work as a careful and scientific process, not unlike how Sir Arthur Conan Doyle’s fictitious (though influential character) Sherlock Holmes solved cases. Such problematizations recurred, beginning with national security policing in the 1960s and 1970s. North American national security intelligence initially lagged behind developments in the United Kingdom. Following World War II, the United States Congress passed the National Security Act of 1947, which established a permanent national security apparatus (United States Senate Select Committee to Study Governmental Operations with Respect to Intelligence Activities (a.k.a. “Church Committee,” 1976, V1, B1)). The official purpose, in short, was to have an ‘early warning system to monitor potential military threats by countries hostile to United States interests’ (Church, 1976, V1, B1, 1). The Church Committee (1976, V1, B1, 1) additionally stressed that the information gleaned by this national security intelligence apparatus

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was: ‘necessary in countering the efforts of hostile intelligence services, and in halting terrorists, international drug traffickers and other international criminal activities. Within this country certain carefully controlled intelligence activities are essential for effective law enforcement’ (emphasis added). This apparatus included the Central Intelligence Agency (CIA), the Defence Intelligence Agency (DIA), the Federal Bureau of Investigations (FBI), the National Recognizance Office (NRO), the National Security Agency (NSA) and Treasury intelligence services. It is certainly notable that the Church Committee was initiated to determine the extent and legality of their domestic spying and counterintelligence operations. Of the agencies listed, only the FBI and Treasury had (and still have) domestic law enforcement mandates. Indeed, the 1947 National Security Act specifically forbade the CIA from conducting domestic human intelligence operations beyond common law powers of ordinary American civilians: specifically, the Act barred the CIA from domestic policing, applying/​obtaining subpoenas, or acting as law enforcement. The other three agencies were strictly military in origin and development but nevertheless conducted domestic operations during the anti-​war and civil rights movements in the 1960s. Following Watergate, the Church Committee brought to light some of the most egregious ethical (if not illegal) practices by these agencies. The Church Committee report encompasses six books and seven addendum volumes, including ‘Mail Opening’ (volume four) and abhorrently the use of ‘Toxic Agents’ (volume one). As far as the latter, the Committee discovered that the CIA developed a firearm that shot a near undetectable projectile with a ‘shellfish toxin’, which would cause a target’s heart to fail (a.k.a. ‘the heart-​attack gun’ (see Church Committee, 1976, V1)). If this capability was troublesome (and the extent of its use is still publicly unknown), the Committee additionally uncovered coordinated plots by the FBI and CIA against Americans. One of these is of particular note, as it was (and still would be) unconscionable: COINTELPRO2 (counterintelligence program). J. Edgar Hoover’s COINTELPRO involved extensive spying on Americans to identify and disrupt extremists, which included communist sympathizers and subversives. COINTELPRO practices used by the FBI and CIA were extensive and treacherous, including an attempt to blackmail Dr Martin Luther King Jr into committing suicide (Church Committee, 1976, B2). It comes as no surprise that the Church Committee concluded that national security and federal

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law enforcement agencies abused their powers, violated federal and local laws, and acted contrary to the United States Constitution. In Canada, the RCMP had investigated potential communist sympathizers as early as the 1930s in an ad hoc fashion. Domestic spying against Canadians was institutionalized and regularized in 1950 with the formation of the Special Branch (premised upon the London Metropolitan Police’s Special Branch). The Special Branch was reorganized twice until it became known as the Security Service in 1970. While the RCMP conducts provincial, federal, national and international policing (the latter of which includes, but is not limited to, illicit drug interdiction, training of foreign police and peacekeeping activities), unlike federal or national police services in most English-​ speaking countries, the RCMP is primarily responsible for day-​to-​day law enforcement in hundreds of local communities across the country. The RCMP Security Service practiced many of the questionable counterintelligence tactics already described in the UK and US contexts against various Canadians, including prominent academics and politicians. In 1981, the McDonald Commission revealed activities ‘not authorized or provided for by law’, including domestic bombing, arson,3 break-​and-​entering, theft and blackmailing (McDonald, 1981). These were all pre-​emptive and/​or disruptive tactics: stopping high crimes before they might occur premised upon spy-​craft. The McDonald Commission recommended the disbandment of the Security Service and the establishment of a separate civilian agency. Combining law-​enforcement powers with the conduct of national security intelligence were viewed as incompatible in a democratic society. In 1984, the Security Service was disbanded, and the Canadian Security Intelligence Service (CSIS) was established (composed of civilians,4 absent law-​enforcement powers such as detention and arrest). The McDonald Commission’s two-​volume report unfortunately stands to this day as the most comprehensive investigation into national security intelligence and counterintelligence activities in Canada. Missing is any public consideration of the activities of the Department of National Defence’s Communications Security Establishment or any other security intelligence branch of government.

Five Eyes signals intelligence In 1943, the United States and United Kingdom signed a secret treaty known as the BRUSA Agreement (British United States of America Agreement) and on March 5, 1946, this secret agreement was entrenched between the predecessor agencies of what would

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eventually become the NSA in the United States and the Government Communications Headquarters (GCHQ) in the United Kingdom. In the years that followed, this secret agreement expanded into what is known today as the ‘Five Eyes’ (a.k.a. FVEY) additionally encompassing Australia, Canada and New Zealand.5 The agreement was (and still is) intended to share intelligence (especially, though not limited to, military signals intelligence (a.k.a. SIGINT) of common interest to all five counties). The totality of this agreement has to this day not been publicized in any comprehensive fashion. Still, we do know some things. For example, it is telling that a 2013 draft report of the EU’s Committee on Civil Liberties, Justice and Home Affairs stated that: the national security agencies of New Zealand and Canada have been involved on a large scale in mass surveillance of electronic communications and have actively cooperated with the US under the so called ‘Five Eyes’ programme, and may have exchanged with each other personal data of EU citizens transferred from the EU. (Moraes, 2013, p. 12) This suggests that the FVEY alliance states are, in fact, intercepting electronic data from their allies, and likely from each other. The NSA was established on November 24, 1952 after more than three decades of evolution as a military cryptographic organ for monitoring and/​or deciphering foreign communiques (including and especially diplomatic cables and financial wire transfers through Western Union). Its establishment was authorized in secret by fiat via a memorandum written by President H.S. Truman. Thus, the existence of this agency was (until the Church Committee) mostly unknown and/​or officially denied. In fact, in official circles, the NSA was often referred to as ‘No Such Agency’. One question for the Church Committee was whether human intelligence agencies (e.g. CIA and FBI) were collaborating with the signals intelligence agencies such as the NSA. To be sure, ‘wiretapping’ could only be lawful for domestic investigations via judicial warrant (lest the fruits of such surveillance would likely be inadmissible in a court of law and the agency conducting such an investigation could face legal action for violating the constitutional rights of surveillance target(s)). The NSA, like all the SIGINT agencies mentioned, were to strictly spy on foreign targets. While initially the boundaries between these two spheres (foreign versus domestic) seemed clear, it did not take long before the two were intermeshed: what if there were foreign agents and foreign influencers acting upon domestic populations (pejoratively viewed

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as ‘useful idiots’) to subvert government and society? Together with the CIA and FBI, Church identified highly questionable activities of the NSA, including spying on domestic civilian targets and, ironically perhaps, on the communications of the Church Committee itself. While alluding to the NSA’s MINARET program, on August 17, 1975 on NBC’s Meet the Press: Senator Frank Church succinctly warned the United States public: [The] United States government has perfected a technological capability that enables us to monitor the messages that go through the air. Now, that is necessary and important to the United States as we look abroad at enemies or potential enemies. We must know, at the same time, that capability at any time could be turned around on the American people, and no American would have any privacy left—​such is the capability to monitor everything—​telephone conversations, telegrams, it doesn’t matter. There would be no place to hide. These words strongly resonate today, despite the passage of nearly half a century. The Church Committee led to the establishment of Senate and judicial oversight. The former was the establishment of the Senate Intelligence Committee in 1976. The latter was the enactment of the Foreign Intelligence Surveillance Act (FISA) of 1978. FISA established a secret/​in-​camera Foreign Intelligence Surveillance Court (or FISC), the purpose of which was/​is to adjudicate warrant applications for the conduct of surveillance on any person(s) believed to be foreign agents working against the national security interests of the United States abroad, foreign agents on US soil (working toward the same) and/​or American citizens believed to be subversively operating with foreign powers to commit espionage, based upon probable-​cause applications from federal law enforcement (e.g. the FBI) and/​or national security intelligence agencies (e.g. the NSA). While establishing a secret court for issuing secret warrants was (and obviously still is) contentious in a liberal democracy, the reasoning behind the Act and courts6 was to balance the sensitive and secretive nature of national security intelligence contained in warrant applications with the constitutional rights of Americans. The purpose was to reign-​in unchecked (and potentially arbitrary) practices of surveillance by the government, especially when conducted at scale (cf. USA, 1978). The Act (though obviously less than perfect) tried to ensure that government surveillance upon its population remained targeted and judicially authorized within the rule of law.

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While this analysis is more a sketch rather than comprehensive, the purpose has been to show that modern democratic government problematizations of high policing tended to recognize the necessity of separation of powers between national security and domestic policing. Modern domestic policing was originally designed to function primarily as a preventive apparatus premised upon maintaining local order (Ericson, 1982). National security is a proactive assemblage that ought to be used sparingly and exceptionally—​with careful attention to preserving rights and rule of law. Unfortunately, proactivity (beginning in the latter 20th century) gained increasing prominence so as to now encapsulate a day-​to-​day enforcement mentality within an ever-​ expanding precautionary and pre-​crime logic (McCulloch & Wilson, 2016). From the 1990s onward, governmental systems-​integration and ministerial, departmental and agency fusion (irrespective of domestic or foreign function) were not only touted as solutions to problems created by an early modern bureaucratic expedient, but with the growth of networked technologies, especially the Internet, governmental integration has and continues to be actualized—​indeed functioning not only globally but also cybernetically. It is to this integration and technological development that we now turn.

Intelligence-​led policing, integration and fusion Since about 1960, English-​speaking countries experienced annual increases in overall crime rates.7 By the mid to latter 1980s, official problematizations of rising crime rates had become commonplace. Together with governmental ‘neoliberalization’ stemming from the Chicago School of Economics in the 1960s, public policing was increasingly criticized for its inability to function within a ‘value for money’ mindset first advocated by Gary Becker (1968). While public police in most English-​speaking jurisdictions were adopting ‘community-​based’ models as an alternative to the Wilson-​esque professionalism of the mid-​20th century (cf. Skogan, 1999), the UK’s Audit Commission (1993) was perhaps the first to advocate cost-​ effective law enforcement through intelligence-​led policing (ILP) approaches—s​ pecifically through cultivating informants and targeting prolific and high-​risk offenders. Though community policing and ILP have fundamentally different foci as the former seeks to reduce crime by developing police-​community partnerships to identify and resolve local problems and the latter seeks to disrupt and/​or contain repeat offenders and major crime, both share common ground in their advocacy for intra and inter-​governmental information-​sharing partnerships

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(Deukmedjian & de Lint, 2007; Ratcliffe, 2008). While both styles of public policing remain popular (depending on jurisdiction), since the 1990s and especially since 9/​11 information and intelligence-​sharing within and between police services, as well as government ministries, departments and agencies has clearly become emphasized, including in former Soviet republics by the Organization for Security and Co-​ operation in Europe (see OSCE, 2017).

Integration and fusion The October 26, 2001 passage of the USA PATRIOT Act (the Uniting and Strengthening America by Providing Appropriate Tools Required to Intercept and Obstruct Terrorism Act of 2001) has generally been understood as counter-​law (Ericson, 2007) and/​or a law authorizing a state of exception (Agamben, 2005) in the United States. The law effectively created exceptions to constitutional freedoms and rights, especially in relation to limits on surveillance (including physical searches). As lawmakers understood its exceptionality, the USA PATRIOT Act had a December 2005 sunset. However, as is often the case with emergency measures, the law was renewed in March 2006 with minor modifications, this time with a 2010 sunset. In 2011, the PATRIOT Sunset Extension Act passed, not only extending the original law but also expanding surveillance provisions to include ‘roving wiretapping’, ‘business record searches’, and increased detection of potential ‘lone wolf ’ terrorists for another four years until 2015. As a parallel development, on September 22, 2001, the White House appointed the first Director of the office of Homeland Security (then Pennsylvania Governor Tom Ridge) ‘to safeguard the country against terrorism’. The Department of Homeland Security was officially established in November 2002 and began full operations in January 2003 (Department of Homeland Security, 2015). The purpose of this new department was to consolidate and integrate 22 US Federal agencies including US Customs and FEMA. Following the publication of the 9/​11 Commission Report on May 27, 2004, DHS, together with the FBI, and the US Department of Justice (DoJ) implemented ‘Fusion Centers’ to ‘create better communication and cooperation between state, local and territorial law enforcement with federal law enforcement entities including the [FBI, DHS], and several others’ (NFCA, 2020, emphasis added). This arrangement essentially created an expansive intelligence network encompassing the various national security intelligence agencies (including both HUMINT and SIGINT), federal, tribal, state and local law enforcement, and of course the

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countless confidential informants (CIs) these procured and unleashed within the population over the years within an ILP rationality. In doing so, this basically achieved the post-​9/​11 vision of the (officially short-​ lived, unofficially still active) Total Information Awareness8 program to ‘create innovative new sources … invent new algorithms for mining, combining, and refining information for subsequent inclusion in the database; and revolutionary new models, algorithms, methods, tools and techniques for analyzing and correlating information in the database to derive actionable intelligence’, (in Mattelart, 2010, p. 144). Similar types of antiterrorism counter-​laws have been passed by parliaments, and similar governmental integrations between law enforcement and national security apparatuses have occurred in all English-​speaking countries. My colleague and I glimpsed into the United Kingdom’s and Canada’s integration of police information and intelligence systems over a decade ago (Deukmedjian & Cradock, 2009). A far more eye-​opening exposé of Integrated Security Units and the Integrated Threat Assessment Centre (which like the US DHS and Fusion Centers) created an intelligence network between the Canadian Department of National Defence (mainly, but not limited to, the Communications Security Establishment Canada (CSEC), CSIS, the RCMP, provincial and municipal police agencies, was published by Monaghan and Walby (2012). The intricate global totality of surveillance and intelligence sharing should be reason for pause over its implications, particularly in relation to achieving a pre-​crime state. We do not have ‘Precogs’ who can see the future, or at least one would assume we do not (see Dick, 2004), but we do have growingly sophisticated and ubiquitous mass surveillance and data acquisition assemblages that function in perpetuity—​a pre-​crime prerequisite. In the words of former NSA Director of SIGINT automation, and whistleblower, William Binney (2020): ‘once you know everybody and what they’re doing, what they’re thinking, what they’re planning … you have the opportunity to manipulate them any way you want, by causing certain things to occur or making certain suggestions in certain areas or you … just simply outright [use] blackmail against them or anything that you can leverage against them or anything [or anyone] they really care about, so you have an opportunity to do all of that’.

Post 9/​11 signals intelligence As we already know from the Church revelations, mass signals surveillance is nothing new. Nevertheless, post-​9 /​1 1 Western democracies have truly embraced the dark side (cf. de Lint, 2004).

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There has been a legislative counter-​law progression and an ever widening/​deepening surveillance progression—​which is a different form of counter-​law (Ericson, 2007). In the United States, following the passage of the USA PATRIOT Act, the FISA was revised several times, resulting in ever-​increasing broadening of what constitutes targeted surveillance. By 2007, one might opine that the FISC no longer served a useful purpose (if it ever really did). The definition of targets was extended to include corporate entities (especially telecommunications corporations) and targeted surveillance by national security intelligence agencies functioned through a ‘three hops’ principle (though later reduced to two).9 Indeed, with the revisions made to FISA between 2001 and 2007, a single FISC warrant could potentially encompass millions of surveillance targets, making the warrant process useless in achieving its intended goals (see Binney, 2019). The publications of leaked NSA documents by Edward Snowden since 2013 seem to confirm that the FISA process is a mere rubber-​stamp formality for day-​to-​day operations. This, of course, depends on how people understand or define search and seizure. If a search and seizure can only occur when humans (such as intelligence analysts) physically look at seized digital and/​or electronic property (such as private communications), then unlimited and unwarranted (or unlawful) government mass surveillance does not regularly happen. If, however, the mere act of seizing and analyzing digital and/​or electronic property suffices to constitute a search and seizure, then the legal and/​ or human rights of almost everyone is being violated in perpetuity. Present-​day surveillance is difficult to present to a reader unless done so macroscopically, particularly for anyone not versed in computer and/​or other technological sciences. Based on a few of the Snowden materials and other leaks, I will attempt to do so here. On June 6, 2013, The Washington Post published the first of what would become a steady stream of revelations in the days, weeks and months following about the NSA, including the programs named UPSTREAM and PRISM (see Gellman & Poitras, 2013). The PRISM program, which appears to have started in 2007, was/​is essentially the mass collection of data from US technology giants and service providers, which agreed to provide the NSA direct access to their servers. At the time, these included: Microsoft in 2007, Yahoo in 2008, Google in 2009, Facebook in 2009, PalTalk in 2009, YouTube in 2010, Skype in 2011, AOL in 2011, and Apple in 2012 (NSA, 2013). Thus, every email, every message, every Google search, all YouTube videos, all Facebook accounts and posts, everyone’s ‘Skype calls’ including conference video and audio, everyone’s ‘virtual chats’ including all the

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metadata and analytical products related to these were collected and stored from the start of these corporate NSA partnerships. We should presume that this collection program has only expanded in breadth and scope, particularly since new social networking platforms have come online, and importantly because users of these products and platforms agree to cryptic ‘terms of services’ and ‘privacy policies’, which generally allows the sharing of user data with third parties, particularly with government and law enforcement. In terms of the latter, the FBI Data Intercept Technology Unit has direct access (NSA, 2013). Compared to PRISM, UPSTREAM was/​is less discussed, perhaps because it was less understood. Nevertheless, the NSA document points out that the UPSTREAM program collects communications and data from ‘fiber cables and infrastructure as data flows past’, (NSA, 2013). The program operates worldwide and, as with PRISM, not only collects and stores everything but also functions in real time (i.e. active electronic surveillance of everything and everyone utilizing worldwide telecommunications). Thus, even if this-​or-​that platform and/​or service provider is not an NSA PRISM partner the UPSTREAM program collects their data anyway. Both these programs are considered to be ‘passive’ as the data essentially comes to the NSA servers both through partnered providers and through fiber taps. The data flows in, and is stored, indexed and analyzed using various big data mining and machine-​learning artificial intelligence software indefinitely. Retail-​grade devices such as televisions, smartphones, tablets, laptop and desktop computers, and Wi-​Fi routers are fair game for targeted and mass surveillance and interception. Sufficed to say that anything the devices can physically do (microphones, cameras, GPS, Wi-​Fi, Bluetooth, gyroscope, etc.) are fair game for SIGINT collection programs. For example, on February 28, 2014 Spencer Ackerman and James Ball of The Guardian reported on the GCHQ’s OPTIC NERVE, a program that collected video imagery and metadata from device cameras (including those used by gaming consoles like XBox). According to the article, OPTIC NERVE began in 2008 to improve upon the GCHQ’s facial recognition database. This information was/​ is also fed to the NSA (Ackerman & Ball, 2014). While the program was not conducted at scale at the time (the article notes that 1.8 million users were targeted within a six-​month period), one can assume that global scaling of device camera data is currently taking place. The NSA and GCHQ are not the only national security intelligence spying through electronic devices. A leaked CIA document in March 2017 indicated the CIA’s and MI5’s Weeping Angel program was used to spy through the cameras and microphones of Samsung Smart TVs

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(Willcox, 2017). While the Weeping Angel program seems targeted rather than bulk, one must wonder if such programs are being executed at scale by other agencies. A more distressing issue is that all devices that connect to the Internet are uniquely traceable in terms of location, velocity if in motion, and type of device connected. The NSA’s TREASUREMAP program identifies, locates and traces all devices simultaneously at global scale and in real time. This information is stored, like all data, indefinitely. Through TREASUREMAP, it is possible to pinpoint a single target-​device anywhere. It is also possible to know all adjacent devices (and who they belong to) within a particular geographical location (NSA, 2011). Thus, for example, if by cross-​referencing data gleaned through PRISM and UPSTREAM, a law enforcement agency has a high degree of confidence that a target is planning to commit a criminal act, the TREASUREMAP system can be used to pinpoint and trace the location of a target’s cellphone. UPSTREAM’s real-​time capabilities can be utilized to see nearby CCTV data transmissions (or even Amazon Ring doorbells) with facial recognition as the target moves. A targeted exploit of the phone’s microphone allows for real-​time intake of conversations and sounds. Since cell transmissions ultimately utilize the servers of telecommunications companies, any text messages or cell calls (including transcription) may also be captured during the surveillance. If a different language is used, translation tools can convert these conversations and texts in real time. Essentially, this kind of integration is what the NSA ‘search tool’ XKEYSCORE accomplishes, a tool accessible not only by US Federal law enforcement but also the FVEY (NSA, 2008). The implications of this are profound, because when assembled together this is a pre-​crime capability scaled globally. The realization of an unfettered pre-​crime world tends to be problematic for the judiciaries of Western democracies. Courts operate in public and defense attorneys question evidence presented by prosecutors—​particularly the nature of sources and investigative methods. If those sources and methods are highly classified, having originated from national security agencies, they cannot be used in court. Apart from the secretive nature of sources and methods, a large number of methods used by national security agencies are likely inadmissible lest the system of justice fall into disrepute. Unfortunately, this has not stopped law enforcement from utilizing the fruits of inadmissible sources and surveillance methods to make ‘lawful’ arrests. According to a 2013 Reuters article by John Shiffman and Kristina Cooke (2013),

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who reviewed leaked ‘Law Enforcement Sensitive’ documents from the highly secretive Special Operations Division (SOD) of the US Drug Enforcement Agency (DEA), one approach to reconcile the incompatibility between national security intelligence and criminal justice is through a process called ‘parallel construction’. The SOD is basically the fusion center of fusion centers in the United Stated. Its personnel are assembled from two-​dozen agencies including the NSA, CIA, FBI and DHS. According to the journalists, one document noted that the utilization of the SOD cannot be revealed or discussed in any investigative function. Parallel construction is a technique used daily. Intelligence gleaned by national security agencies suggestive of crime that is about to happen (such as illicit drug trafficking) is shared by SOD with fusion centers, state and local law enforcement. Instructions to law enforcement will not reveal how the intelligence was formulated, but rather be in the form of a ‘tip’. For example, law enforcement is told to ‘be at a certain place at a certain time and look for a certain vehicle’. Police then stop that vehicle for a routine traffic violation whereupon they coincidentally find illicit drugs or firearms. The prosecutor only knows that the case began with a routine and lawful traffic stop. The rest of the evidence is produced normally, for example through interviewing the suspect and obtaining a warrant to search the suspect’s residence, cellphone communications and social media posts. Thus, we already live in a pre-​crime world. The only limitations to its efficacy—​its depth and breadth—are resources. Clearly, the national security apparatus does not (yet) care about minor offending.

Is anything being done to curtail national security states of exception? While there was, and still is public outrage (though to a much lesser extent), little has been done to curtail this development. Public outrage and protests in the United States appear to have led to legislative change through the passage of the USA FREEDOM Act (Uniting and Strengthening America by Fulfilling Rights and Ensuring Effective Discipline Over Monitoring Act of 2015). This law replaced its predecessor, the USA PATRIOT Act. The USA FREEDOM Act sought to assuage outrage by criminalizing mass metadata collection (only) activities of the US intelligence community, and most notably the NSA. Nevertheless, the FREEDOM Act provided for a three-​year transition period (i.e. allowing mass collection for another three years) and this extension has already been renewed twice at time of writing.

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Conclusion Present-​day capabilities obviously dwarf the capabilities that Frank Church uncovered in 1976. The same must be said of the totality of capabilities of an integrated international intelligence community fused with high and low intelligence-​led policing and big data technology companies. This is essentially a world where (near) total information awareness now exists as envisioned by the US Information Awareness Office in early 2002. National security intelligence resources will continue to advance, including through increased corporate partnerships. On October 19, 2019, Microsoft was awarded a US Department of Defense (DoD) contract worth ten billion dollars over a ten-​year period to develop what the DoD calls the ‘Joint Enterprise Defence Infrastructure’ (JEDI) in cloud computing. Not ironically, little else is publicly known about what the JEDI cloud is. What is obvious is that there does not seem to be too much ‘walling-​off’ between the Microsoft Corporation, the CIA and the NSA (since both latter agencies function as part of the DoD). With greater resources, national security agencies and fusions like SOD will likely be able to dig further down in crime severity in the future. In the eyes of the NSA’s Threat Operations Center (NTOC) the ‘Bad guys are everywhere, good guys are somewhere!’ (NSA, 2010). If bad people are everywhere, then government surveillance and associated interventions must also be everywhere. This chapter has provided a mere glimpse into Alice In Wonderland’s rabbit hole of national security and pre-​crime. There is much that must and still can be academically studied from publicly available sources and leaks. From what is currently apparent, readers should by now understand that the security assemblage, rather than functioning merely to fend off potential attacks (or even major or hi-​crimes), is fundamentally a behemoth that aims to control the global population. Notes 1

2

3

4

Melville went on to help establish MI5 (UK’s domestic security intelligence agency) in 1903. The US Navy used teletype communications limited to all-​capital letters beginning in the 19th century. The use of ‘all-​caps’ was (and to a lesser extent still is) a communications standard within all military and intelligence branches until 2013. The RCMP Security Service burnt down a barn in the province of Quebec to pre-​empt/​disrupt a meeting between senior members of the American Black Panthers Party and the Canadian Front de libération du Québec (FLQ). Initially, CSIS recruited mainly from the former pool of RCMP Security Service officers.

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6 7

8

9

The FVEY are the core of this sharing agreement, however there are further agreements with European member states. There is also an appellate FISA court. Depending upon jurisdiction, officially recorded national crime rates rose from 1959–​61 to a peak in 1991–​93, then decreased until about 2015–​17. After a few short months, ‘Total Information Awareness’ was renamed ‘Terrorist Information Awareness’. A single hop is generally defined as all entities that have direct and significant contact with a target. The second hop includes all entities with direct and significant contact with those identified within the first, and the third hop includes those in direct and significant contact with all those identified in the second.

References Ackerman, S. & Ball, J. (2014). Optic nerve: Millions of Yahoo webcam images intercepted by GCHQ. The Guardian. [online] Available at: https://​www.theguardian.com/​world/​2014/​feb/​27/​ gchq-​nsa-​webcam-​images-​internet-​yahoo. Agamben, G. (2005). State of Exception. Chicago: The University of Chicago Press. Audit Commission for Local Authorities and the National Health Service in England and Wales (1993). Helping with Enquiries: Tackling Crime Effectively. London: HMSO. Beccaria, C. (2004). Of Crimes and Punishments. Salinas, CA: eBooksLib. Beck, U. (2009). World at Risk. Cambridge, UK: Polity Press. Becker, G.S. (1968). Crime and punishment: An economic approach. Journal of Political Economy 76 (2): 169–​217. Binney, W. (2020). CIA’s deadly coup. In C. Hedges, On Contact with Chris Hedges. RT News [online] Available at: https://​www.youtube. com/​watch?v=vHb1Zebr2is. Binney, W. (2019). An open forum with Bill Binney: Reflections of an NSA whistleblower. Presentation at Allard Hall, Peter A. Allard School of Law, University of British Columbia, March 14, 2019 available at: https://​youtu.be/​YqSQaJfz9GY. Brodeur, J.P. (2010). The Policing Web. Oxford, Oxford University Press. Cobbett, W.M. (1833). Popay the Police Spy: A Report on the Evidence Laid Before the House of Commons by the Select Committee Appointed to Inquire Into the Truth of the Allegations of a Pettition, Presented by Mr. Cobbett, from Members of The National Union of The Working Classes (resident In Camberwell and Walworth) in which They Complained that Policemen Were Employed as Government Spies. London: Cleave, J., Shoe Lane (one door from Fleet Street).

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Cook, A. (2004). M: MI5’s First Spymaster. Stroud, UK: Tempus. Costello, A.E. (1892). History of the Police Department of New Haven from the Period of the Old Watch in Colonial Days to the Present Time. New Haven, CT: The Relief Book Publishing Co. de Lint, W. (2004). Neoconservativism and American counter-​ terrorism: Endarkened policy? In M. Deflem (ed.) Terrorism and Counter-​Terrorism: Criminological Perspectives (vol 5). Amsterdam, NL: Elsevier (pp. 131–​53). Deukmedjian, J. & Cradock, G. (2009). From community to public safety governance in policing and child protection. Canadian Review of Sociology 45 (4): 367–​88. Deukmedjian, J. & deLint, W. (2007). Community into intelligence: Resolving information uptake in the RCMP. Policing and Society 17 (3): 239–​56. Dick, P.K. (1987/​1991). The Minority Report. New York: First Carol Publishing Group. Department of Homeland Security (2015). Creation of the Department of Homeland Security. [online] Available at: https://​www.dhs.gov/​ creation-​department-​homeland-​security#:~:text=Department%20 Creation&text=With%20the%20passage%20of%20the,doors%20 on%20March%201%2C%202003. Ericson, R. (2007). Crime in an Insecure World. Cambridge, UK: Polity. Ericson, R.V. (1982). Reproducing Order: A Study of Police Patrol Work. Toronto: University of Toronto Press. Ericson, R.V. & Haggerty, K.D. (1997). Policing the Risk Society. Oxford: Clarendon Press. Feeley, M.M. & Simon, J. (1992). The new penology: Notes on the emerging strategy of corrections and its implications. Criminology 30 (4): 449–​74. Flinn, J. (1887). History of the Chicago Police: From the Settlement of the Community to the Present Time. Chicago: Chicago Police Book Fund. Foucault, M. (1978). About the concept of the ‘dangerous individual’ in 19th-​century legal psychiatry. International Journal of Law and Psychiatry 1 (1): 1–​18. Garland, D. (1985). The criminal and his science: A critical account of the formation of criminology at the end of the nineteenth century. British Journal of Criminology 25 (2): 109–​37. Gellman, B. & Poitras, L. (2013). US, British intelligence mining data from nine US Internet companies in broad secret program. The Washington Post. Washington DC: The Washington Post Company. Hansard (1833). House of Commons Debate of 22 August. London: T.C. Hansard. 20.

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Keenan, K. & Brockman, J. (2010). Mr. Big: Exposing Undercover Investigations in Canada. Halifax and Winnipeg Canada: Fernwood Publishing. Lee, M. (1901). A History of Police in England. London, UK: Methuen & Co. Locke, J. & Laslett, P. (1966). Two Treatise of Government. New York, NY: New American Library. Mattelart, A. (2010). The Globalization of Surveillance: The Origin of the Securitarian Order. Cambridge, UK: Polity. McCulloch, J. & Wilson, D. (2016). Pre-​crime: Pre-​emption, Precaution and the Future. New York, NY: Routledge. McDonald, D. (1981). Freedom and Security under the Law: Second Report. Ottawa: The Commission. Monaghan, J. & Walby, K. (2012). Making up ‘Terror Identities’: Security intelligence, Canada’s Integrated Threat Assessment Centre and social momvement supression. Policing and Society 22 (2): 133–​51. Moraes, C. (2013). Draft Report on the US NSA Surveillance Programme, Surveillance Bodies in Various Member States and Their Impact on EU Citizens’ Fundamental Rights and on Transatlantic Cooperation in Justice and Home Affairs. Brussels: European Parliament Committee on Civil Liberties, Justice and Home Affairs. NFCA (2020). National Fusion Center Association: Helping Protect America. [online] Available at: https://​nfcausa.org/​default.aspx?Men uItemID=322&MenuGroup=2020Public+Home. NSA (2008). “XKEYSCORE” (Power Point). Fort Meade, USA: NSA. NSA (2010). “Bad guys are everywhere, good guys are somewhere!” (Power Point). Fort Meade, USA: NSA. NSA (2011). SIDToday “TREASUREMAP Announces a New Release.” Fort Meade, USA: NSA. NSA (2013). PRISM/​US-​984XN Overview or The SIGAD Used Most in NSA Reporting Overview. Fort Meade: NSA. Omand, G. (2016). B.C. bomb plotters set free after judge rules RCMP entrappeed pair. The Globe and Mail. Vancouver, BC: The Canadian Press. OSCE (2017). OSCE Guidebook: Intelligence-​Led Policing. Vienna: OSCE. Payley, R. (1989). ‘An imperfect, inadequate and wretched system’? Policing London before Peel. Criminal Justice History: An International Annual 10: 95–​130. Peel, S.R. (1853). The Speeches of the Late Right Honourable Sir Robert Peel, Bart. Delivered in The House of Commons. With a General Explanatory Index, and a Brief Chronological Summary of the Various Subjects on which the Speeches Were Delivered. London, UK: George Routledge and Co.

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Pike, L. (1873). A History of Crime in England Illustrating the Changes of the Laws in the Progress of Civilization. London, UK: Smith, Elder & Co. Porter, B. (1987). The Origins of the Vigilant State: The London Metropolitan Police Special Branch before the First World War. London, UK: Widenfeld and Nicolson. Ratcliffe, J. (2008). Intelligence-​led Policing. Cullompton, UK: Willan. Shiffman, J. & Cooke, K. (2013). Exclusive: US Directs Agents to Cover Up Program Used to Investigate Americans. Washington DC: Reuters. Skogan, W.G. (1999). On the Beat: Police and Community Problem Solving. Boulder, CO: Westview Press. United States Senate Select Committee to Study Governmental Operations with Respect to Intelligence Activities (1976). Final Report of the Select Committee to Study Governmental Operations with Respect to Intelligence Activities, United States Senate: Together with Additional, Supplemental, and Separate Views. Washington DC: US Government Printing Office. United States. President’s Commission on Law Enforcement and Administration of Justice (1967). The Challenge of Crime in a Free Society: A Report. Washington DC: US Government Printing Office. Vollmer, A. (1936). The Police and Modern Society. Berkeley, CA: University of California Press. USA (2001) Uniting and Strengthening America by Providing Appropriate Tools Required to Intercept and Obstruct Terrorism Act a.k.a. USA PATRIOT Act. Washington: Public Law 107-​56, 107th Congress. USA (2015) Uniting and Strengthening America by Fulfilling Rights and Ensuring Effective Discipline Over Monitoring Act a.k.a. USA FREEDOM Act. Washington: Public Law 114-​23, 114th Congress. Willcox, J. (2017). A Closer Look at the TVs From the CIA ‘Vault 7’ Hack: The Samsung Models Cited in Leaked Documents Were among the First to Have Built-​in Microphones and Cameras. [online] Available at: https://w ​ ww.consumerreports.org/p​ rivacy/a​ -c​ loser-l​ ook-a​ t-t​ he-​ tvs-​from-​the-​cia-​vault-​7-​hack/​. Wilson, O.W. (1950). Police Administration. New York, NY: McGraw-​Hill.

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PART IV

Systems of Surveillance, Discipline and the New Penology

13

Supermax Prison Isolation in Pre-​Crime Society Terry A. Kupers

Solitary confinement and supermax prisons A supermax is a prison, or a unit within a prison, that is dedicated to keeping all prisoners in solitary confinement. There might be 1,000 solitary confinement cells—​as there were in Unit 32 at Mississippi State Penitentiary before that unit was closed following a class action lawsuit several years ago—​or 1,500 cells, as there are at Pelican Bay State Prison in California. Prisoners remain alone in a cell for more than 22, even 24 hours per day; they are permitted very few possessions in their cells; and they eat in their cells, inches or a few feet from the toilet. They are allowed an hour several times per week for recreation alone on a ‘yard’ that is typically a fenced off area not much larger than their cell. When I look across a row of outdoor ‘yards’ in a supermax prison, I get the sense of looking at a row of cages in a dog kennel. And the prisoners call them ‘cages’. Solitary confinement units, until recently, were operating at full capacity, some with the forced double-​celling that comes with prison overcrowding. Solitary confinement has very damaging effects on human beings, especially those who are psychotic or suicidal. I am one of the researchers and expert witnesses who have published professional articles and books on the subject and I have testified about this phenomenon in multiple class action lawsuits (Kupers, 2013, 2017).1 Prominent among the symptoms reported by the denizens of solitary confinement are severe anxiety or panic disorder, disordered thinking including paranoia,

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compulsive activities including pacing and repeatedly cleaning the cell, difficulty concentrating, memory problems, agitation, irritability, hyperawareness, strong startle reaction, mounting irrational anger, impairment of judgment, despair and suicidal inclinations (Haney, 2003; Scharff-​Smith, 2006; Kupers, 2013, 2017). In prisoners with serious mental illness (SMI), the mental illness is greatly exacerbated. Suicide is disproportionately prevalent in solitary confinement settings, fully 50 per cent of all prison suicides—​and the suicide rate in prison is at least twice as high as in the community at large—​occur among the 4 per cent to 8 per cent of prisoners who dwell in solitary confinement units and supermax prisons (Way, 2005; Mears & Watson, 2006; Patterson, 2008). Part of the damage wrought of time spent in solitary confinement is what I have termed ‘the decimation of life skills’, an example being forgetting how to converse casually with others (Kupers, 2008). The result? When the prisoner gets out of solitary, he or she is less capable or inclined to get along with others, and more prone to get into further trouble and then be returned to solitary. Not surprisingly, research shows that the mortality rate in the years after being released from prison is significantly higher in prisoners who have spent time in solitary confinement (Brinkley-​Rubinstein et al, 2019; Wildeman & Andersen, 2020). Sophisticated technology is obvious as soon as one arrives at a supermax unit. There are the control booths located one half floor above the level where one enters the sterile, concrete and steel chamber containing horizontal rows of cells, or pods. Officers in the control booth sit in front of video screens on which they keep watch of much that happens on the unit. The doors open and close by remote control, managed by the officers in the booth. Officers have the latest law enforcement technology, including tasers, phone communication with all staff on the shift, and with a click on an iPad, they can call up a large amount of information about each prisoner they encounter. Corrections staff are even able to digitally mass-​monitor prisoner phone calls (Francscani, 2019). Soon there will be computerized face recognition programs to make it much easier for correction officers to capture events such as fights on a surveillance camera, immediately identify the participants and have them sent to solitary.

Risk assessment and technology Risk assessment is an important part of almost all criminal justice operations, and risk assessment usually involves a certain amount of technology. Corrections officers do informal risk assessments every day.

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Prisoners who have in their file multiple rule violation reports (‘tickets’) for fighting are more likely to be sent to supermax solitary confinement, the rationale employed by the hearing officer tasked with adjudicating the rule violation report being that their prior unacceptable behaviors predict a high risk of future altercations (Silberman, 1995). Solitary is one of the worst punishments the hearing officer can mete, especially for an indefinite term. Eventually, risk assessments are also the critical ingredient in the reports psychologists prepare for the parole board. Risk assessment plays a part every step of the way to the prisoner’s warehousing in solitary or, when the risk is predicted low, his release on parole. The parole board wants to know the risk that a prisoner, if released from prison, would resort again to illicit substances, commit crimes or be assaultive. Michel Foucault (1977) foresaw in the 1970s that psychiatrists and psychologists were fated to be ordained experts on risk assessment. According to Foucault: Throughout the penal ritual, from the preliminary investigation to the sentence and the final effects of the penalty, a domain has been penetrated by objects that not only duplicate, but also dissociate the juridically defined and coded objects. Psychiatric expertise, but also in a more general way criminal anthropology and the repetitive discourse of criminology, find one of their precise functions here: by solemnly inscribing offences in the field of objects susceptible of scientific knowledge, they provide the mechanisms of legal punishment with a justifiable hold not only on offences, but on individuals; not only on what they do, but also on what they are, will be, maybe. (Foucault, 1977, p. 18) The parole board’s interest in the prisoner’s psychological history can be a ruse, the board actually seeking the psychologist’s expert risk assessment. This reality is reflected in the name of the form psychologists fill out with their psychological assessment for the parole board in the California Department of Corrections and Rehabilitation: ‘COMPREHENSIVE RISK ASSESSMENT’. Risk assessment has become an area of expertise, and the field continually imports new technological developments to accomplish scientific assessments. One very popular way to study future risk is to compile a subject group such as formerly incarcerated people, document as many variables as possible about them (age, race, educational level,

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mental illness, past criminal convictions, participation in pro-​social rehabilitation programs and so forth), observe them over a certain period of time,2 and then correlate the documented variables with future criminal acts. A prisoner who is White, older, has few criminal convictions, has little in the way of disciplinary trouble in prison and has participated in many rehabilitation programs and held good prison jobs, is much more likely to win parole than is a younger Black prisoner who had several convictions and jail terms as a teen, has had multiple disciplinary write-​ups in prison and has spent time in punitive segregation. That is the way risk assessment works. Technology permits immediate access to a lot of data and a huge number of documents that can be included in the current assessment. And technology enters into the large forensic literature that has accumulated about the science of risk assessment. For example, there has been some debate in the scientific literature about the importance of age as a factor in risk assessment (Hunt & Beasley, 2017). For a long time it was assumed that, as prisoners age, the risk is diminished that they will re-​offend or become violent again. Some researchers argue it is more complicated; and for some prisoners there is no significant drop-​off to risk with age (Marvel & Moody, 1991; Moffitt, 1993; Levitt, 1999). Of course, the statistical proofs offered by both sides in such debates are quite extensive. The risk assessment industry depends on technology. There are the computer searches and artificial intelligence (AI) involved in every stage of research; there are detailed descriptions of psychological proclivities (the characteristics for antisocial personality disorder (ASPD) in the DSM 5 or Diagnostic and Statistical Manual comes to mind); and there are articles in professional journals evidencing the latest technology-​ aided research proving the scientific veracity of particular types of risk assessment. I include in the notion of technology the detailed quantification of the characteristics of diagnoses such as antisocial personality disorder, the computer-​generated test results employed to determine a diagnosis, and the statistical methods involved in research proving one or another correlation, for example that recidivism declines with advancing age or that certain prior criminal acts correlate with future criminality. Leaving the ivory tower, corrections officers, especially hearing officers at disciplinary hearings, apply the research as well as their own intuitive sense, and categorize prisoners as high or low risk for future rule violation and violence. The staff’s sense of each prisoner’s risk, especially risk of violence against staff, will determine how quickly that prisoner will be subdued by force in the future, will play a big

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part in determining who goes to solitary confinement, and eventually will determine who gets paroled (Poole & Regoli, 1980). Psychologists also administer psychological assessment instruments, or ‘psych tests’, and work their test results into their risk assessment for the parole board. But there is a huge debate about the objectivity and fairness of the psychological assessment instruments. Have they been ‘normed’ for the population they are being used on? Are the questions even relevant to the prisoner’s life experiences? For example, there is a question on the Symptom Checklist 90-​R’, an instrument I administer to prisoners, ‘Do you feel afraid in open spaces or on the streets?’ When I administered that test to a prisoner in a supermax isolation unit who had been in the Security Housing Unit (SHU) for 11 years, he looked up at me with sadness in his eyes and said, “I haven’t been on the street for 20 years, and there are no open spaces in this dungeon.” The guise of scientific veracity, supported by the sophisticated classification of diagnoses, the computer-​generated interpretations of psychological tests and the statistical proofs contained in risk assessment studies, gives a false sense of confidence about risk assessments. Wrong science, buffeted by impressive technical proofs, is still wrong science. There are two levels to this discussion. On one level, there is the question whether one or another individual is rightfully consigned to SHU or granted parole. On another level, it doesn’t matter which specific individuals are in SHU or granted parole. There is a legitimation function to the entire process. Someone has to be in the SHU, and someone has to be granted parole, simply in order to sustain the premises of the criminal justice system, to justify the huge budget for criminal justice, and to testify to the importance of the work of correction officers and parole board commissioners. Even with the racial biases and other flaws, and very many people wrongly punished and wrongfully denied their freedom, the entire process serves its legitimation purpose.

Surveillance Surveillance is key to the pre-​crime society. Those individuals deemed by police and corrections officers to pose significant risk of future criminal acts must be rigorously surveilled, so they will be detected early as they plan to commit crimes, and they can be quickly apprehended. Ankle bracelets are a favorite these days, the probation officer feeling more secure approving probation if the person’s whereabouts will be constantly monitored. Artificial intelligence is employed to scan prisoners’ telephone calls in order to uncover and foil plans for criminal

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acts such as gang operations or the smuggling of drugs into the prison (Francscani, 2019). Face recognition is quickly becoming the method of choice in the surveillance industry. There are three entirely false assumptions underlying public discussion of technology-​enhanced surveillance, and whether it is a positive or even acceptable development for our society. The first assumption is that ‘law-​abiding citizens’ who do not break laws have nothing to fear from the surveillance. But the truth is we all break laws. For example, we jaywalk. What if the surveillance cameras all along the street were programmed to recognize our faces as we jaywalk and an attached computer automatically mailed us a citation for jaywalking? It is very unlikely that cities and states will opt to police jaywalking this way, but the method can be applied to more serious crimes, or to identifying and arresting people on their way to a demonstration or to lead a protest. The technology is being used in China, especially with the Uigher community. Do we want to live in a society with this level of automated surveillance? The second false assumption is that a high-​tech surveillance system will be used to surveil everyone equally, in other words it is a random accident that one or another of us walks in front of the security camera at the corner store. This assumption is entirely false. Certain people would be surveilled more closely than others, for example young Black inner-​city males.3 In comparison with their White middle-​class counterparts, young Black men are more often stopped and frisked, more often arrested, more often convicted in court, more likely to receive a very long sentence; and—​a less well-​known fact—​behind bars they are more likely to be consigned to some form of solitary confinement. It is not that technology discriminates; rather it is that the cameras are mounted—​by people—​in areas where Black males are likely to appear on camera. After Black youth are surveilled, they are treated differently, in ways that confirm the assumption that fed the drive to surveil them in the first place—​that is, that there is a high risk they are up to no good. Racist assumptions like that have guided police activity for over a hundred years. What is new is the technology. Now, with face recognition technology in place, it will disproportionately be the faces of young Black men that are displayed on video screens at police stations—​with arrests following—​just as the police more frequently stop and frisk young Black men on the streets. The third false assumption is that all the science underlying research on risk assessment is valid. In fact, it is uneven at best. I find many articles in peer-​reviewed professional journals that do not deserve to be published because their design, their methodology and their

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interpretation of data are so faulty.4 And the psychological assessment instruments (psych tests) typically administered to prisoners can be quite misleading and unscientific in their methodologies, with quite a lot of racial bias. For example, the Minnesota Multiphasic Personality Inventory (MMPI) was created by testing White college students, and even with several subsequent revisions, there is still strong evidence of racial bias in the MMPI (McCreary & Padilla, 1977). In today’s debate, we talk about psych tests being ‘normed’, and that means the questions and results are adjusted to fit a different population than the college students whose test results are known. Far too little ‘norming’ is utilized in testing prisoners of color. Surveillance is used and abused by those in power to control those they have power over (Marx, 2016). There are immense implications for the survival of democracy (Webster & Krieger-​Lamina, 2013). Foucault (1977) referred to Jeremy Bentham’s Panopticon to make this point. For Bentham, the Panopticon was a reform, an Enlightenment way to quarantine and rehabilitate prisoners. The idea was for guards to be able to watch prisoners while prisoners were unable to see their warders but the experiment quickly morphed into a form of oppression, just as Benjamin Franklin’s and Friends’ experiment with social isolation at Philadelphia’s Walnut Street Jail soon turned into a crowded and abusive form of solitary confinement. The modern supermax prison shares a lot in common with the Panopticon but the surveillance is more advanced, with much better technology.

What does race have to do with it? Prisoners of color disproportionately fill super maximum solitary confinement cells. I discovered that tendency when I toured the prisons of a Midwestern state in the early 1980s for the Civil Rights Division of the US Department of Justice. The Civil Rights Division wanted my opinion about any racial bias there might be in the state’s prisons. In the course of the investigation I typically do in order to form a basis for expert opinions, I entered the state’s high security segregation units, the precursors of today’s supermaxes. There, I found a disproportionate number of prisoners of color, as well as many prisoners suffering from SMIs. Then, when I toured the sophisticated training workshops, for example a large cabinet making shop, I found mostly older White prisoners. These White men, in contrast to prisoners in solitary confinement, were learning a craft that would allow them to support themselves comfortably in the community after their release from prison. Prisoners who spend most of their time in

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solitary confinement will have much less chance to succeed at going straight after they are released. Indeed, recidivism rates are higher for prisoners who spend significant time in solitary confinement (Peterson & Jemelka, 2004; Lovell, Johnson & Cain, 2007). Thus prisoners who spend significant time in solitary confinement are sentenced in advance to poor post-​release adjustment in the community, their consignment to solitary having been based on past rule infractions with the prediction that their future behavior would likely mimic their past record. And it does. Is that because they are inherently trouble-​makers, or is it because their consignment to solitary causes a ‘decimation of life skills’ (Kupers, 2008), and after their stint in solitary they are much less capable of success in love and work, and therefore more prone to return to substance abuse and criminal acts? When prisoners of color disproportionately spend an inordinate amount of time in solitary, and subsequently fail in their attempts at ‘going straight’ after being released from prison, that data is used to confirm the prediction of risk that led to their long stints in solitary. Researchers examining recidivism rates and race are rarely interested in looking for that kind of flaw in their research methodology. A considerable amount of research reflects that significantly disproportionate numbers of Black prisoners and other prisoners of color are consigned to solitary. Thus, a 2016 report by the Association of State Correctional Administrators and The Arthur Liman Public Interest Program at Yale Law School concludes: ‘In 31 of the 43 reporting jurisdictions, the male restricted housing population contained a greater percentage of Black prisoners than did the total male custodial population in each of those jurisdictions’ (Camp, Camp & Resnik, 2016, p. 35). Margo Schlanger (2013) reviewed available data and concluded that in Arkansas, Colorado, Connecticut and New York, prisoners of color are overrepresented in supermax facilities. And Mears and Bales found a notably higher rate of supermax isolation placement for Black compared with non-​black prisoners in the Florida prisons between 1996 and 2001 (Mears & Bales, 2009, 2010). Andrea Armstrong (2015) studied the ways risk assessment plays a part in the consignment of a disproportionate number of prisoners of color to SHU: First, minority offenders may be more likely to be perceived as a disciplinary threat by correctional officers, regardless of an offender’s actual behavior. For example, a correctional officer may be more likely to perceive contraband in a black offender’s hand than in a white offender’s hand. A prison

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guard may also decide more quickly that a black offender is a threat as compared to a white offender, leading perhaps to increased citations for black offenders. It is also possible that the threat is exaggerated for minority offenders, and therefore, minority inmates may face more serious conduct reports than their fellow white inmates for the same type of behavior. (Armstrong, 2015, p. 770) Technology does not have political motives, the people who design the studies and run the technology do. Face recognition programs help surveil middle-​class shoppers for the purpose of advertising other commodities they might want to purchase. But in the inner city the larger use of face recognition technology is to surveil young men of color and prove they have committed or are about to commit a crime. This is racism. The fact that the discrimination and oppression of minority groups is accomplished through the utilization of advanced technology such as face recognition devices does not change the fact that the cameras are utilized for different ends along racial lines. In that sense, the newer technologies, and the future ones, will serve to preserve the current order by making the work of police and prisons much more efficient. But the uses of police and prisons are determined by those in power, and their job is to make certain that technology, including the technology of surveillance, serves their interests. Technology merely helps them get the job done. Today, mass incarceration is a major focus of attention for the public. Sentencing reform, the end of private prisons, the future of the death penalty, the end of supermax solitary confinement, and yes, the fact that racial bias played a huge part in the imprisonment binge of the last 40 years, all of these things are squarely at the center of our culture wars. Since it is no longer acceptable to openly express racist and bigoted ideas, they go underground. People don’t openly talk that way anymore. However, the old racism inevitably re-​emerges, for example in the racist notion that young Black males are especially prone to crime and violence (Alexander, 2010). Then, on a societal level, actions are taken that will make it all the more likely that this kind of racist risk assessment is proven correct. In other words, more Black youth will be frisked and more charged with crimes, they will spend longer terms in prison, which will greatly diminish their chances of succeeding at ‘going straight’ back in the community, and so forth. However, an even more important outcome of linking male Black youth with crime and violence is the conviction anchored in many people’s minds that young

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Black males are a threat to safety, and this becomes the rationale for the mass incarceration of a huge number of young Black men. Parole boards and correction officers are aware of research showing that Black prisoners are more prone to violence and crime in the future, as they dole out harsher terms in solitary confinement to the Black prisoners they believe to be at highest risk (Poole & Regoli, 1980; Silberman, 1995; Calavita & Jenness, 2015). And again, the way they treat Black prisoners makes it very likely that their negative assessment of them will prove correct—​that is, the prisoners in solitary now will be at increased risk of being cited for a rule violation or blamed for a fight after they are returned to the general population. And they will have to wait a longer time, on average, than their White counterparts to gain parole. Then, because of the relative lack of preparation for post-​release success, they are more likely to get into trouble back in the community (Gendreau, Little & Goggin, 1996; Lovell, Johnson & Cain, 2007).

Horace Horace is a Black prisoner in a maximum-​security prison who was sentenced to 90 days in solitary confinement—​it’s called administrative segregation in many states—​as a punishment for being in a fight on the prison yard. The truth is that he was only defending himself against a much larger prisoner who had aggressively propositioned him for sex. If he had not fought the man and made a good showing, he would have been raped. However, he can’t tell officers that he was fighting in self-​defense because that would constitute ‘snitching’ on the prisoner who assaulted him. Then he would be in danger of attacks from other prisoners because he broke the unwritten prison code’s prohibition against ‘snitching’ (Kupers, 2003). He decided it was better to accept the punishment than take on the risk of deadly retaliation for ‘snitching’. Horace soon discovers, as he sits on the narrow bunk in his cell all day with nothing to do, and eats meals on that same bed, that his anger is mounting. He keeps getting angrier and angrier about the stark conditions of isolation and idleness he is forced to endure. He feels the conditions are inhuman, or amount to torture, and on that we agree. However, the anger keeps mounting the more time he spends in solitary. Mounting anger that seems out of proportion with events is widely reported by the denizens of solitary confinement units. Eventually, after all attempts to control his anger have failed, he gets furious with an officer who is slow to bring food trays to his tier. That officer writes him a ‘ticket’, a disciplinary report, which results in his further punishment with an additional six months in ‘Ad Seg’.

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And on and on in the same fashion, until Horace ends up spending 12 years in solitary confinement. The man is deemed the ‘worst of the worst’, he is transferred to a supermax unit, a place dedicated to solitary confinement cells, and actually, far from being ‘the worst of the worst’, Horace sincerely dreads getting into fights and arguments with guards, but his situation requires he stand up for himself by fighting and the mounting anger in solitary is something he simply cannot control. Horace is the prototypic ‘guilty-​before-​the-​crime’ person. He really has not had a violent criminal background. He is in prison for robbing a corner store to get money to support his drug habit. He has never used a weapon, he did not deal drugs, and it was mostly bad luck that resulted in his arrest—​the officer who arrested him happened to be parked on the street when he ran out of the store he had just robbed. In prison, he tried his best to follow all the rules. He tried to stay out of fights, but he explained to me that sometimes you just have to fight to maintain your honor. He is Black, and that is a critical variable. Many more people of color, especially African Americans, wind up in supermax solitary confinement than do their White counterparts. That one fight got Horace sent to ‘the hole’ for 90 days. How did he wind up doing years and then decades in solitary confinement? Prison guards, on average, believe that Black men are more dangerous than prisoners of other races (Poole & Rigoli, 1980; Armstrong, 2015). When they enter the fray, for example, they heed the alarm and go to the ‘yard’ to break up a fight, they try to pick out the prisoners who started the fight and prisoners who seem to be beating up others, and they perform the in-​prison version of an arrest, writing a disciplinary ticket for the men they think are the toughest and the most responsible for the fight. Horace fits their pre-​conceived notion of a troublemaker. He is Black, muscular and can handle himself in a fight. So they write him a ‘ticket’. After a ‘ticket’ is written, a prisoner has a ‘hearing’, and a hearing officer decides whether he is guilty and what will be his punishment. A huge majority of ‘tickets’ that come to hearings are decided in favor of the officers and against the prisoner (Calavita & Jenness, 2015). In addition, implicitly the hearing officer calculates the prisoner’s risk for future violence and metes the longest term in SHU to prisoners who appear most at risk of future violence, and too often those prisoners are Black.

A self-​fulfilling prophecy A self-​fulfilling prophecy is deeply entrenched in our contemporary criminal justice system. The wave of ‘truth-​in-​sentencing’ laws of

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the late 20th century—​mandatory minimums, three-​strikes, harsher sentences for just about every crime—​were built on the logic of risk assessment. The defendant in a current criminal trial is given a longer and harsher sentence because his history includes other violent crimes, and past criminal behaviors are the best predictors of future dangerousness. That logic is mirrored by its reversal in the procedures for determining which prisoners are ready to be paroled. The parole board considers the prisoner’s past criminal convictions as well as his rule violations behind bars (and other factors, of course, such as his demonstrated remorse and the degree to which he has availed himself of rehabilitation programs) and decides if he is low enough risk of future crime and violence to be safe for release from prison. The fate of the Center for the Study of Pathologically Violent Individuals, a.k.a. the UCLA Violence Center of the early 1970s, provides an important lesson in the ‘tagging’ of underdog populations for surveillance and later for arrest and incarceration. In those days, research funds from the National Institute of Mental Health (NIMH) were drying up, and entrepreneurial mental health researchers were turning to law enforcement to fund their research. Law enforcement was relatively well funded and was seeking more psychology-​and science-​informed approaches. The federal Law Enforcement Assistance Agency (LEAA) funded a large research project at the UCLA Neuro-​ Psychiatric Institute (NPI) designed to identify potentially violent individuals. From the start there were moral and political problems with the Violence Center, such as the fact that early versions of the research proposal included plans to utilize neurosurgical interventions—​ psychosurgery for high-​risk individuals—​to reduce the occurrence of violence in the future (Kupers, 1973; Lemov, 2018). Here is the pre-​crime society at its worst; individuals deemed to be a high risk of future violence are punished pre-​emptively with psychosurgery to reduce the risk but also to cause flat affect and dull wit. The study within the Violence Center proposal that caught my eye was a plan to identify students in public high schools who would be prone to future violence. Of course, there would be follow-​up data on the fate of the research subjects, and if it turned out that the very individuals tagged in advance by the Violence Center researchers were, in fact, subsequently discovered to be serving time in jail or prison, then the researchers’ predictions of their future harm would have been confirmed. Or would this experiment prove that? As I pointed out at the time, one of the two schools set to be studied was in south central Los Angeles, the other in east Los Angeles (Kupers, 1974). The researchers planned to selectively study kids at a

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predominantly Black and a predominantly Latinx school. Why not a White school in a middle-​class neighborhood? And then, once they found that there were, indeed, some individuals in the high schools who they believed posed a high risk of future violence (it was inevitable they would find such individuals; in any group there are always individuals who appear as outliers on any variable being measured), they proposed watching the youth over time to see who, in fact, did eventually get involved in crime or violence. But the fact they were studying the youths would inevitably bring wider attention to the boys’ criminal acts. Remember, youths of color are more often stopped and frisked and more often arrested. So in fact, the treatment these young males would be subjected to subsequent to their assessment as posing a high risk of future violence,—​that is, having researchers carefully document their every contact with law enforcement—​would tend to support the stereotype that had already been in the researchers’ minds, that young Black and brown males are prone to crime and violence. How convenient that no White middle-​class school was included in the study, all the attention going to the risk of crime and violence from Black and Latinx youth. The diagnosis of Antisocial Personality Disorder (ASPD) is part and parcel of this self-​fulfilling prophecy. ASPD is presumably a lifetime pattern of criminal behaviors including callous disregard for the feelings of others (i.e. crime victims), impulsivity and an inability to plan ahead, a lack of empathy and other negative attributes. The pattern of law-​ breaking and callous disregard must begin by the mid-​teen years for the diagnosis of ASPD to be warranted. There are people who are properly diagnosed with antisocial personality disorder in early adulthood, about the time they arrive in prison, but contrary to popular belief, they are actually a small minority of those serving prison terms. I have met a large number of prisoners who were diagnosed ASPD at the time of their commitment offense at age 18 or 19, or 22 or 23. However, in prison, they had time to think about the destructive trajectory of their lives, they stopped using illicit substances, and they set about rehabilitating themselves. Most who dropped out of high school earned a General Educational Development degree (GED) in prison. Quite a few took college correspondence courses and worked hard to learn legal skills or skills in rehabilitation programs that will serve them well when they are released. Some act as jailhouse lawyers, helping other prisoners with appeals of their sentences and complaints about abuse in prison. And when I meet these prisoners during my prison tours in preparation for expert testimony in class action lawsuits, I am impressed with their self-​taught intellectual prowess, their capacity

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for empathy, their wisdom and their commitment to changing their ways. While in a certain number of cases it might have been accurate to say they exhibited callous disregard for the feelings of their crime victims when they were in their late teens, clearly the 35-​or 40-​year-​ old person I meet nowadays is a very different human being. In other words, they are quite the opposite of ASPD, but nevertheless, the tag has stayed with them. There are two places in prison where the diagnosis ASPD typically blocks the prisoner’s progress: the pursuit of mental health treatment and rehabilitation programs behind bars and application for parole. There is a bias in mental health treatment and rehabilitation programs against applicants who are diagnosed ASPD. The idea is that someone with ASPD is very resistant to mental health treatment and does not have the proper motivation to make good use of rehabilitation programs. Unmotivated and incorrigible. It is assumed prisoners diagnosed with ASPD are more interested in scamming the system than in self-​improvement. Prisoners diagnosed with ASPD are likely to wind up in solitary confinement rather than receiving the mental health treatment their condition requires, and rather than winning enrollment in sought-​after rehabilitation programs. And the psychologist who writes a report for the parole board is likely to weigh a diagnosis of ASPD as an indicator of high risk of future criminality and violence, and then the parole board is all the more likely to deny that prisoner parole. My own empirical observation, after interviewing and examining well over a thousand prisoners over the course of my career as a forensic psychiatrist, is that a huge majority of them no longer satisfy criteria in DSM 5 for the diagnosis of ASPD, though a certain number of them probably would have satisfied the criteria as much younger individuals. The ascription of current antisocial tendencies is simply erroneous and unfair in very many cases. The problem, when it comes to risk assessment, is that the diagnosis of ASPD is a lifelong tag. The psychologist performing risk assessments for the parole board looks at a number of variables, including the presence of ASPD, a record reflecting very serious and violent crimes, many disciplinary write-​ups during a prison career, a lengthy history of drug and alcohol problems, long stints in punitive segregation, a lack of positive programming and so forth. Missing is room for the prisoner to change, to reform, to prepare for a constructive life in the community following release from prison. Risk assessments conducted by correctional psychologists tend to penalize the prisoner applying for treatment, a prison job or for parole, with negative attributes dating back to the far past, and give the prisoner too little benefit of the

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doubt—​for example, when he proves, with disciplined study of the law and success in representing himself in court, that he is not impulsive and is capable of sustained and disciplined effort (impulsivity and lack of planning are criterion symptoms for the diagnosis of ASPD); or when he logs many years in prison serving as a mentor and tutor for younger prisoners who he helps stay out of trouble. A longer prison term will predictably make one more likely to reoffend after eventually being released from prison, and spending significant time in supermax isolation will worsen that prognosis. After all, people who spend relatively longer terms in prison and in solitary confinement are, in fact, more likely to re-​offend after leaving prison. The statistics on recidivism support that point (Gendreau, Little & Goggin, 1996; Lovell, Johnson & Cain, 2007). This is the self-​fulfilling prophecy. There is a risk assessment. The parole board accepts the psychologist’s calculation of risk of future crime and violence and releases those prisoners who are eligible for parole and seem to offer a low risk of reoffending. Those deemed high-​ risk are left to suffer the harms of incarceration for a longer period while those adjudged low risk are released into the community. Then, the outcome of events, for example the recidivism rate, is taken as proof of the accuracy of the original risk assessment. The way prisoners are treated in the meanwhile matters quite a bit—​that is, some are forced to endure more years in prison (i.e. they are repeatedly denied parole) and others enjoy a quicker return to the community and a better chance to re-​establish family ties and become productive participants in the community. There is a very popular notion in the criminal justice system that identifying individuals likely to be involved in future crime and violence, and instituting preventive measures, will somehow diminish the prevalence of crime and violence in the future. This was the hypothesis slated for testing at the UCLA Violence Center in the early 1970s. The methodology of the research proposed for the UCLA Violence Center, like much of the research involved in risk assessment, fits this template: • First, select potential perpetrators of future crime and violence. (Racial discrimination and stereotypes play a large role here.) • Next, study them, part of the study being more rigorous surveillance over time. For example, keep track of every contact they have with law enforcement. • Meanwhile, enhanced knowledge of their potential for eventual criminal activity leads law officers to keep even more of a close eye

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on them, perhaps suspecting them each time a crime occurs, and being quick to take them down to the station and book them. • Hypothesis confirmed! But could it be a self-​fulfilling prophecy? (Typically, the researchers are entirely uninterested in asking such questions.)

Conclusion We already live in a pre-​crime society. People who ran afoul of the law and went to prison (and people of color are vastly overrepresented here) are punished throughout their prison term and even after leaving prison with a thwarted future, before they commit any further crimes. Prisoners tagged as high-​r isk are not provided adequate opportunity to rehabilitate themselves, they spend inordinate amounts of time idle in solitary confinement, and then the tag makes it extremely difficult for them to succeed at ‘going straight’ after leaving prison. This self-​fulfilling prophecy has programmatic implications for jail and prison security in the digital age. Imagine progress toward mass de-​carceration (asymptotic diminution of the jail and prison population toward zero), beginning with an end to solitary confinement, massive expansion and upgrading of rehabilitation and education programs behind bars, as well as mental health treatment for those in need.5 From existing research it seems clear the result would be a great reduction in rule violations, prison violence and eventual recidivism rates (Ahalt, 2017; Bonita, 2017). Prisoners with something meaningful to do are simply much less prone to break rules and jump into violent altercations than are prisoners in overcrowded facilities or solitary confinement units where there is nothing meaningful to do and no way to prepare for success after release from prison (Smith, 2013; Bonta & Andrews, 2017). Currently there is a lot of interest in correctional circles in Norwegian and other Scandinavian prisons (Ahalt, Haney, Ekhaugen & Williams, 2020). There the emphasis is on rehabilitation, preparing prisoners to return to the community to work, to be loving family members and constructive members of the community. Not accidentally, the violence rate in Norwegian prisons as well as the recidivism rate for formerly incarcerated individuals are far lower than in the US, where rehabilitation is nowhere near as robust, and punishments, especially solitary confinement, are much more widely applied. What about the rest of us? What are the implications for society at large? Michel Foucault (1977) theorized that the chilling drama enacted in the prisons has the effect of making all of us that much more uncritically accepting of the reigning order. Bruce Arrigo (2013)

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goes on to provide us with a theoretical model for understanding the social meaning and implications of criminal justice practices. He points out that ‘the dominant institutional mechanisms/​techniques of risk management … reduce/​repress expressions of difference to sameness’. He continues, the forces of fear and desperation nurturing how human risk is presently experienced and institutionally managed [prison, solitary confinement and denial of parole] only further the marginalization of identity (pathologize, criminalize, demonize or sanitize difference). … This is the dysfunctional and maladaptive juncture wherein a society of captives (i.e. those whose difference is reduced/​repressed fearfully and desperately through extant institutional mechanisms/​ techniques that manage human risk dangerously) yields society’s own captivity. Thus, in Arrigo’s model, we create a ‘society of captives’, the prison industrial complex, and in the process we become a captive society wherein the ‘social person’s’ productive and dynamic potential is vastly limited (Arrigo, 2013, pp. 673–​76). One concrete expression of this repressive dynamic is the lack of initiative and constrictive lives I find among many, but certainly not all, formerly incarcerated people, especially if they have spent significant time in solitary confinement. Prison staff are singularly obsessed about prisoners’ conformity with the rules (Kupers, 2017). The ‘good prisoner’ is the one who unquestioningly follows the rules. And good prisoners avoid solitary and win parole. However, while they are in prison, and after they are released, they are prone to become noticeably passive, having forgotten how to think for themselves. I have discovered a ‘SHU post-​release syndrome’ in formerly incarcerated individuals who spent an inordinate amount of time in solitary confinement (Kupers, 2016, 2017). All too many of them are prone to be reclusive in the community, nervous about attending social events, hyperaware and quick to startle, and very hesitant to express any idiosyncratic thought or craving. I am afraid this is an embodiment of Arrigo’s ‘vastly limited dynamic potential’. On the other hand, I must note that it is truly inspiring to see the many formerly incarcerated individuals who struggle fiercely not to fall into passivity and reclusiveness in spite of the forces (including stigma toward ex-​prisoners) that obstruct their way forward. The example of the Angola Three is very compelling in this regard. Robert King (2009) and Albert Woodfox (2019), from the

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day they were finally released from prison, have campaigned relentlessly to bring an end to the prison industrial complex. There is a compelling parallel between the dynamics of prison life and the way our entire society works. In prison, putting more energy and resources into rehabilitation and lightening up on the harsh punishments would clearly lessen the violence rate and make solitary confinement obsolete. In society, putting fewer resources into the prison industrial complex and more into the schools, health care and social safety net would reduce society-​wide crime and violence. Zach Norris (2020) questions the effectiveness of long prison sentences and harsh prison conditions in reducing violence and keeping populations safe. He poses the contrast between the expansion of society’s education system and safety net with the ‘law and order’ mentality that drives longer sentences and more punitive correctional practices: ‘If lawmakers in the US had taken the path of investment to address issues most salient in poor communities, rather than dehumanization, deprivation, and punishment, it would have benefited everyone. We might now be in an era of less harm and greater prosperity for all’ (Norris, 2020, p. 9). Ultimately, the question we need to be most concerned about is not whether the prisoner under consideration for SHU consignment or for parole is a dangerous criminal, rather we should be most concerned about whether what is done to the prisoner during a term behind bars will make him or her more or less likely to reoffend and resort to drugs and violence after being released. And well over 90 per cent of prisoners will be released. If departments of correction would focus on utilizing the newer technologies to maximize the benefits of education and rehabilitation rather than to stigmatize prisoners as at high risk of future offending, then the criminal justice system could serve to alleviate the many ways people who commit crimes in their youth are condemned, before they even commit any further crimes, to fail in their efforts to re-​emerge from prison as law-​abiding, productive and loving members of the community. Notes 1

2

I have the privilege of serving as psychiatric expert witness in class action lawsuits challenging unconstitutional conditions and inadequate mental health treatment in jails and prisons. The lawsuits cannot accomplish all the changes that are needed. There must be mass mobilizations and legislative interventions along with the lawsuits if any real change is to be attained (Kupers, 2019). Three years is a popular choice for this kind of research, it is not that difficult to run a research project for three years, and it is likely that most of the recidivism will occur within the first three years.

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4

5

See OIG (Office of Inspector General) Finds a Lack of Controls and Procedural Fairness Protections in the Chicago Police Department’s ‘Gang Database’ That Undermine Public Trust and Confidence in the Police, April 11, 2019, Available at https://​www. lifepulsehealth.com/​pr/​oig-​finds-​a-​lack-​of-​controls-​and-​procedural-​f airness-​ protections-​in-​the-​chicago-​police-​departments-​gang-​database-​that-​undermine-​ public-​trust-​and-​confidence-​in-​the-​police/​203738. For example, researchers studied prisoners with serious mental illness in solitary confinement in the Colorado Department of Corrections and compared their symptomatology and disability to prisoners in the general population (O’Keefe, Kelli, Klebe, Stucker, Strum & Leggett, 2010). The study involved a comparison between a group of prisoners with serious mental illness in administrative segregation and another group, with equivalent psychiatric disorders, who were in general population settings. However, there were such fatal flaws in their methodology that the study should never have passed peer review (Grassian & Kupers, 2011; Haney, 2018). Of course, these changes would need to be accompanied by widespread de-​ carceration, including radical sentencing reform and robust efforts at diversion, the transfer of people in the criminal justice program to appropriate programs in the community, including supported housing, halfway houses, drug recovery programs and so forth. Robust restorative justice programs would be needed at every level, so the prison population could be massively reduced.

References Ahalt, C., Haney, C., Ekhaugen, K. & Williams, B. (2020). Role of a US-​Norway exchange in placing health and well-​being at the center of US prison reform. American Journal of Public Health. [online] Available at: https://​ a jph.aphapublications.org/ ​ d oi/​ full/​ 1 0.2105/ ​ A JPH.2019.305444?url_​ ver=Z39.88–​ 2 003&rfr_​ id=ori%3Arid%3Acrossref.org&rfr_​dat=cr_​pub%3Dpubmed&. Ahalt, C., Haney, C., Rios, S., Fox, M. P., Farabee, D. & Williams, B. (2017). Reducing the use of solitary confinement in corrections. International Journal of Prisoner Health 13: 41–​8. Alexander, M. (2010). The New Jim Crow: Mass Incarceration in the Age of Colorblindness. New York, NY: New Press. Armstrong, A. (2015). Race, prison discipline, and the law, Loyola University New Orleans College of Law Research Paper No. 2016–​ 01. [online] Available at: https://​papers.ssrn.com/​sol3/​papers. cfm?abstract_​id=2759562. Arrigo, B. (2013). Managing risk and marginalizing identities: On the society-​of-​captives thesis and the harm of social dis-​ease. International Journal of Offender Therapy and Comparative Criminology 57 (6): 672–​93. Bonta, J. & Andrews, D. (2017). The Psychology of Criminal Conduct (6th ed.). New York, NY: Routledge.

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Brinkley-​Rubinstein, L., Sivaraman, J., Rosen, D., Cloud, D., Junker, G., Proescholdbell, S., Shanahan, M. & Ranapurwaia, S. (2019). Association of restrictive housing during incarceration with mortality after release. Journal of the American Medical Association. [online] Available at: https://​jamanetwork.com/​journals/​jamanetworkopen/​issue/​2/​10 Calavita, K. & Jenness, V. (2015). Appealing to Justice: Prisoner Grievances, Rights, and Carceral Logic. Oakland, CA: University of California Press. Camp, G., Camp, C. & Resnik, J. (2016). Aiming to Reduce Time-​In-​ Cell: Reports from Correctional Systems on the Numbers of Prisoners in Restricted Housing and on the Potential of Policy Changes to Bring About Reforms. New Haven, CT: Yale Law School. [online] Available at: https://​www.cor.pa.gov/​About%20Us/​Initiatives/​Documents/​ Admin%20Segregation/ ​ A SCA%20Report%20November%20 2016%20Liman%20Aiming%20to%20Reduce%20Time%20In%20 Cell.pdf. Foucault, M. (1977). Discipline and Punish: The Birth of the Prison. New York, NY: Pantheon. Francscani, C. (2019). US prisons and jails using AI to mass-​monitor millions of inmate calls, ABC News. [online] Available at: https://w ​ ww. asca.net/​index.php?option=com_c​ ontent&view=article&id=209:us-​ prisons-​and-​jails-​using-​ai&catid=23:hot-​off-​the-​press-​. Gendreau, P., Little, T. & Goggin, C. (1996). A meta-​analysis of the predictors of adult offender recidivism: What works! Criminology 34: 575–​607. Grassian, S. & Kupers, T. (2011). The Colorado study vs. the reality of supermax confinement. Correctional Mental Health Report 1: 11. Haney, C. (2003). Mental health issues in long-​term solitary and ‘supermax’ confinement. Crime and Delinquency 49 (1): 124–​56. Haney, C. (2018). The psychological effects of solitary confinement: A systematic critique. Crime and Justice 47: 1. Hunt, K. & Easley, B. (2017). The Effects of Aging on Recidivism among Federal Offenders. Washington DC: The US Sentencing Commission. [online] Available at: https://​www.ussc.gov/​sites/​default/​files/​pdf/​ research-​and-​publications/​research-​publications/​2017/​20171207_​ Recidivism-​Age.pdf. King, R. (2009). From the Bottom of the Heap: The Autobiography of Black Panther Robert Hillary King. Oakland, CA: PM Press. Kupers, T. (1973). Brain Center for Violence. Health Policy Advisory Center. Kupers, T. (1974). Violence center: Psychotechnology for repression. Science for the People 6 (3): 17–​21.

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Kupers, T. (2003). Rape and the prison code. In D. Sabo, T. Kupers & W. London (eds.) Prison Masculinities. London & P ​ hiladelphia: Temple University Press (pp. 111–​17). Kupers, T. (2008) Prison and the decimation of pro-​social life skills. In A.E. Ojeda (ed.) The Trauma of Psychological Torture (vol. 5). Westport, CT: Praeger. Kupers, T. (2013). Isolated confinement: Effective method for behavior change or punishment for punishment’s sake? In B. Arrigo & H. Bersot (eds.) The Routledge Handbook of International Crime and Justice Studies. Abingdon, UK: Routledge (pp. 213–​32). Kupers, T. (2016). The SHU post-​release syndrome. Correctional Mental Health Report 17 (6): 81–​95. Kupers, T. (2017). Solitary: The Inside Story of Supermax Isolation and How We Can Abolish It. Oakland, CA: University of California Press. Kupers, T. (2019). Prospects for correctional mental health litigation. Correctional Mental Health Report 21 (4): 51–3. Lemov, R. (2018). An episode in the history of pre-​crime. Historical Studies in the Natural Sciences 48 (5): 637–​47. Lovell, D., Johnson, L. & Cain, K. (2007). Recidivism of supermax prisoners in Washington. Crime and Delinquency 52 (4): 633–​56. Marvell, T. & Moody, C. (1991). Age structure and crime rates: The conflicting evidence. Journal of Quantitative Criminology 7: 237–​73. Marx, G. (2016). Windows into the Soul: Surveillance & Society in an Age of High Technology. Chicago, IL: The University of Chicago Press. McCreary, C. & Padilla, E. (1977). MMPI differences among black, Mexican-​American, and white male offenders. Journal of Clinical Psychology 33 (1): 171–​2. Mears, D. & Bales, W. (2009). Supermax incarceration and recidivism. Criminology 47: 1131–​66. Mears, D. & Bales, W. (2010). Supermax housing: Placement, duration, and time to reentry. Journal of Criminal Justice 38: 545–​51. Mears, D. & Watson, J. (2006). Towards a fair and balanced assessment of supermax prisons. Justice Quarterly 23 (2): 232–​70. Moffitt, T. (1993). Adolescence-​limited and life-​course-​persistent antisocial behavior: A developmental taxonomy. Psychological Review 100: 674–​701. Norris, Z. (2020). We Keep Us Safe: Building Secure, Just, and Inclusive Communities. Boston: Beacon Press. O’Keefe, Maureen L., Kelli, J. Klebe, Stucker, A., Strum, K. & Leggett, W. (2010). One Year Longitudinal Study of the Psychological Effects of Administrative Segregation. Colorado Department of Corrections. [online] Available at: www.ncjrs.gov/p​ dffiles1/​nij/​grants/​232973.pdf.

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Patterson, R. & Hughes, K. (2008). Review of completed suicides in the California Department of Corrections & Rehabilitation, 1999 to 2004. Psychiatric Services 59 (6): 676–​82. Peterson, P. & Jemelka, R. (2004). Forecasting recidivism in mentally ill offenders released from prison. Law & Human Behavior 28 (2): 133–​55. Poole, E. & Regoli, R. (1980). Work relations and cynicism among prison guards. Criminal Justice and Behavior 7 (3): 303–​14. Smith, P.S. (2006). The effects of solitary confinement on prison inmates: A brief history and review of the literature. Crime and Justice 34 (1): 441–​528. Schlanger, M. (2013). Prison segregation: Symposium introduction and preliminary data on racial disparities, U of Michigan Public Law Research Paper No. 322 (June 28, 2013). Michigan Journal of Race & Law 18: 241–​4 [online] Available at: SSRN: https://​ssrn.com/​ abstract=2237979. Silberman, M. (1995). A World of Violence: Corrections in America. Belmont, CA: Wadsworth. Smith, P. (2013). The psychology of criminal conduct. In F. Cullen & P. Wilcox (eds.) The Oxford Handbook of Criminological Theory. New York, NY: Oxford University Press (pp. 69–​88). Way, B., Miraglia, R., Sawyer, D., Beer, R. & Eddy, J. (2005). Factors related to suicide in New York State prisons. International Journal of Law & Psychiatry 28 (3): 207–​21. Webster, R.J. & Krieger-​Lamina, J. (2013). Social perspectives of surveillance and democracy. Technical Report: Increasing Resilience in Surveillance Societies. [online] Available at: irissproject.eu/​?page_​id=9. Wildman, C. & Andersen, L. (2020). Solitary confinement placement and post-​release mortality risk among formerly incarcerated individuals: A population-​based study. The Lancet 5 (2): 107–​13. Woodfox, A. (2019). Solitary: Unbroken by Four Decades in Solitary Confinement, My Story of Transformation and Hope. New York, NY: Grove Press.

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Mass Monitoring: The Role of Big Data in Tracking Individuals Convicted of Sex Crimes Kristen M. Budd and Christina Mancini

Introduction In the United States, compared to persons convicted of violent, property or white-​collar crimes, individuals convicted of sex crimes are arguably one of the most highly monitored groups of offenders in contemporary times. While historically this was not always the case, sensationalized media accounts of high-​profile sexual assault-​homicide cases, particularly those committed against children, changed the sociolegal landscape—​from one of treatment amenability to one of punishment and deterrence (Sutherland, 1950; Jenkins, 1998). As a result, scrutiny of these individuals by lawmakers, criminal justice actors, and the public has continued to intensify over time. This level of scrutiny, in combination with new ways of managing these individuals’ access to or restriction from social spaces, spurred on by media narrative, public outcry, and reactionary policy making, led to numerous changes in law (Jenkins, 1998; Lynch, 2002; Sample & Kadleck, 2008; Budd & Mancini, 2017). Legislation crafted to monitor and track these individuals in communities started to proliferate and has become institutionalized at both the federal and state level (Jenkins, 1998; Lynch, 2002; Sample & Kadleck, 2008). A key aspect to implement this

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legislation was to leverage technology in conjunction with personnel power (e.g. law enforcement) to accomplish these legislative aims. Digital technology, such as databases to prevent, respond to, and investigate crimes, and technological monitoring, such as Global Positioning System (GPS) devices, has played an ever-​increasing role in criminal justice work (Eisenberg, 2017). The use of these technologies has become particularly prominent in tracking and monitoring individuals convicted of sex crimes (Eisenberg, 2017; McJunkin & Prescott, 2018). Improvements in technology and the ability to capture and store large quantities of data have evolved; therefore, the ways in which individuals who have been convicted of committing a sex crime(s) are monitored have become more sophisticated. This chapter will focus on the ways persons convicted of sex crimes are contemporarily monitored, specifically through two mechanisms: sex offender registration and notification (SORN) and electronic monitoring (EM). Both of these monitoring strategies amass large quantities of data (e.g. personal information, location tracking information) that are gathered, housed and maintained by law enforcement and various other agencies. While law enforcement generally has a primary role in monitoring this group of people, at the community level other branches of criminal justice, such as probation and parole, are also tasked with the day-​to-​day monitoring of these persons if they are still under correctional supervision. Additionally, the public has opportunities to monitor registrants within their communities, if and when they choose, via certain forms of publicly available data. Regardless of who is ‘watching’, it is the mass accumulation of data that makes this possible.

The use of technology: the rise of registration and public notification History, logic, and constitutionality Two pieces of legislation in the 1990s gave rise to sex offender registry and notification (SORN) systems in the US. The first, the Jacob Wetterling Act, was enacted in 1994 to respond to fear that individuals with prior sex crime convictions were a dangerous population in need of additional monitoring and surveillance by law enforcement. In 1996, the federal government mandated that states notify communities about the whereabouts of released, presumably, high-​r isk sex offenders. As a result, all US territories and tribal jurisdictions are required to develop and maintain SORN procedures.

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SORN laws are premised on a capable guardianship logic. That is, if there is greater surveillance by both law enforcement and the public of potentially dangerous offenders, crime prevention should occur. SORN is far-​reaching in the US. As of 2018, The National Center for Missing and Exploited Children (NCMEC) estimated there are close to one million registered sex offenders in the US. Although some evidence suggests this number could be inflated due to ‘double-​ counting’ of registrants (Harris, Levenson & Ackerman, 2014), what is not contested is that SORN now affects an increasing number of individuals who must abide by various ‘invisible punishments’ (Travis, 2005) including continued surveillance and monitoring post-​ incarceration. This includes the dissemination of personal data to law enforcement and the public. The US Supreme Court has upheld SORN practices in two notable decisions. In Smith v. Doe (2003), it ruled that registry and notification policies are not ex-​post facto punishment given that their purpose is regulatory and civil in nature. Thus, because the SORN requirement is not technically a separate sanction or punishment, registrants have no legal basis for ‘relief ’ from registry and notification requirements. A separate decision, Connecticut v. Doe (2003), involved claims from registrants that SORN procedures violated procedural due process. In particular, ‘Doe’ argued that the automatic registration and notification requirement triggered by a sex crime conviction was insufficient for ensuring ‘dangerousness’ and instead the state should be required to first have a hearing to establish suitability (i.e. one’s level of risk of recidivating) of registration. The High Court disagreed and reasoned that because SORN obligations are determined by prior conviction, and not a vague notion of ‘dangerousness’, there was no due process violation of the automatic restoration process requirements.

Amassing data through SORN: registries While ‘SORN’ is often discussed as one policy, there are distinctions between registry and notification procedures. Registries are databases maintained by law enforcement that include identifying information about registrants. While registry requirements might vary from jurisdiction to jurisdiction, at a minimum registrants are required to visit their local law enforcement on a regular basis and provide their names, home addresses, work addresses, aliases and other identifying and personal data. Additionally, during the intake procedure, law

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enforcement officials take a photo of the registrant and note details about their prior offense history.

Sharing data through SORN: public notification In contrast, public notification is the process by which such data are shared with the public. Public notification is most associated with a website, typically managed by the state law enforcement agency. Other forms of public notification include sending email alerts to citizens, distributing flyers, holding a public briefing and similar outreach efforts (Levenson, Brannon, Fortney & Baker, 2007). To be clear, there may be additional information that law enforcement collects that remains private, such as fingerprints and email addresses. The decision on what data to post publicly depends on the state; however, a key piece of federal legislation, the Sex Offender Registration and Notification Act (SORNA), which we turn to next, now provides a minimum set of data that must be shared with the public.

SORNA and new federal data collection requirements While the Wetterling Act and Megan’s Law compelled states and jurisdictions to develop SORN systems, federal law initially permitted wide discretion in the design of registries and notification procedures. As a result, registry and notification laws varied widely across jurisdictions (Mancini, Barnes & Mears, 2013; Lytle, 2019). For example, states were tasked with determining what constitutes a sex offense (and thus subjects one to register), the length of the obligation, and procedural aspects (e.g. how often should registry checks occur, how should information be disseminated?). Given concerns about the variation, in 2006 the federal government implemented the Sex Offender Registration and Notification Act (SORNA), which was embedded in the 2006 Adam Walsh Act (AWA). The Act aims to provide guidance to jurisdictions concerning their monitoring of registrants and set a guideline of minimum standards regarding data collection. As the government makes clear, SORNA sets a ‘floor, not a ceiling’ in that jurisdictions have authorization to go beyond these minimum guidelines (Office of Sex Offender Management, Apprehending, Registration, and Tracking Office, SMART, 2020, p. 6). Complicating this discussion is that fact that while over 60 percent of tribal jurisdictions and most US territories are in compliance with SORNA, only 20 states have met its minimum provisions (SMART,

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2019a). Thus, what follows is a broad overview of SORNA’s major provisions concerning surveillance and monitoring of registrants, with the caveat that non-​compliant jurisdictions might have practices that differ. SORNA’s new guidelines include: a) increasing/​standardizing the required minimum duration of registration for registrants, b) requiring additional jurisdictions (e.g. Indian tribes) to design and implement registry and notification policies, c) extending SORN to a greater number of individuals (including juveniles), d) clarifying that jurisdictions are responsible for documenting not just the residence of registrants but also the locations of their workplace and/​or school, e) requiring additional information from registrants and in-​person appearances to verify disclosed information, f) requiring more extensive registration information, g) increasing the scope of data shared with the public via notification, and h) mandating that registrants make periodic in-​person appearances to verify and update their information to local law enforcement agencies. Thus, SORNA dramatically increases the breadth of data that law enforcement should collect for registry systems. In particular, this includes: registrant name, including aliases; date of birth; physical description and identifying photograph; internet identifiers and addresses; telephone numbers; social security numbers; residence information, including for temporary lodging (e.g. travel); travel and immigration documents (e.g. passports); employment information; professional license(s) information; school information (name of school, address); vehicle information and driver’s license information; prior criminal arrest and conviction history; text (statute) of current offense; and DNA, fingerprints and palm prints.

SORNA and public notification Notably, SORNA does not mandate the disclosure of all of these data to the public (SMART, 2020). However, the Act specifies eight core types of personally identifiable data that should be shared on public websites and/​or through community notification including: a) name, including aliases, b) residence address, c) employment address, d) school or college address (if current student), e) license plate number and a description of any vehicle owned or operated by the registrant, f) physical description of the registrant, g) the sex offense for which the person is registered and any other sex offense for which the person has been convicted, and h) a current photograph of the registrant. States may go beyond these notification requirements, but are statutorily prohibited from posting data that could identify the victim (beyond

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sex and age) and the following data about the registrant: social security numbers, fingerprint and palm prints, DNA identifiers, and travel and immigration document numbers (SMART, 2020). Moreover, the federal government suggests that states provide a mechanism by which members of the public can check email addresses to verify whether they belong to a registrant. However, it cautions against posting registrants’ email addresses, citing the unintended effects (e.g. permitting ‘networking’ among registrants, and harassment of registrants; SMART, 2020). Two themes relevant to our discussion on monitoring and technology emerge from these federal changes. One is that it is the federal government’s position that SORNA should apply to a greater proportion of registrants—​amassing more data about more individuals convicted of sex crimes, which also includes juvenile perpetrators who are at least 14 years of age and have committed one of the offenses specified in SORNA. SORNA also makes it clear that jurisdictions need ever more information regarding registrants and, in many instances, should share several of those details to the public. Although the US Supreme Court has struck down a few technical aspects of SORNA, it has upheld it in numerous other cases, finding that it does not violate, for instance, constitutional protections barring ‘double jeopardy’, ‘retroactivity’ or ‘cruel and unusual punishment’ (SMART, 2019b, p. 1).

SORN and the public As mentioned previously, SORN laws assume public notification of registrants (i.e. making portions of registrant data publicly available for almost one million people; NCMEC, 2018), leads to a crime reduction of new offenses and particularly a reduction in repeat sex offenses. This awareness of potential offending by registrants, via public consumption of their registrant data, should theoretically encourage behavioral changes among the public, such as speaking to children and vulnerable populations about the presence of nearby registrants or avoiding contact with such individuals. This requires examining the extent of SORN awareness, consistency of use of registry data, and post-​viewing behavior following access.

Awareness and action While public awareness of SORN is high, prior scholarship, particularly during the height of federal intervention efforts to monitor registrants more stringently, indicated that only a small proportion of Americans

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had ever accessed their local registries. For example, in a 2014 study, Mancini reported that 22 percent of Americans had accessed their state registry in the past year. State-​level analyses, particularly in Nebraska and Michigan, suggest limited public engagement with their state or local registry as well, with 34 percent and 37 percent of the public reporting access, respectively (Anderson & Sample, 2008; Anderson, Evans & Sample, 2009; Kernsmith, Comartin, Craun & Kernsmith, 2009). Therefore, while mass quantities of data are available in order to monitor and track registrants, evidence thus far indicates that only a small proportion of community members are viewing these data. Recent research indicates an increase in usage percentages nationally. For example, in a comprehensive study of the public, Harris and Cudmore (2018) found 45 percent of Americans have checked a sex offender registry in the past. Of that group, though, only 4 in 10 people accessed the registry consistently (three or more times). Unexpectedly, most of those who reported checking the registry admitted that ‘curiosity’ was a primary motive, rather in an effort to inform their own future behaviors (e.g. avoiding registrants, educating children). For example, in the national study conducted by Harris and Cudmore (2018), while 60 percent of those who accessed the registry claimed to take some type of protective measures after visiting the registry, when probed, only a small proportion engaged in proactive behaviors theoretically assumed to result in crime reduction. To illustrate, only one in four disclosed the information to minors in the household; less than 10 percent improved their home security and less than 6 percent reported either varying their daily routine and/​or modifying plans regarding childcare. The guiding premise underpinning SORN is that the public will use the data gleaned from checking the registries and modify their behavior in some way as to prevent crime. However, based on extant scholarship, including across large national samples, that does not appear to be the way SORN functions in practice. Indeed, this mismatch between behavior and the logic of SORN is a likely contributor to what is well-​established in the criminological literature; namely, that prior studies have uncovered no consistent effect on SORN in reducing recidivism among registrants (Lussier & Mathesius, 2019, in review).

Perceptions of public notification The public is largely supportive of the release of registrant data, despite the inconsistent and questionable use of SORN systems and the lack of empirical analysis to support any deterrent function (Lussier &

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Mathesius, 2019). They support its use for a wide variety of offenders. Nationally, support for mandating registry obligations for those who have committed crimes against children and adults exceeds 90 percent (Mancini, 2014; Harris & Socia, 2016). Notwithstanding the absence of widespread utilization, most of the public believes notification is highly effective (Levenson et al, 2007). Moreover, the public expresses approval for the disclosure of personal and identifying data concerning registrants. For example, a study of Floridians found that majorities felt notification should include a registrant’s name, photo, home address, vehicle description and license plate number, victim age and HIV/​ AIDS status (Levenson et al, 2007). However, only a small proportion of residents were supportive of systems that would share registrants’ fingerprints, home telephone number and employment data (Levenson et al, 2007). Although there is widespread approval of registries across the public, some groups are especially supportive of SORN laws. For example, those who express a fear of crime and are misinformed about the nature and extent of sex offending (e.g. believing in ‘stranger-​danger’) view notification positively (Comartin, Kernsmith & Kernsmith, 2009; Kernsmith, Comartin & Kernsmith, 2016). Individuals who have children or minors living in the household, are politically conservative, and have less educational attainment are also significantly more supportive of management policies like SORN, compared to their respective counterparts (Pickett, Mancini & Mears, 2013; Kernsmith et al, 2016; Harris & Cudmore, 2018). At the same time, reliance on the registry and believing registrants are unlikely to be rehabilitated results in less concern about its collateral effects, such as the data on the registry being used to harass or intimidate registrants (e.g. Mancini, 2014). What about the people who are involved in managing this population—​law enforcement? Do such individuals view the registry positively? In comparison to the public, law enforcement is less convinced registries function to reduce crime. In a sample of police officers attending a training institute, Tewksbury and Mustaine (2013) found over 60 percent disagreed that registries result in deterring the general population, and an even greater proportion, exceeding 75 percent of officers were skeptical that registries deter registrants (Tewksbury & Mustaine, 2013). More recently, in a large national study of officers (N = 765), Cubellis, Walfield and Harris (2018) found that while a majority of officers believed the registry assisted with their investigatory duties, they were simultaneously doubtful that registries reduced recidivism. Moreover, in the Cubellis et al (2018) investigation, a majority of law enforcement professionals, especially

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those who worked in jurisdictions with a large number of registrants, recognized the potential for the unintended effects of registries (e.g. stigma, difficulty with reintegration) due to the public availability of a portion of their registrant data. While registry and notification laws are clearly preferred among the public, there is concern among scholars and law enforcement professionals that publicizing personal and identifying data about registrants has done little to influence crime rates, and instead has resulted in collateral consequences, such as displacement, harassment and employment difficulties (Pacheco & Barnes, 2013; Cubellis et al, 2018; Zgoba, Jennings & Salerno, 2018; also, Harris & Socia, 2016). Even so, as the new federal requirements outlined in SORNA suggest, SORN systems are only likely to expand in scope and content; in other words, continue to amass more data on individuals convicted of sex crimes and particularly for registrants who by either federal or state law are lifetime registrants.

The use of technology: the rise of electronic monitoring History, logic and constitutionality It is of importance to discuss how the rise of EM and its growing popularity, although in the margins in the early years, was interconnected with its use-​value to track and monitor persons convicted of sex crimes. EM in relation to managing convicted persons began with work at Harvard University in the early 1960s where they built the technology, portable transceivers, which allowed volunteer offenders to take a portable unit with them that sent messages back and forth from the volunteer to the base station (Burrell & Gable, 2008). At this point in history, this tracking via location data had a rehabilitative aim particularly given the psychological backdrop in which the device was created—​a way to make transportable positive-​reinforcement with the aim of behavioral change (Burrell & Gable, 2008). Ultimately, this version of EM never took off in popularity and EM went dormant. During this period of dormancy, the rehabilitative ideal fell out of favor and was replaced with a deterrence philosophy, which included strategies of surveillance and tracking to enforce criminal justice sanctions and rules put in place to socially control convicted persons living in communities (Halleck & Witte, 1977; Beyleveld, 1979). With this change in philosophy so too came the change in how EM would be subsequently applied to persons who violated the law.

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While experimentation with EM began in the early 1960s, commercial use of EM did not begin to propagate until the 1980s. Given the rapidly rising rate of incarceration at this time, certain judges were looking for innovative ways to keep non-​violent offenders out of the jail and/​or prison system (Burrell & Gable, 2008). A judge in New Mexico was the first judge to use EM to track three probationers with some success (Burrell & Gable, 2008). As time passed, EM became more and more intertwined with the workflow of the criminal justice system, particularly in terms of intermediate sanctions. Moreover, these methods of tracking became tools to supervise individuals at different stages of the criminal justice process, such as pretrial supervision, jail release programs, probation, parole and treatment enhancement (Crowe, Sydney, Bancorft & Lawrence, 2002). As the EM manufacturing market continued to grow, and as technology continued to improve, the rise of Global Positioning System (GPS) tracking came to fruition for public use in the 1990s (Burrell & Gable, 2008). Ideas were also starting to percolate about how this technology could be used in tracking and monitoring people who committed sex crimes. In 1998, the Journal of Offender Monitoring published an article titled ‘GPS: Is now the time to adopt?’ The advice put forth was that agencies needed to evaluate how tracking would assist their work, including how they would manage and ‘responsibly use’ data gathered from EM (Rensema, 1998, p. 5). Within this narrative was also the assumption that this technology first and foremost would be used by agencies to track and monitor ‘stalkers and pedophiles’ (Renesema, 1998, p. 5). Whether this was foreshadowing of what the future entailed for EM’s use with individuals convicted of sex crimes, ‘mass monitoring’ these individuals by way of EM has proliferated around the US, and while variation in EM laws and practice exists, this form of social control via data tracking does not seem to be waning any time soon (Eisenberg, 2017). In contemporary times, EM came to the forefront when John Couey, who was on the Florida sex offender registry, kidnapped Jessica Lunsford in 2005 and then sexually assaulted and murdered her. Couey was also working at Jessica’s school as a contract construction worker due to the omission of a background check (Memmott, 2005). Even though Couey was a registrant, which should have been one way to monitor and surveil him, there was no way to know where this person was located in the community in real time. The facets of the case led to intense media attention, public outcry and lobbying, as Jessica’s father urged Florida government officials to take immediate action to close the perceived loophole in monitoring and tracking this population (Dante, 2012). Mirroring the trajectory of other sex offender-​specific

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laws, the result was the passage of the Jessica Lunsford Act (2005) or Jessica’s Law, which increased sentencing severity for certain sex crimes, strengthened registration requirements, and stipulated GPS monitoring for persons convicted of certain sex crimes and also lifetime monitoring for those assessed as sexual predators (Calkins, Jeglic, Beattey, Zeidman & Perillo, 2014). Nationally, shortly thereafter, the AWA (2006) included specifications for electronic monitoring: 1) it was required as a condition of release if a person was convicted of certain sex crimes or failed to register and 2) it provided states with an opportunity to get federal money if they mandated persons convicted of certain sex crimes to be monitored electronically (Calkins et al, 2014). Once federal monies became available, EM in relation to sex offender management quickly spread. Between the rise of SORN and the rise of EM, big data to track and monitor persons convicted of sex crimes was the next evolution to keep the public safe. Although throughout history no other group of offenders has been monitored with such intensity and longevity. In a case that may have ramifications moving forward for EM programs of persons convicted of sex crimes, the US Supreme Court in Grady v. North Carolina (2015) ruled that attaching a continuous satellite-​based monitoring system on a person was considered a search under the Fourth Amendment. In this case, Torrey Dale Grady challenged the North Carolina law that would have required him to be on continuous and lifetime GPS monitoring after he served his term of incarceration. The law stated The satellite-​based monitoring program shall use a system that provides all of the following: 1) Time-​correlated and continuous tracking of the geographic location of the subject using a global positioning system based on satellite and other location tracking technology. 2) Reporting of subject’s violations of prescriptive and proscriptive schedule or location requirements. Frequency of reporting may range from once a day (passive) to near real-​time (active). (North Carolina Gen. Stat. Ann. §14–​208.40) The Supreme Court would not decide on whether the search was unreasonable but they did concur, a search occurred. Hence, the case was remanded back to the lower courts and the lower courts will have to assess (un)reasonableness under the Fourth Amendment. According to McJunkin and Prescott (2018), some of the questions the courts will have to decide are whether such monitoring and mass data collection

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intrudes upon reasonable expectations of privacy particularly when having an EM device on a person is nonconsensual.

Types of electronic-monitoring data While this chapter will refer to EM generally as an all-​encompassing term for different types of EM, we will describe the different types of GPS tracking here, given this is the most prominent type of EM generally, and used with this population. GPS tracking can take three forms: active, passive and hybrid. Active GPS tracking is the closest type of tracking resembling ‘real-​time’ data. This may also be the type of tracking most people conjure when thinking about GPS tracking more generally (e.g. media portrayals). When an offender is actively tracked, their GPS tracking device sends data within small intervals (e.g. every ten seconds or every few minutes). Therefore, community management personnel can know where someone is in almost real time including alerts to possible violations (e.g. being too close to a place where children congregate). While one would think this version of GPS tracking would be ideal and used most widely, it is quite expensive and used less frequently (Meloy, 2014). Passive GPS tracking also monitors the offender in ‘real time’, but data are only viewed retrospectively. Data from passive GPS tracking are only downloaded once per day, for example. Community management personnel then review the data to see if any violations occurred. This is the least expensive type of GPS tracking and used most frequently (Meloy, 2014). The final version of GPS tracking is the hybrid model. In hybrid models, data are collected in real time but sent to community management personnel much less frequently compared to the active model. Still though, the hybrid transmission rate is still higher than the passive model. If the unit registers a violation under this model, the system switches to ‘active’ mode so that community management personnel can investigate in real time. This system is less expensive than the active system but more expensive than the passive system (Meloy, 2014). To collect tracking data, offenders are fitted with either a two-​ piece or one-​piece GPS unit; therefore, the GPS unit(s) becomes part of their person for the duration of their EM tracking.

State models Because the criminal justice system in the United States is decentralized, it is difficult to ascertain exactly how many persons convicted of sex crimes are on EM. As one example though, data from a 2010 California Department of Corrections and Rehabilitation report

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estimated approximately 6,600 individuals convicted of sex crimes in California were monitored by GPS tracking while on parole and living in the community (CDCR, 2010). It is somewhat easier to estimate the number of states who have EM laws. Based on available data, over 40 states have laws on the books and in action allowing the EM of individuals convicted of sex crime(s) (NCLS, 2008; Dante, 2012; Corsaro, 2015). As of 2014, there were ten states that had enacted lifetime EM (Dierenfeldt & Carson, 2017). While there is variation in law by state, three models will be discussed that have either been the basis of adoption by other states or because the model itself is unique in some way.

Florida Florida was the frontrunner for EM implementation. Within the Florida model, as of September 1, 2005, the effective date of the Jessica’s Law, all individuals convicted of certain violent sex offenses were required to be monitored using EM during their period of community supervision (e.g. probation; Dante, 2012). This law was written to apply retroactively and therefore had possible ramifications for offenders who were convicted on October 1, 1997 onward, although their EM was discretionary (Dante, 2012). However, the Florida legislature passed an additional statute that same year stating that if an offender violated their community supervision, the court must impose EM (Dante, 2012). Through a series of court cases, it became clear—​the court had no discretion over these individuals’ lives and their sanctions if they violated community supervision. Even if the violation occurred well after the original sex crime conviction (e.g. decades later) and even if the violation was not sex crime related (e.g. habitually driving on a suspended license), the court had to impose EM (Dante, 2012). Ultimately, this model rests on the conviction offense, does not use validated risk assessment tools to inform decisions regarding EM and is both prospective and retroactive in its application.

California California’s version of Jessica’s Law was passed in 2006—​the Sexual Predator Punishment and Control Act (Proposition 83). Viewed by Dante (2012) as the ‘harshest statutory model’, this law requires lifetime EM as soon as a person is paroled (p. 1177). Compared to the Florida model, the California version is distinct in a few specific ways: a) a wider variety of sex crimes triggers EM; b) convicted offenders must

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pay for their EM; and c) the law is only prospective in nature (Dante, 2012). The California courts have interpreted the language of the statute to not apply retroactively. Regardless, this model has resulted in the state of California having the largest EM program in the US (Gies, Gainey & Healy, 2016).

Massachusetts In Massachusetts, judges have discretion in the initial sentencing when determining length of probation, but they have no discretion on whether probation should include EM. By law, the offender must be on EM for the full term of their probation (Dante, 2012). Similar to California, the list of offenses that would trigger EM is broad and offenders have to pay for their own EM (Dante, 2012). Somewhat akin to Florida, the statute also has a violation clause although it focuses on sex offender registration violations. If a registrant continually violates registration requirements, they may be put on community supervision for life, which also means mandatory EM for life (Dante, 2012). In Massachusetts, SORN data collection may ultimately be supplemented by EM data collection. Unique in this model is that the law actually details how these data will be used (Dante, 2012; Corsaro, 2015).

Law enforcement and the use of electronic-monitoring data One of the initial attractions of EM to justice system professionals was its ability to track and surveil registrants, who may, like John Couey, ‘fall through the cracks’. Put differently, although EM was viewed initially as a mechanism to address the perceived shortcomings of SORN alone, as the number of registrants increased, it was subsequently seen as a way to address workload management while also being able to increase the effectiveness of community supervision (Payne & DeMichele, 2011). Based on the published research, it does not seem that EM is meeting all of these goals. Even with such technological advances, this work has become an increasingly time intensive job for law enforcement (Horst, 2007; Bishop, 2010; Payne & DeMichele, 2010; Armstrong & Freeman, 2011; Chamberlain, Smith, Turner & Jannetta, 2019). For studies assessing workload, EM seems to increase rather than maintain or decrease workload (Payne & DeMichele, 2010; Armstrong & Freeman, 2011; Chamberlain et al, 2019). In Payne and DeMichele’s work (2010), 80 percent of their probation and parole

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survey respondents who used GPS to monitor persons convicted of sex crimes said their work load was slightly too large or much too large. Chamberlain and colleagues (2019) found similar results with parole officers in California. Given the function of alerts produced from EM (e.g. possible violations), these would play a critical part in law enforcement’s use of EM data and their workload. Armstrong and Freeman (2011) assessed alerts triggered by EM for ‘dangerous crime against children’ offenders as defined by Arizona law. Over the roughly two-​year time span of tracking alerts since the implementation of their EM program, which used both passive and active GPS systems, alerts were produced less than 100 times during the first two months but toward the last quarter of data collection, almost 2,200 alerts—​a 2000 percent increase over 29 months—​occurred. This result speaks indirectly to the increase in workload over time (Armstrong & Freeman, 2011). Of those alerts, 63% were defined as ‘other technical violations’, which included loss of signal (~37 percent), power or phone line disconnects (~20 percent), or the inability to connect to caller ID (~6 percent). During these technical difficulties with equipment, which are much less likely to be deliberate by the offender, offenders were not being tracked (Armstrong & Freeman, 2011). If one goal is public safety, technology still has flaws that limit its capability to continuously collect data from the device about the person being monitored (e.g. entering a building and losing signal). Equipment tampering alerts had the second highest percent at 22 percent, which would be seen as deliberate by an offender (e.g. tampering with or removing equipment; Armstrong & Freeman, 2011). Considering the goal of GPS monitoring is to ensure public safety, the alerts that would seem most crucial would involve area violations (i.e. offenders were somewhere they were not supposed to be) and time violations (e.g. breaking curfew)—​most likely deliberate actions by the offender (Armstrong & Freeman, 2011). These alerts accounted for approximately 9 percent of alerts—​inclusion zone violation (~5 percent), exclusion zone violation (~2 percent), and curfew violation (~2 percent; Armstrong & Freeman, 2011). Taken all together, these findings echo a provocative thought put forth by Chamberlain and colleagues (2019): Are we spending more time monitoring the equipment versus monitoring those on EM? While this mass data collection should theoretically assist law enforcement, the instruments of mass data collection can have their own problems. For example, in 2010 a storage facility exceeded its

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data limit crashing its system leaving 49 states without access to their EM data for 12 hours on roughly 16,000 offenders, which included individuals convicted of sex crimes (The Wichita Eagle, 2010; Osher, 2016). Colorado requested to have their EM program reviewed federally by the National Institute of Corrections after a series of parolees on EM committed additional sex crimes and homicides (Osher, 2016). Tennessee also had an audit that revealed 80 percent of their alerts were not cleared or confirmed (Osher, 2016). Based on an open records request, The Denver Post calculated that within six months the Colorado Department of Corrections team of 212 parole officers had to respond to nearly 90,000 alerts (Osher, 2016). These illustrations highlight a multitude of issues with big data and mass monitoring—​ potentially burdensome workloads and technological failures. Would these tradeoffs be worth it if EM resulted in lower recidivism rates?

Electronic monitoring and recidivism The research addressing the use of EM with persons convicted of sex crimes in relation to sexual recidivism is still sparse; therefore, we cannot make firm conclusions about the success of EM in relation to its capacity to stem sexual recidivism but some general patterns are evident. When comparing rates of sexual recidivism, evidence indicates that whether or not persons convicted of sex crimes are subjected to EM, their sexual recidivism rates are the same or similar with no significant differences (Gies et al, 2012; Turner, Chamberlain, Jannetta & Hess, 2015; Gies, Gainey & Healy, 2016). Other research has assessed the implementation of EM legislation to see if it affected the rate of forcible rapes within states (Button, DeMichele & Payne, 2009; Dierenfeldt & Carson, 2017). Thus far, this line of inquiry has found no significant decreases in the rate of forcible rates pre-​and post-​EM implementation (with the exception of a small decrease in Georgia; see Dierenfeldt & Carson, 2017). Segments of the public do buy in that EM is an effective strategy to reduce sexual recidivism, even though thus far research shows null results (e.g. parents; Budd & Mancini, 2017). That is not to say EM has no use-​value with this population. Some research has found EM increases parole compliance (Gies et al, 2012; Turner et al, 2015) and reduces absconding (Turner et al, 2007). Reflecting on Renzema (1998), ‘If the net effect of tracking is to make it easier to prove a violation rather than to prevent recidivism, then tracking may not be worth the cost’ (p. 5).

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Discussion Big data are playing an ever-​increasing role in managing persons convicted of sex crimes. With the implementation of SORN and the rise of EM, this population arguably has more about their life amassed on data servers compared to other populations of offenders. Portions of this data are publicly available. Moreover, built into federal and state laws are the possibilities and probabilities these data-​amassing mechanisms may be for life. Given the compounding effects of increasing numbers of those subjected to lengthy or lifetime monitoring and surveillance, this system is molding a new generation of criminal justice practices—​ whether or not they are evidenced-​based. This in and of itself has implications not only for the justice system generally but also criminal justice actors who are charged with implementing and maintaining these mechanisms of social control and for those who are mandated by law to SORN and/​or be subject to EM. The criminal justice system is already a massive conglomeration at the local, state and federal level, which carries a hefty price tag to operate and maintain. Public safety initiatives such as the SORN and EM compound those costs at the state level even with grants and lines of funding from the federal government. Unknown is how much it costs to manage and maintain state-​level SORNs, but some preliminary analysis has been conducted to tap these expenditures. According to data provided by the Justice Policy Institute (2009), states would have been fiscally better off not implementing SORNA. For example, states would have had to spend anywhere from roughly $900,000 (Wyoming) to $59 million (California) to implement it (JPI, 2009). In relation to EM, according to Omori and Turner (2015), who studied California’s GPS monitoring program, parolees on GPS versus not on GPS were more expensive to manage, yet parole violations for the two groups were similar. Moreover, those who were on GPS had to remain on parole longer, which means additional costs for monitoring, equipment and personnel (Omori & Turner, 2015). While some states do require probationers, parolees and others being monitored under these programs to pay for the EM, which may be one way to offset costs, the price tag to maintain such public safety initiatives will be a steep one. Additionally, persons convicted of sex crimes face challenges related to employment. If they cannot pay, and violate parole, is prison their next destination? Costs are not only fiscally related but also related to personnel. Given the evidence of correctional officers’ increasing workloads (Payne & DeMichele, 2010; Armstrong & Freeman, 2011;

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Chamberlain et al, 2019), the growing number of individuals subject to SORN and/​or to EM will continue to increase particularly in states where lifetime EM is a reality and federal and state laws make lifetime SORN a possibility.

Pre-​crime society implications Pre-​crime societies, in their simplest form, are those where social control measures are taken to prevent anticipated crimes that may never come to fruition, particularly in the name of (public) security (Zedner, 2007). While those convicted of sex crimes have technically been adjudicated and sanctioned, post-​crime society attributes (Zedner, 2007), their management in the community speaks to pre-​crime society attributes. This has translated into mechanisms of hyper-​security and hyper-​control to prevent sex crimes that no longer just include state-​sanctioned government actors but also community members (e.g. SORN, particularly public notification) and private industry (e.g. EM). In short, the espoused pre-​crime society security logic to protect community members from potential and anticipated sex crime victimization by those already convicted of these crimes has become big business in the private sector and also a time intensive and expensive endeavor for government and criminal justice agencies. How did this pre-​crime society approach with this population come to be? Myths surrounding sex crime perpetration and treatment amenability play a prominent role, which has influenced multiple pre-​crime society laws, like SORN and EM (e.g. Quinn, Forsyth, & Mullen-​Quinn, 2004; Mancini & Budd, 2016; Budd & Mancini, 2017). Through sex crime recidivism research though, we have learned that recidivism for those convicted of sex crime(s) is much more likely to be the commission of non-​sex crime(s) and, while this line of research is still developing, sex crime recidivism varies depending on the type of sex crime(s) committed, tends to be low, and can be further lowered through treatment (Przybylski, 2015; Kim, Benekos & Merlo, 2016). Hence, the risk for sexual reoffense is not equal across offender categories. Yet pre-​crime society security mechanisms are designed to address the anticipated recommission of a sex offense at an assumed homogenous high rate. Moreover, based on current data, these security mechanisms have not been shown to meet their objective of lowering sex crime recidivism, which contradicts the pre-​crime society logic used to design them (Gies et al, 2012; Turner et al, 2015; Gies et al, 2016; Lussier & Mathesius, 2019). While SORN and EM have public support, as we culturally grapple

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with how to respond to individuals who commit sexual assault, we must ask if these laws and policies as designed continue to feed into a culture of fear about crime generally, and sexual assault specifically, which then perpetuates the need for such intensive pre-​crime society mechanisms of social control.

Conclusion We ask, in light of the implications of a pre-​crime society and hyper-​ focus on security and social control, would these laws be more effective in increasing public safety and other aspects of criminal justice functioning (e.g. workload, cost) if they were used in a more constrained manner? For instance, does SORN data need to be publicly accessible? Large portions of the public are not accessing these data (Anderson & Sample, 2008; Anderson et al, 2009; Kernsmith et al, 2009). Based on survey data, many community members who access SORN websites admit doing so out of curiosity rather than due to concern about their safety or the safety of others (Harris & Cudmore, 2018). Perhaps the US should consider modeling countries such as Canada where only law enforcement has access to SORN data. On one hand, it is logical to provide law enforcement with data that assist them in doing their job (e.g. SORN data and investigations such as a readymade list of suspects). Yet, on the other hand, can too much data bog down law enforcement and actually make it more difficult to do their job, resulting in systematic inefficiencies (e.g. ‘false alert’ data from EM)? Questions law enforcement agencies should ponder is how much data are needed to meet the goals of improving public safety while not sacrificing the quality of police work (e.g. due to increasingly heavy workloads). These long-​term and lifetime stipulations written into these laws should also be evaluated in terms of evolving research. One of the big critiques of the AWA/​SORN law and EM laws is that these were not first evaluated as evidence-​based before widespread implementation throughout the US. Looking back at history, it typically tends to be rare to see a massive overhaul and or rollback when it comes to criminal justice policies like these. Despite this wide reach, two of SORN’s guiding assumptions—​that it deters recidivism and increases capable guardianship among the public—​have not been realized. Overall, in line with the impressions of law enforcement (Tewksbury & Mustaine, 2013; Cubellis et al, 2018), registries are not associated with a reduction in recidivist sex crimes (for a recent review, Lussier & Mathesius, 2019). Secondly, and most critical to

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the logic underpinning community notification, most Americans do not check their local registries with any consistency or with the goal of using such information to better protect themselves or others (Anderson et al, 2009; Mancini, 2014; Harris & Cudmore, 2018). Among those who do access registry information, on occasion or with any regularity, very few fail to translate that knowledge to action (e.g. modify daily routines in a manner that would reduce victimization; Harris & Cudmore, 2018). Suggesting similar null effects, while EM evaluation is young, studies thus far have not uncovered any appreciable deterrence effect (e.g. sexual recidivism) although there have been a few positive outcomes of EM (e.g. general parole violations and absconding; Turner et al, 2007; Gies et al, 2012; Turner et al, 2015; Gies et al, 2016). This begs the question, are lifetime schemas worth the investment/​cost if they are not meeting their intended objectives (e.g. reduce sexual recidivism) nor based on scientific risk assessment? To note, research shows that high-​r isk sex offenders may not be high-​r isk forever—​that over time the longer one is ‘sex offense free’ the likelihood of sexual recidivism decreases over time (Hanson, Harris, Helmus & Thornton, 2014). Hanson and colleagues (2014) found this relationship to be particularly strong for those deemed high-​r isk. Therefore, evidence such as this calls into question any type of lifetime EM. Moreover, if scientific evidence continues to build in this regard, SORN could be tailored so that those on lifetime registration have a means of removing their name from the registry. In short, they would have a way to break the metaphorical data tether, particularly with community management strategies that impart such a high level of stigma where successful crime-​free integration becomes extremely challenging (Robbers, 2009; Dante, 2012; McJunkin & Prescott, 2018). What is the future of technology, data, and mass monitoring for those who commit sex crimes? Is it just to have persons registered and/​or tracked via EM for life if their designation was based on crime type versus scientifically validated risk assessment tools; if they never have a way to show, via well-​developed scientific tools, that they no longer pose a risk to community safety? To echo Button and colleagues (2009), are these data-​driven laws an emotional reaction versus being grounded in best practices? Ultimately, can we balance the needs of public safety, fiscal responsibility and human capacity, and the reentry needs of those subjected to registration and/​or EM, permanently or temporarily, to create a more just, equitable, and safe society?

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Pacheco, D. & Barnes, J.C. (2013). Sex offender residence restrictions: A systematic review of the literature. In K. Harrison & B. Rainey (eds.) The Wiley-​Blackwell Handbook of Legal and Ethical Aspects of Sex Offender Treatment and Management. Hoboken, NJ: John Wiley (pp. 424–​44). Payne, B.K. & DeMichele, M.T. (2010). Electronic supervision for sex offenders: Implications for work load, supervision goals, versatility, and policymaking. Journal of Criminal Justice 38b(3): 276–​81. Payne, B.K. & DeMichele, M.T. (2011). Sex offender policies: Considering unanticipated consequences of GPS sex offender monitoring. Aggression and Violent Behavior 16: 177–​87. Pickett, J.T., Mancini, C. & Mears, D.P. (2013). Vulnerable victims, monstrous offenders, and unmanageable risk: Explaining public opinion on the social control of sex crime. Criminology 51: 729–​59. Przybylski, R. (2015). Recidivism of adult sex offenders. Washington, DC: SMART. [online] Available at: https://​www.smart.gov/​pdfs/​ RecidivismofAdultSexualOffenders.pdf. Quinn, J.F., Forsyth, C.J. & Mullen-​Quinn, C. (2004). Societal reaction to sex offenders: A review of the origins and results of the myths surrounding their crimes and treatment amenability. Deviant Behavior 25 (3): 215–​32. Renzema, M. (1998). GPS: Is now the time to adopt? Journal of Offender Monitoring 11 (2): 5. Robbers, M.L. (2009). Lifers on the outside: Sex offenders and disintegrative shaming. International Journal of Offender Therapy and Comparative Criminology 53: 5–​28. Sample, L.L. & Kadleck, C. (2008). Sex offender laws: Legislators’ accounts of the need for policy. Criminal Justice Policy Review 19 (1): 40–​62. Sutherland, W.H. (1950). The diffusion of sexual psychopath laws. The American Journal of Sociology 56: 142–​8. Tewksbury, R. & Mustaine, E.E. (2013). Law-​enforcement officials’ views of sex offender registration and community notification. International Journal of Police Science & Management 15: 95–​113. The Wichita Eagle. (2010, October 7). Sex offender monitor system out for 12 hours. The Wichita Eagle. [online] Available at: https://​ www.kansas.com/​news/​nation-​world/​national/​article1049156.html. Travis, J. (2005). But They All Come Back: Facing the Challenges of Prisoner Reentry. Washington, DC: The Urban Institute.

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Turner, S., Chamberlain, A.W., Jannetta, J. & Hess, J. (2015). Does GPS improve recidivism among high risk sex offenders? Outcomes for California’s GPS pilot for high risk sex offender parolees. Victims & Offenders: An International Journal of Evidence-​Based Research, Policy, and Practice 10: 1–​28. Turner, S., Jannetta, J., Hess, J., Myers, R., Shah, R., Werth, R. & Whitby, A. (2007). Implementation and Early Outcomes for the San Diego High Risk Sex Offender (HRSO) GPS Pilot Program. Irvine, CA: Center for Evidence-​Based Corrections. Available at: http://​ucicorrections. seweb.uci.edu/​files/​2013/​06/​HRSO_​GPS_​Pilot_​Program.pdf. Zedner, L. (2007). Pre-​crime and post-​criminology? Theoretical Criminology 11 (2): 261–​81. Zgoba, K.M., Jennings, W.G. & Salerno, L.M. (2018). Megan’s law 20 years later: An empirical analysis and policy review. Criminal Justice and Behavior 45 (7): 1028–​46.

Cases cited Connecticut Department of Public Safety v. Doe, 538 U.S. 1 (2003) Grady v. North Carolina, 135 S. Ct. (2015) Smith v. Doe, 538 U.S. 84 (2003)

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Towards Predictivity? Immediacy and Imminence in the Electronic Monitoring of Offenders Mike Nellis

Introduction ‘Electronic monitoring (EM)’ is a form of ‘coercive connectivity’, a generic term for a range of correctional technologies which utilize networked communication systems and body-​worn sensors (‘tags’—​ usually on ankles, sometimes wrists) to pinpoint and track the locations and movements of defendants and offenders. They are used by judicial and penal authorities to monitor real-​time compliance with supervisory regimes of varying restrictiveness and duration, at the pretrial, sentencing and post-​release stages of the criminal justice process. More recently, immigration authorities in some countries, notably the US, have adopted location monitoring, using the same rationale—​they are an ostensibly cheaper form of control than imprisonment and detention, albeit with distinct restrictions and ‘pains’ of their own. Although short range radio frequency (RF) detection systems for enforcing home confinement (the original judicial form of EM), still exist, Global Positioning System (GPS) satellites, ostensibly for tracking movement, and enforcing inclusion/​exclusion zone boundaries (including house arrest), have become dominant. Biometric voice verification of identity and location simultaneously (which unlike RF and GPS does not require a wearable device, just a phone) has been relatively little used. Remote alcohol monitoring technologies—​wearable or portable

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devices connected to communication networks, used to enforce or regulate court-​ordered sobriety—​have expanded the definition of EM beyond mere location monitoring. What all existing forms of EM have enabled in community corrections and law enforcement is ‘immediacy’—​a capacity to know, or verify, an offender’s location remotely in real-​time, which made new forms of compliance, control and containment possible. The forms in which EM has developed since the 1980s, and the discourses surrounding it, have always reflected wider developments in what was until quite recently called ‘information and communication technology’, but is now more usually glossed as ‘networked connectivity’ (Nellis, 2018). The companies and corporations that have manufactured, sold and rented EM to state agencies have, by and large, customized pre-​existing technologies for penal markets rather than inventing anything new, which is not to deny the engineering ingenuity required to build small, compact and secure/​non-​removable wearable devices. RF EM utilized a 1940s ‘object identification’ technology that had gradually become part of a wider RFID (Radio Frequency Identification) movement to revolutionize logistics, stock control and complex supply chains by attaching a ‘tag’, or inserting a ‘chip’ into any stored or moving object—​package in transit, consumer product, vehicle, container, library book or livestock—​that could be read at a fixed checkpoint or scanned with a handheld mobile device (Bloomfield, 2001; Attaran, 2006). GPS EM utilized a once secret, 1970s US military satellite tracking system that was progressively made available for a vast range of civilian and commercial uses, including, in the mid-​1990s, offender monitoring (Milner, 2016). GPS tracking greatly increased the scale of data available to corrections, and led to the first applications of analytic software to EM, a process, which unfolds to the present day. Given the demonstrable historical tendency of EM companies to adapt existing technological infrastructures, the increasing availability of AI to management in commerce and government means we must ask: whither EM—​and community corrections—​in the age of AI? (Crawford et al, 2019; Canals & Heukamp, 2020). Aspects of correctional practice have long been mediated by computer-​processed information, and actuarial risk assessments of reoffending, absconding and/​or program completion can be accomplished algorithmically (Aas, 2004; Phillips, 2017; Metz & Satariano, 2020). Statistical, multi-​ factorial risk prediction techniques—​‘the old predictivity’, an ostensibly scientific basis for planning interventions—has a long and checkered history in corrections (Harcourt, 2009). So is it implausible that future

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EM systems will evolve beyond the real-​time monitoring of distant incidents (and all that ‘immediacy’ offers) to detecting ‘next events’ in offenders’ data streams—​and the obvious corollary of that, triggering pre-​emptive action (‘imminence’)? ‘Predictive policing’ is a possible template although thus far, operationally, it has been better at predicting places where crimes might soon occur than individual decisions (Perry et al, 2013; McCulloch & Wilson, 2015; Fergusson, 2017;). Some companies, but certainly not all (judging by their websites), seemingly anticipate ‘imminence detection’, or ‘the new predictivity’—​as EM’s future. The National Institute of Justice’s (NIJ) (2019) ongoing funding of research into AI and community supervision, coupled with the growing use of smartphones in supervision and tracking (which generate far more data than mere location monitoring) could indeed presage a shift from ‘immediacy’ to ‘imminence’ in community corrections. It is not, however, a foregone conclusion that the ‘new predictivity’ will be the next big thing in EM, or that talk of it is quite what it seems, or that real-​time control will be superseded in community corrections, as this chapter will demonstrate.

Immediacy, compliance and containment ‘Immediacy’—​a capacity to know remotely in real-​time, whenever required—​is what originally gave EM its notional edge over traditional community correctional practices. EM vendors strategically challenged the adequacy of periodic in-​person contact with supervisees in homes and offices as a tenable model of control. It had insufficient controlling presence in their lives and required too much trust. ‘Do you know where your offenders are?’, a vendor advertisement asked corrections agencies in JOM: ‘We check every ten seconds’. The argument was hard to gainsay: RF EM was readily accepted as a means of enforcing otherwise hard-​to-​enforce house arrest, and GPS tracking actively looked forward to provide ‘reliable scrutiny around the clock’ (Anderson, 1998, p. 43). ‘Immediacy’ is a consequence of the ‘real-​time connectivity’ arising from the fusion of networked computers and cable and satellite-​linked communication systems that began in the late 20th century (Tomlinson, 2010). It grants, to the observer of a (connected) computer screen, an instant awareness of distant things and events—​visual, auditory or simulated (numbers, charts, maps, symbols) and implicitly, a telematic capacity to influence those distant things and events by the transmission of information (or data). It constitutes (for connected people) a

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new sensory-​temporal experience overlain on and entwined with the requirements of clock-​time and circadian rhythms. It has been an unremarked facet of everyday life since networked connectivity diffused into all aspects of social life, starting in the economy with the imperative, ‘compete in real-​time or become extinct’ (Goldman & Papson, 2011, p. 109), altering the pace at which things could be done (or known) and the cultural and political expectations of the pace at which they should be done (or known). Real-​time connectivity made new forms of time management available in business and government, including ‘economies of presence’. Decisions about face-​to-​face meetings could be supplemented (or replaced) by phone; video checking remotely on staff whereabouts and activities could be made on the basis of cost-​ efficiency (Mitchell, 1999). EM, it can be said, enabled ‘economies of penal presence’ in community corrections, the establishment of more cost-​efficient ratios between labor-​intensive personal contact and remote locational surveillance. A new form, and experience, of penal control emerged. Although monitor and monitoree are ‘present’ to each other in EM, they experience connectivity asymmetrically: the monitor sees simulations and infographics on a screen, and makes assessments; the monitoree feels and sees the ankle bracelet, and senses impersonal, incessant oversight from afar. While time may run fast for the busy office-​based monitor with a large caseload, it may run slow for the individualized, part-​immobilized monitoree. Occasional phone calls may put them in brief ‘human’ contact but in the context of the same larger apparatus that mediates their ‘presence’ to each other (Nellis, 2010). Mirroring the intensification of time management in US workplaces that grew in the same period (Gregg, 2019; Manhoka, 2019) EM enabled hitherto unprecedented forms of time management in the lives of supervisees, to control and (for higher risk offenders) contain them. Demands that were once unenforceable became available with EM: the immediacy of remote monitoring could make compliance and violation visible in times and places hitherto beyond the correctional gaze (Nellis, 2013). Automation is crucial here. Supervisors do not gaze ceaselessly at screens, because the reception, processing and recording of locational data is done (technical glitches apart) ceaselessly by machines, which also send out violation-​alerts to relevant actors. Responses to violations—​deciding what constitutes a breach, and what action is required and when—​is a matter of agency or policy choice, determined by perceptions of risk, liability and available resources, not something immanent in the technology. The scale

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and pace of EM’s adoption in a particular place, and the character of the regimes it is used to create is fundamentally political, shaped by the culture of the agencies that deploy it, making them more or less onerous (Ibarra, Gur & Erez, 2016). In respect of breach, processing cases can take time, especially if a return to court is required, but an archive of reliably time-​stamped location data—​the digital legacy of immediacy—​remains available to be used retrospectively as evidence in court. Over the years, the American Probation and Parole Association (APPA) has played a key role in shaping EM use. It has tolerated some extraordinarily punitive uses of EM imposed at state and federal levels, while sustaining a narrative about EM’s appropriate-​but-​limited place in corrections, subordinate to its core professional interests and values. Relational and interactive (human) skills necessary to effect changes in the attitudes and behavior of offenders over time have been foregrounded, plus compliance with various appointments, requirements and rules. EM’s immediacy extended the range and reach of the latter, notionally without affecting the overarching probation and parole’s rehabilitative and reintegrative mission, which, increasingly, was mediated by computerized assessment and record keeping, and augmented by mobile phone contact. APPA has accommodated EM but resisted the idea that immediate, continuous compliance with remote monitoring technology could ever supersede probation’s core skills, because that would patently threaten the very identity of correctional agencies. While state and professional agencies are formally responsible for the legal and practical character of the regimes, which EM enforces, commerce has been a constant, nudging presence in their formation. RF EM originated outside the formal structures of penal innovation in the US (Ball, Huff & Lilly, 1988) but was taken up by entrepreneurs who sensed its potential in criminal justice, precisely because it mirrored ‘smart machine’ developments elsewhere in US society (Zuboff, 1988). Once the principle and utility of ‘real-​time knowledge’ (‘immediacy’) had been embedded in community corrections, companies vied with each other to customize new developments in information and communication technologies (ICT) for the penal market, and to offer a ‘commercial perspective’ on how offenders could be better managed and contained, and probation officers helped with their workloads, if their products were adopted. Upgrading to GPS offered more versatile ‘mobility monitoring’ over a potentially large area, and did begin to replace notionally obsolete RF ‘presence monitoring’ systems, but, perhaps contrary to commercial

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expectations, notionally ‘tracked’ offenders remained as likely to be subject to localized containment as permitted to roam freely, followed by an ‘eye in the sky’. While monitored roaming does occur (Shklovski, Troshynski & Dourish, 2015), ‘home confinement’ is still the Office of the Attorney General’s (2020) stated purpose for GPS EM, despite the far greater flexibility permitted by the technology. Many judges and prison managers impose home confinement and limited daytime movement corridors on offenders (say between home and work, school or college), with tracking serving only as a disincentive to abscond. The initial marketing narratives surrounding EM products are not necessarily a guide as to how they actually get used, but they are not unimportant in overcoming correctional resistance to innovation in indicating responsiveness to government agendas or, in the case of start-​ups, in signaling cutting-​edge ambition to potential investors. This has a bearing on the way companies interested in the corrections market are currently positioning themselves, as digitally sophisticated societies move into a future in which algorithmic prediction will be commonplace in commerce, governance and everyday life. It may be trivial, and barely visible—​text on mobile phones, consumers’ ‘next choice’ on a streaming service—​or fateful, excising human judgment—​creditworthiness, eligibility for welfare benefits, insurance payouts, risk of reoffending or likelihood of completing a community sentence. Some businesses will prosper because of it, others will decline, but there is no reason to think that enduring structures of power and inequality will be mitigated by it. Technological innovation impacts unevenly: it does not inexorably alter or displace established institutions and practices when they fulfill indispensable political and cultural functions. The story of EM and imprisonment in the US is a perfect illustration of this.

Electronic monitoring and the problem of punitiveness in the US ‘Techno-​utopian’ claims have periodically been made about EM from its earliest experimental phases in the 1960s and 70s to the present day: namely, that its large-​scale adoption would enable decisive reductions in actual prison use, even its near abolition, and effect reduced crime rates (Schwitzgebel et al, 1964; Toombs, 1995, Lilly & Nellis, 2013). EM has never come near to achieving this, expanding in tandem with mass incarceration and mass supervision, and never becoming extensive in the US correctional system. Against the five million per day under parole or probation supervision in the

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US, and the two million in prisons and jails, the 125,000 per day on EM remains strikingly small—​less than 1 per cent of its overall correctional population (Pew Charitable Trusts, 2016). Numbers have probably increased somewhat since the Pew Centre reported but—​notwithstanding arguments about what would actually constitute ‘mass’—​Eisenberg’s (2017) claim that ‘mass monitoring’ is actually occurring in the US is premature. There is nonetheless an emerging commercial aspiration to achieve this, and smartphone monitoring—​a kind of EM that Eisenberg does not mention (and to which I will return)—​makes it more feasible than it has hitherto been. But why the low use of EM in the US? This is mostly explained by the exceptional punitiveness of US penal culture, which has forced EM itself to take very punitive forms (in order to be marketable) and simultaneously rejected it as an adequate replacement for prison. As an automated socio-​technical system, EM is designed to be controlling and regulatory. However, it is not inherently punitive and repressive: hardware and software can be configured to create penal regimes of very variable intensity and duration, some light touch and supportive of rehabilitative measures, others overtly containing and consciously ‘prison-​like’ (Hucklesby, Beyens & Boone, 2020). The US has mostly favored the latter, creating regimes that are rightly dubbed e-​carceration. Regional variations notwithstanding, this has tended to focus EM on medium and higher risk offenders on correctional caseloads, leaving the mass of lower risk offenders under supervision untouched. This has not been for want of traditional right-​wing political and judicial attempts to impose RF and GPS EM on lower risk offenders, but these have been militantly resisted by liberal-​left interests, precisely because EM takes such overtly punitive forms, citing due process, disproportionality and the undesirability of net widening in their support. Somewhat inchoately, punitiveness is being recognized as an obstacle to EM’s expansion, and ingenious judicial—​and technical—​ways to circumvent this are developing. EM’s use at the pretrial stage has, by definition, always been merely regulatory, if often no less restrictive than explicitly punitive monitoring. A highly politicized judicial debate has begun in some US states to reframe EM at the sentencing and post-​ release stages as regulatory rather than punitive, thereby obviating the due process and proportionality considerations that otherwise arise (Eisenberg, 2017). Limited at the moment, this shift could impact significantly on EM’s future development, especially if combined with technical innovations.

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To date, many EM vendors have reluctantly accepted the circumscribed parameters—​medium and high-​r isk offenders only—​of the US market, while competing ferociously to sustain their share of it. Paradoxically, it is neoliberal and neoconservative interests, concerned about the rising costs of—​and continued role of Big Government in—​penal and public services that are beginning to unsettle, and perhaps disrupt this state of affairs. New commercial players, armed with newer technologies, and some revitalized older players, sense the time is right to enlarge the US EM market, taking their cues, perhaps, from global accountancy leader Deloitte, which, in the aftermath of the 2008 financial crash, offered increased automation as the basis of a new, ‘more for less’, approach to public expenditure. In a specific penal context, Deloitte (2011, p. 14) revived the techno-​utopian hope that EM house arrest, properly used, could remove over half the US’s ‘low-​level offenders from jails and prisons’ so that ‘local, state and federal governments could dramatically reduce their spending on incarceration’. Texas’s Right on Crime movement, launched by a neoconservative thinktank slightly before this (2007–​10), was not quite so bold but nonetheless wants Republican attitudes, state by state, to shift away from costly and excessive punishments to fiscally responsible measures in the community, mostly halfway houses, community supervision and home confinement (Bauer, 2014; Lyons, 2017). As yet, Right on Crime’s achievements do not match their aspirations, but their hostility to Big Government in criminal justice and favorable disposition to technology guarantees continuing commercial attention. The First Steps Act 2018 gave only limited expression to its ‘early release’ agenda, but was appreciated by an academic supporter for its welcome ‘boost’ to EM. ‘Any use of GPS to monitor discharged prisoners is an idea whose time has come’ wrote Barry Latzer (2018a), ‘a welcome down payment on the best hope for the future of criminal justice—​ technology’ (Latzer, 2018b). Smartphone monitoring is emerging, commercially, as a way of finally cracking the vast—​untapped, profitable—​low-​r isk offender market in community corrections, although it still tends to be discussed as ‘just another’ phase of innovation (Drake & Russo, 2017; Fagan, 2017; Morris & Graham, 2020). Two converging strands of innovation—​one framing smartphones as tracking devices, the other seeing smartphones as conduits for educational and rehabilitative services (‘probation with apps’)—​are converging, creating a monitoring tool with multiple functionalities—​audio (for therapeutic counseling); messaging (for automated reminders and behavioral nudging); internet access (to download apps, or block certain websites); camera and video (for remote

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check-​ins and portable breathalyzer verification); and location tracking (for zone monitoring). APPA (2020, p. 1) itself acknowledges that smartphones will ‘leverage’ doing more for less with lower risk offenders ‘in ways that traditional electronic supervision devices simply can’t’, because they are too punitive or too expensive. It imagines smartphones will free up hard-​pressed officers to focus time and resources on medium and high-​r isk offenders, without contemplating how widely they will be used. APPA recognizes ‘the amount of data that can be collected [by smartphones] is almost endless’ (p. 10) but worries more about ‘information overload’ on officers, and offenders’ data protection issues, than about the ways this data will need to be managed, and the analytic uses to which it could be put. Smartphone monitoring has cogent critics (Caido, 2019), but the operational and technical difficulties it still presents are probably not insurmountable. What remains under-​discussed is the likelihood that such an indispensable, everyday, non-​stigmatizing device will deflect the ‘proportionality critique’ that has rightly stopped RF and GPS EM from being systematically extended to lower risk offenders. It also neutralizes the argument—​easily leveled at RF and GPS—​that EM can never be a relational technology, as all manner of contemporary relationships are patently mediated by smartphones. Commercial narratives link smartphone EM to rehabilitative goals because these, more so than retributive punishment, justify the continuous extraction of biometric, audio and digital information from devices and apps. Some parole officers already demand that supervisees periodically scan themselves, their associates and their surroundings using a phone camera or video—​or monitor themselves (for identity verification purposes) while using an app-​connected portable breathalyzer (Kilgore, Sanders & Hayes, 2018). Such ‘correctional selfies’ could clearly serve crudely punitive purposes, but in themselves would hardly warrant the mass rollout of smartphone monitoring. Its transformational potential lies in its overarching data-​extractive capabilities and the management of this by artificial intelligence (AI). The National Institute for Justice (NIJ)—​a longstanding pacesetter in penal innovation, tightly meshed with commercial interests—​has seemingly recognized this.

The National Institute for Justice and data analytics The NIJ assesses the value of ‘emerging technologies’ for law enforcement and has consistently championed data analytics to support offender tracking technologies, mediating vendor-​produced

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programs to regional and local agencies, and awarding university-​ agency partnerships grants to create ‘geospatial toolkits’ of their own. In 2010, for example, the NIJ funded partners in Oklahoma to develop TRACKS, which enabled tracked offenders’ known destinations, routes, stopping points, durations of stop, proximity to other tracked offenders and to crime scenes to be turned into ‘corrections-​actionable knowledge’, usable in supervision, alongside existing interventions. It next undertook surveys of the businesses involved and the products available on the open market, together with analyses of their viability (Taylor et al, 2016; Heaton, 2016a, 2016b). In passing, Taylor et al (2016, p. v) pertinently noted that the shift from RF to GPS technologies was altering the composition of the EM industry, bringing in new businesses that had not hitherto had correctional backgrounds or interests. Predictive analytics were not prominent in the new commercial offerings at this point. Out of 43 possible capabilities (from basic zone templates to sophisticated visualizations of ‘heat maps’) only five were concerned with prediction—​of offender suitability for monitoring, behavioral trends, next-​event forecasting, ways of modeling these and computing the statistical significance of predictions. Two companies offered all of these (SAS Institute and Track Group); most offered none, largely because community corrections agencies had signaled no interest: Although the analytics capabilities of offender monitoring products do not appear to have been a strong motivator for vendor selection to date, analytical tools comprising various combinations of statistical analysis procedures (including crime scene analysis), data and text mining, social network analysis, and predictive modelling can enable the discovery of hidden behavioral patterns and the prediction of future outcomes. As analysis technology progresses and becomes more user friendly, the correctional agencies queried during this study indicated that analytics would become more of a consideration in any replacement systems that are contemplated in the future. (Taylor et al, 2016, p. v) In a later NIJ report Harold Heaton noted that the innovations the agencies actually wanted were those which improved the existing compliance and containment models of EM, hardware and software that ‘accurately tracked clients indoors, underground (e.g. in subways), during poor weather conditions, and within multi-​story buildings’

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(Heaton, 2016a, p. 13). He attributed agencies’ limited interest in analytics to three factors. The first concerned feasibility: agencies understood that sophisticated data mining required vast amounts of reliable data and extensive automation that it was beyond their resources to procure, particularly if the crime control gains were merely marginal. The second concerned professional self-​interest: agencies were reluctant to cede further authority, as they saw it, to sophisticated forms of automation, given how much it had already encroached on their work. Heaton’s third factor specifically addressed predictive analytics, noting agencies’ fear of the legal liabilities to which they might logically be exposed if they publicly claimed predictive capabilities—​and then failed. Any failure to pre-​empt harm would surely render agencies vulnerable to litigation by victims. GPS monitoring had already increased that risk, with the public simplistically believing that if an agency knew where an offender was, (or was heading to) they could and should be able to disrupt any crime. Heaton grasped that correctional agencies’ relied on rational choice models of criminality not only in their everyday dealings with offenders but also to mitigate their responsibility for reoffending that occurred on their watch, allowing them to plausibly say that despite their best efforts a serious crime undertaken by a calculating miscreant cannot always be foreseen (Heaton, 2016a, p. 21). The deterministic models of behavior underpinning predictivity were markedly at odds with prevailing agency culture. To overcome the lack of ‘customer pull’ in respect of predictive analytics, Heaton anticipated commercial suppliers initiating a ‘vendor push’ to raise their profile, further supported by ‘research and development, possibly in partnership with academia, [and] catalyzed by government sponsorship’ (Heaton, 2016a, p. 27). This was not a long time coming. In May 2019, building on its earlier awards program the NIJ invited bids (from commerce and academia) for experimental projects which applied ‘advances in artificial intelligence (AI) to promote the successful reentry of offenders under community supervision in the United States’, ideally resulting in sustainable operational programs (p. 4). ‘Due to the high number of individuals under supervision’, the NIJ explained disingenuously, ‘community supervision agencies have found it challenging to provide the degree of supervision and immediacy that may be required to help guide an individual’s use of services and programs to assist their successful re-​entry into their communities’ (National Institute of Justice, 2019a, p. 5, emphasis added). Framed thus, technological solutions seemed more viable than human solutions. The NIJ had three types of project in mind: firstly, situationally dependent, real-​time updates to an offender’s risk-​need-​responsivity

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(RNR) assessment; secondly, mobile service delivery to offenders (via smartphones) of personalized rehabilitation resources and reinforcement of compliance outside of treatment and education sessions; thirdly, intelligent offender tracking, building on data from existing GPS monitoring systems: Using the geospatial and temporal data from those devices, coupled with an understanding of how the attributes of the places an offender visits interact with their recidivism risks and how that changes with the time of the visit, AI can detect (and possibly predict) potentially risky behavior. Based on the nature of the event, an AI could autonomously take a number of different actions to address the risk. Those might include, alerting the supervising officer or a mentor, or initiating a chat bot system through an offender’s mobile device that is trained to de-​escalate situations. AI-​initiated actions may also include notifying the offender through their mobile device to suggest a cooling-​off period in a safe space, or to promote behavior modification techniques. (National Institute of Justice, 2019a, pp. 5–6, emphasis added) In September 2019 the NIJ awarded almost $2 million to Purdue University and Tippecanoe County, Indiana to create, manage and evaluate an ‘AI-​based support and monitoring system’ (AI-​SMS) for 250 high-​r isk adult offenders over four and half years: AI-​SMS will provide supervising officers and offenders early warning of risky behavior on an offender’s part and the means and mechanisms for reducing that behavior. Offenders will be provided with a smartphone and a tracking-​health-​related wearable device or bracelet. Officers and practitioners (e.g. clinicians) and caseworkers assigned to that offender will be provided with smartphones/​tablets with specific dashboards (user interfaces) that would be used to communicate with the offender. (National Institute of Justice Award Information, 2019b) A ‘better than human’ narrative is emerging in respect of the NIJ/​ Purdue initiative, focused longer term on transforming community corrections agencies. ‘The new predictivity’ features in this but is not dominant. The emphasis remains on immediacy—​control and change

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in the here and now—​emulating digital developments elsewhere, as NIJ researchers explain: One purpose of the re-​entry smartphone line of research is to empower offenders to take control of their lives by giving them continuous access to the information and resources they require to do so. The greater the sense of personal agency a returning offender has with respect to a rehabilitation plan, the greater the likelihood of success, studies have shown. Behavioral change is hard, but people are more likely to have success when they can see their progress and receive encouraging messages, as with many fitness trackers. (Green & Rigano, 2020) Whether machine-​assisted empowerment is true, or necessary, or better than trained human officers, remains speculative but is probably irrelevant to the NIJ, whose aim is to make AI central—​definitive—​to the character of community corrections: Smartphone-​facilitated re-​entry can also benefit supervisors responsible for assessing the risks and needs of every offender in their portfolio. Growing supervisor caseloads tend to reduce the time and attention that a single officer can devote to each assigned offender, making recidivism more likely. AI-​equipped smartphones can automate and streamline the supervision workflow, using data to better predict recidivism risks and rehabilitative needs. (Green & Rigano, 2020) Traditional Risk Assessments Instruments (RAIs) have already been augmented by the kind of ‘automated decision support systems’ long used in commercial management, customized for correctional purposes (Canals & Heukamp, 2020; Metz & Satariano, 2020). Narratively, at least NIJ are acknowledging ‘the new predictivity’ but not foregrounding it as a vital next step. Commercial stakeholders in EM are hinting at something more.

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Electronic monitoring companies and ‘the new predictivity’ EM vendors appraise emerging technological trends and upcoming market opportunities themselves, irrespective of NIJ’s signals. Not all vendors want to depart from the prevailing compliance model, believing that ‘enhanced immediacy’ is still what their customers want. GEO, an old company with roots in the private prison business, has stayed with compliance and branched out into the profitable immigration monitoring market. Omnilink, a newer GPS tracking company, was promoting nothing more sophisticated on its 2019 website than crime scene correlation software. Track Group in the US, and Geosatis in Europe (a competitor in US markets), on the other hand, are moving towards a ‘software as a service’ model of EM in which profitability lies in data analytics as much, if not more, than the provision of devices and systems. Track Group, which has entered a strategic partnership with IBM to provide a cloud-​based infrastructure for its new services, claims to have ‘a different approach to offender monitoring’ to other EM companies. ‘We think data is an agency’s most valuable asset, not technology. … Data has always been there, unseen and uncollected. … Big data is only getting bigger. … Agencies can no longer afford to be anything but data-​driven.’ Track Group—​which, as SecureAlert, had delivered GPS tracking services, rebranded itself in 2014 after making three strategic acquisitions to improve its market position. One acquisition was G2 Research, a Canadian data analytics company already serving security, intelligence and law enforcement agencies (Hamilton, 2017). G2’s icuSUITE became the basis of new INTELLITRACK software and enabled Track Group to pitch itself as ‘a first mover in predicting offender behaviour’ and the creator of ‘a platform which will transform electronic monitoring’, one which can help you [correctional agencies] manage offenders on GPS more effectively—​it can also help you identify problems before they happen to improve victim safety, prioritize your caseload, enhance offender outcomes and streamline resources. … Track Group’s suite of predictive analytics software applications is dedicated to quickly and automatically analyzing comprehensive GPS and behavioral data to recognizing patterns, associations and trends and help officers and managers find the best course of action for a given situations. (Track Group, 2019, emphasis added)

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In Europe, Geosatis, a commercial GPS provider spun from the University of Lucerne in Switzerland, had an interest, from its inception, in predicting and pre-​empting offending (Hunkeler, 2015). Its current CEO accepts that what his customers want at the moment is effective real-​time tracking, hopefully using their distinct toroidal (shackle-​like) ankle band, which can pick up signals using ‘4 different geo-​positioning satellite systems (GPS, Galileo, GLONASS and BeiDou)’ (Demetriou, 2019). He hopes nonetheless to take EM to ‘the next level’, using AI and big data analytics, which ‘are growing an unprecedented pace’ (Demetriou, 2018). To his regret, ‘today’s EM solutions’, are ‘still focusing exclusively on a reactive approach’, responding to alerts or violations of rules when—​if the location, movement, tamper and violation data that EM systems generate are combined with other data sets—​it could be so much more: a new AI-​powered EM system could take historical data into account and mix it with any other relevant source of data to be correlated (other offenders, a map of criminogenic zones, crime scenes, CCTV records, car speed, etc.). [This] set of functionalities … would enable a predictive intervention … that allows a superviser or probation officer to identify a potential problem before it actually occurs. (Demetriou, 2018, emphasis added) As the self-​p roclaimed ‘world’s most innovative company in this industry’, Geosatis aims to retain pole position by ‘studying and developing solutions that will outpace the “traditional” EM technologies’. It assumes an unfolding logic to these developments driven by competition between tech companies and the allure of efficient governance but acknowledges—​realistically—​that progress ‘will not be linear: it will certainly pose challenges with regard to data protection and bias, not to mention the implications that such EM advanced features will have on the academic-​technical profile of probation agencies’ staff who will be in charge of analysing, drawing conclusions and acting on them’ (Demetriou, 2018). Unguarded commercial comment on EM’s projected future is rarely as explicit as Demetriou is here admitting that upcoming technological developments could have a transformational effect on the character and culture of correctional agencies, rather than maintaining the tactful pretense that vendors are merely there to serve existing correctional agendas. The Geosatis CEO is probably right to sense an imminent

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‘tipping point’ in correctional arrangements, but there are projections of EM’s future, which go far beyond his own expectations.

Towards ultra-​punitive electronic monitoring? It was established earlier in the chapter that exceptional punitiveness in US culture has constrained the expansion of EM: even when EM itself has been punitively inflected, it has been no meaningful substitute for incarceration. Neither the NIJ nor Track and Geosatis’s near-​future visions encompass imprisonment: their concern is only with the transformation of community corrections, grounded in data analytics and inflected towards rehabilitative and reintegrative practices, which are mutably in terms of digital technologies in a way that prisons are not. AI—​ostensibly a rational, cost-​effective measure—​will expand into community corrections management because it is expanding everywhere in corporate management, but EM is no more likely now to encroach upon imprisonment than it has in the past. Protracted sequestration behind prison walls serves material and symbolic functions, shoring up extreme social inequality in ways that existing forms of EM could not compete with. Legal academic Mirko Bagaric (2019) and his colleagues hold a naïve and pragmatic view of imprisonment—​it is simply for containing bad people—​and think it can be challenged if EM is redesigned. They argue that AI, big data and the sorts of biometric monitoring systems used in the self-​tracking movement could now be synthesized into an ultra-​ punitive form of monitoring, which, cumulatively implemented over 15 years, could subject two million US prisoners to ‘mass monitoring’, at a third of the cost of existing arrangements. Their condemnation of imprisonment—​focused on harmful effects on individuals rather than its role shoring up social injustice—​aligns with, but exceeds in severity those of Right on Crime. Crucially, and against existing proponents of using EM to reduce prison use (Yeh, 2010, 2014), Bagaric et al (2019) argue that any viable new alternative to incarceration must be as equally retributive, painful and shameful in intent as prison itself, and even more effective at reducing crime. ‘Technological incarceration’ (henceforth TI), as they call their alternative, pushes containment to vindictive and humiliating extremes: The alternative to prison that we propose involves the fusion of three technological systems. First, offenders would be required to wear electronic bracelets that monitor their location and ensure that they do not move outside of

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the geographical areas to which they would be confined. Second, prisoners would be compelled to wear sensors so that unlawful and suspicious activity could be monitored remotely and by computers. Third, conducted energy [i.e. electroshock] devices would be used remotely to immobilise prisoners who attempt to escape their areas of confinement or commit other crimes. (p. 73) TI extrapolates directly from existing tendencies to use tracking technology to immobilize, control and contain. Its geo-​fenced inclusion zones might extend for 50 meters, or—​if linked to Wi-​Fi for more accurate pinpointing—​shrunk still further, down to ‘confinement to the house’, or even to one’s room. Its body-​worn ‘sensor harness’ containing a small, upward facing body-​cam for constantly verify identity, haptic sensors that reveal posture and movement (tensing for a fight?) and microphones that detect verbal exchanges with nearby people are intrusive innovations. Software that could infer from stress factors in the wearer’s voice their feelings and state of mind in real-​ time, and other signs of imminent or actual violation, may trigger (subject to an automated health check) a remote, taser-​like electric shock to the offender, while simultaneously summoning local law enforcement support. TI requires AI. The ‘synchronous monitoring’ of two million offenders’ movements and behaviors has become penally feasible because of ‘recent advances in signal processing and artificial intelligence to perform automated processing of audio and visual surveillance streams’ (Bagaric et al, 2019, p. 99). This is the technology intended to facilitate widespread use of autonomous vehicles (Burns, 2018). Complex imminence detection is integral to it—​anticipating road conditions, other vehicles’ and pedestrians’ likely movements—​but as a means to an end, not a rationale. Similarly with TI: predictivity is neither a selling point nor its declared penal purpose. Its point is the brute material domination of an offender’s everyday life. Bagaric et al do not assume any deterrent impact arising from offenders’ knowing that authorities could predict their next move: what matters most in terms of control, punishment and public legitimacy is the tangible burden placed on the offender by tight spatio-​temporal restrictions, and the stigmatizing sensor harness and constant pressure to comply. This is containment—​immediate, continuous control in the here and now—​with a vengeance.

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Conclusion The emergence of AI-​infused governance in the US, including in community corrections—​and revived commercial ambitions to achieve ‘mass monitoring’—​now frame the initial focus of this chapter on ‘the new predictivity’. Smartphones are emerging as the key to both agendas. Although targeted primarily on lower-​risk offenders—​a hitherto untapped market for EM companies—​as an alternative RF and GPS location monitoring, they may not be restricted solely to them. They could be used in tandem with GPS with medium-​and higher-​r isk offenders too, to build up their all-​important, analyzable data profile—​the justification for turning to AI, and the basis of any predictivity that may occur. The normalization of smartphone monitoring among low-​risk correctional caseloads is nonetheless the driver of these developments and may inadvertently be aided by the emerging critique of inappropriate ‘mass supervision’ of low-​ risk offenders in community corrections (Adjer et al, 2018; Morris & Graham, 2019). It would be a steep irony if the space created by ending human supervision for this cohort were filled by smartphone monitoring—​conceived in regulatory rather than punitive terms—​and expanded at scale. It does not follow from the infusion of AI into community corrections and the expansion of smartphone monitoring—​or even from the example of predictive policing—​that ‘the new predictivity’(imminence detection of the ‘pre-​crime’ kind) will actually be the hallmark of future EM, even if it is technically feasible. ‘The old predictivity’, relating to the risk of, time to and location of reoffending, will retain its place, augmented by automated decision support systems but so too will immediacy itself—​the visible assertion of real-​time control over offenders as a necessary and legitimate punishment for their past crimes. Enhanced immediacy using multiple forms of EM is as likely to be the consequence of AI-​dominated community corrections as anything to do with predictivity, but this itself will be transformative of the agency, and disruptive of probation and parole ideals. APPA’s desire to keep EM subordinate to a person-​dominated supervision process will not survive this. Mass monitoring via smartphones for all, and ankle tags for some, will be ubiquitous and human supervision will be subordinate to that and more mediated by the smartphone than now. Rehabilitation will be a largely online activity. Chatbots, or Siri-​like ‘personal assistants’, already used in customer service industries, could replace or augment some human correctional officers, and an AI—​perhaps branded ‘cloud-​ based probation’ for continuity’s sake—​would oversee it all.

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So how do we account for the presence of ‘the new predictivity’ in and around contemporary discourse on EM? Predicting ‘next events’ is grounded in undeniably real techno-​scientific possibilities, and likely to be ubiquitous in some form in all-​future smart environments. As a narrative among commercial EM providers it is, however, less than what it seems, and may be ephemeral. It is first and foremost a way of ‘selling’ cost-​effective AI in community corrections, an enticement to purchase data-​extracting hardware, software and analytic services—​ nothing different in principle from the marketing narratives used by EM vendors in the past (Lilly, 1992; Lilly & Ball, 1993; see also Wilson, 2019). AI, for all the managerial awe it evokes, is hard to sell as an end in itself. Actual political, financial and professional investment in AI, in any particular agency, requires a game-​changing rationale to warrant the initial expenditure—​and in respect of corrections the allure of improved ‘predictivity’, beyond what existing RAIs can do, is that rationale. Just as EM vendors once pushed ‘immediacy’ as a must-​have capability in community corrections, so some now pitch ‘imminence’ as an indispensable upgrade. The allure of predictivity in penal and policing contexts constitutes both a utopian and dystopian trope in contemporary penal debate, anchored in dramatic depictions of ‘pre-​crime’ and imminence detection in popular culture, notably Steven Spielberg’s (2002) film Minority Report and the CBS television series Person of Interest (2011–​ 16), as well as a raft of American science fiction stories dating back to the 1950s (Jarvis, 2004). Person of Interest, an aslant commentary on America’s war on terror and burgeoning surveillance state, made AI-​driven predictivity seem (in the hands of ‘good guys’) useful but dangerous otherwise (Rothman, 2014). To the extent that hope and optimism about AI’s capacity to predict and benignly control all human contingencies is indeed alive and well in Silicon Valley, it owes a debt to behaviorist B.F. Skinner’s (1971) firm conviction that ‘operant conditioning’ could easily eradicate the use of punishment. As with Skinner, there are contemporary tech thinkers for whom faith in predictivity is a calculated patrician rebuke to the enduring barbarism of imprisonment in the US, and a forlorn plea for a civilized, scientific governance. This vision, ever oblivious to its own ethical flaws, has less purchase in political and correctional debate than 50 years ago, but remains useful for marketing purposes (Townsend, 2013). Mass monitoring will predominate in—​and transform—​community corrections but will not bring an end to imprisonment. The harsh, ostentatious punishment that Bagaric et al (2019) propose—​which is indeed one extrapolation of EM’s future—​constitutes an equally carceral

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but vastly cheaper penal system that continues to foreground immediacy and containment. Any appeal it has to America’s punitive penal culture depends less on its techno-​scientific allure and more on the enduring penal norms it upholds—​retribution, vengeance, incapacitation, deterrence and stigma. It is premised on a classical, ‘common sense’ view of lawbreakers as malign moral actors who deserve harm and need accountability, not a pseudoscientific trope about determined, predictable behavior that can be inferred by algorithms. It does satisfy neoconservative fiscal ideals, but it is fundamentally so similar in ethos to existing penal confinement that there will be limited incentive for the wholesale transformation it presages. Penal expenditure may be reduced by wholly automating some prisons, and something akin to TI may, regrettably, be experimented with as a niche penal product in some states, not as the harbinger of systemic change. America’s penal landscape will continue to contain prisons: it is community corrections that are being transformed by AI, and the allure of ‘the new predictivity’ will have played a transient part in that. References Aas, K.F. (2004). From narrative to database technological change and penal culture. Punishment & Society 6 (4): 379–​93. Adger et al (2018). Statement on The Future of Community Corrections. Cambridge, MA: Malcolm Weiner Center for Social Policy, Harvard University. American Probation and Parole Association. (2019). Incorporating Location Tracking Systems into Community Supervision. Issue Paper from the Technology Committee. Lexington, KY: American Probation and Parole Association. American Probation and Parole Association. (2020). Leveraging The Power of Smartphone Applications to Enhance Community Supervision. Issue Paper from the Technology Committee. Lexington, KY: American Probation and Parole Association. Anderson, D.C. (1998). Sensible Justice: Alternatives to Custody. New York, NY: The New Press. Attaran, M. (2006). The coming age of RFID revolution. Journal of International Technology and Information Management 15 (4): 77–​87. Bagaric, M., Hunter, D. & Wolf, G. (2019). Technological incarceration and the end of the prison crisis. Journal of Criminal Law and Criminology 108 (1): 73–​135. Ball, R., Huff, R. & Lilly, J.R. (1988). House Arrest and Correctional Policy: Doing Time at Home. London, UK: Sage.

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Bauer, S. (2014). How conservatives learned to love prison reform. Mother Jones (March/​April) [online] Available at: https://​www. motherjones.com/​politics/​2014/​02/​conservatives-​prison-​reform-​ right-​on-​crime/​. Burns, L. (2018). Autonomy: The Quest to Rebuild the Driverless Car, and How It Will Reshape Our World. London, UK: William Collins. Bloomfield, B.P. (2001). In the right place at the right time: Electronic tagging and problems of social order/​disorder. The Sociological Review 49 (2): 174–​201. Caiado, N. (2019). Smartphones are here to stay, let’s be smart about using them. Journal of Offender Monitoring 31 (2): 17–​19. Canals, J. & Heukamp, F. (2020). The Future of Management in an AI World: Refining Purpose and Strategy in the Fourth Industrial Revolution. London, UK: Palgrave Macmillan. Crawford, K. et al (2019). AI Now Institute 2019 Report. New York, NY: New York University. Deloitte (2011). Public Sector Disrupted: How Disruptive Innovation Can Help Government Achieve More for Less. A GovLab Report. Deloitte: London. Demetriou, J. (2018). From a reactive to a preventive approach: What is on horizon of electronic monitoring technologies? Justice Trends 3. Demetriou, J. (2019). Taking electronic monitoring to the next level. Justice Trends 4. Drake, G. & Russo, J. (2017). The smartphone as a correctional tool. Journal of Offender Monitoring 29 (1): 5–​8. Eisenberg, A. (2017). Mass monitoring. Southern California Law Review 90 (2): 123–​180. Fagan, D. (2017). Enhancing probation practice and safety with smartphone applications. Probation Journal 64 (3): 282–​5. Fergusson, A.G. (2017). The Rise of Big Data Policing: Surveillance: Race and the Future of Law Enforcement. New York, NY: New York University Press. Goldman, R. & Papson, S. (2011). Landscapes of Capital. Cambridge, UK: Polity. Gregg, M. (2019). Counterproductive: Time Management in the Knowledge Economy. London, UK: Duke University Press. Green, B. & Rigano, C. (2020). Specialised Smartphones Could Keep Released Offenders On Track for Successful Re-​entry. [online] Available at: file://​/U ​ sers/​mike/​Desktop/​%20NIJ%20-% ​ 20Smartphones%20 Could%20Keep%20Released%20Offenders%20on%20Track%20 for%20Successful%20Reentry%20%7C%20National%20Ins. webarchive

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Hamilton, S. (2017). Big data and the future of electronic monitoring. Journal of Offender Monitoring 29 (1): 9–​11. Harcourt, B. (2009). Against Prediction: Profiling, Policing and Punishment in an Actuarial Age. Chicago: The University of Chicago Press. Heaton, H.I. (2016a). GPS Monitoring Practices in Community Supervision and the Potential Impact of Advanced Analytics. A Report for the US Department of Justice. Baltimore, MD: John Hopkins University. Heaton, H.I. (2016b). Geospatial Monitoring of Community-​Released Offenders: An Analytics Market Survey Version 2.0. Baltimore, MD: John Hopkins University, National Institute of Justice. Hucklesby, A., Beyens, K. & Boone, M. (2020). Comparing electronic monitoring regimes: Length, breadth, depth and weight equals tightness. Punishment & Society 22 (3). Hunkeler, U. (2015). New generation of EM technology: Soon too many sensors? Journal of Offender Monitoring 26 (2): 6–​9. Ibarra, P., Gur, O. & Erez, E. (2016). Surveillance as casework: Supervising domestic violence defendants with GPS technology. Crime, Law and Social Change 62 (4): 417–​44. Kilgore, J., Sanders, E. & Hayes, M. (2018). No More Shackles: Why We Must End the Use of EL for People on Parole. Urbana, IL: Centre for Media Justice. Jarvis, B. (2004). Cruel and Unusual: Punishment and Its Cultures. London, UK: Pluto Press. Latzer, B. (2018a). Two cheers for criminal justice reform. Law and Liberty [online] Available at: https://​lawliberty.org/​two-​cheers-​for-​ criminal-​justice-​reform/​. Latzer, B. (2018b). Beware the next step on criminal-​justice reform. Wall Street Journal (23 December). Lilly, J.R. (1992). Selling justice: Electronic monitoring and the security industry. Justice Quarterly 9 (3): 493–​503. Lilly, J.R. & Ball, R.A. (1993). Selling justice: Will electronic monitoring last? Northern Kentucky Law Review 20 (2): 505–​30. Lilly, J.R. & Nellis, M. (2013). The limits of techno-​utopianism: Electronic monitoring in the United States of America. In M. Nellis, K. Beyens & D. Kaminski (eds.). Electronically Monitored Punishment: International and Critical Perspectives. Abingdon, UK: Routledge. Lyons, T. (2017). Smart Electronic Monitoring Leads to Real Savings. Right on Crime website [online] Available at: www.rightoncrime.com. Manokha, I. (2019). New means of workplace surveillance: From the gaze of the superviser to the digitalisation of employees. Monthly Review: The Independent Socialist Magazine 70 (9): 25–​39.

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McCulloch, J. & Wilson, D. (2015). Pre-​crime: Pre-​emption, Precaution and the Future. Abingdon, UK: Routledge. Morris, J. & Graham, H. (2020). Using technology and digitally-​ enabled approaches to support desistance. In P. Ugwidike et al (eds.) The Routledge Companion to Rehabilitative Work in Criminal Justice. Abingdon, UK: Routledge. Metz, C. & Satariano, A. (2020). An algorithm that grants freedom or takes it away. New York Times (9 February):1. Milner, G. (2016) Pinpoint: How GPS is Changing Technology, Culture and Our Minds. New York, NY: W.W. Norton. National Institute of Justice (2019a). Artificial Intelligence Research and Development to Support Community Supervision: Invitation to Apply for Funding. Washington, DC: US Department of Justice. National Institute of Justice Award Information (2019b). AI Enabled Community Supervision for Criminal Justice Services. Washington, DC: US Department of Justice. Nellis, M. (2010). Eternal Vigilance Inc: The satellite tracking of offenders in real-​time. Journal of Technology and Human Services 28: 23–​43. Nellis, M. (2013). Surveillance-​based compliance using electronic monitoring. In P. Raynor & P. Ugwudike (eds.) What Works in Offender Compliance? London, UK: Palgrave Macmillan. Nellis, M. (2018). Electronically monitoring offenders as ‘coercive connectivity’: Commerce and penality in surveillance capitalism. In T. Daems & T. Vander Bekken (eds.) Privatising Punishment in Europe. Abingdon, UK: Routledge. Office of the Attorney General (2020). Memorandum for Director of Bureau Prisons. Prioritisation of Home Confinement as Appropriate in Response to Covid-​19. 26 March. Washington, DC: Office of the Attorney General. Pew Charitable Trusts (2016). Use of Electronic Offender-​Tracking Devices Expands Sharply. Washington, DC: Pew Charitable Trusts. Phillips, J. (2017). Probation practice in the information age. Probation Journal 64 (3): 209–​25. Rothman, J. (2014). ‘Person of Interest’: The TV show that predicted Edward Snowden. The New Yorker (14 January). Schwitzgebel, R., Schwitzgebel, R., Pahneke, W. & Hurd, W. (1964). A programme of research in behavioural electronics. Behavioral Science 9 (3): 233–​8.

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Shklovski, I., Troshynski, E. & Dourish, P. (2015). Mobile technologies and the spatiotemporal configurations of institutional practice. Journal of the Association for Information Science and Technology 66 (10): 2098–​115. Skinner, B.F. (1971). Beyond Freedom and Dignity. Harmondsworth: Penguin. Taylor, S.R., Kandaswamy, S., Evans, T. & Mahaffey, D. (2016). Market Survey of Location-​Based Offender Tracking Technologies Version 1:1. Washington, DC: National Institute for Justice. Tomlinson, J. (2010). The Culture of Speed: The Coming of Immediacy. London, UK: Sage. Toombs, T.G. (1995). Monitoring and controlling criminal offenders using the satellite Global Positioning System coupled to surgically implanted transponders: Is it a viable alternative to prison? Criminal Justice Policy Review 7 (3–​4): 341–​6. Townsend, A. (2013). Smart Cities: Big Data, Civic Hackers, and the Quest for a New Utopia. London, UK: W.W. Norton. Wilson, D. (2019). Algorithmic patrol: The futures of predictive policing. In A. Zvrsnik (ed.) Big Data Crime and Social Control. Abingdon, UK: Routledge. Yeh, S. (2010). Cost-​benefit analysis of reducing crime through electronic monitoring of parolees and probationers. Journal of Criminal Justice 38: 1090–​6. Yeh, S. (2014). Criminal justice in the United States: A proposal for reform. Laws 3 (1). Zuboff, S. (1988). The Age of the Smart Machine: The Future of Work and Power. Oxford, UK: Heinemann.

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The Digital Technologies of Rehabilitation and Reentry Bianca C. Reisdorf and Julia R. DeCook

Introduction The reentry process for formerly incarcerated people is fraught with uncertainty and there is a long list of tasks that needs to be achieved for them to successfully reintegrate back into society (Petersilia, 2003; Mears & Cochran, 2014). Upon release, returning citizens (RCs) need to find housing, secure employment, reconnect with family and their communities, continue substance treatment (if required) and maintain regular contact with their parole or probation officer. In addition, many returning citizens who served longer sentences re-​enter a society that is very different from the one they left when starting their sentence. The fast-​paced developments in digital technologies over the last 20 years and the ubiquitousness of the Internet and digital devices has changed the way societies work, which leaves returning citizens overwhelmed by a speed-​of-​light society (Jewkes & Reisdorf, 2016; Reisdorf & Jewkes, 2016). Even short spans of disconnection from the Internet and digital devices have been shown to have negative effects, such as missing out on benefits or job offers (Gonzales, 2016; Gonzales et al, 2016). As Internet access in correctional facilities in the United States is generally not available to incarcerated people, returning citizens inevitably experience periods of disconnection. However, these technologies are necessary for many everyday life tasks and by 2021,

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people will manage over 85 per cent of their interactions without interacting with a human (Pirzada & Khan, 2013). Companies across most industries have digitized their operations and processes. As a result, today’s jobseekers require skills to help them bridge this digital divide. Digital skills can ‘reduce poverty level to some extent and increase an employment rate or at least a basic step towards securing higher paying jobs’ (Pirzada & Khan, 2013, p. 124). In other words, a strong digital skillset is no longer a luxury for individuals—​gaining digital skills is a fundamental component in navigating day-​to-​day life. Most reentry programs do not include any digital skills training. However, in recent years, some efforts have been made to address these issues for RCs, including Rhode Island’s ‘Pivot the Hustle’ reentry program (Pivot the Hustle, n.d.), San Quentin’s ‘Last Mile’ project (The Last Mile—​Paving The Road To Success, n.d.), and New York City’s ‘Tech 101’ (Tech 101, n.d.), run by the Prisoner Reentry Institute (PRI) at the John Jay College of Criminal Justice. Most recently, the Mecklenburg County Sheriff’s Office (MCSO) in North Carolina joined these efforts in providing digital skills training before jail residents’ release (Powell, 2019). In addition, scholars have begun to research this issue, and a handful of pilot studies have been published to date (Reisdorf & Jewkes, 2016; Ogbonnaya-​Ogburu et al, 2018, 2019). These pilot studies show that digital skills training that is tailored to returning citizens’ needs is generally positively perceived by returning citizens themselves and can lead to an increase in employment-​related skills (Ogbonnaya-​Ogburu et al, 2018, 2019). Adding to issues directly pertaining to the use of digital technology, societies have shifted from a post-​crime to a pre-​crime logic, in which the goal is to prevent crime before it has happened (Zedner, 2007; Arrigo et al, 2020). Rapidly developing changes in the availability of large amounts of data and surveillance through the collection of such data—​that is, dataveillance—allow for policing and controlling. As such, surveillance and dataveillance have been largely accepted by society in exchange for convenience, using information and communication technologies (ICTs), and the promise of more security and safety (Bekkers et al, 2013; van Dijck, 2014), returning citizens and the communities they return to find themselves in a continuous cycle of surveillance during and after incarceration. In this chapter, we will discuss the kinds of technologies that returning citizens encounter during rehabilitation and reentry, as well as the small number of programs that focus on digital technologies and digital literacy, and how they may contribute to better reentry outcomes.

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Framing digital technology in the reentry process Digital inequalities In examining the relationship between reentry and digital technologies, issues related to digital divides and digital inequalities need to be considered to provide a comprehensive account of the issues and opportunities that returning citizens face after their release. Digital divides have been examined for over two decades, mostly for general populations. Simply put, the digital divide is defined as the gap between those who have access to the Internet and digital devices and those who do not (Norris, 2001). Over time, this dichotomous definition of Internet access and use has been replaced with a more nuanced approach to examining digital inequalities, rather than divides, which explores not just who has access and who does not but also what kinds of activities people engage in once online and how these activities are affected by socio-​economic background and digital skills (DiMaggio & Hargittai, 2001; DiMaggio et al, 2004). Numerous studies have demonstrated that those who are socio-​economically worse off, that is, those with lower incomes, those with lower educational attainment, people of color (particularly, non-​white Hispanics, Latinos, and African Americans), and the elderly are disproportionately offline and, if online, they participate in fewer online activities on fewer devices. They may have less stable types of access, or may depend on mobile phones only (Livingstone & Helsper, 2007; Zillien & Hargittai, 2009; Robinson et al, 2015; Van Deursen et al, 2017; Reisdorf et al, 2018; Fernandez et al, 2019). In addition, disadvantaged populations are more likely to struggle with maintaining their devices and being able to pay for data plans and Wi-​Fi connections in their homes (Gonzales, 2016; Gonzales et al, 2016).

Digital skills Using the Internet frequently is associated with positive outcomes, such as higher social support (Rains & Tsetsi, 2017; Tsetsi & Rains, 2017), finding work, saving money, finding important information (including health information) or connecting to others via email or social networks (Zillien & Hargittai, 2009; Van Deursen & Helsper, 2018), as well as better general well-​being (Büchi et al, 2018). However, positive outcomes of Internet use are closely intertwined with digital skills (Van Deursen & Van Dijk, 2011; Van Deursen et al, 2017), as is

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the ability to stay safe on the Internet, for example to make sure your privacy is protected (Hargittai & Litt, 2013; Büchi et al, 2017). In addition, having good digital skills is an important factor in securing employment in the 21st century economy (Pirzada & Khan, 2013). However, digital skills, in turn, are closely related to socio-​economic background (Hargittai, 2001) in the same way that gaining access and using the Internet for a variety of different activities is. This means that those who are socio-​economically worse off are facing multiple layers of digital inequality: they experience fewer access opportunities and tend to rely heavily on public access, such as libraries (Dailey et al, 2010; Rhinesmith, 2012). They struggle to maintain stable access and functioning devices (Gonzales, 2016; Gonzales et al, 2016), and once online they engage in fewer activities (Livingstone & Helsper, 2007; Reisdorf & Groselj, 2017) and fewer capital enhancing activities (Zillien & Hargittai, 2009). In the United States, there is also a strong relationship between race and digital inequalities (Turner, 2016; Pew Research Center, 2019b, 2019a).

Digital inequalities and reentry These same sociodemographic factors, including low income, lower educational attainment, and race and ethnicity, are strongly associated with the likelihood of serving a prison sentence (Pettit & Western, 2004; Mauer & King, 2007; Loury, 2008; Lyons & Pettit, 2011). Accordingly, returning citizens face what Reisdorf and Jewkes (2016) call ‘supercharged digital exclusion’. During incarceration, those who are incarcerated are not allowed to access and use digital devices such as cellphones, computers or tablets. In addition, a large number of prisons do not provide access to computer classes and if they do, those classes often use outdated devices that are not connected to the Internet (Reisdorf & Jewkes, 2016). To add to this debate, urban myths and rare cases of misuse and hacking of computers in correctional facilities that make the news (Lecher, 2017; Fortin, 2018) stifle efforts to make digital skills training a core component of rehabilitation and reentry programs. In addition to this lack of access during incarceration, many returning citizens also face digital inequalities after their release due to their lower socio-​economic status. However, in a qualitative pilot study in greater Detroit, Ogbonnaya-​Ogburu and colleagues (2019) demonstrated digital skills training could fill a gap in learning how to utilize technologies for job-​related tasks such as building a resume or finding and applying for jobs online. As most returning citizens relied on family to learn digital skills post-​release, the skills

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they learned were often limited to basic uses (Ogbonnaya-​Ogburu et al, 2019). In addition, higher digital skills are necessary not just to gain more from the Internet but also to stay safe online (Büchi et al, 2017). More formalized training before and directly after release may provide opportunities to learn or improve digital skills before returning citizens are required to utilize digital technologies to function in a highly technology-​dependent society.

Existing digital skills programs for returning citizens There are existing programs available to people who are currently incarcerated. Notably, these often take shape in the form of ‘tablet programs’ where private companies will provide tablets to incarcerated people for free, but all of the services provided on the tablets come at a cost (Finkel & Bertram, 2019). If they are not free, purchasing just the tablet can cost upwards to $140 (Riley, 2018). This means that in addition to purchasing the tablet, services that are touted as being a benefit of the tablet—​like email, music, eBooks and even commissary purchases—​come at a high cost to those who use the tablets. To put the cost in context, the average wage for work in prison is $0.86 per day (Sawyer, 2017). This would mean that family or friends would have to purchase the tablet as well as the content for them. Additionally, many of these tablets are not meant to teach those who are currently incarcerated digital skills. Instead, many states that have rolled out these ‘tablet programs’ are eliminating law libraries, physical books and even mail services (Finkel & Bertram, 2019). The cutting of services like mail are also occurring in other ways that may be considered human rights violations. Notably, some places are replacing in-​person visits with ‘video visitations’ (Sims, 2017). In-​person visits come at no cost to the incarcerated person—​in some of these video visitation programs (which are just video calls), the cost of a single call can be $12.99 or $30 for 20 minutes of call time (Kozlowska, 2018). Further, if prisons switch to ebooks, the cost of the ebooks is a huge barrier to access. Additionally, many of these tablet programs use extremely cheap and poorly made tablets that do not even have Internet access, and an incarcerated person’s use of them completely depends on how much money they can pay to access the tablet’s applications. Thus, tablet programs can be more restrictive and costly than they are beneficial and helpful and can be used to deny even more services to incarcerated people, worsening the digital divide. There are only a handful of private companies that control the prison tablet system in the United States. These include JPay, GTL and Securus Technologies (Kozlowska, 2018;

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Finkel & Bertram, 2019). None of these programs are interested in teaching incarcerated people digital skills to prepare them for reentry—​ rather, these are companies who have identified a new market ripe for exploitation. Their interests are purely for profit and tablet programs are not an appropriate substitute for actual digital skills training and literacy. Many states are adopting these programs as a way of appearing innovative and adapting to a changing world. However, many of the programs are woefully inadequate for these skills and are extremely costly for those who are supposed to benefit from them. Aside from the issues that manifest with tablet programs, the existing skills-​based programs are often inconsistent with the skills that they teach. Although there are localized efforts, such as New York City’s Prisoner Reentry Institute’s ‘Tech 101’ course, instruction of ICTs is not a core component of prisoner reentry across the United States. Some reentry training is computer-​assisted and some prisons offer basic computer classes. Yet, most courses do not cover how to operate the Internet and there is little research on access to ICTs and the digital skills of returning citizens. For instance, many incarcerated people may lack any knowledge in using something as basic as email, and there are some programs that are opting to teach incarcerated people ‘how to code’ (Higgins, n.d.). Further, many of these initiatives are being led and justified by private companies such as Google (Weidmayer, 2019), who state that they are teaching valuable skills, cutting costs for prisons, and in the case of the ‘learn to code’ camps, giving incarcerated people marketable skills. However, none of these programs addresses the structural inequalities and issues that incarcerated people face once they are released—​even if they learn coding skills, they will still struggle to find work due to their former incarceration. And although these initiatives may have good intentions, they are not addressing the structural and cultural issues that keep women, Black people and other ethnic minorities out of the technology industry and may be in place to make the labor even cheaper by saturating the market (Tarnoff, 2017).

Evidence from the field Studies previously cited in this study (Jewkes & Reisdorf, 2016; Reisdorf & Jewkes, 2016; Ogbonnaya-​Ogburu et al, 2018, 2019), as well as our own study that conducted focus groups with returning citizens support the claims that the digital divide in the United States may be worsening, particularly for formerly incarcerated persons. We conducted focus groups with 78 male and female returning

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citizens in a large Midwestern city in spring 2018. The mean age was 52 years (M=52.07, SD=19.4). Participants had been released from prison within four months of the focus groups and they had served a sentence of at least 2–​3 years. We used a semi-​structured approach to ask questions about ICT use, use and access barriers and the kinds of ICTs needed during reentry. We conducted various rounds of thematic coding of the transcribed data using NVivo. In our focus groups, many returning citizens reported that the JPay tablets they had during incarceration were inadequate, and they also stressed the need for more digital skills training. Many did not see technology as being a ‘bad’ thing or a barrier in and of itself, but rather lamented their lack of skills in being able to navigate their reentry process more effectively. All participants had cell phones, mostly smartphones, but only few owned laptops or tablets. In particular, access to computers and the Internet was unstable and often non-​existent due to many participants living in temporary housing, such as homeless shelters and halfway houses. The issue that many participants raised, though, was not just access but also a lack of skills. Although some did report an issue accessing computers (like travel distance and time being main factors to go to public libraries or other community centers, etc.), lack of skills was still a main barrier and frequently discussed even when access was not a problem. Of course, lack of skills varied depending on the participant’s age, length of sentence, and whether they had engaged with ICTs before (see also Reisdorf & Jewkes, 2016). For instance, one of our participants was incarcerated for only five years, whereas another had been incarcerated for 40 years, with many of our participants falling in the 10-​to 20-​year sentence length. Regardless of sentence length, however, participants reported issues in using ICTs to search and apply for jobs, write emails and use apps on their phones. Whereas some were able to learn from friends, family, shelter staff, community centers or teach themselves, many were unsure where to ask for help and what kinds of questions or help to ask for. In other words, their lack of understanding of the technology left them unsure where to start. The lack of skills was particularly stressful in the context of communication with parole officers. Some participants reported that because they did not know how to send text messages, read and send emails, or even to check voicemails on their smartphones, they were concerned about missing important and crucial communications from their parole officers. This would indicate that even basic classes on computer and Internet use could provide a useful starting point for acquiring the digital skills necessary to navigate a heavily tech-​ dependent world.

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Further, many of our participants did report initially feeling overwhelmed with the ubiquity of technology in the world. Despite this, many reported positive aspects of an ICT driven world (see also Ogbonnaya-​Ogburu et al, 2019). Even though there were many negatives, participants were quick to offer a positive thing that they had experienced with ICTs. Many pointed to an easier way to connect with loved ones, ability to apply for jobs, securing housing, and one participant reported that they had started learning how to build their own website for a clothing company they were hoping to start. Another acknowledged the utility of being able to easily access online databases for legal research that they were conducting and that they were also taking online university courses, and many participants noted that their lack of knowledge was an opportunity to connect with children and grandchildren. The focus groups reported many things that we had anticipated—​but some of what emerged was quite different from what we expected. The lack of digital and ICT skills that returning citizens reported contributes to exacerbating already existing structural issues. The lack of skills also extends to confusion around evolved social norms when it comes to communicating in a digital world. Many of the sessions turned into support groups for the participants, with them helping each other by showing each other how to do things on their phones, asking questions about what certain emojis mean, explaining where to access digital literacy services, and most significantly the participants had in-​depth and thought-​out ideas for solutions. The innovative thinking and drive that were present during these discussions demonstrated that the issue is not that returning citizens are unaware of their circumstances—​rather, they are acutely aware of their circumstances, the barriers that they face and ways to fix them. Proposed solutions by our participants included providing more classes in digital skills training before and after release, as well as providing information to parole officers about where these classes are occurring. Returning citizens complained that upon release, they are often just thrown into the world with no regard for their level of digital literacy—​for instance, the participant who had been incarcerated for 40 years reported that upon release, he was given a debit card, and he had no idea how to use it. This example demonstrates that ICTs are not purely about being able to access more advanced uses, but lack of ICT training is a barrier to basic facets of everyday life like banking, public transportation, and applying for employment. Despite stressing the need for digital skills training, many of our participants did not think that the Department of Corrections (DOC) would be a good

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provider for these classes. Understandably, our participants perceived the DOC’s role being that to punish and suppress rather than aid in successful reentry to society. Instead, they recommended that nonprofit organizations, college students volunteering for service-​learning opportunities, and other civic organizations and community centers provide these classes.

Pre-​crime society, dataveillance, surveillance and reentry In addition to experiencing issues with accessing and using digital technologies, returning citizens and marginalized populations more generally deal with increasing levels of surveillance and so-​called dataveillance, whereby large amounts of data that are collected through CCTV, smart city technology, digital devices, such as smartphones, online activities, and use of social media. ‘Such data production processes permit authorities with informational access the ability to view, measure, describe, categorize, classify, sort, order, and rank subjects’ data doubles in order to detect previously unknown patterns and anomalies’ (Arrigo et al, 2020, p. 5). These kinds of predictions are, in turn, used to (re-​)stigmatize individuals who are considered to be a risk to security and law and order. This shift from surveillance during incarceration to a different, albeit equally comprehensive, type of surveillance through data collection poses another type of literacy that returning citizens may need to acquire, as knowledge about privacy and surveillance is part of broader digital literacy (Büchi et al, 2017). Building on our participants’ experiences, this section examines the role of the pre-​crime society, surveillance, dataveillance and hyper-​ securitization in the context of reentry.

Pre-​crime and dataveillance In the context of the pre-​crime society, the focus shifts from post-​ crime punishment and incapacitation to a logic of security that aims to prevent crimes from happening in the first place. The ultimate goal of such logic is ‘to anticipate and forestall that which has not yet occurred and may never do so’ (Zedner, 2007, p. 262). Collecting vast amounts of ‘big data’, storing them and analyzing them at greater efficiency and speed than has ever been possible before allows for much broader surveillance based on these data—​dataveillance—​which can be used to control crime (den Boer & van Buuren, 2010). In this context, individuals are less relevant. Rather, dataveillance allows for

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the identification and classification of whole population groups in relation to the risk they may pose to security. ‘In this context the prison is less an instrument of punishment, still less reform, than a carceral warehouse for detaining those categorized as posing the highest risks’ (Zedner, 2007, p. 265). This categorization is not coincidental, of course, with more vulnerable populations, such as people of color and low-​income communities being disproportionately represented in such ‘high-​r isk’ categories (Benjamin, 2019)—​the same populations who are disproportionately incarcerated (Pettit & Western, 2004; Mauer & King, 2007; Loury, 2008). Upon reentering society, individuals and their communities alike are, then, still part of a population that is subject to more surveillance and dataveillance than their white and well-​off counterparts. The idea of using technologies and big data for crime detection and prevention is most generally encouraged by governments and the idea of a smart city. The notion that this kind of dataveillance is necessary to keep society safe is also widely accepted by large segments of society in exchange for ease and convenience using ICTs (van Dijck, 2014), following the ‘I’m not doing anything wrong, I don’t care that they’re watching me’ logic. However, such a logic would assume that technologies are neutral. However, technologies and the way that big data and algorithms work are inherently biased against communities of color and other marginalized groups due to the nature of the data feeding into the algorithms, as well as the algorithms themselves (Eubanks, 2018; Noble, 2018). In the context of the pre-​crime logic, data are not collected or analyzed equally for every citizen. Rather, ‘the algorithmic truth is the digital computation of a “data double”, simulated and reproduced for observation and profiling purposes’ (Arrigo et al, 2020, p. 5), which focuses on certain segments of the population that are considered ‘higher risk’ than others. For returning citizens, as well as at-​r isk youth and low-​income communities more generally, developments in predictive policing mean a continued experience of surveillance and an increased risk of (re)arrest and (re)incarceration (Goffman, 2014). This is potentially due to use of or dataveillance through digital devices or social media that could get them into trouble (e.g. Fuchs & Trottier, 2015); and mainly through the utilization of digital computer-​mapping systems, including Geographic Information Systems (GIS) and CompStat crime data systems, which allow law enforcement to map ‘high-​r isk’ areas that are correlated with criminal activity (Arrigo et al, 2020). While many of our participants were aware of mass surveillance and that use of the Internet and social media can lead to increased surveillance, they were less sure about what

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could be done to protect themselves and their privacy when online, as is the case with many people in the general population (Büchi et al, 2017). However, for returning citizens, many of whom are on parole upon release, the stakes are often higher than for people who are not caught up in the justice system, as a relatively minor ‘slip-​up’, which would not be problematic for someone who is not on parole or probation, could lead to a parole violation, rearrest, and in the worst case, reincarceration.

The mass surveillance state and hyper-​securitization The 17th century philosopher Jeremy Bentham’s conception of the panopticon as a form of punishment via collective surveillance has infiltrated nearly every aspect of daily life (Lyon, 2017). Indeed, Foucault’s reimagining of the concept of the panopticon as a means of surveillance—​and thus, discipline and control—​in prisons, schools and other aspects of daily life has merely extended itself to our current hyper-​digital world. In the name of safety, surveillance has become a part of modern life in the form of massive CCTV systems in urban spaces, the tracking of cellular data, and the monitoring of social media accounts and other modes of computer-​mediated communication (Leman-​Langlois, 2002; Lyon, 2017). Starting as early as the 1990s, concerns about how computer-​mediated communication would oppress rather than liberate most factions of society were raised (Spears & Lea, 1994), with the point being made that these technologies often reify power structures and relations rather than dismantle them. We see this playing out in the prison system in both the obvious and subtler ways in which incarcerated people are allowed access to technology, and the allowed uses of such devices. Incarcerated individuals are allowed only rudimentary access to ICTs. In fact, tablet programs and other initiatives like them are more repressive and oppressive than they are liberating. Not only are they being hyper-​monitored while within the institution’s walls, but also this logic of mass surveillance follows them upon release. However, they are woefully unprepared for a world that requires their buy-​in and embrace of such surveillance via technology. For example, some of our participants reported their frustration that their parole officers would text them, because they did not know how to text them back. Additionally, the move online for nearly all forms and applications for government assistance, job applications, and even banking, served as considerable barriers for our participants. And, most importantly, when informed that the focus group session would be recorded,

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many of the participants across sessions expressed initial discomfort and needed repeated reassurance that their data would not be released to the DOC. Privacy, and the very concept of it, did not emerge often in our focus group sessions, but the undercurrents of such concerns did peek out through the participants’ concerns about being recorded. In addition, some participants reported that, as a part of their probation, they had restrictions around their ICT use that had since been lifted. In fact, depending on the kind of crime committed, probation officers are allowed by law to install monitoring software on returning citizens’ computers, smartphones and other devices, as well as unannounced searches and seizures of such devices (United States Courts, n.d.). Although meant to deter criminal activity that occurred over ICTs, such as hacking, child pornography and other cybercrimes, we are seeing the extension of this kind of surveillance, and control exerting its influence more and more for all citizens. The issue remains, however, that it is not only returning citizens who are subjected to the mass surveillance state, but all individuals—​ whether they are aware of it or not—​to maintain social control (Bohlander, 2018). Hyper-​securitization in the name of safety has also resulted in virtually unusable technologies in prisons (like JPay tablets), the withholding of internet access from incarcerated individuals, and surveillance upon release. In fact, Reisdorf and Jewkes (2016) found that notions of hyper-​securitization were one of the main reasons mentioned by prison staff for not allowing incarcerated people to access the internet—​even if such access was highly structured and limited to white-​listed pages and educational content only. In addition, they found that Skype visitations, which were offered to residents at two institutions in Northern Ireland to connect with faraway loved ones, were monitored by prison staff for the complete time they were online with their families—​a practice that is only employed for phone calls if there is evidence that the incarcerated person is engaged in illegal activities (Jewkes & Reisdorf, 2016; Reisdorf & Jewkes, 2016). As a method of control, mass surveillance and dataveillance techniques are also being used on people who are considered to be ‘at risk’ of committing crimes—​whether they have previously committed crimes or not. This results in the over-​policing and over-​surveillance of minority, immigrant and low-​income communities in the United States (as well as other countries), and surveillance of social media has become an accepted part of digital life (Semitsu, 2011; Bekkers et al, 2013).

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Conclusion This chapter focused on the technologies and tech-​related issues that returning citizens encounter once they are released from jail and prison. The focus of our discussion revolves around the idea that increasing digital skills during the later stages of incarceration and immediately after release could aid in a better and more successful reentry experience for returning citizens, and thereby potentially combat the ‘revolving door effect’ that sees two thirds rearrested (67.8 per cent), and nearly half returning to prison (49.7 per cent) three years following release (Durose et al, 2014). While there are digital technologies to control those who are on parole and probation, such as ankle monitors or other surveillance technology (Yeh, 2010; Nellis, 2013; Bales et al, 2010; Bülow, 2014; Vanhaelemeesch et al, 2014), we focus instead on how technologies may improve reentry by providing the digital skills and access to technologies necessary to equip returning citizens with some of the skills they need to survive (and thrive) in the 21st century, although it is questionable whether such access and training could mitigate the consequences of surveillance, dataveillance and hyper-​securitization that returning citizens and their communities experiencing in the pre-​crime society (Arrigo et al, 2020). In addition to structural and socio-​economic disparities, returning citizens carry with them the burden of a criminal record, and now also a lack of digital skills and, in many cases, digital access. This lack of skills is often perceived by returning citizens as a sure giveaway of time spent in prison, as they believe everyone else had a chance to pick up these skills on the outside (Jewkes & Reisdorf, 2016; Reisdorf & Jewkes, 2016), leaving them ‘behind’ and branded as digital outsiders. The majority of returning citizens perceive digital skills as both necessary and desirable, yet they mainly depend on their families to help them with both access and skills in order to navigate the Internet and digital devices, leading to a lack of more sophisticated skills that are needed to find and obtain employment (Ogbonnaya-​Ogburu et al, 2018, 2019). As returning citizens are not just facing basic digital divides or inequalities, but a combination of generally restrictive factors and stigma, Reisdorf and Jewkes (2016) refer to the situation many formerly incarcerated people find themselves in as ‘supercharged digital exclusion’. However, it is easy to fall into technologically deterministic patterns here. Rather than arguing that throwing technology and digital skills at returning citizens will fix any and all reentry issues and solve the revolving door effect, we contend that this is a realm that can simply not be ignored in rehabilitation and reentry (Reisdorf & Rikard,

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2018). Technologies are central to an increasing number of everyday functions that are occurring through digital devices and the Internet, such as communication (social media, email), financial transactions (online banking, PayPal, Venmo, online shopping, etc.), information seeking and job placement. Digital technologies can be helpful in finding information, navigating job searches and applications, and connecting with others through social media or email. However, they can also cause problems in making users vulnerable to privacy violations, exploitation and surveillance. This double-​edged sword makes it even more important to provide digital skills training to returning citizens before they encounter these technologies ‘in the wild’ post-​release. Not only could digital devices and the Internet provide them with opportunities that they may not have ‘offline’, they also open them up to potential dangers and issues, such as having their data or identities stolen, being scammed or being surveilled. Higher digital skills levels have been shown to not only aid in getting more out of using the Internet (Van Deursen & Van Dijk, 2011; Van Deursen & Helsper, 2018) and increasing employment opportunities (Pirzada & Khan, 2013), they also prevent negative experiences such as privacy violations (Büchi et al, 2017). Digital skills and access to digital devices and the Internet are no longer a luxury for the privileged few, they are considered necessary to navigate everyday life in the digital society, to the point that the UN declared Internet access a basic human right in 2011 (Kravets, 2011). In addition, given the prevalence of dataveillance through CCTV, device location data and data on online activities, which can be paired and analyzed with general data on criminal activity and place, returning citizens, and marginalized populations in general, need to learn specifically about the risks that come with being online. Whereas returning citizens themselves are acutely aware of the value and necessity of having digital skills (Ogbonnaya-​Ogburu et al, 2018, 2019), efforts on the side of Departments of Corrections have been slower, with some notable exceptions, such as the Google-​funded ‘Last Mile’ project, which teaches incarcerated people coding skills (Weidmayer, 2019), and more basic digital skills classes that are beginning to be offered on a local scale, such as the ‘Pivot the Hustle’ program in Providence, RI (Pivot the Hustle, n.d.), the ‘Tech 101—​Prisoner Reentry Institute’ program in New York (Tech 101, n.d.), or in Charlotte’s Mecklenburg County Jail (Powell, 2019). Although some of these programs only teach basic computer skills, they can act as a gateway for higher comfort levels with digital technologies that could lead to a desire to learn more about how to utilize the Internet and digital devices. Formerly incarcerated people

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understand the value of needing these skills, but policymakers, parole agents, and DOCs across the country and their negligence in teaching these skills are reifying an already existing social issue (digital literacy and access) for an already vulnerable population. As the world becomes more digitized, this becomes less of an issue of ‘the right skills’ and one that is becoming a human rights issue. From a policy perspective, more focus needs to be on speaking to those who are in the reentry process in order to understand their needs, and not what policymakers think that returning citizens need. In addition to useful programming, such as drug and alcohol abuse recovery programs and general employment readiness, digital skills, including those that deal with issues of dataveillance and online privacy, should be at the core of rehabilitation and reentry programs across the country. The existing programs and studies are a first step in the right direction, but a broader approach that is available to all returning citizens is needed to address a new realm of concern during the reentry process. References Arrigo, B.A., Sellers, B.G. & Sostakas, J. (2020). Pre-​crime, post-​ criminology, and the captivity of ultramodern desire. International Journal of the Semiotics of Law 33 (2): 497–514. Bales, W., Mann, K., Blomberg, T., Gaes, G., Barrick, K., Dhungana, K. & McManus, B. (2010). Quantitative and Qualitative Assessment of Electronic Monitoring. BiblioGov. Bekkers, V., Edwards, A. & de Kool, D. (2013). Social media monitoring: Responsive governance in the shadow of surveillance? Government Information Quarterly 30 (4): 335–​42. Benjamin, R. (ed.) (2019). Captivating Technology: Race, Carceral Technoscience, and Liberatory Imagination in Everyday Life. Durham, NC: Duke University Press. Bohlander, M. (2018). ‘The global Panopticon’: Mass surveillance and data privacy intrusion as a crime against humanity? In M. Böse M. Bohlander, A. Klip & O. Lagodny (eds.) Justice Without Borders: Essays in honor of Wolfgang Schomburg. Leiden/​Boston: Brill Nijhoff (pp. 73–​102). Büchi, M., Just, N. & Latzer, M. (2017). Caring is not enough: The importance of Internet skills for online privacy pr otection. Information, Communication & Society 20 (8): 1261–​78. Büchi, M., Festic, N. & Latzer, M. (2018). How social well-​being is affected by digital inequalities. International Journal of Communication 12: 21.

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Powell, H. (2019, June 1). Digital literacy class gives students another chance at jail. Spectrum News [online] Available at: https://​spectrumlocalnews.com/​nc/​charlotte/​news/​2019/​06/​ 01/​digital-​literacy-​class-​a-​first-​in-​mecklenburg-​county-​jail-​. Rains, S.A. & Tsetsi, E. (2017). Social support and digital inequality: Does Internet use magnify or mitigate traditional inequities in support availability? Communication Monographs 84 (1): 54–​74. Reisdorf, B.C. & Groselj, D. (2017). Internet (non-​) use types and motivational access: Implications for digital inequalities research. New Media & Society 19 (8): 1157–​76. Reisdorf, B.C. & Jewkes, Y. (2016). (B) Locked sites: Cases of Internet use in three British prisons. Information, Communication & Society 19 (6): 771–​86. Reisdorf, B.C. & Rikard, R.V. (2018). Digital rehabilitation: A model of reentry into the digital age. American Behavioral Scientist 62 (9): 1273–​90. Reisdorf, B.C., Hampton, K., Fernandez, L. & Dutton, W.H. (2018). Broadband to the neighborhood: Digital divides in Detroit. SSRN. [online] Available at: https://​papers.ssrn.com/​sol3/​papers. cfm?abstract_​id=3103457. Rhinesmith, C. (2012). Free library hot spots: Supporting broadband adoption in Philadelphia’s low-​income communities. International Journal of Communication 6: 2529–​54. Riley, T. (2018). “Free” tablets are costing prison inmates a fortune. Mother Jones. [online] Available at: https://​www.motherjones.com/​ politics/​2018/​10/​tablets-​prisons-​inmates-​jpay-​securus-​global-​tel-​ link/​. Robinson, L., Cotten, S.R., Ono, H., Quan-​Haase, A., Mesch, G., Chen, W., Schulz, J., Hale, T. M. & Stern, M. J. (2015). Digital inequalities and why they matter. Information, Communication & Society 18 (5): 569–​82. Sawyer, W. (2017). How much do incarcerated people earn in each state? Prison Policy Initiative. [online] Available at: https://​www. prisonpolicy.org/​blog/​2017/​04/​10/​wages/​. Semitsu, J.P. (2011). From Facebook to mug shot: How the dearth of social networking privacy rights revolutionized online government surveillance. Pace Law Review 31: 291. Sims, S. (2017). The end of American prison visits: Jails end face-​ to-​face contact—​a nd families suffer. The Guardian. [online] Available at: https://​www.theguardian.com/u ​ s-n ​ ews/2​ 017/d​ ec/0​ 9/​ skype-​for-​jailed-​video-​calls-​prisons-​replace-​in-​person-​visits.

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Spears, R. & Lea, M. (1994). Panacea or Panopticon?: The hidden power in computer-​m ediated communication. Communication Research 21 (4): 427–​59. Tarnoff, B. (2017). Tech’s push to teach coding isn’t about kids’ success—​it’s about cutting wages. The Guardian. [online] Available at: https://​ w ww.theguardian.com/​ t echnology/​ 2 017/​ s ep/​ 2 1/​ coding-​education-​teaching-​silicon-​valley-​wages. Tech 101 (n.d.). Prisoner Reentry Institute. [online] Available at: http://​ johnjaypri.org/​tech-​101/​ The Last Mile—​Paving The Road To Success. (n.d.). [online]Available at: https://​thelastmile.org/​. Tsetsi, E. & Rains, S.A. (2017). Smartphone Internet access and use: Extending the digital divide and usage gap. Mobile Media & Communication 5 (3): 239–​255. Turner, S.D. (2016). Digital Denied: The Impact of Systemic Racial Discrimination on Home-​Internet Adoption. [online] Available at: https://​ www.freepress.net/​sites/​default/​files/​legacy-p​ olicy/d​ igital_d​ enied_​ free_​press_​report_​december_​2016.pdf. United States Courts. (n.d.). Chapter 3: Computer and internet restrictions (probation and supervised release conditions). In Overview of Probation and Supervised Release Conditions. [online] Available at: https://​www.uscourts.gov/​services-​forms/​computer-​internet-​ restrictions-​probation-​supervised-​release-​conditions. Van Deursen, A.J. & Van Dijk, J.A. (2011). Internet skills and the digital divide. New Media & Society 13 (6): 893–​911. Van Deursen, A.J. & Helsper, E.J. (2018). Collateral benefits of Internet use: Explaining the diverse outcomes of engaging with the Internet. New Media & Society 20 (7): 2333–​51. Van Deursen, A.J., Helsper, E.J., Eynon, R. & Van Dijk, J.A. (2017). The compoundness and sequentiality of digital inequality. International Journal of Communication 11: 452–​73. Van Dijck, J. (2014). Datafication, dataism and dataveillance: Big Data between scientific paradigm and ideology. Surveillance & Society 12 (2): 197–​208. Vanhaelemeesch, D., Vander Beken, T. & Vandevelde, S. (2014). Punishment at home: Offenders’ experiences with electronic monitoring. European Journal of Criminology 11 (3): 273–​87. Weidmayer, M. (2019). Google-​funded Program Connects Michigan Prison Inmates to Coding Skills—​Mlive.com. MLive. [online] Available at: https://​www.mlive.com/​news/​jackson/​2019/​10/​google-​funded-​ program-​connects-​michigan-​prison-​inmates-​to-​coding-​skills.html.

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PART V

Globalizing Surveillance, Human Rights and (In)Security

17

Surveilling the Civil Death of the Criminal Class Natalie Delia Deckard

Introduction Judge Henry Wingate explained the importance of the right to vote and the use of disenfranchisement as a form of punishment as follows: Disenfranchisement is the harshest civil sanction imposed by a democratic society. When brought beneath its axe, the disenfranchised is severed from the body politic and condemned to the lowest form of citizenship, where voiceless at the ballot box … the disinherited must sit idly by while others elect his civic leaders and while others choose the fiscal and governmental policies which will govern him and his family. Such a shadowy form of citizenship must not be imposed lightly. (Shapiro, 2001) In the liberal democracies of late capitalism, being a citizen without the right to self-​representation through voting is akin to civil death (Miller & Spillane, 2012). This medieval concept describes the banishment of the convicted from the umbrella of the state—​a punishment reserved for only the most heinous crimes (Agamben, 1998; Miller & Spillane, 2012). Civil death resulted in outlaw status, and left the indicted a political non-​entity, both unprotected by systems of law and unrepresented in legislative structures (Agamben, 1998). Yet judicial decisions have confirmed that citizenship does not necessarily

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include the right to vote; rather states can decide who has that right (Schultz, 2007). In the United States today, varying state-​level practices of disenfranchising the incarcerated, those on parole or probation, those still paying court fines or fees, and those who have completed carceral sentences mean that approximately 6.1 million American citizens cannot legally vote (The Sentencing Project, 2016). Without the ability to vote, those who have had experiences with the criminal justice system cannot participate in the democratic conversation about crime and crime control. More broadly, because carceral systems of enforcement fall disproportionately heavily on racialized and impoverished citizens, electoral exclusion falls disproportionately on their communities (Behrens, Uggen & Manza, 2003; Cammett, 2012). Voting matters. It converts people from governed subjects to citizen governors. At the level of the community, it makes claims-​making on the state possible and elected officials accountable to community needs (Dunning, 2011). The increasingly ubiquitous surveillance of voters means that candidates choose platforms in tandem with voter preferences (Bennett, 2015). With those with felony convictions excluded, a feedback loop of criminalization is inevitable. Thus, the inescapable underlying logic of felon disenfranchisement is one of pre-​crime. Although the usual justification for the practice is that disenfranchisement is part of the criminal penalty designed to punish the offender in a way not dissimilar to other carceral punishments. Control of the electorate represents control of the definition of crime itself—​by carefully excluding named criminals from the construction and replication of laws that determine what constitutes a crime, felon disenfranchisement controls who commits crime. Crime becomes whatever it is that excluded people do. The mechanisms through which criminals and voters are surveilled are increasingly sophisticated, and the documentation of that surveillance is increasingly detailed. Yet the line between who can vote and who, as a function of criminalized status, cannot is notoriously unclear. This lack of clarity is, perhaps, one of the strongest arguments for the fundamentally exclusionary nature of felon disenfranchisement law.

Felon disenfranchisement Felony disenfranchisement laws, legislation passed at the state or national level to restrict the voting rights of those who have been convicted of serious criminal offenses, range from inability to participate in elections during the time of incarceration to permanent,

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lifelong exclusion from suffrage (Ewald, 2002; Beckman, 2009; Miller & Spillane, 2012). They are the only significant exception to universal adult suffrage in the United States (Ewald, 2002). In the United States, for example, 11 states rescind voting rights of released felons as a default, with restoration of voting rights accomplished only through complex, expensive and uncertain application procedures attempted on years after other elements of sentencing have been completed (Aviram, Bragg & Lewis, 2017). An estimated 6.1 million Americans were disenfranchised as a function of their criminal records in 2016 (The Sentencing Project, 2016). The number of citizens that are affected by the felony disenfranchisement laws in the state government and its judicial system grows with the restrictiveness of the laws—​as ‘disenfranchised’ becomes a more encompassing and enduring state, it follows that more people are ensnared by it. In Florida, over 21 per cent of African Americans cannot vote, implying that the proportion of the most criminalized bodies in the state—​African American men—​who cannot vote approaches a majority (Uggen, Larson & Shannon, 2016). Existing research suggests that this pattern of disenfranchisement may affect the political reality of local and regional-​level politics (Ewald, 2002; Beckman, 2009; Ewald & Rottinghaus, 2009), and even national politics in the close or contentious elections in which acts of exclusion may be particularly damaging (Uggen & Manza, 2002). While the individual’s act of voting does not materially affect his or her particular life outcomes in that each vote has a generally negligible role in the actual passage of legislation (Riker & Ordeshook, 1968), the symbolic value of disenfranchisement cannot be overstated. Lacking the ability to vote means existing without representation, and the disproportionate disenfranchisement of a community’s members very strongly affects the representation accorded these communities. With this extraordinary wholesale deprivation of political rights, entire populations are rendered politically and civilly marginalized, a process explored thoroughly in discussions of the effects of American Apartheid-​era voting restrictions (Alexander, 2012). In the aggregate, community disenfranchisement has very real effects in terms of resource allocation, causing particular groups to be unrepresented in the political process and delegitimized as claims-​makers. Systematic exclusion of a criminalized population from political participation when criminalization is, itself, gendered, racialized, and classed has ramifications not just for who is able to vote but for what communities enjoy full political participation and value. Mauer (2004, p. 1) argues that ‘[t]‌he racial impact of disenfranchisement policies is sometimes justified as an inevitable if unfortunate aspect

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of a race neutral criminal justice system: if members of a particular racial or ethnic group are more involved in crime, the consequent disproportionate loss of voting rights is merely a result of their activity’. The use of race and ethnicity synonymously here elides an important truth: communities become racialized as their members become marginalized and objectified through the use of the criminal justice system. As the criminal equivalency Mauer notes becomes increasingly essentialized—​with group members excluded, rendered criminal by non-​members, and further excluded in turn—​the common sense of group members’ bodies as inherently criminal becomes less questionable. An important example is the case of African Americans in the United States. Indeed, referencing the US Bureau of Justice Statistics Bulletin (Kaeble & Cowhig, 2018), African Americans represented 40 per cent of a total of 829,344 convicted felons and 48 per cent of felons convicted of violent crimes in 1990, although they made up only 12.1 per cent of the US adult population in that year. Drug cases are among the primary reason for African American imprisonment (Kerby, 2012), and in 1990, African Americans represented 56 per cent of convicted felons charged with drug trafficking and possession. Ample literature demonstrates that these disproportionate figures are mere samples of the myriad results of significant institutionalized racism within the US criminal justice system (Alexander, 2012). Activities associated with African Americans are more likely to be criminalized (Cacho, 2012) and, once this is the case, African Americans are more likely to be strenuously punished for engaging in them (Mustard, 2001; Schanzenbach, 2005). Attempting to control the electorate in order to better control election outcomes is not new in US history. As early as 1787, the Three-​Fifths Compromise constructed state population for the purposes of congressional representation as comprising the aggregation of full White lives and African American lives at 60 per cent of the whole (Ohline, 1971). Indeed, it was the haphazard program of poll taxes and literacy tests that allowed Jim Crow legislation to dominate the US South from the Reconstruction Period until the passage of the Civil Rights Act in 1964 (Highton, 2004). Simply, if African Americans had been able to vote, they would have voted themselves to be full citizens—​it was only through either total or significant disenfranchisement of the African American people that their oppression was possible. Separating the empirically-​demonstrated criminalization of activities linked with African Americans from their systematic disenfranchisement is a fool’s errand.

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Felon disenfranchisement as pre-​crime control Pre-​crime, of course, seeks not to better punish those who have committed crimes but rather avoid that which is deemed undesirable from ever occurring. ‘In a pre-​crime society, there is calculation, risk and uncertainty, surveillance, precaution, prudentialism, moral hazard, prevention and, arching over all these, there is the pursuit of security’ (Zedner, 2007). That the security framework demands the control of people as a way to control behavior is largely accepted in the existing literature (Loader & Sparks, 2002; O’Malley, 2004; Shearing & Johnston, 2013)—​that it also demands a control of the electorate in order to control what constitutes crime itself is largely unexplored. Here, I posit disenfranchisement to be the principal mechanism through which this latter system of control is exerted, exploring different ways in which policies under the larger umbrella of felon disenfranchisement work to shape the electorate in ways that replicate ideas of the secure state. Cammett (2012) notes the practice of requiring ex-​felons completely pay ‘carceral debts’—​the combination of criminal justice-​related monetary penalties levied on prisoners, including user fees assessed to recoup the operating costs of the justice system, and other debt incurred during incarceration—​before the right to vote may be reinstated. These laws have obviously disparate implications for the poor but also for the never-​married young fathers of color who comprise the overwhelming majority of parents who owe child support debt (Maldonado, 2005). Important here is that the felon disenfranchisement works not only to exclude poor people from the ranks of voters—​but the morally suspect young men who are historically constructed as risks to public security writ large (Cohn, 2006). This observation about the disparate impact of felon disenfranchisement laws is not unique or particular to the case of carceral debt (Aviram, Bragg & Lewis, 2017). Rather felon disenfranchisement laws may be understood to amplify all of the existing racial (Behrens, Uggen, & Manza, 2003; Phillips & Deckard, 2016), class (Uggen & Manza, 2002) and gender (Haney, 2004) disparities noted in the criminal justice process to the level of membership in the national group itself. Phillips and Deckard use the case of Florida particularly to track the effects of racialized bias in sentencing, to racialized exclusion at the ballot box, to racialized legislation with life-​altering ramifications for communities, to racialized death at the hands of the state. Felon disenfranchisement is akin to civic death in a system in which ‘bare life’ (Agamben, 1998) makes one not only vulnerable to physical death

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(Cacho, 2012; Phillips & Deckard, 2016)—​but to being rendered tautologically and unavoidably criminal in a carceral state. One could understand felon disenfranchisement in this context as functioning in a manner similar to that of shunning or shaming in many religious sects. Church members who act in a manner deemed fundamentally irreconcilable with community beliefs are formally pushed outside of that community—​rendered literally voiceless and invisible to convert punishment of their behavior into stigma of their person (Tanaka, 2001; Bahk, 2001). The systematized shaming process becomes key to the reaffirmation of community values, and the excommunication of non-​conforming former members crucial to the reification of member identity (Bahk, 2001). Austin (2004) notes that the public shaming of ex-​felons and their families through the formal voicelessness of disenfranchisement is at the heart of the punishment. This can be understood as not only about more than punishment at the level of the individual but also about the manufacturing of security at the community level through the maintenance of existing norms (Altman, 2005). While extending the vote to ex-​offenders and allowing them to participate fully in political debates would specifically enrich political discourse around the criminal justice system (Austin, 2004), it would also tautologically change how we talked about criminal justice. In changing the voices in the conversation, it would extend the identity of the body politic to include ex-​offenders as members—​an undesirable outcome in a change-​averse society. The extension of punishments rooted in exclusion from political inclusion has a long history, and felon disenfranchisement does not inhabit a space that is categorically new (Agamben, 1998; Miller & Spillane, 2012). The convicted criminals of Athens could neither vote nor speak publicly (Ewald, 2002), while those of medieval Europe lacked suffrage and property rights—​lest voice could accrue from wealth (Miller & Spillane, 2012). The specter of the outlaw, forced to exist outside of the law, is well-​established in Western legal and political history (Agamben, 1998; Ewald, 2002; Miller & Spillane, 2012). Unlike the civil death of medieval times, however, disenfranchisement is widespread in those countries in which it is practiced and thus has the capacity to meaningfully effect the making of laws. This has rendered a large, and systematically biased, segment of the population unable to participate in the most basic elements of democratic life and exist outside of the realm of self-​governance, in a permanent state of exception in which they are subjects to be governed by citizens engaged in pre-​crime control.

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Disenfranchisement as civil death Central to the pre-​crime control endeavor is the idea of crime as an ineradicable social reality to be managed as a risk pool rather than as a series of individual actions or events (Zedner, 2007). In the infamous security state hypothesized to have originated in the post-​9/​11 Global North, crime and terrorism are the productions of criminal and terrorist populations who, when properly surveilled and controlled, enact less violence against citizen bodies and cause less fiscal damage to the coffers of late capitalism’s neoliberal state. This management paradigm is particularly useful in that it is recollective of international and historical attempts to make nations safer for members of the dominant culture through the political exclusion of stigmatized and distrusted domestic populations. One manages the costs of reproduction at the national level, for example, by denying women the right to vote—​and then democratically voting to deny them access to reproductive care, free movement, remunerated work, or private property before using their beleaguered state to justify their disenfranchisement (Little, 2004). Alternatively, acceptable migration levels are determined in representative bodies constituted through the systematic disenfranchisement of immigrants, allowing non-​citizens to exist as objects of law, rather than constituents. This cyclical dynamic may be thought of as a feedback loop, within which felon disenfranchisement is the motivating mechanism for exclusion at the intersection of gender, race and marginalized status (Phillips & Deckard, 2016). Exclusion begets powerlessness, which begets still more exclusion. In a time of burgeoning carcerality and exploding prison populations throughout the Global North, the enduring role of felon disenfranchisement in perpetuating marginalization in late capitalism cannot be overstated (Delia Deckard, 2017). Work by Shineman (2019) in Virginia confirms empirically what theory suggests: restoring the right to vote causes formerly disenfranchised individuals to develop higher levels of internal and external efficacy, generating citizens who are more confident in their own abilities and have stronger tendencies toward democratic engagement. Empirically, the denial of vote in a democracy contributes to alienation and exclusion from that democracy—​c ivil death (Ewald, 2002). The concept of civil death originates in medieval Europe, when convicted of certain crimes one would suffer the loss of civil rights (Miller & Spillane, 2012). Those convicted of the most heinous crimes

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received the most severe of punishments—​effectively social and political banishment. With this exclusion, the civilly dead become outlaws, and were both outside of the protection of the law and incapable of making claims for inclusion (Agamben, 1998; Miller & Spillane, 2012). To be rendered civilly dead is to be rendered outside of the rubric of political life, to have one’s interests made irrelevant in the public sphere. In previous periods of history, civil death as a criminal punishment was used in a very small number of extraordinary cases. In contrast, in the United States in 2016 an estimated 6.1 million people—​or 2.5 per cent of the adult population—​was so encumbered. In order to accomplish a ‘common sense’ around widespread marginalization such that permanent civil death can be accepted in the midst of purported democracy, there must be a dehumanization of the felons disenfranchised and a belief that their voting represents a real threat to that democracy’s security. In order to manage pre-​crime, the electorate must limit dangerous people’s access to the mechanism of governance—​the ballot box. Existing scholarship thoroughly explores the ways in which the carceral politics of the present moment does the work of dehumanizing those accused and convicted of crimes (Alexander, 2012; Cacho, 2012; Ewald, 2002). Little theorized, however, are the ways in which felon voting is understood to threaten the collective national security.

The power of voter fraud and electoral illegitimacy The specter of voter fraud and electoral illegitimacy works to add a narrative of threat aversion to felon disenfranchisement laws—​and gives life to the pursuit of security through stringent disenfranchisement. Conceptually, if ex-​felons had no wish to vote, or problem with their disenfranchisement, then the laws themselves would be needless. If, however, frightening criminals were attempting to illegally access ballot boxes and sway elections in their favor, then only a strict regime of enforcement would be sufficient to protect the threatened integrity of the electoral process and election results themselves. The prevalence of voter fraud in US elections is highly contested (Schultz, 2007; Fund, 2008; Keyssar, 2009). Existing scholarship indicates that this contention is largely driven by political realities in times of high polarization and close elections (Minnite, 2007, 2011; Schultz, 2007). Current concern with the danger of illegal voting began in the investigation around the 1,800 votes separating Republican presidential candidate George Bush from Democrat Al Gore. For

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the first time in a while, every vote mattered, and so the provenance of every vote was made to matter (Schultz, 2007). In the years that followed, the Attorney General made the stamping out of election fraud and corruption a Department of Justice priority—​yet only 26 individuals of the millions casting ballots were convicted with illegally voting from 2002 to 2005 (Minnite, 2011). Regardless of the statistical prevalence of voter fraud in elections, the specter of this fraud and the resultant imperative to pre-​emptively protect elections has been used to introduce a variety of legislation to make voting more difficult. One particularly popular reform has been the passage of voter photo identification requirements, which demand that voters have a piece of identification from an approved list of identification types before being allowed to cast a ballot (Rocha & Matsubayashi, 2014). These requirements are theorized to have a disproportionate impact on voter turnout among poor people and minority voters, who may find the additional burden of having approved identification too onerous to make voting possible (Sobel & Ellis Smith, 2009; Rocha & Matsubayashi, 2014). Yet empirical evidence to this effect is sparse, and almost certainly as negligible in impact as the original concern of voter fraud that put the laws in place. Not negligible, however, is the effect of racism and racial resentment on the popularity of these laws’ as a mechanism for combating voter fraud (Wilson & Brewer, 2013; Wilson, Brewer & Rosenbluth, 2014; Banks & Hicks, 2016). Simply, limiting access to polls by marginalized people was a desirable way to combat potential voter fraud for those voters who disliked African Americans the most. As today, in the period immediately following the Civil War, threats of voter fraud were used to strengthen restriction on voting by African American, poor and immigrant voters (Keyssar, 2009). These types of restrictions can be categorized in two ways—​those that sought to ensure only legally eligible voters cast ballots, and those that sought to restrict legally eligible voters to those who were ‘real’ citizens. These latter efforts can be understood as seeking to avoid a sort of ideological, if not technical, voter fraud and they still exist in the present day. John Fund wrote in his influential exploration of voter fraud as a partisan issue stemming from the 2000 Bush-​Gore presidential election: ‘The Florida controversy also offers a pretext for some to talk about other changes they want to make in election laws. (The NAACP, for example, wants to ‘re-​enfranchise’ four million felons who have lost the right to vote because of their crimes.) Some liberals would even like to extend voting privileges to noncitizens’. Here, the laws that determine who is voting legally and who fraudulently can,

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in themselves, be fraudulent—​or at least understood to be illegitimate. By including those who have committed crimes in the ranks of voters, ‘liberals’ threaten to further delegitimize the entire voter pool—​and by extension the electoral outcomes themselves. In this reading, instances of technical, legal voter fraud get to a larger, philosophical problem—​ many legal voters should not really be voting anyway because they are essentially criminals. This thinly-​veiled belief suggests that over-​purging rolls may not be considered a real danger to US democracy. Thus, in the post-​2000 election frenzy to restore electoral integrity, while some on the left advocated expanded access that would enhance equality, others on the right advocated tougher antifraud measures that would presumably enhance belief in electoral integrity (Tokaji, 2004).

Ubiquitous marginalizing surveillance Spurred forward by the threat of voter fraud, the enforcement of felon disenfranchisement legislation falls to individual states and municipalities. Given that felons have no particular barrier to the documentation of citizenship that makes one eligible to vote, how then to ensure they do not actually do so? In individual localities, secretaries of country election boards process voter cancellations, but the surveillance they relied on varied depending on the extent of the disenfranchisement legislation—​with those states who only disenfranchise the incarcerated sometimes only investigating absentee ballots that bore prison addresses (Ewald, 2005). Although the mechanisms for prosecuting ineligible voters for having voted are relatively clear—​proof of their disenfranchised status as of the time of election and of their having voted in violation of this disenfranchisement—​stopping them from voting to begin with requires widespread voter surveillance, database creation, and list distribution (Ewald, 2005). Current regulations around the creation and maintenance of voter lists are governed by the Help America Vote Act of 2002, or HAVA (Ruda, 2003; Tokaji, 2004; Ewald, 2005). The legislation was imagined to be a part of widespread national election reform in the aftermath of the 2000 election (Ruda, 2003), and it promised substantial changes in the way all elections were to be conducted (Tokaji, 2004). In its requirements around voter roll validation, HAVA mandates that all states, irrespective of felon disenfranchisement laws, coordinate their new computerized voter rolls ‘with State agency records on felony status’ (Tokaji, 2004). But while these changes have introduced a new layer of surveillance into voters’ lives, the felon lists and the resultantly purged voter lists

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have been plagued with inaccuracies (Schultz, 2007; Berman, 2015). These inconsistencies have been variously understood as benefiting candidates on both the left (Fund, 2008) and the right (Berman, 2015)—​but the idea that eligible voters are being systematically purged from voter rolls using the surveillance systems designed to track felons is inarguable. Importantly, while these lists are created to exclude people from existing as political actors, other types of surveillance are used to control voters who remain within the democratic system. Surveillance, or ‘any collection and processing of personal data, whether identifiable or not, for the purposes of influencing or managing those whose data have been garnered’ (Lyon, 2001) must be understood holistically as an increasingly ubiquitous part of life in modern democracies (Monahan, 2008; Delacourt, 2013; Bennett, 2015). Voters are surveilled as well—​the Cambridge Analytics debacle shows that presumed voters are tracked and monetized (Gordon, 2019). Bennett (2015) makes the point that the term ‘voter surveillance’ is not sufficiently broad or descriptive enough to capture the range of practices currently observed in different democracies across the wealthy world. Because no algorithm can determine who will actually vote—​although existing data can certainly predict the behavior—​data of all types are captured for everyone, not just voters. Increasingly, politicians are said to ‘shop’ for voters (Delacourt, 2013; Bennett, 2015), and tailor their platforms to best attract the largest swath of the electorate that could conceivably vote for them. Despite this ubiquity, surveillance is experienced distinctly by individuals of different positionalities, with race, class, gender, sexual orientation and nationality statuses influencing the ways in which surveillance may be understood as empowering or oppressive (Monahan, 2008). The gathering of consumer behavior data, for example, may help companies to hone their products to best appeal to potential buyers and let prospective clients know what offerings are available (Berry & Linoff, 2004), or it may exploit newly-​visibilized weaknesses in consumers’ psyches that render them particularly vulnerable to purchasing particular goods or services (Turow, Hennessy & Draper, 2015). The increasingly invasive monitoring of people using public services, such as means-​tested cash assistance TANF and food assistance through SNAP could be correctly described as oppressive to recipients, it might also be empowering to taxpayers who seek to control those understood as dependent on tax proceeds for survival (Hier, 2003). The overpowering surveillance of all aspects of behavioral, financial and physical attributes necessary to power insurance firms, credit reporting agencies and incarceration decisions is demonstrably designed

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and applied unequally, acting to replicate existing social inequalities (Noble, 2018). Yet although inclusion in these systems can be predatory, exclusion represents a clear case of digital redlining (Taylor & Sadowski, 2015). Simply, although surveillance represents a locus of oppression, exclusion from surveillance in a completely surveilled system comes to represent invisibility. It is reflective of the civil death that results from ‘marginalizing’ surveillance—​which exists to simultaneously elevate some while diminishing others (Monahan, 2008).

The vagaries of exclusion The current use of felon disenfranchisement to create a specific, criminalizing electorate is not new or unique to the United States. It has always functioned as a type of pre-​crime at some level. With the specific carceral framing of the current moment, however, surveillance powers the movement to use disenfranchisement to make criminal bodies coherent realities in the public discourse. The practice of disenfranchisement is, perhaps unsurprisingly, less coherent than the theory, however. The intention is to maintain electoral integrity and avoid voter fraud by enforcing a regime of voter disenfranchisement that employs marginalizing surveillance to empower voters while rendering the disenfranchised effectively without representation or voice. This intention is steeped in the governmentality of pre-​crime. In its execution, however, the legislative goals of felon disenfranchisement are unevenly and uninformedly accomplished. Inaccuracies in voter purges resulting from faulty mechanisms of surveillance certainly accomplish electoral chaos—​failing to purge voters with convictions from the voter rosters while inaccurately purging other voters with no criminal record (Schultz, 2007; Berman, 2015). Work by Ewald (2005) explores the actual knowledge exhibited by local election officials at various jurisdictions in the United States. He finds: In practice, election officials overwhelmingly fail to understand the actual laws governing felon disenfranchisement … On these initial questions, of ninety-​three local officials interviewed, thirty-​four—​about 37% either described their state’s fundamental eligibility law incorrectly, or stated that they did not know a central aspect of that law … Of those thirty-​four, seventeen erred in an exclusionary direction—​ incorrectly stating, for example, that probationers may not vote in a state where only incarcerated people are excluded,

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or wrongly declaring that only an official pardon restores eligibility in a state where a routine Corrections procedure will do. Just five erred in an inclusionary direction … And twelve of those thirty-​four officials gave an answer which did not indicate a clear ’direction’ … Thus, 85% of the officials who misidentified their state’s law either did not know the eligibility standard or specified that the law was more restrictive than in practice. (Ewald, 2005, p. 15) Simple apathetic ignorance appears to be the driver of much confusion regarding the practice of felon disenfranchisement at the local level. If accurately distinguishing who can vote from who cannot were a priority, then local officials would do so. As it is, ensuring that all eligible voters, including those at the boundaries of felon status for the purposes of voting law, could cast a legal ballot is not sufficiently important to learn where exactly those boundaries are drawn. Questions of the acceptability for voting of nativity and citizenship, established residency, designated polling place, and identification standards fall to local elections officials (Tokaji, 2004; Kropf, Vercellotti & Kimball, 2013; White, Nathan & Faller, 2015). In keeping with the broader literature of bureaucracies and policy enforcement, existing scholarship has explored the ways in which the administration of election law may change depending on the race, nationality and class of the prospective voter (White, Nathan & Faller, 2015). Other work evaluates the importance of election official political party affiliation on voter law decisions (Kropf, Vercellotti & Kimball, 2013). In contrast to felon disenfranchisement requirements, which appear steeped in indeterminacy and the ‘opinions’ of those whose duty it is to enforce them (Ewald, 2005), other boundaries of voter eligibility are well-​ understood and used to enact political outcomes (Tokaji, 2004; Kropf, Vercellotti & Kimball, 2013; White, Nathan & Faller, 2015). Despite the lack of reliable infor mation regarding felon disenfranchisement legislation, and lack of systematic and accurate voter rosters in many states, the surveillance that tracks felons and ensures that they are moved from prisons to parole, and probation to civil and court fee payment, to any additional period of disenfranchisement is systematically ubiquitous and onerous (Finn, 2009; Brayne, 2014; Warren, 2015). The surveillance that allows for the prosecution of illegal voters is only a part of the larger system—​and the documentation that results from this surveillance serves to justify the carceral regime specifically and neoliberal governmentality generally (Hetherington, 2011).

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How can one prognosticate the future, or speak to the possible results of dynamics that are still developing? Certainly, some political and social ramifications of existing systems of voter surveillance and felon disenfranchisement are already apparent: widespread gerrymandering (Tufekci, 2014), increased segregation of public goods on axes that replicate those of criminal justice involvement (Phillips & Deckard, 2016), and growing polarization of the electorate enmeshed in increasingly closed echo chambers . In the era of pre-​crime and mass dataveillance, marginalized communities are intentionally politically isolated, physically separated in public spaces and institutions, and the object of abject judgment and blame. While there is a temptation to warn of future ramifications should current systems of control persist, a more accurate warning is almost certainly one that speaks to the extent of already-​present conditions.

Conclusion Felon disenfranchisement laws, while extensive in their reach, may appear to be simply one facet of the larger carceral apparatus. With the incarcerated population of the United States at over two million, and another 6.6 million Americans under active supervision through probation or parole programs (Kaeble & Cowhig, 2018), the realities of mass incarceration are far-​reaching and deleterious. Systems of fines and fees ensure the impoverished are often one step away from reincarceration (Katzenstein & Waller, 2015), as criminal records make it difficult to attain employment (Pager, Western & Sugie, 2009), benefit from public resources (Sugie, 2012), rent appropriate housing (Sugie, 2012), and make other financial decisions that would lessen rates of recidivism. The experiences of the nearly three million US children of incarcerated parents ensure that consequences are not limited to a single generation but promise to be replicated over time (Turney, 2018). Not being able to vote may be just one more punishment (Altman, 2005)—​and not a comparatively onerous one at that. If felons could vote, though, they could vote against discrimination in employment. They could vote to be included in means-​tested social programs and have equal access to housing and, even if they lost, they would exist as entities in a democracy. Felon disenfranchisement means that these questions can be debated with convicted people as objects of governance rather than partners. In both theory and practice, felon disenfranchisement becomes the mechanism of rendering citizens subjects, effectively accomplishing civil death.

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Agamben (1998) argues that without the recognition of full citizenship and inclusion in the nation-​state, the human being becomes vulnerable to violence and exploitation—​living a ‘bare life’ instead of that of a counted person. This chapter builds on existing research (Delia Deckard, 2017) to posit a mechanism through which exclusion to the point of commodification can occur. The fundamental governmentality that animates these dynamics is one of pre-​crime. By forcing criminalized citizens far from membership in the national community, crime can be controlled as a behavior engaged in by alien others. This manner of crime control may be understood as characteristic of neoliberal governance broadly. References Agamben, G. (1998). Homo Sacer: Sovereign Power and Bare Life. Stanford, CA: Stanford University Press. Alexander, M. (2012). The New Jim Crow: Mass Incarceration in the Age of Colorblindness. New York, NY: The New Press. Altman, A. (2005). Democratic self-​d eter mination and the disenfranchisement of felons. Journal of Applied Philosophy 22 (3): 263–​73. Austin, R. (2004). The shame of it all: Stigma and the political disenfranchisement of formerly convicted and incarcerated persons. Columbia Human Rights Law Review 36: 173–​92. Aviram, H., Bragg, A. & Lewis, C. (2017). Felon disenfranchisement. Annual Review of Law and Social Science 13: 295–​311. Bahk, D. (2001). Excommunication and shunning: The effect on Korean churches in America as a social networking structure. Rutgers Journal of Law and Religion 3: 4. Banks, A.J. & Hicks, H.M. (2016). Fear and implicit racism: Whites’ support for voter ID laws. Political Psychology 37 (5): 641–​58. Beckman, L. (2009). The Frontiers of Democracy: the Right to Vote and its Limits. New York, NY: Springer. Behrens, A., Uggen, C. & Manza, J. (2003). Ballot manipulation and the ‘menace of negro domination’: Racial threat and felon disenfranchisement in the United States, 1850–​2002. American Journal of Sociology 109 (3): 559–​605. Bennett, C. (2015). Trends in voter surveillance in Western societies: Privacy intrusions and democratic implications. Surveillance & Society 13 (3/​4): 370–​84. Berman, A. (2015). How the 2000 election in Florida led to a new wave of voter disenfranchisement. The Nation (28 July).

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Berry, M.J. & Linoff, G.S. (2004). Data Mining Techniques: For Marketing, Sales, and Customer Relationship Management. New York: John Wiley & Sons. Brayne, S. (2014). Surveillance and system avoidance: Criminal justice contact and institutional attachment. American Sociological Review 79 (3): 367–​91. Cacho, L.M. (2012). Social Death: Racialized Rightlessness and the Criminalization of the Unprotected. New York, NY: New York University Press. Cammett, A. (2012). Shadow citizens: Felony disenfranchisement and the criminalization of debt. Penn State Law Review 117 (2): 349–​406. Cohn, C. (2006). Motives and methods: Using multi-​sited ethnography to study US national security discourses. Feminist Methodologies for International Relations, 91–​107. Delacourt, S. (2013). Shopping for Votes: How Politicians Choose Us and We Choose Them. Madeira Park: Douglas and McIntyre. Delia Deckard, N. (2017). Prison, coerced demand, and the importance of incarcerated bodies in late capitalism. Social Currents 4 (1): 3–​12. Dunning, T. (2011). Fighting and voting: Violent conflict and electoral politics. Journal of Conflict Resolution 55 (3): 327–​39. Ewald, A. (2002). Civil death: The ideology paradox of criminal disenfranchisement law in the United States. Wisconsin Law Review, 1045–​132. Ewald, A. (2005). A Crazy-​Quilt of Tiny Pieces: State and Local Administration of American Criminal Disenfranchisement Law (vol. 16). Washington, DC: The Sentencing Project. Ewald, A. & Rottinghaus, B.E. (2009). Criminal Disenfranchisement in an International Perspective. Cambridge, UK: Cambridge University Press. Finn, J.M. (2009). Capturing the Criminal Image: From Mug Shot to Surveillance Society. Minneapolis, MN: University of Minnesota Press. Fund, J.H. (2008). Stealing Elections: How Voter Fraud Threatens Our Democracy. New York, NY: Encounter Books. Gordon, J. (2019). When Data Crimes are Real Crimes: Voter Surveillance and the Cambridge Analytica Conflict. Victoria, BC: University of Victoria. Haney, L. (2004). Introduction: Gender, welfare, and states of punishment. Social Politics: International Studies in Gender, State & Society 11 (3): 333–​62. Hetherington, K. (2011). Guerrilla Auditors: The Politics of Transparency in Neoliberal Paraguay. Durham, NC: Duke University Press.

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Hier, S.P. (2003). Probing the surveillant assemblage: On the dialectics of surveillance practices as processes of social control. Surveillance & Society 1 (3): 399–​411. Kaeble, D. & Cowhig, M. (2018). Correctonal Populations in the United States, 2016. Washington, DC: US Department of Justice. Katzenstein, M.F. & Waller, M.R. (2015). Taxing the poor: Incarceration, poverty governance, and the seizure of family resources. Perspectives on Politics 13 (3): 638–​56. Keyssar, A. (2009). The Right to Vote: The Contested History of Democracy in the United States. New York, NY: Basic Books. Kropf, M., Vercellotti, T. & Kimball, D.C. (2013). Representative bureaucracy and partisanship: The implementation of election law. Public Administration Review 73 (2): 242–​52. Little, S.M. (2004). A woman of property: From being it to controlling it—​A bicentennial perspective on women and Ohio property law, 1803 to 2003. Hastings Women’s Law Journal 16: 177. Loader, I. & Sparks, R. (2002). Contemporary landscapes of crime, order and control: Governance, risk and globalization. In A. Liebling, S. Maruna, & L. McAra (eds.) The Oxford Handbook of Criminology (vol. 4) Oxford, UK: Oxford University Press (pp. 78–​101). Lyon, D. (2001). Surveillance Society: Monitoring Everyday Life. Buckingham, UK: Open University Press. Maldonado, S. (2005). Deadbeat or deadbroke: Redefining child support for poor fathers. University of California at Davis Law Review 39: 991. Mauer, M. (2004). Felon Disenfranchisement. [online] Available at: http://​ w ww.sentencingproject.org/​ d oc/​ p ublications/​ f d_​ fdpolicywhosetime.pdf. Miller, B.L. & Spillane, J. (2012). Civil death: An examination of ex-​ felon disenfranchisement and reintegration. Punishment and Society 14 (4): 402–​28. Minnite, L.C. (2007). The Politics of Voter Fraud. Washington, DC: Project Vote. Minnite, L.C. (2011). The Myth of Voter Fraud. Ithaca, NY: Cornell University Press. Monahan, T. (2008). Surveillance and inequality. Surveillance & Society 5 (3): 217–​26. Noble, S.U. (2018). Algorithms of Oppression: How Search Engines Reinforce Racism. New York, NY: New York University Press. O’Malley, P. (2004). Risk, Uncertainty and Government. London, UK: The Glasshouse Press.

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Pager, D., Wester n, B. & Sug ie, N. (2009). Sequencing disadvantage: Barriers to employment facing young black and white men with criminal records. The ANNALS of the American Academy of Political and Social Science 623 (1): 195–​213. Phillips, A.J. & Deckard, N. (2016). Felon disenfranchisement laws and the feedback loop of political exclusion: The case of Florida. Journal of African American Studies 20 (1): 1–​18. Riker, W.H. & Ordeshook, P. (1968). A theory of the calculus of voting. American Political Science Review 62 (1): 25–​42. Rocha, R.R. & Matsubayashi, T. (2014). The politics of race and voter ID laws in the states: The return of Jim Crow? Political Research Quarterly 67 (3): 666–​79. Ruda, G.B. (2003). Picture perfect: A critical analysis of the debate on the 2002 help America vote act. Fordham Urban Law Journal 31: 235. Schaub, M. & Morisi, D. (2020). Voter mobilization in the echo chamber: Broadband internet and the rise of populism in Europe. European Journal of Political Research 59 (4): 752–​73. Schultz, D. (2007). Less than fundamental: The myth of voter fraud and the coming of the second great disenfranchisement. William Mitchell Law Review 34: 483. Shapiro, A. (2001). The disenfranchised. The American Prospect (19 December). Shearing, C.D. & Johnston, L. (2013). Governing Security: Explorations of Policing and Justice. New York, NY: Routledge. Shineman, V. (2019). Restoring voting rights: Evidence that reversing felony disenfranchisement increases political efficacy. Policy Studies 41 (2–3): 1–​20. Sobel, R. & Ellis Smith, R. (2009). Voter-​ID laws discourage participation, particularly among minorities, and trigger a constitutional remedy in lost representation. PS: Political Science & Politics 42 (1): 107–​10. Sugie, N. F. (2012). Punishment and welfare: Paternal incarceration and families’ receipt of public assistance. Social Forces 90 (4): 1403–​27. Tanaka, T. (2001). The identity formation of the victim of ‘Shunning’. School Psychology International 22 (4): 463–​76. Taylor, A. & Sadowski, J. (2015). Digital red lining. Nation 300 24: 24–​7. The Sentencing Project. (2016). 6 Million Lost Voters: State-​Level Estimates of Felony Disenfranchisement, 2016. Washington, DC: The Sentencing Project.

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Tokaji, D.P. (2004). Early returns on election reform: Discretion, disenfranchisement, and the Help America Vote Act. George Washington Law Review 73: 1206. Tufekci, Z. (2014). Engineering the public: Big data, surveillance and computational politics. First Monday 19 (7). DOI: http://dx.doi. org/10.5210/fm.v19i7.4901 Turney, K. (2018). Adverse childhood experiences among children of incarcerated parents. Children and Youth Services Review 89: 218–​25. Turow, J., Hennessy, M. & Draper, N. (2015). The Tradeoff Fallacy: How Marketers Are Misrepresenting American Consumers and Opening Them Up to Exploitation. Philadelphia, PA: University of Pennsylvania. Uggen, C. & Manza, J. (2002). Democratic contraction? Political consequences of felon disenfranchisement in the United States. American Sociological Review 67 (6): 777–​803. Uggen, C., Larson, R. & Shannon, S. (2016). 6 Million Lost Voters: State-​ Level Estimates of Felony Disenfranchsiement 2016. Washington, DC: The Sentencing Project. Warren, I. (2015). Surveillance, criminal law and sovereignty. Surveillance & Society 13 (2): 300–​5. White, A.R., Nathan, N. & Faller, J.K. (2015). What do I need to vote? Bureaucratic discretion and discrimination by local election officials. American Political Science Review 109 (1): 128–​42. Wilson, D.C. & Brewer, P.R. (2013). The foundations of public opinion on voter ID laws: Political predispositions, racial resentment, and information effects. Public Opinion Quarterly 77 (4): 962–​84. Wilson, D.C., Brewer, P.R. & Rosenbluth, P.T. (2014). Racial imagery and support for voter ID laws. Race and Social Problems 6 (4): 365–​71. Zedner, L. (2007). Pre-crime and post-criminology? Theoretical Criminology 11 (2): 261–​81.

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Big Data, Cyber Security and Liberty Jin Ree Lee and Thomas J. Holt

Introduction The growth of digital technology has created opportunities for individuals to interact and share information in real-​time using any combination of text, image and video (Wall, 2001; Newman & Clarke, 2003; Holt & Bossler, 2016; Lee & Holt, 2020). There are now vast quantities of data generated from humans’ use of various technologies, providing both industry personnel and academic researchers with an alternative way to examine social phenomena (Silverman, 2013; Holt, 2017). In fact, there is now distinct terminology used to reference such data, commonly called ‘big data’, which is generally defined as voluminous datasets that cannot be ‘perceived, acquired, managed, and processed by traditional information technology and software/​ hardware tools within a tolerable time’ (Chen et al, 2014, p. 173). Big data is increasingly used by interested stakeholders to illustrate trends and patterns that confirm and/​or challenge wider assumptions (Laney, 2001; Khoury & Ioannidis, 2014; Wu, Zhu, Wu & Ding, 2014; Liu, Li, Li & Wu, 2016; Williams et al, 2017; Song, Song & Lee, 2018; Lee & Holt, 2020). Researchers across numerous disciplines examine big data sets to address various topics (see Sensmeier, 2015; Lee & Holt, 2020). Nursing scholars, for example, use big data to improve patient-​ clinician communications, as well as improve their awareness of

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emerging health issues within the wider population (Sensmeier, 2015). Real-​time access to patient information provides nurses with the ability to make optimal clinical decisions regardless of care setting, satisfying an integral part of the profession (Sensmeier, 2015). Similarly, criminologists and other social scientists use big data to assess offenders’ motivations, methods and target preferences on various computer-​mediated communications (CMC) platforms (D’Ovidio et al, 2009; Maimon et al, 2014; Song et al, 2018). Exploring these sources provide deeper insights at the individual and aggregate level to understand both offender perspectives and potential targets for victimization (Lee & Holt, 2020). In essence, big data allows interested stakeholders to make data-​driven predictions and better-​informed decisions that can result in more favorable outcomes and effective strategies (McAfee & Brynjolfsson, 2012). While analyses of big data have the ability to reveal various trends and patterns that can be explored to support and/​or challenge wider assumptions, the data on its own does not enable researchers to make any inferences (Smith, Bennett Moses & Chan, 2017; Song, Song & Lee, 2018; Lee & Holt, 2020). That is, big data does not assign any qualitative assessment or value to the observed relationships—​these meanings and interpretations are attributed by the interested stakeholders themselves upon examination of the results (see Song et al, 2018). The benefits of big data rests in users’ ability to consolidate a larger volume of data and validate the thoughts of participants, lending to better predictions (Williams et al, 2017; Lee & Holt, 2020). Despite its benefits, big data presents many challenges to both its participants and users. Furthermore, while its use is commonplace within certain disciplines (e.g. nursing, engineering and business), other fields have not yet actualized the potential and utility of big data (see Smith et al, 2017; Williams et al, 2017). This chapter will examine the benefits and concerns of big data, beginning with an introduction of big data and its defining characteristics. Then, we consider why and how big data is used by both industry and academic researchers. The chapter will conclude with a discussion on the cybersecurity risks and implications posed by big data.

Benefits and challenges of big data Numerous sectors have shown interest in the potential utility of big data to predict trends and inform decisions (boyd & Crawford, 2012;

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Lohr, 2012). Recognized for its wide scope and applicability, big data is generally characterized using the ‘3 Vs’: volume, velocity and variety (Liu et al, 2016). Volume denotes the large size of these data, specifically its ability to aggregate multiple data sets into a single file rather than its overall size. Velocity refers to the time it takes for these data to be generated. Variety underscores the diversity of these data sources, structures and applications (see Liu et al, 2016). In other words, big data is defined by its capacity, speed of collection, unique application and inability to be processed by traditional technologies (Wu, Zhu, Wu & Ding, 2014; Williams et al, 2017). Given the unconventional attributes of big data, a fundamental change in computing architecture and large-​scale data processing is required to maximize its full potential (Chen et al, 2014). Big data has altered the way many institutions engage in data collection, transitioning from traditional methods involving survey distribution and in-​person interviews to fast automated processes using information and communication technologies (ICT). There is now an emphasis on the use of digital sensors to measure individuals’ location, behavior, movement and temperature in various industrial equipment, motor vehicles, electrical meters and portable electronic devices (Lohr, 2012). Other common examples of big data sources include websites, search engines and social media platforms (Lohr, 2012). These outlets record users’ sentiments in real-​time using a combination of formats (e.g. text, images and videos), providing insight into users’ location, behavior, movement and thoughts. Big data has also changed the way data is conventionally processed and examined due to its capacity to involve real-​time data in large quantities (Liu et al, 2016). Such tasks require new techniques, tools and instruments, which can be costly depending on the institution’s size and level of available resources (Cheshire & Batty, 2012). The Obama Administration announced a $200 million investment to launch the ‘Big Data Research and Development Plan’ in March 2012, making it the second major scientific and technological development initiative since 1993 (Chen et al, 2014). Relatedly, the International Data Corporation (IDC) reported an increase in global spending and investment in big data analytics at a compound annual growth rate of 11.9 per cent with expected revenues upward of $210 billion by 2020 (Harvey, 2018). Regardless of how much capital one invests in big data, positive outcomes are derived from how the information is used. Even if institutions spend exorbitantly on big data approaches,

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limited benefits may result if they are unable to adequately harvest its potential or overcome its challenges (Harvey, 2018).

Benefits of big data One of the greatest benefits of big data lies in its ability to save users’ costs and time. First, big data expedites conventional data collection by automating the process. The somewhat passive nature of data collection allows researchers to produce exponentially more data for analysis in less time. The time saved from disengaging in traditional data collection approaches can be devoted to other avenues such as data analysis or research and development. The upfront costs of data collection can also be offset by better-​informed decisions and increased productivity in other areas, as unnecessary spending and misinformed investments are avoided (Harvey, 2018). Another benefit of big data is its ability to allow users to more precisely locate the area of need and identify solutions to address that particular inquiry. For instance, instead of spending time and resources exploring various avenues that may not be of concern, big data provides large amounts of information that can inform users on the specific areas that its customers and/​or respondents identify as needing attention. Given that big data processes large amounts of data, it has the ability to reveal various hidden patterns and correlations that may have been overlooked using traditional datasets. The ability to quickly identify this need and do so with more precision saves both time and cost—​as poor decisions can be more costly than acquiring and implementing big data analytics—​but more importantly, improves the quality of the outcome. In a business setting, this can lead to better customer acquisition and retention rates, whereas in a research setting, this can result in greater contributions to the field. Big data also provides detailed information in small analysis units. Small units of analysis (e.g. per-​hour basis, per minute basis) enable users to explore the causality of a phenomenon, avoiding ecological fallacies (Liu et al, 2016). Furthermore, longitudinal studies using big data are less time and cost intensive than traditional methods of conducting longitudinal analyses. For example, smartphone data collected at the individual level can contain units of analysis at the minute and/​or hour level, allowing users to examine a variety of hypotheses and explore questions using shorter intervals (Liu et al, 2016). These smaller units of analysis allow interested stakeholders to explore longitudinal designs where causal inferences can be explored, improving their decision-​making ability.

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Challenges with big data While the advantages of big data are wide-​ranging, its growth has produced many challenges that require precise solutions. In particular, analysts using big data must determine ways to obtain meaning and value from these datasets that have enormous scales and rapid development (Chen et al, 2014; Smith et al, 2017). This includes figuring out how to manage large quantities of unstructured data that require significant amounts of real-​time-​analysis. Additionally, big data analysts must collect information from a wide pool of sources in order to use for analysis (Chen et al, 2014; Williams et al, 2017). Multiple sources and/​or units of analysis are needed to corroborate the validity of data, which can be both a time-​consuming and challenging endeavor, especially if these sources are not readily available or known. Finally, all of this information must be stored in spaces that are large enough to process and hold such data. This may require the use of more advanced and/​or expensive hardware and software infrastructure. Another concerning aspect with big data is the increased risk of false conclusions and/​or discoveries (Lohr, 2012). Extracting meaningful information from large amounts of unstructured data can pose challenges to different actors and stakeholders. In particular, the challenge lies in both filtering and compressing raw data in a way that separates the useful variables from those of minimal interest (Labrinidis & Jagadish, 2012). Most big data will not be gathered in a format ready for analysis. The challenging task is to process information by drawing required information from its sources while expressing it in a form appropriate for analysis (Labrinidis & Jagadish, 2012). Given the density and voluminous nature of big data, an effective extraction process has to be done using an automated system. This process requires complex understanding of data structure and semantics (Labrinidis & Jagadish, 2012). Big data analyses are of limited utility if users are unable to comprehend the results. Similar to other data-​driven results and outcomes, one has to be knowledgeable enough to interpret the findings. Even if the results are interpreted correctly, big data can contain various errors if the findings were based on erroneous, biased and/​or incomplete data (Labrinidis & Jagadish, 2012). Another concern with big data is its authenticity and credibility during data collection (Liu et al, 2016). Since most of these datasets come from commercial businesses that were not established for scientific research purposes, there is room for these platforms to ignore scientific protocols for data collection that avoid biases and/​or other data issues (e.g. random sampling) (Loshin, 2012). Moreover, since

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these data were collected for commercial purposes, the algorithms behind the data processing may be unknown or hidden from public knowledge (Loshin, 2012). This gives platforms the ability to not only conceal their sampling method but also change it whenever they desire without users’ knowledge. Findings generated from data that had multiple competing algorithms can engender biased or misleading conclusions (Loshin, 2012; Liu et al, 2016). Relatedly, these entities are not required to conduct authenticity or validity checks. For instance, Twitter has no intrinsic motivation to track or erase automated accounts operated by machines since these accounts were set up to generate profit (Liu et al, 2016). Another example of inauthentic data collection is the Google Flu Trends Index. Despite widespread attention, scholars reported that Google often changes the algorithms to make the prediction unstable (Lazer et al, 2014). A comparison of the Google estimates and that of the United States Center for Disease Control and Prevention (CDC) illustrates that Google’s findings of doctor visits for influenza-​like conditions are more than twice those generated from the CDC (Lazer et al, 2014). It is important to note that the volume of big data—​regardless of the source—​should not be mistaken for it being a random and representative sample, nor should its massive quantity be interpreted as being high quality (boyd & Crawford, 2012; Cheshire & Batty, 2012). For instance, big data derived from mobile phones come from users who have contracts with service providers (Krings et al, 2009), summarily dismissing users who are not under contract with mobile service carriers. This makes the data unrepresentative of the general population of those who own phones. To generate conclusions about mobile phone users or their behaviors using such data would be biased and misleading as it fails to account for those who are unaffiliated with service providers.

Big data and industry Big data use among industry has grown rapidly over the past few years (McAfee & Brynjolfsson, 2012). Most corporations have implemented some sort of big data analytics to strengthen their company’s research and development, customer acquisition and retention, as well as overall agenda and direction (Harvey, 2018). One of the biggest reasons for industry adopting big data is its ability to better measure and evaluate business decisions by translating enormous amounts of information into consumable knowledge that improves performance and outcomes (McAfee & Brynjolfsson, 2012). McAfee and Brynjolfsson (2012)

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conducted structured interviews with executives at 330 public North American companies about their organizational and technology management practices, collecting performance data from their annual reports among other independent sources. The study revealed that the more companies characterized themselves as data-​driven, the better they performed on objective measures of financial and operational results. Specifically, companies in the top third of their industry in data-​driven decision-​making were 5 per cent more productive and 6 per cent more profitable than their competitors. This difference remained significant even after controlling for factors such as labor, capital, purchased services and traditional information technology (IT) investment (McAfee & Brynjolfsson, 2012). Giant retail corporations like Walmart also invest heavily in big data analytics by exploring sales, pricing, demographic and weather data to guide product selection at stores, including determining the timing of price markdowns. Similarly, shipping and delivery companies like United Parcel Service (UPS) examine large volumes of data on truck delivery times and traffic patterns to improve carrier routing, while online dating services such as Match.com use big data to examine their listings of personal characteristics, reactions and communications to improve the algorithms used to pair individuals (Lohr, 2012). Regardless of the company’s specific goals or objectives, big data provides industry with the ability to both better inform decision-​making and evaluate outcomes by converting large amounts of information into easily consumable knowledge that provide direction and guidance (McAfee & Brynjolfsson, 2012). Even public service organizations use big data analytics to achieve their goals. Law enforcement, for instance, have started to use computerized mapping and analyses of historical arrest patterns, paydays, sporting events, rainfall and holidays to predict crime hotspots (Lohr, 2012). The use of big data, machine learning and predictive analytics to understand and prevent crime has given law enforcement the predictive ability to position police resources in response to anticipated dangers (Clark, 2017). In fact, there is substantial value in operationalizing big data and data mining analyses to combat modern crime problems (Chan & Moses, 2017). For instance, when previous arrest records are examined alongside real-​time internet of things (IoT) data, such as censored cameras constructed to recognize gunshots, it becomes easier for law enforcement to diagnose problem locations and understand the conditions in which crimes flourish (Clark, 2017). By applying predictive analytics and machine learning to large datasets, police departments are able to improve their ability to forecast both

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where and when violent crimes will emerge and ensure that they have the adequate resources in place to prevent such behaviors from occurring (Clark, 2017).

Big data and criminological inquiry The abundance of big data increasingly influences the work of criminologists who seek additional data points to understand social phenomena (Chan & Moses, 2017; DeLisi, 2018; Hannah-​Moffat, 2018; Lynch, 2018). Big data provides a novel opportunity for criminologists to study unique artifacts of online and offline life and how they may be correlated with crime and victimization. A recent meta-​analysis of studies utilizing big data to examine environmental criminology issues found 84 studies involving big data analysis (Snaphaan & Hardyns, 2019). The majority of these studies utilized the US or UK as their country of origin for data, with volunteered data or those using user-​generated content such as Twitter (Snaphaan & Hardyns, 2019). Researchers were also more likely to combine big data sets with other data points, such as crime statistics for a given place (Snaphaan & Hardyns, 2019). One of the more prominent scholars utilizing big data, Matthew Williams, published multiple pieces using Twitter data in experimental ways to test criminological theories. For instance, Williams, Burnap and Sloan (2017) utilized data collected from Twitter posts regarding the presence of neighborhood disorder conditions within a physical location. When these posts were compared to actual reported crimes in a physical location, the authors found that disorder related posts were positively correlated with forms of physical crime in otherwise low-​crime areas. There was no relationship observed in high-​crime areas, suggesting that there may be a sensitivity issue at play. Residents in low-​crime areas may be more likely to both use social media and be inclined to discuss the presence of disorder issues generally (Williams et al, 2017). Similarly, Williams and Burnap (2016) utilized Twitter posts in the UK to examine the dissemination and spread of online hate messages in the wake of a physical terror attack in 2013. The authors applied machine learning and natural language processing to classify content and found that Twitter users associated with right-​wing political groups were more likely to be the point of origination for racial and religious-​based vitriolic posts. There was also a relatively short lifespan of hate-​based online posting in the wake of the physical event, and they were relatively self-​contained among networks of actors who actively sought out such content.

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These examples highlight the potential application of social media data in conjunction with other data sets. There are many other online data sources that could be utilized for scientific research. For one, web scraping tools that collect posts across various online communications platforms, including internet relay chat (IRC) forums, blogs and social networking sites, could extract large data sets with massive user populations for analysis (Quinn & Forsyth, 2005; Holt, 2010; Maratea, 2011). A number of computer scientists have started to practice such techniques to assess hacker behaviors and model online communications (see Benjamin, Samtani & Chen, 2016; Holt & Bossler, 2016). In fact, some platforms exist solely to facilitate crime, such as dark web illicit markets that sell personal information (e.g. Franklin et al, 2007; Holt & Lampke, 2010; Hutchings & Holt, 2015; Holt & Lee, 2020), hacking tools (Holt, 2013; Dupont, Côté, Boutin & Fernandez, 2017; Liggett, Lee, Roddy & Wallin, 2019), drugs (e.g. Barratt, 2012; Décary-​Hétu & Quessy-​Dore, 2017; Liggett et al, 2019) and sexual services (Kosloski, Bontrager-​Ryon & Roe-​ Sepowitz, 2017; Horswill & Weitzer, 2018; Liggett et al, 2019). These sources provide insights at both the individual and aggregate level to understand offender perspectives as well as potential targets for victimization (Chen, Mao & Liu, 2014; Clark, 2017; Williams, Burnap & Sloan, 2017). Although CMCs provide an immediate and obvious source of data for research, there are a number of other sources that may be employed to better understand social phenomena, including various hidden forms of cybercrime. For instance, forum data from underground markets can be used to explore malicious software attacks, which are difficult to assess through traditional survey metrics, as the symptoms of infection may go unrecognized by the end user (Maimon et al, 2013; Holt & Bossler, 2016). Researchers also utilize both qualitative and quantitative methods to further their understanding of social phenomena using information across various websites. Websites include a range of content, such as social media feeds like Facebook and Twitter, as well as blogs and simple text-​based pages. The content available on these platforms provides the thoughts of individuals in their own words through text, images and video, as well as links to other groups that share similar interests (Hine, 2005). Such content can be explored to better understand perceptions of and attitudes toward various phenomena. For instance, researchers have utilized linguistic analysis methods to identify keywords in large samples of posts made in far-​r ight extremist group forums to assess the presence of violent words and phrases (Anahita, 2006; Wong, Frank & Allsup, 2015; Figea,

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Kaati & Scrivens, 2016; Baumgarten, 2017; Cohen, Holt, Chermak & Freilich, 2018). Social scientists across numerous disciplines have also examined big data from dating sites and online personal advertisements to understand the ways in which individuals solicit others for both traditional romantic entanglements as well as more deviant sexual encounters (Tewksbury, 2003; Grov, 2004; Frederick & Perrone, 2014). For instance, a number of studies explored the phenomenon of bugchasing, where HIV negative individuals actively seek out sex with HIV positive partners for the purposes of becoming infected (Grov, 2004; Tewksbury, 2003, 2006). Researchers applied qualitative analysis to ads posted on dating sites and forums dedicated to this behavior, finding that individuals actively pursuing HIV infection employed different languages to construct their ads in comparison to those who were simply seeking sexual partners. Limited studies have also explored big data using blogs and social networking sites. Blogs function as an electronic diary that document individuals’ thoughts, feelings and experiences through user-​generated text, video and images. Many blog sites allow users to make their layout as a single web page, although social networking sites like Facebook increasingly fill the same purpose by providing users with the ability to document their thoughts and feelings in reverse chronological order (Hookway, 2008). To that end, researchers utilized data generated from Facebook and related social media sources to examine the prevalence of street gangs in these spaces, and the nature of their posted communications (Morselli & Décary-​Hétu, 2010; Womer & Bunker, 2010; Décary-​Hétu & Morselli, 2011). For example, Décary-​Hétu and Morselli (2011) searched Facebook and Twitter to quantify how many known gang names were used in accounts relative to specific geographic areas in Canada. Others conducted semantic analyses of posted content to assess the presence of outward symbols of gang membership like colors or music, as well as the presence of bragging and threatening content (Morselli & Décary-​Hétu, 2010; Wormer & Bunker, 2010).

Cybersecurity risks and implications of big data There are a variety of risks that accompany big data use. One such concern involves online privacy and ownership of personal content, which has led to extensive media coverage (Wigan & Clarke, 2013; Williams et al, 2017). Even after excluding data that are not made publicly available for mass consumption, billions of data points are

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shared and disseminated publicly by individuals every day. There are also smartphone applications that automatically produce and disseminate data to third-​party databases, such as sleeping patterns, fitness reports and dietary statistics. Although companies may give users the option to delete their data or profiles, such data are still owned and stored within companies’ databases and records. In fact, data companies such as Google, Facebook and Twitter use and purchase data warehouses to store all of their data and information. While user agreements are provided to individuals before a platform or service is initiated, users are often uninformed of the fact that they voluntarily give companies their data at virtually no cost (Wigan & Clarke, 2013). Further, users are often unfamiliar with who collects their data and why it is collected, what it is used for, when it is sold to third parties, and the identity of these third parties. The details of such practices are often explained in user agreements, though most users neither read nor understand these documents. As a result, individuals may become involved as subjects in research studies by virtue of using social media without necessarily giving consent in the same way as traditional research projects using surveys or interview-​based methods. Another challenge associated with big data is the possibility for misinterpretation. Conclusions drawn from big data analyses are only as valid as the source it is comes from. For instance, Google Flu Trends—​a data source which calculates disease prevalence on the basis of Internet searches for symptoms—​highly overestimated the extent of the flu outbreak (Pentecost, 2015). In fact, people searched for flu-​like symptoms without personally having been diagnosed with the disease (Pentecost, 2015). Thus, the value in big data lies not in the data itself but in how stakeholders choose to use and operationalize these data (Song, Song & Lee, 2018). A failure to properly understand the strengths of big data and the patterns it identifies may lead to erroneous conclusions and findings (Wigan & Clarke, 2013). Lastly, given the novelty of big data, users may not recognize the ethical issues evident when analyzing data and developing results. Users working with online communities that require individuals to either create an account or post in order to maintain their registration begs the question as to whether the user must disclose their identity to the community (see Hine, 2005; Rutter & Smith, 2005; Holt, 2010). The fact that individuals’ identifiable information could be aggregated to document an individual’s offline identity makes it difficult for them to use quotes and reference user content directly without increasing the risk of harm to the users. Ethics concerns like these need to be considered and handled by the research community (Silverman, 2013).

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Data scientists may not, however, consider these issues in advance of data collection or determine best practices to minimize risk of attribution. The lack of consensus around standards for online data collection only exacerbates these issues. For instance, social networking profiles may be publicly accessible and indexed via search engines. Some researchers would suggest they can be treated as open source with no need for human subjects’ considerations from an ethical standpoint (Holt & Bossler, 2016). Individual users who set their profile to private in order to limit outsider access may, however, wind up in broader data sets due to profile-​based connections. As a result, there is a clear need for increased discussions of the ethics constraints required to protect people, and greater awareness of the need for human subjects’ protections across all academic disciplines.

Conclusion As big data continues to gain prominence, new cybersecurity threats involving data manipulation, data loss and unauthorized access of devices will surface as pressing inquiries that require both immediate and long-​term solutions. One way to manage these cybersecurity risks is through legal institutions enforcing more comprehensive cybercrime laws. In order for legal institutions to be effective, however, they need to be able to understand and match the continuously changing dynamic of digital technology (Dupont, 2013). Previous research has demonstrated that more resources are needed by law enforcement, government officials and policymakers to ensure that they are knowledgeable of the growing cybersecurity threats posed by cybercrime (Holt & Bossler, 2012; Bossler & Holt, 2012, 2013; Dupont, 2013; Koziarski & Lee, 2020). Reducing legal loopholes and developing effective strategies to apprehend online offenders are also beneficial approaches that legal institutions must adopt to address emerging cybersecurity threats (Dupont, 2013; Dolly, 2018; Lee & Holt, 2020). Another way to enhance cybersecurity is to give online users more power and control over their own data, while minimizing technology companies’ (e.g. social media service providers) influence and authority. Although user agreements that outline data rights are often provided before a service or platform is utilized, users are generally unknowledgeable of these details because of the obscure and complicated way they are worded or presented (Wigan & Clarke, 2013). Users often come to the realization that their data is collected and used for miscellaneous purposes after the fact, raising concerns as to whether users truly consented to their data being used. In 2019, Google

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was fined $57 million for failing to be transparent in obtaining users’ valid consent for the personalization of its ads—​Google had violated the European Union’s General Data Protection Regulation (GDPR) policy that requires users to consent to each use of their data (Hill, 2019). In June 2018, California passed a similar law that provides data privacy rights to online users (Hill, 2019). The law was constructed so that users can request their data be deleted or they could open civil action if they believed their data privacy rights were violated. This law, however, does not require explicit consent from users, giving companies space to exploit users’ data (Hill, 2019). Relatedly, a recent controversy regarding big data and users’ privacy surfaced as a result of the novel coronavirus (COVID-​19) pandemic and contact-​tracing apps. Various governments worldwide began developing contact-​tracing apps in order to monitor its citizens’ social contact with others to reduce COVID-​19 infection rates, a highly contagious virus that typically spreads through respiratory droplets from coughing, sneezing or talking (Anscombe, 2020; FDA, 2020). More than 30 countries have developed, or are in the stages of releasing, a contact-​tracing app to limit the spread of COVID-​19 within their national borders (Anscombe, 2020). The general purpose of a contact-​ tracing app is to alert people when they come into close contact with others who reported contracting an infectious virus or are showing symptoms of that illness. These notifications allow individuals to exercise safety measures (e.g. self-​isolation) to limit the spread of the disease. In fact, contact-​tracing apps have proven effective in reducing other highly contagious diseases such as tuberculosis and measles (Anscombe, 2020). The implementation of contact-​tracing apps, however, has been met with resistance in certain countries because of app developers’ stance on data rights and user privacy (Anscombe, 2020). A privacy issue is generated if the identity of the user who reported positive can be recognized (Anscombe, 2020). Further, contact-​tracing apps collect sensitive information that can be leaked or misused, such as users’ location, name, sex, date of birth, phone number, home address and passport or social security number. To that end, the Norwegian government was recently ordered to delete all of its collected data and suspend use of its contact-​tracing app because of a Norwegian Data Protection Authority ruling (Anscombe, 2020). Relatedly, the UK government stated that it was halting further development of its contact-​tracing app (Anscombe, 2020). Most contact-​tracing apps are government-​sponsored and tend to employ either a global positioning system (GPS) or Bluetooth system

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to track users’ location and physical contact with others (Anscombe, 2020). The GPS system utilizes satellite-​based radio-​navigation to locate users, whereas Bluetooth systems allow devices to exchange ‘handshakes’ rather than track the physical location of users, which provides users with a higher degree of data privacy (Anscombe, 2020). To clarify, when an individual running a Bluetooth-​enabled contact-​ tracing app comes into contact with another person operating the same app, unique keys are exchanged (e.g. handshake) (Anscombe, 2020). These keys are unique to the device running the app and are formed on a time basis (Anscombe, 2020). When users indicate they are infected with the disease, all their generated keys are added to a cloud system. All devices operating the app will collect keys to determine if there is a match with the keys that confirmed positive. If there is a match, then those users are alerted that they have been in contact with a user who reported infectious symptoms (Anscombe, 2020). Recent studies from MIT Technology Review found that contact-​ tracing apps using Bluetooth systems might not be as accurate as initially conceived (see O’Neill, 2020). For instance, if a mobile phone running the app is standing up vertically (e.g. portrait) rather than horizontally (e.g. landscape), this may affect the signal and make it appear that an individual is farther away in distance (Anscombe, 2020). Research also found inaccurate distances might be generated if Bluetooth signals are transmitted through bodies (e.g. people are standing back to back) (O’Neill, 2020). Similar to other big data issues, it appears that there are no easy solutions that satisfy both the individual user and the app developer (Anscombe, 2020). The challenges facing government task forces are in identifying what data is necessary because of its potential for future use, what users are willing to share for contact-​tracing purposes, and the difficulties in accurately assessing users’ distance and location (Anscombe, 2020). The uncertainty of how long these data will be stored for, what will happen to these data afterwards, and who has access to these data are all elements that concern users’ rights to data privacy. The overarching challenge is in generating an app that will both work effectively and provide users with acceptable data rights and privacy. One solution would be to ensure app developers only collect the necessary data, state the reasons and objectives for data collection, and clearly express the duration of data storage and who has access to it (Anscombe, 2020). All collected data should be deleted once the objectives of the app have been achieved and is no longer needed. The issues observed with contact tracing applications and public health point to the need for strategies that give users’ power over their

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own data. For instance, various individuals have proposed that users should become ‘data shareholders’ that can sell their data to companies for monetary compensation (Hill, 2019). While innovative, this approach would disproportionately favor company profits as each user would receive an insignificant amount of monetary payment for their data—​it is estimated that Facebook’s two billion monthly users would each receive only about $9 annually if the company proportionally distributed its profits using this data shareholders framework (Hill, 2019). Others have suggested a ‘privacy as paid service’ approach where companies like Facebook, Twitter and Google offer a premium service that charge for a privacy-​friendly, ad-​free user experience (Hill, 2019). Both of the aforementioned propositions detract from the primary concern of whether it is ethical and appropriate for companies to have significant control and authority over their users’ personal data. Minimizing companies’ control over users’ data and allowing users to make informed personal decisions with their own data would reduce the amount of unauthorized access companies have to users’ data. Cybersecurity threats can also be addressed by increasing online target hardening and digital guardianship levels. Since data is the product under attack, coming up with innovative ways to guard it from unauthorized access and manipulation would benefit both industry and individuals’ cybersecurity efforts. For example, creating a faster detection process by increasing the noise that hacking and malware attacks make, as well as developing devices that have stricter authentication processes would increase online target hardening and digital guardianship, making it more difficult for individuals to offend and avoid apprehension (Dolly, 2018). Another concern associated with big data is its susceptibility to error, bias and misguided predictions. This is especially problematic when big data is used as a tool to predict crime patterns involving different people groups and geolocations. Several private companies and criminal justice agencies appear to actively use predictions generated from crime related research to create profiles and descriptions of various people groups (see Barocas & Selbst, 2016; Smith, Bennett Moses & Chan, 2017; Bennett Moses & Chan, 2018). Civil liberty advocates suggest that such big data driven procedures, especially those deployed by criminal justice actors, reflect pre-​existing prejudices against certain historically disenfranchised racial and socio-​economic groups (Barocas & Selbst, 2016; Smith et al, 2017; Bennett Moses & Chan, 2018). In fact, there is evidence that facial recognition software used for identification and targeting by law enforcement are subject to racial biases against minority group members (e.g. Allen & Gillis, 2020). As

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a result, widespread use of such tools could lead to increased risks of false accusations against racial minorities. Similarly, misguided crime predictions from big data analyses may suggest racial minority groups living in visibly disordered neighborhoods are more criminogenic or delinquent. Such evidence could be used to argue for increased police attention in specific communities, potentially leading officers to engage in unreasonable search and seizure procedures (e.g. pre-​emptive and proactive policing strategies) on the basis of justification from data patterns. For example, a recent study by Williams and colleagues (2017) examined the relationship between crime and disorder related Twitter posts and actual police crime rates. Their study intended to determine whether big data derived from open source communications can be used to predict crime patterns across various neighborhoods in London (see also Asur & Huberman, 2010; Sakai et al, 2010; Tumasjan et al, 2010). The study found that the frequency of Twitter posts was positively associated with numerous criminal acts, including burglary in a dwelling, criminal damage, violence against the person, and theft from shops. In addition, Twitter mentions of perceived neighborhood disorder1 were positively associated with criminal damage, theft from a motor vehicle, possession of drugs, and violence in low-​crime areas. In contrast, Twitter mentions of disorder were negatively correlated with burglary in a dwelling, burglary in a business property and theft of a motor vehicle in high-​crime areas (Williams et al, 2017). The authors concluded that their analysis demonstrated the effectiveness of using social media big data to estimate various offline crime patterns (see also Bendler et al, 2014; Malleson & Andresen, 2015). Specifically, the study found social media data to be a valuable source of information on the crime problem, particularly using textual content on social media as a measure of broken windows. At the same time, the authors highlight numerous limitations with its ability to accurately predict crime (see Williams et al, 2017). For one, social media posts may be fabricated, based in sarcasm, or generated from unsubstantiated rumors, resulting in inaccurate depictions of actual crime and disorder in a given area and time (Williams et al, 2017). Furthermore, social media posts may contain numerous reporting biases, including individuals’ varying perceptions of neighborhood disorder; knowledge and use of social networking sites (SNS); and willingness to post about crime and disorder related issues on social media (see Sloan et al, 2015; Williams et al, 2017). These issues seem inherently important, and possibly of greater impact than the authors’ overall claims of the potential use of social

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media data for criminological inquiry. In particular, variations in social media posting and general technology use by race, class and geographic groups could drive massive biases in big data sources. There is evidence of clear Internet deserts in urban environments due to income inequality, as well as in rural areas due to limited access to broadband equipment and economic issues (see Reisinger, 2016; Anderson, 2018). As a result, individuals living in these areas may not be accurately reflected in big data sets, creating gaps in the reliability and generalizability of the findings. There is, however, a misconception that big data analytics are more objective in orientation and less susceptible to subjective biases, errors and corruption (Barocas & Selbst, 2016; Smith et al, 2017). Instead, big data is only as reliable as the information that it is drawn from. Researchers, policymakers and practitioners must also be careful not to skew their analyses in favor of predictive models that are more accessible (Bennett Moses & Chan, 2018). To the extent that it is possible, triangulation of data should be employed to ensure that accurate predictions are made and limitations in each source are clearly understood and elaborated (Williams et al, 2017). Researchers must also take great care to avoid making any policy implications that would directly impact the civil liberties of the populations whose data are used for analyses and/​or prognostications. The nature of data collected for big data analyses can come from sources that the average person may not realize or want to share with researchers or government agencies. The fact that social media sites like Facebook can meta-​tag users for the purposes of targeted political advertising with no transparency as to the nature of the entity paying for the ad represents an excellent encapsulation of concerns over the use of big data. Not only were users unaware of these features until after the 2016 elections in the United States but also that they had participated in political and industry funded research projects using their information. This is just the tip of the iceberg in terms of the potential for misuse of data, to say nothing of the potential ways that individual decisions may have been skewed or steered by others for political or economic gain. Should similar strategies be used to track and trace immigrant groups to identify individuals who may have unlawfully entered a country, or worse, then there are clear potential legal and civil rights infringement issues that must be considered. Despite the aforementioned challenges and limitations of big data, it is a growing phenomenon that will continue to expand its reach in both research and industry. As a result, it is imperative that we identify and implement effective solutions for many of the ethical and cybersecurity

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concerns associated with big data usage. Progressing in this way will not only enhance the field of data science but also improve the quality of findings in research and decision-​making in industry moving forward. Note 1

Williams et al (2017) used broken windows theory as its guiding theoretical framework—​the theory argues that visible signs of neighborhood disorder are causally linked to crime (Wilson & Kelling, 1982).

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Liu, J., Li, J., Li, W. & Wu, J. (2016). Rethinking big data: A review on the data quality and usage issues. ISPRS Journal of Photogrammetry and Remote Sensing 115: 134–​42. Lohr, S. (2012). The Age of Big Data. [online] Available at: https://​ www.nytimes.com/​2012/​02/​12/​sunday-​review/​big-​datas-​impact-​ in-​the-​world.html. Loshin, D. (2012). Market and business drivers for big data analytics. DataInformed. [online] Available at: http://​data-​informed. com/​ market-​and-​business-​driversfor-​big-​data-​analytics/​. Lynch, J. (2018). Not even our own facts: Criminology in the era of big data. Criminology 56 (3): 437–​54. Maimon, D., Kamerdze, A., Cukier, M. & Sobesto, B. (2013). Daily trends and origin of computer-​focused crimes against a large university computer network. British Journal of Criminology 53: 319–​43. Maimon, D., Alper, M., Sobesto, B. & Cukier, M. (2014). Restrictive deterrent effects of a warning banner in an attacked computer system. Criminology 52 (1): 33–​59. Malleson, N. & Andresen, M. (2015). The impact of using social media data in crime rate calculations: Shifting hot spots and changing spatial patterns. Cartography and Geographic Information Science 42: 112–​21. Maratea R. (2011). Screwing the pooch: Legitimizing accounts in a zoophilia on-​line community. Deviant Behavior 32 (10): 918–​43. McAfee, A., Brynjolfsson, E., Davenport, T.H., Patil, D.J. & Barton, D. (2012). Big data: The management revolution. Harvard Business Review 90 (10): 60–​8. Morselli, C. & Décary-​Hétu, D. (2010). Crime Facilitation Purposes of Social Networking Sites: A Review and Analysis of the ‘Cyberbanging’ Phenomenon. Sécurité publique Canada. Newman, G. & Clarke, R. (2003). Superhighway Robbery: Preventing E-​commerce Crime. Cullompton, UK: Willan. O’Neill, P.H. (2020). Bluetooth Contact Tracing Needs Bigger, Better Data. [online] Available at: https://w ​ ww.technologyreview.com/​2020/​04/​ 22/​1000353/​bluetooth-​contact-​tracing-​needs-​bigger-​better-​data/​. Pentecost, M.J. (2015). Big data. Journal of the American College of Radiology 12 (2): 129. Quinn, J.F. & Forsyth, C.J. (2005). Describing sexual behavior in the era of the Internet: Typology for empirical research. Deviant Behavior 26: 191–​207. Reisinger, D. (2016). Four in ten Detroit residents lack broadband Internet access. Fortune [online] Available at: https://​fortune.com/​ 2016/​05/​23/​detroit-​broadband-​access/​.

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Rutter, J. & Smith, G.W. (2005). Ethnographic presence in a nebulous setting. Virtual Methods: Issues in Social Research on the Internet:. 81–​92. Sakai, T., Okazaki, M. & Matsuo, Y. (2010). Earthquake shakes Twitter users: Real-​time event detection by social sensors. Proceedings of the 19th International Conference on World Wide Web. New York, NY: Association for Computing Machinery Press. Sensmeier, J. (2015). Big data and the future of nursing knowledge. Nursing Management 46 (4): 22–​7. Silverman, D. (2013). Interpreting Qualitative Data: Methods for Analyzing Talk, Text, and Interaction (4th ed.). Thousand Oaks, CA: Sage Publications. Sloan, L., Morgan, J., Burnap, P. & Williams, M.L. (2015). Who Tweets? Deriving the demographic characteristics of age, occupation and social class from Twitter user meta-​data. PLoS One. DOI: 10.1371/​ journal.pone.0115545. Smith, G.J.D., Bennett Moses, L. & Chan, J. (2017). The challenges of doing criminology in the Big Data era: Towards a digital and data-​ driven approach. British Journal of Criminology 57: 259–​74. Snaphaan, T. & Hardyns, W. (2019). Environmental criminology in the big data era. European Journal of Criminology 1–​22. Song, J., Song, T.M. & Lee, J.R. (2018). Stay alert: Forecasting the risks of sexting in Korea using social big data. Computers in Human Behavior 81: 294–​302. Tewksbury, R. (2003). Bareback sex and the quest for HIV: Assessing the relationship in Internet personal advertisements of men who have sex with men. Deviant Behavior 24: 467–​82. Tewksbury, R. (2006). ‘Click here for HIV’: An analysis of internet-​ based bug chasers and bug givers. Deviant Behavior 27: 379–​95. Tumasjan, A., Sprenger, T., Sandner, P.G. & Welpe, I.M. (2010). Predicting elections with Twitter: What 140 chatacters reveal about political sentiments. Proceedings of 4th ICWSM. AAAI Press, 178–​85. Wall, D.S. (2001). Cybercrimes and the Internet. In D.S. Wall (ed.), Crime and the Internet. New York, NY: Routledge (pp. 1–​17). Wigan, M.R. & Clarke, R. (2013). Big data’s big unintended consequences. Computer 46 (6): 46–​53. Williams, M.L. & Burnap, P. (2016). Cyberhate on social media in the aftermath of Woolwich: A case study in computational criminology and big data. British Journal of Criminology 56 (2): 211–​38. Williams, M.L., Burnap, P. & Sloan, L. (2017). Crime sensing with Big Data: The affordances and limitations of using open-​source communications to estimate crime patterns. British Journal of Criminology 57: 320–​40.

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Wilson, J.Q. & Kelling, G.L. (1982). The police and neighborhood safety: Broken windows. Atlantic Monthly 127: 29–​38. Womer, S. & Bunker, R.J. (2010). Sureños gangs and Mexican cartel use of social networking sites. Small Wars & Insurgencies 21 (1): 81–​94. Wong, M.A., Frank, R. & Allsup, R. (2015). The supremacy of online white supremacists: An analysis of online discussions by white supremacists. Information & Communications Technology Law 24 (1): 41–​73. Wu, X., Zhu, X., Wu, G. Q. & Ding, W. (2014). Data mining with big data. IEEE Transactions on Knowledge and Data Engineering 26 (1): 97–​107.

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Drone Justice: Kill, Surveil, Govern Birgit Schippers

Introduction In October 2013, Rafiq ur Rehman and two of his children, Zubair and Nabila, traveled from North Waziristan, in the Federally Administered Tribal Areas (FATA) along Pakistan’s border region with Afghanistan, to Washington. They were invited to give a witness account to the United States Congress, recalling their experience of a drone attack. On the day of the attack, on October 24, 2012, Rafiq’s mother, Mamana Bibi, gathered okra with her grandchildren Zubair and Nabila. Mamana was killed and both children were injured (Amnesty International, 2013). The meeting in Washington was attended by just five members of Congress. Rafiq’s family lawyer was denied a visa for the United States and could not accompany the family on their journey (McVeigh, 2013). The experience of ‘living under drones’ (Stanford Clinic and NYU Clinic, 2012), which Rafiq and his family were subjected to, exemplifies the entanglement of the geopolitics of the war on terror with drone technology and drone strikes, and with a dispensation of justice that proceeds via a ‘scopic regime’,1 which identifies drone victims as terrorist targets, and thus as killable. Drones fascinate. They offer a visual spectacle, a ‘drone-​o-​rama’ (Kaplan, 2017) of seemingly untouchable power that has captured the public imagination through movies such as Enemy of the State (Scott, 1998) and Eye in the Sky (Hood, 2015). Although drones tend to be associated with military deployments in the battle spaces of the

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Middle East, studying them exclusively through the lens of a military ‘Gorgon stare’ (Holland Michel, 2019), as the material embodiment of the all-​seeing and lethal eye of a military object, misses the wide-​ ranging and versatile usage and effects of drone technology, which, as I demonstrate in this chapter, ranges from the kill capacity that works through a database of terrorist suspects—​the disposition matrix—​ (Gettinger, 2015), to the biopolitical management of life during the COVID pandemic. My point of departure is Derek Gregory’s (2014) call that we should not be unduly preoccupied with a technical object but attend instead to a wider ‘matrix of military violence’ generated by the drone. As I argue, this attention must extend to the militarized practices of surveillance and governmentality that seep into the realm of domestic life. This chapter presents drones as a central element in the contemporary techno-​political assemblage of global violence, which proceeds via killing, surveillance and the formation and government of conduct. I argue that drones materialize and visualize the contemporary techno-​ juridical matrix of global violence and of justice as spectacle, while their performative qualities generate a new discourse of justice as violence. They portend to project global ‘power without vulnerability’ that extends into the future by seeking to foreclose a justice-​to-​come, generating structures of unequal risk distribution, which engage in the networked construction of digital subjects as killable. I theorize this quality with reference to recent work in posthumanism and selected poststructuralist concepts, which foreground human ‘entanglement’ with autonomous and intelligent systems; and which excavate the ontological, ethical and political effects of this entanglement. Furthermore, developing Grégoire Chamayou’s (2015) claim regarding the lack of clarity with respect to the ontological, ethical and legal-​ strategic quality of drones, I argue that such attention opens up a wider conversation about conceptions and practices of justice generated by drone technology and drone strikes. The rapid proliferation of drone usage across the spectrum of domestic and international politics, and its deployment as a tool of governance in contested spaces scrambles and rescripts the always porous boundaries between the domestic and the international; between the private and the public; between territoriality and extra-​territoriality; and between lawfulness and the extrajudicial; between military and policing, between time and space, between surveillance and killing. The chapter is divided into four parts. I begin with a brief history of drone development and drone technology (section one), which locates drones within a wider context of aviation, aerial surveillance

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and warfare, and remote killing. Section two theorizes the role of drone technology and drone strikes in the contemporary re-​ordering of global power. Drawing on lessons from the 9/​11 wars, this section presents drones as a central tool in the emerging techno-​political assemblage of global violence, which scrambles existing understandings of international law, space and time. The latter aspect points towards the development of anticipatory conceptions of justice that extend from the global to the domestic. I develop this point in section three, where I address the role of drone strikes in a biopolitical regime that proceeds via pattern-​of-​life analyses in the war on terror and encroaches into the sphere of domestic life of democratic and non-​democratic states alike. The fourth section attends to recent deployments of drones in the fight against COVID-​19, and it considers the biopolitical effects of drones in the generation of conduct. I conclude with a brief reflection on practices of resistance and counter-​conduct that envisage new ways of thinking about justice in the age of drones.

A short history of drones The term ‘drone’ typically denotes remotely controlled, unmanned aerial vehicles (UAVs), also referred to as ‘unmanned aerial systems’, or UAS (see Kaag and Kreps, 2014). Even though much of the public and scholarly attention has focused on weaponized drones that are deployed in the battle spaces of the Afghan-​Pakistani border regions, in Iraq, Yemen or the Horn of Africa, where they engage in lethal strikes and surveillance missions, or support ground troops, drones serve a variety of purposes and are deployed in non-​military contexts. For example, domestic law enforcement agencies use drones to trace suspects and their movements; drones survey wildlife and assist in environmental protection; they deliver goods to remote locations; or simply contribute to private enjoyment. Such wide-​ranging deployment of drones owes much to the versatile materialization of the drone and its technology: drones come in many sizes, ranging from the full-​scale aircraft size of the US military’s Reaper or Predator drones at one end of the spectrum,2 to household size flying machines that are purchased for recreational usage, right down to mini-​or micro-​ drones that, as some worry, could be used for domestic tracking and targeting in the near future.3 Remotely controlled drones typically require an operator to guide the drone’s various functions. Depending on type, the degree of technological sophistication and the task required, drone operators are involved in take-​off, landing, flying and tracking during surveillance

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missions. Weaponized drones on targeting missions will include a larger ground team, which involves military lawyers. Drone operators can be based within the vicinity of the drone’s flying radius but, as is common for US drone operators, will be stationed thousands of miles away, on a military base, from where they direct drone operations abroad. The development of autonomous functions, for example with respect to take-​off and landing, which are becoming more prevalent and more sophisticated, reduces the role and input of drone operators. However, this shift towards autonomy, especially with respect to weaponized drones, raises a significant attendant set of concerns from an ethics and human rights perspective. These concerns relate to the prospect of using drones as a platform for near-​future, autonomous weapons systems with the capacity to select, track and kill targets (see e.g. Drone Wars UK, 2018; see also Boulanin, 2016; Schwarz, 2018; Schippers, 2020a). The proliferation of scholarly and public interest in drones remains bound up with the global war on terror and, as I discuss in the next section, drone usage escalated with a shift in military emphasis that commenced with the Obama administration in 2009. However, it is important to bear in mind that the history of drones, and of the use of UAVs for military surveillance and targeting, precedes their rapid deployment since the 2000s. This history is intimately connected with the development of aviation, with aerial surveillance and warfare (van Crefeld, 1991), and with the emergence of remote killing (Carvin, 2015). Further, as Derek Gregory (2017) advises, it should be read through the lens of colonial control and the imposition of power through aerial warfare that produces post-​colonial territories as spaces of exception. Attempts to launch UAVs date back to at least the 19th century and, according to Kindervater (2016), their development went through several stages that commenced with the use of hot air balloons and led to the subsequent development of fully mechanized UAVs. Despite the current association of UAVs with lethal targeting, they were initially deployed for intelligence, surveillance and reconnaissance (ISR) operations, a function that continues to play a key role in drone usage to this day. The major military confrontations of the 20th century, especially World War I and World War II, constitute important staging posts in the development of aviation and aerial warfare, and they also serve as catalysts for the development of UAVs. Technological limitations, especially with respect to communications issues, as well as political opposition to the use of unmanned aerial vehicles, are two factors that explain the long gestation period towards a wider-​ranging deployment of drones, as we know them today. As Kindervater (2016) demonstrates,

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a ‘pro-​pilot bias’, which prioritized the development of manned military aircraft, hampered the expansion of drone development and usage through the decades. Moreover, following the end of World War II in 1945 and against the backdrop of escalating Cold War confrontations between the United States and the Soviet Union and their respective allies, technological advances in kill functions concentrated on the development of missiles. But the ISR potential of drones did not go unnoticed. The Vietnam War saw the beginning of elementary forms of drone usage, as we know them today, when reconnaissance and aerial surveillance drone missions became increasingly frequent (see esp. Shaw, 2016). While the persistent pro-​pilot bias may have hampered the expansion of drone development and deployment in the aftermath of the Vietnam War, this reluctance to deploy drones in combat changes with the conflicts of the 1990s, during the first Gulf War and especially in the war on the Balkans, accelerating as this conflict moves into Kosovo. Advances in the drone’s technological capabilities, such as improved data transmission and enhanced loitering capacities, contribute to this change and transform the drone into a suitable tool for this kind of conflict. Accordingly, advances in drone technology should be read alongside a change in the conduct of warfare, towards so-​called ‘new wars’ (Kaldor, 2012) and an increased focus on humanitarian interventions in the wake of the Responsibility to Protect (R2P) doctrine (Bellamy, 2020), which called for interventionist policies as a response to massive human rights violations. In brief, the term ‘new wars’ captures the phenomenon of new forms of organized violence, which emerged in the late 1980s and which extended the range of actors beyond states’ regular armies to include paramilitaries, mercenaries and a diaspora network invested in the conflict. Coupled with a low appetite on the part of states to commit ground troops to foreign battlefields in conflicts that garnered little domestic enthusiasm, drones became an attractive tool for continued military actions that seek to minimize the risk to, even the necessity for military personnel on the ground. Furthermore, difficult geographical terrain, as well as fast-​moving opponents with highly mobile military equipment, which NATO forces encountered in the war in Kosovo, called for prolonged aerial surveillance and dynamic targeting, two tasks at which drones excel. These usages illustrate how drones should not be viewed in isolation, but ‘as intimately connected to other military and security practices’ (Kindervater, 2016, p. 224), as elements in a wider network composed of military strategy and tactics (see Carvin, 2015). It is at this juncture

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that the techno-​political potential of the drone—​to engage in ‘lethal surveillance’ (Chamayou, 2015; see also Kindervater, 2016; Shaw, 2016)—​comes to the fore. As I discuss in the following, it blurs the distinction between surveillance and killing, and it provides an additional analytical handle on the lethal effects of non-​weaponized drones, which can enhance the effectiveness and lethality of other weapons and weapons systems (see Holland Michel, 2020). One other factor led to the increasing use of drones: this is the drone’s alleged capacity for precise targeting at relatively low altitudes, and the attending scaling back of high altitude bombing from manned aircraft or the use of laser-​guided missiles, both of which were prone to mistakes resulting in the loss of civilian lives. In the next two sections, I discuss the manifestations of the drone’s disposition matrix and its implication for justice, beginning with a consideration of the global dimensions of warfare, before turning to the impact of its domestic applications. As I seek to demonstrate, we witness the birth of a narrative that marries technological capabilities with ethical justifications and legal compliance, generating a discourse that depicts the dispensation of justice via drone strikes.

‘Power without vulnerability’: drones, the re-​ ordering of global power and international justice The almost seamless transition from the Kosovo conflict to the 9/​11 wars, which began in Afghanistan in October 2001, and extended into Iraq and beyond since 2003, occurred against the backdrop of a widening use of military drones. Drone warfare sits at the heart of the 9/​11 wars (see e.g. Woods, 2015), and drones, together with improvised explosive devices (IEDs), which are used widely by non-​ state combatants, with devastating impact on ground troops, could be described as the most iconic tool of these conflicts. Already during the presidency of George W. Bush in the United States (2001–​9), drones become a growing feature of the military campaign of the US and their allies, but since the early days of President Bush’s administration, the use of military drones has undergone a massive expansion. The data visualization Out of Sight, Out of Mind, which utilizes information compiled by the Bureau of Investigative Journalism, depicts the civilian casualties of drone strikes in Pakistan in the period between 2004 and 2015, and it illustrates the acceleration of drone usage since 2008, the year that coincides with the transition from the Bush administration to the Obama presidency.4 In this section I discuss the ramifications of military drone usage for international

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justice. I argue that the use of military drones portends to project a global ‘power without vulnerability’ (see Gregory, 2011a), where, as Chamayou (2015, p. 13) contends, it becomes ‘a priori impossible to die as one kills’, and where structures of unequal risk distribution extend both geographically, creating an ‘everywhere war’ (Gregory, 2011b) and a ‘borderless form of sovereignty’ (Shaw, 2016, p. 9; see also Pugliese, 2015), as well as temporally, generating a ‘forever war’ (Gregory, 2011b) that rescripts international law and longstanding principles of military engagement. Several factors explain the link between the expansion of drone usage in the global war on terror and the onset of the Obama administration, which puts to rest the ‘pro-​pilot bias’ with an increasing reliance on drones. Faced with a military campaign in difficult terrain on the one hand, and the American ‘body bag’ syndrome, the US public’s reaction to military losses on foreign battlefields in conflicts that lack domestic support on the other, drones enable the continuation of military activities in Afghanistan, in the FATA regions of Pakistan, and in Iraq, while also facilitating a reduction in the number of US military personnel stationed overseas, and a decrease in the number of military casualties, which suffered heavily as a result of the use of IEDs.5 In this wider strategy, drones fulfill several functions. They work in tandem with the air force and can be used to coordinate lethal strikes of manned aircraft, assisted by the development of wide-​area motion imagery (WAMI), which enables a ‘Gorgon stare’ that captures large-​scale territory on the ground (Holland Michel, 2019, p. xiii; see also Chamayou 2015, pp. 38–​43). Their ISR capabilities are also used to back up the operation of ground troops, for example by tracking suspects and transmitting data to ground troops. Of course, drones are also used to conduct lethal strikes without direct intervention of ground troops or manned aircraft. As I alluded to earlier, remote warfare and remote killing are not a novelty of the drone age. But the expansion of weaponized drone usage in the contemporary theaters of combat in Afghanistan, Iraq and elsewhere, coupled with the technological capabilities of drones, facilitate the temporal and geographical extension and expansion of military engagement, and raise a distinctive set of questions about international justice, ethics and compliance with international law (see Boyle, 2015). This latter point is particularly poignant when considering the extensive, and secretive, drone program run by the CIA, and the attendant blurring of responsibilities between the military and a domestic intelligence agency, and their respective roles in theaters of war (see esp. Woods, 2015; see also Gregory, 2011a; Shaw, 2016). Overall, though, as Carvin

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(2015) has argued, what is at stake is less the weapon itself, but how the weapon, or, to be precise, the drone as a weapons platform, is being used, especially how drones become integral to military strategies. It is my contention that drone technology and decisions on military strategy mutually reinforce one another, insofar as the drone’s technological capabilities enable particular military strategies and tactics. This relationship, between drone technology and military strategy, calls for attention to three areas: first, it calls for a broader discussion on drone compliance with the laws of war, which I address in the remainder of this section; second, it requires an analysis whether the conditions of drone strikes qualify as war; and third, it requires a more specific focus on the legality of particular uses of drones, such as targeted killings or anticipatory self-​defense (Boyle, 2015, p. 111), which I consider in this section and the next. The use of weaponized drones raises significant worries over their compliance with international humanitarian law (IHL), specifically concerns over compliance with the laws of war, and with the wider framework of international justice. Efforts to locate military drones within the conceptual and normative scheme established by the just war tradition (JWT) poses significant challenges (Chamayou, 2015, p. 168), with scholars and Non-​governmental organization (NGOs), such as Amnesty International (2013, 2018), raising concerns that military drones constitute a violation of the ad bellum and in bello aspects of JWT. Two aspects structure this discussion: these are potential violations of the principle of proportionality and of the principle of distinction. The ad bellum requirements of the laws of war, which regulate the conditions under which war can be declared, make it imperative that the onset of military hostilities must be proportionate to the causes of war. The gravity of warfare, including its impact on a warring state’s military personnel, calls for a careful consideration as to if, when, where and how military personnel should be deployed. UAVs have become a game-​changer in this calculation: they promise ‘power without vulnerability’, participation in military hostilities with limited exposure of one’s own troops to the military assault of one’s enemy. Such unequal risk distribution lowers the threshold for moral and political restraints that state actors normally apply and could ease the threshold for military action. Concerns over the impact of the principle of proportionality on the in bellum principles, which govern conduct during warfare, must also be considered; these, in turn, connect closely with the principle of distinction, and should be examined in relation to the political and military context of contemporary warfare. The challenge of locating

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drone warfare within the framework of JWT is compounded with the onset of asymmetrical, or new, wars, where the involvement of non-​state combatants, and the blurring of lines between combatant and civilian status, complicates legal, ethical, strategic and tactical considerations (see Boyle, 2015). Drones enable remote warfare on faraway battlefields in conflicts that do not meet the characteristics of the narrative of traditional warfare (see Gregory, 2011a, p. 204; Chamayou, 2015, p. 163). It is thus extremely difficult, even impossible, to establish whether ‘targets’ identified by drone operators qualify as combatants. This is partly a technical issue, which stems from limitations with respect to the visual accuracy of remotely operated drones that could mis-​identify potential targets, a problem complicated by the conditions of new wars, where combatants do not necessarily wear identifiable military uniforms. Misidentification leads to wrongful killing. As a victim of drone strike has stated, ‘We thought that if we were not doing anything wrong or associating with the wrong kind of people, no one would think we are terrorists’ (quoted in Greenwald, 2015). Cultural traditions, such as the carrying of guns in the FATA areas of Pakistan, have also led to misidentification and resulted in the killing civilians, including children, who were falsely believed to be combatants. But these misidentifications also stem from the ‘scopic regime’ (Gregory, 2011a) of the drone assemblage, and the racialized ‘frames of war’ (Butler, 2009) that construe local populations as terrorists. They are compounded by the concept of the ‘military-​aged male’ (MOM), a gendered and racialized frame used by the US military to identify potential enemy combatants. As Thomas Gregory (2020), drawing on the work of Judith Butler (2009), has demonstrated compellingly, drone strikes are embedded in a racialized discourse of livability where some lives come to matter while others are deemed unlivable. Compounding the problematic issue of the legality and legitimacy of drone usage in the forever war and everywhere war (Gregory, 2011b), the concept of MOM presumes the guilt and killability of individuals who are not identifiable and recognizable as combatants, in contravention of long-​ held conceptions of international justice. Disputes over the compliance of drone warfare with the JWT are set to continue. But, as T. Gregory argued in a previous article (2015), the focus on international law, at the expense of ethico-​political concerns, frames the debate about drones in a way that obscures considerations of ethics and politics, and that obfuscates and erases the suffering of those at the receiving end of drone warfare. What calls for particular attention is not just whether drones meet the characteristics of just

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war, important as this question may be. Rather, it is the question of how drones, performatively, rescript discourses about justice, and in doing so transform long-​established principles of international law. This challenge is intimately connected with the claim that drones are more surgical in their kill capacity, and thus more ethical and just, than for example the carpet-​bombing associated with World War II or the Vietnam War. The narrative underpinning this claim draws on conceptions of drone technology as highly advanced, smart platforms with data collection, processing and analysis capabilities that can identify and surgically extract enemies while leaving civilian populations largely unharmed.6 This assertion of a surgical kill capacity of smart weapons, and the attending discourse of ‘precision ethics’, has been deftly debunked by Maja Zehfuss (2010; see also Walters, 2014). This ‘precision ethics’ narrative draws from the performative quality of drones to generate new conceptions of ethics and justice, turning the drone into a just tool in contemporary warfare. However, the drone’s performative production of precision ethics prevents a deeper engagement with the politics and ethical permissibility of killing in specific conflicts (see esp. Schwarz, 2018), turning drone strikes into a ‘necro-​ethics’ (Chamayou, 2015, p. 146) and, I want to argue, generating a necro-​justice that is dispensed via killing. I develop this discussion in the next section, where I turn to particular uses of drones with a focus on the drone’s implication in practices of networked killing based on metadata. Through the use of pattern-​of-​life analyses, the spectacle of drone warfare dispenses justice as a spectacle via a politics of verticality (Weizman, 2002) and against the backdrop of a state of exception and the suspension of legal safeguards in the international arena; further, this trend is increasingly framing law-​and-​order responses at the level of domestic politics.

‘We kill people based on metadata’:7 biopolitical drones Compliance issues with respect to international law, and their ramifications for how we conceive of international justice, continue to occupy the scholarly and public discussion on drones. This remains important work, especially for the human rights and humanitarian communities. However, it is my contention that reading drones through the lens of legal compliance overlooks how drones resist the disciplining effects of already existing law and also how they generate new tactics and strategies that produce new renditions of law, and new discourses of justice, which work through the violence dispensed by the drone

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(see also Gregory, 2015). Moreover, analyzing drone usage and drone strikes through the lens of international law risks omission of the way that drones, in fact, scramble the boundaries between the legal and extralegal, between the domestic and the international, and between military and policing functions, a quality they share with a range of other new technologies.8 Developing my discussion from the previous section, I now shift the focus from the specific conditions for the legality of drone usage within the context of JWT to the more granular ramifications of drone deployment via the networked constitution of killable subjects through so-​called pattern-​of-​life (POL) analyses. As I suggest, this capacity positions drones within a framework of bio-​ power that shifts the focus from the identity of the drone target to the analysis of the behavioral patterns of a data subject who is linked into a global digital network. To develop this point further, I draw on Michel Foucault’s conception of bio-​power. In Society Must be Defended (2003), Foucault’s 1975–​6 lectures delivered at the Collège de France, he tracked a shift in the modalities of power in the context of war. His lectures offer an analysis of the transitioning of power in the modern age, from the model of sovereignty to disciplinary power and bio-​power. Whereas sovereign power is exercised unilaterally, disciplinary power constitutes a form of productive surveillance that shapes and molds individuals, right down to their bodily gestures and practices. As I demonstrate in the next section, such form of disciplinary power propels the deployment of drones during the current coronavirus pandemic—​but what interests me at the moment is the effect of drone deployment in a regime of bio-​power. What makes bio-​power a force to be reckoned with is its impact on populations, occupied as it is with the regulation of particular ways of life and the government of populations. Conceptualizing drones through the lens of bio-​power is relevant for at least two reasons: first, it extends the discussion of drone power beyond their sheer killing capacity, and second, it is emblematic of the way that power and ‘relations of subjugation can manufacture subjects’ (Foucault, 2003, p. 265). Thus, as part of a biopolitical assemblage, drones govern subjects and produce them as killable, assisted by a ‘scopic regime’ (Gregory, 2011a) of culturally selective killability. Therefore, the drone should be understood as more than a weaponized flying machine: it is a biopolitical platform, part of the repertoire of a technology of power that materializes data points in the flesh of its subject-​targets (see esp. Wilcox, 2017; see also Gregory, 2020), producing them as killable within the context of a ‘forever war’ (Gregory, 2011b), stripped of clear legal reference points.

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I will illustrate this notion of the biopolitical drone by returning to the military usage of drones, specifically their deployment in the pursuit of extrajudicial killings. What propels this practice is a biopolitical assemblage that, according to Pugliese (2015, p. 225), building on the work of Bourdieu, includes ‘technologies, subjects, spaces, and relations of power’. To develop the operation of this ‘dronescape’ assemblage (Pugliese, 2015), I draw on the work of N.K. Hayles (2017)9 who suggests that drones operate in a complex command structure that includes military leadership, lawyers, government officials and their policies, engineers and so on. Drawing, albeit selectively, on Latourian assertions of the agentic capacity of material objects, or actants (see e.g. Latour, 2002), technologies interact with and transform the conditions and terms of (human) decisions (Hayles, 2017, pp. 37–​8). This claim informs Hayles’s deployment of the notion of a cognitive assemblage, which presumes ‘the entanglements and interpenetrations of human and technical cognitive systems’ (2017, p. 40), where, furthermore, ‘technological actors perform constitutive and transformative roles along with humans’ (2017, p. 37). According to Hayles, cognitive assemblages have ethical significance because ‘technologies interact with and transform the very terms in which ethical and moral decisions are formulated’ (2017, pp. 37–​8). She contends that (ethical) decision-​ making occurs within these cognitive assemblages, not in isolation from them: while humans remain the prime ethical actors, they articulate and exercise their agency in the context of an assemblage that they co-​create with the patterns of informational flows and material objects, such as drones. It is within the context of this assemblage that drone strikes, working through pattern-​of-​life (POL) analyses, become intelligible. To reiterate: the agency and, in the final instance, responsibility, of drone operators and decision-​makers emerge from the interpretation of information: human-​technic cognitive assemblages that interact with as well as transform the terms and terrain where agency, ethical or otherwise, is exercised (Hayles, 2017, pp. 36–​8). Let us unpack this further. The connection between hardware and software, and the dual usage of drones for kill and surveillance operations are part of a POL analysis, which drills down into the patterns of behavior, practices and networks and relationships of those who are tracked and killed by drones. Whereas so-​called ‘personality strikes’ refer to the targeting and killing of named terrorist suspects, signature strikes link the kill capabilities of drone technology with the wider capabilities of new technologies, including data analytics, geolocation data and image recognition.

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Personality strike are conducted on the basis of kill-​lists of named terrorist suspects and they work through the claims and assertions of the drone’s surgical capacity to ‘hit’ (read: kill) identified targets and reduce the number of civilian deaths. This particular practice of targeted killing has caught the attention of scholars and campaigners, such as Philip Alston, former UN Special Rapporteur on extrajudicial, summary or arbitrary executions (see UNGA, 2010), who expressed concerns over the compliance of drone strikes with international humanitarian law and also, potentially, human rights law. Signature strikes are even more far-​reaching than personality strikes in their ramifications for justice. Based on a POL analysis of a data subject whose data output, such as geolocation data, travel patterns, or communication networks, including phone connections, are used to construct individuals as killable targets, brings this subject into the lethal orbit of the drone. Signature strikes, like personality strikes, operate in a deeply problematic legal space where the lines between warfare and surveillance are blurred, where the protection of life and the presumption of innocence, and thus the prospect of justice, is suspended. Drones, as Joseph Pugliese argues, reconfigure the practices of daily life of those living under what he terms the ‘dronescape’ (2015, p. 225), and they also ‘establish new conceptualizations of the relation between the local and the international’ (2015, p. 223). This reconfiguration of daily living under an ‘eye turned into a weapon’ (Chamayou, 2015, p. 11) also seeps into domestic life in the Global North, where, as I discuss in the final section, drones are acquiring a novel importance in the policing of COVID regulations.

Pandemic drones10 The incorporation of drone technology into the arsenal of military tools that are used in foreign battle spaces of the Global South, and its attendant production of those spaces as lawless, encroaches into the domestic realm of states in the Global North. While drones, as argued earlier, produce borderless forms of sovereignty (Shaw, 2016), overriding borders and producing spaces of extraterritorialization (Pugliese, 2015), they simultaneously, and paradoxically, install and entrench borders, through the policing and tracking of migrant movements. Drones are increasingly incorporated into the repertoire of domestic law enforcement,11 where they are used to police public order events, such as large sports gatherings, carnival parades, political protests, even individual gatherings. To date, their primary domestic usage appears to be in the field of surveillance: drones equipped with

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cameras can record and upload images of people into law enforcement databases where these images can be used to identify individuals. While the creation of video footage during public events, including political protests, is not a novelty of the drone age, the use of drones for these purposes normalizes military-​style techniques such as aerial surveillance in domestic contexts. At the time of writing, there are media reports that Predator drones, which are normally deployed for military purposes, have been flown over US cities such as Minneapolis and possibly Portland, where people were participating in Black Lives Matter protests. Further, the increasing popularity of drones for recreational purposes raises additional issues over non-​state surveillance practices and over the possible access of state agencies and private corporations to images collected by private individuals. While the analytical framework of lethal surveillance provides us with an important tool to understand the use of drones in military contexts, I suggest that the drone’s biopolitical capabilities generate a more granular perspective, not just on the drone’s surveillance and kill capacities but also how it generates and forms behavior and conduct. As I illustrate in this final section, the pandemic drone, and its deployment within a framework of wide-​ranging emergency powers, illustrates this capacity starkly. The surveillance capabilities of drones are currently acquiring novel importance in the policing of the COVID-​19 pandemic regulations. Although it is too early to assess the wider ramifications of this pandemic, and to ascertain how measures intended to trace the pandemic and those infected with the virus will transition into a post-​pandemic era, it is quickly becoming evident that drones play a significant role in the tracking, surveillance and support efforts deployed to combat the coronavirus. The experience of living under drones in the conflicts of the Middle East and the Horn of Africa, is modified and integrated into the most mundane aspects of everyday life in many parts of the world. The drone’s disciplinary, regulatory, productive and behavior-​forming capacities play a central role in this emerging constellation. The deployment of medical narratives, and the wider discourse of techno-​biopolitical expertise that has accompanied the use of weaponized drones (see Schwarz, 2016), is finding a new application in states’ domestic fight against the coronavirus. It is widely accepted that the protection of life during the COVID-​19 pandemic requires extraordinary responses, and drones can play a very useful role during a pandemic, ranging from the serious to the curious. They deliver food, medication and medical equipment to vulnerable and often isolated individuals and communities. Drones are used to

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disinfect public spaces. And they can boost public morale and counter the boredom of social isolation by offering us a glimpse of our empty cities and isolated beauty spots. But as governments begin to prepare exit strategies from the lockdown, it is imperative that the attention turns to the long-​term effects of this surveillance technology, and the likelihood of its continued use. To fully grasp the role of pandemic drones, it is essential to recall that drones are a multi-​tool surveillance platform. They are embedded in, and networked with a host of other technologies, such as image recognition and data processing, which, in the context of the pandemic, can be used to monitor compliance with lockdown measures, enforce behavior changes, and track and collect health data. These are central strategies in the global effort to fight the virus and flatten the curve. To give just a few examples, police drones that fly over our cities, towns and local beauty spots monitor the public’s compliance with lockdown measures and can measure social distancing. Drones can track and collect highly personal and sensitive data. When fitted with thermal cameras, drones can identify symptoms that are associated with a COVID-​19 infection, such as increased heart and respiratory rates, a raised body temperature, coughing and sneezing. But despite assurances that such health data will be anonymized, there are worries that it can be used to identify individuals.12 Cameras installed on pandemic drones can be linked to CCTV networks that are equipped with facial recognition technology. This is a particular worry, as the images collected can be used to identify individuals and re-​purpose sensitive data, such as facial images, for actions such as law enforcement. There is a related concern that personal and thus highly sensitive data collected by drones, such as health data or facial images, will be shared with private corporations without our knowledge or consent. To give another example, while so-​called ‘shout drones’—​drones equipped with a speaker—​have been used in China to spread public health messages, they also issue verbal warnings and publicly shame people who violate social distancing rules or who are out in public without wearing a facemask. There is more to this than the overzealous deployment of surveillance drones by individual police forces. The encroachment of drone technology and drone surveillance into domestic politics and into everyday life has the potential to create a ‘new normal’ that could persist after the coronavirus emergency has passed. Embedded in conceptions of law and politics informed by state of exception, which, as Walter Benjamin so poignantly reminded us in his eighth thesis on history, is the rule (Benjamin, 1991, p. 697), the COVID pandemic could act as a catalyst that accelerates the expansion of technological surveillance via a politics

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of verticality. Drones could become a key building bloc of a surveillance architecture that may last well into the future.

Conclusion This chapter presented drones as versatile kill-​ and surveillance platforms, part of a techno-​p olitical assemblage that blurs the boundaries between the domestic and the international; between territoriality and extra-​territoriality; and between lawfulness and the extrajudicial. I argued that the dronification of global politics should be read through a racialized and orientialized lens, a scopic regime that projects ‘power without vulnerability’. I suggested further, with respect to the performative quality of drones, that drone assemblages rescript previously established conceptions of international law and international justice, producing instead a ‘sudden justice’ (Woods, 2015) that is exercised through the unequal global distribution of risk and the claim to extend sovereign power both geographically and into the future. Moreover, as I demonstrated, the current coronavirus pandemic accelerates the intensification of drone surveillance at the domestic level, increasingly prominent in the policing of borders and political protest and embedded in emergency legislation that normalizes the state of exception. Although my discussion in this chapter focused on drone usage by state agencies and public bodies, including the military, intelligence agencies and the police, it would be amiss to ignore the growing usage of drone technology by non-​state actors. Much of this covers the innocent use of drones for recreational purposes, but with rapid advances in image recognition technology, this private use of a technology with significant surveillance capabilities expands the prospect for increased private and state surveillance. Further, public-​ private collaborations with respect to drone usage, as seen during the current pandemic, raises the specter of enhanced surveillance and the sharing of personal data by private corporations with state agencies. Of course, drones are also used by non-​state actors with criminal or disruptive intent, and with dangerous implications, such as the use of drones to smuggle drugs into prisons; the flying of drones within the vicinity of London’s Gatwick airport during 2019, which caused considerable disruption to air traffic; or the use of weaponized drones by non-​state armed groups, including Hamas and Hezbollah. Moreover, the use of drones as a way to disrupt the sovereign power of states is complemented by resistance to drone use for the purposes of killing and surveillance, as exemplified in civil society campaigns against

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drone targeting. As I argued in this chapter, drones have become a tool in a new regime of governmentality, executing a ‘politics of verticality’ (Weizman, 2002) that encompasses killing and surveillance and forms the conduct of dronified subjects. To counter such drone ‘justice’ becomes an important task for contemporary struggles for rights and freedom, and it calls for a ‘hyper-​and pessimist activism’ (Foucault, 2000, p. 256) that pushes for ‘the art of not being governed quite so much’ (Foucault, 2002, p. 193). Notes 1

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4 5

6 7

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12

The term ‘scopic regime’ draws on the work of film theorist Christian Metz to articulate specifically cultural ways of seeing. Further developed in Martin Jay’s account of the ocular-​centric quality of Western modernity, the notion of the scopic regime has acquired recent prominence in work on drones (see esp. D. Gregory, 2011a, pp. 190–​1) and in what Eyal Weizman (2002) refers to as the ‘politics of verticality’. For a detailed discussion of the scopic regime of drones see Grayson and Mawdsley (2019). MQ-​9 Reaper has a wingspan of 66 feet, is 36 feet in length and 12.5 feet in height (see https://​www.af.mil/​About-​Us/​Fact-​Sheets/D ​ isplay/A ​ rticle/1​ 04470/​ mq-​9-​reaper/​). In contrast, Raven, a drone used for intelligence, surveillance and reconnaissance (ISR) activities, has a wing span of 1.37 meters and is 3 feet in length (see https://​www.af.mil/​About-​Us/​Fact-​Sheets/D ​ isplay/A ​ rticle/1​ 04533/​ rq-​11b-​raven/​). The video Slaughterbots, produced by Future of Life Institute (2017), gives a fictionalized account of drone swarms equipped with image recognition technology that student activists and elected representatives. The data visualization can be accessed here: https://​drones.pitchinteractive.com/​ See in particular Holland Michel (2019) for an analysis of the role of IEDs in the development of militarized drones during the war on terror. On the use of medical discourse in drone strikes see esp. Schwarz (2016). This phrase is ascribed to Michael Hayden, former Director of the US National Security Agency. See https://​www.nybooks.com/​daily/​2014/​05/​10/​we-​kill-​ people-​based-​metadata/​?insrc=wbll. The notion of ‘dual usage capacity’ is frequently invoked to highlight the deployment of new technologies, including drones, for both military and civilian purposes, and with the prospect of beneficent and maleficent outcomes. This paragraph borrows from Schippers (2020a). This section develops a recent article published in The Conversation. See Schippers (2020b). The video Slaughterbots (Future of Life Institute, 2017) alludes to the possibility of drone usage in domestic contexts although the video leaves open whether such drone usage emanates from (domestic) state agencies or from non-​state actors. In Westport, in the US state of Connecticut, plans to introduce these types of pandemic drones have been abandoned following concerns over privacy infringements.

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References Amnesty International (2013). ‘Will I Be Next?’ US Drone Strikes In Pakistan. London: Amnesty International Publications. [online] Available at: https://​www.amnestyusa.org/fi ​ les/a​ sa330132013en.pdf. Amnesty International (2018). Deadly Assistance: The Role of European States in US Drone Strikes. London: Amnesty International Ltd. [online] Available at: https://​www.amnesty.org.uk/​files/​2018–​04/​ Deadly%20Assistance%20Report%20WEB.pdf?nnxzvq2lenq0LiFu 64kg6UtyT2I8Zs3B. Bellamy, A. (2020). ‘The Responsibility to protect’ and the ethics of humanitarianism. In B. Schippers (ed.) The Routledge Handbook to Rethinking Ethics in International Relations. London & New York: Routledge (pp. 343–​53). Benjamin, W. (1991). ‘Über den Begriff der Geschichte’ in Gesammelte Schriften I.2, Frankfurt, DE: Suhrkamp, pp. 691–​704. Boulanin, V. (2016). Mapping the Development of Autonomy in Weapon Systems: A Primer on Autonomy. Solna, SE: Stockholm International Peace Research Institute. Boyle, M.J. (2015). The legal and ethical implications of drone warfare. The International Journal of Human Rights 19 (2): 105–​26. Butler, J. (2009). Frames of War: When Is Life Grievable?, London & New York, NY: Verso. Carvin, S. (2015). Getting drones wrong. The International Journal of Human Rights 19 (2): 127–​41. Chamayou, G. (2015). Drone Theory. London, UK: Penguin Books. Drone Wars UK (2018). Off the Leash: The Development of Autonomous Military Drones in the UK. Oxford: Drone Wars UK. [online] Available at: https://​dronewars.net/​wp-​content/​uploads/​2018/​11/​dw-​leash-​ web.pdf. Foucault, M. (2000). On the genealogy of ethics: An overview of work in progress. In P. Rabinow (ed.) Ethics: Essential Works of Foucault 1954–​1984 (vol. 1). London, UK: Penguin Books (pp. 253–​80). Foucault, M. (2002). What is critique? In D. Ingram (ed.) The Political. Malden, MA & Oxford, UK: Blackwell (pp. 191–​211). Foucault, M. (2003). Society Must Be Defended. Lectures at the College de France, 1975–​76. New York, UK: Picador. Future of Life Institute (2017). Slaughterbots. [online] Available at: https://​futureoflife.org/2​ 017/1​ 1/1​ 4/a​ i-​researchers-​create-​video-​ call-​autonomous-​weapons-​ban-​un/​?cn-​reloaded=1.

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Gettinger, D. (2015). The Disposition Matrix. [online] Available at: https://​dronecenter.bard.edu/​the-​disposition-​matrix/​. Grayson, K. & Mawdsley J. (2019). Scopic regimes and the visual turn in International Relations: Seeing world politics through the drone, European Journal of International Relations 25 (2): 431–​57. Greenwald, R. (2015). Unmanned: America’s Drone Wars. Brave New Films. Gregory, D. (2011a). From a view to a kill: Drones and late modern war. Theory, Culture & Society 28 (7–​8): 188–​215. Gregory, D. (2011b). The everywhere war. The Geographical Journal 177 (3): 238–​50. Gregory, D. (2014). Drone geographies. Radical Philosophy 183 (Jan/​ Feb): 7–​19. Gregory, D. (2017). Dirty dancing: Drones and death in the borderlands. In L. Parks & C. Kaplan (eds.) Life in the Age of Drone Warfare. Durham, NC & London, UK: Duke University Press (pp. 25–​58). Gregory, T. (2015). Drones, targeted killings, and the limitations of international law. International Political Sociology 9: 197–​212. Gregory, T. (2020). Drones and the ethics of war. In B. Schippers (ed.) The Routledge Handbook to Rethinking Ethics in International Relations, London & New York: Routledge (pp. 297–​311). Hayles, N.K. (2017). Unthought: The Power of the Cognitive Nonconscious. Chicago, IL & London, UK: The University of Chicago Press. Holland Michel, A. (2019). Eyes in the Sky: The Secret Rise of Gorgon Stare and How It Will Watch Us All. Boston, MA & New York, NY: Houghton Mifflin Harcourt. Holland Michel, A. (2020). Unarmed and Dangerous: The Lethal Applications of Non-​Weaponized Drones. Center for the Study of the Drone at Bard College. [online] Available at: https://​dronecenter. bard.edu/​files/​2020/​03/​CSD-​Unarmed-​and-​Dangerous-​Web.pdf. Hood, G. (2015). Eye in the Sky. Raindog Films. Kaag, J. & Kreps, S. (2014) Drone Warfare. Cambridge, UK and Malden, MA: Polity. Kaldor, M. (2012). New and Old Wars: Organised Violence in a Global Era (3rd ed.). Cambridge, UK and Malden, MA: Polity. Kaplan, C. (2017). Drone-​O-​Rama: Troubling the temporal and spatial logistics of distance warfare. In L. Parks & C. Kaplan (eds.) Life in the Age of Drone Warfare. Durham, NC & London, UK: Duke University Press (pp. 161–​77). Kindervater, K.H. (2016). The emergence of lethal surveillance: Watching and killing in the history of drone technology. Security Dialogue 47 (3): 223–​38.

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Latour, B. (2002). Morality and technology: The end of the means. Theory, Culture & Society 19 (5/​6): 247–​60. McVeigh, K. (2013). Drone strikes: Tears in Congress as Pakistani family tells of mothers’ death. The Guardian (29 October). [online] Available at: https://​www.theguardian.com/​world/​2013/​oct/​29/​ pakistan-​family-​drone-​victim-​testimony-​congress. Pugliese, J. (2015). Drones. In M.B. Salter (ed.) Making Things International: Circuits and Motion. Minneapolis, MN & London, UK: University of Minnesota Press (pp. 222–​40). Schippers, B. (2020a). Autonomous weapons systems and ethics in International Relations. In B. Schippers (ed.) The Routledge Handbook to Rethinking Ethics in International Relations. London & New York, NY: Routledge (pp. 312–​25). Schippers, B. (2020b). Coronavirus: Drones used to enforce lockdown pose a real threat to our civil liberties, The Conversation (26 May). [online] Available at: https://​theconversation.com/​coronavirus-​ drones-​used-​to-​enforce-​lockdown-​pose-​a-​real-​threat-​to-​our-​civil-​ liberties-​138058. Schwarz, E. (2016). Prescription drones: On the techno-​biopolitical regimes of contemporary ‘ethical killing’. Security Dialogue 47 (1): 59–​75. Schwarz, E. (2018). Death Machines: The Ethics of Violent Technologies. Manchester, UK: Manchester University Press. Scott, T. (1998). Enemy of the State. Touchstone Pictures. Shaw, I.G.R. (2016). Predator Empire: Drone Warfare and Full Spectrum Dominance. Minneapolis, MN & London, UK: University of Minnesota Press. Stanford Clinic and NYU Clinic (International Human Rights and Conflict Resolution Clinic at Stanford Law School and Global Justice Clinic at NYU School of Law) (2012). Living Under Drones: Death, Injury, and Trauma to Civilians from US Drone Practices in Pakistan. [online] Available at: https://​ w ww-​ c dn.law.stanford.edu/​ w p-​ content/​uploads/​2015/​07/​Stanford-​NYU-​Living-​Under-​Drones. pdf. United Nations General Assembly (2010). Report of the Special Rapporteur on Extrajudicial, Summary or Arbitrary Executions. [online] Available at: https://​www2.ohchr.org/​english/​bodies/​hrcouncil/​ docs/​14session/​A.HRC.14.24.Add6.pdf. Van Crefeld, M. (1991). Technology and War: From 2000 B.C. to the Present. New York, NY: The Free Press. Walters, W. (2014). Drone strikes, dingpolitik and beyond: Furthering the debate on materiality and security. Security Dialogue 45 (2): 101–​18.

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Weizman, E. (2002). Control on the air. OpenDemocracy: Free Thinking for the World. [online] Available at: https://w ​ ww.opendemocracy.net/​ en/​article_​810jsp/​. Wilcox, L. (2017). Embodying algorithmic war: Gender, race, and the posthuman in drone warfare. Security Dialogue 48 (1): 11–​28. Woods, C. (2015). Sudden Justice: America’s Secret Drone Wars. London, UK: Hurst & Company. Zehfuss, M. (2010). Targeting: Precision and the production of ethics. European Journal of International Relations 17 (3): 543–​66.

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Global Surveillance: The Emerging Role of Radio Frequency Identification (RFID) Technology Brian G. Sellers

Introduction We are seeing changing patterns of governance in a globalizing world. Globalization initially gestured at interconnectedness, with others involved in our lives as we in theirs—​it was envisioned as a metaphor for the ‘Global Village’ (McLuhan, 1964). Yet, globalization was reconstructed through the lens of global neoliberal capitalism, which is governed by market logics, technologies and homogenizing modes of human interaction that often produce marginalizing and dehumanizing processes geared toward control (Bauman, 1998). In our ultramodern era, crime is also reassembled so that the criminal and the vulnerable are linked to danger and surveillance, justifying new ventures in securitization policy and practice. The responsibilization of citizens globally through devices of post-​panoptic bio-​power require researchers in the post-​criminology era of pre-​crime to reexamine the matters of identity-​making and rights-​claiming as they relate to the concept of citizenship by critically re-​problematizing this static construction of the social person (Sellers & Arrigo, 2016). Global neoliberal capitalism seeks to weather its own crises and creatively consume its contradictions while imposing uniformity—​that is sameness in the sense of the same everywhere (Noys, 2011). A closer

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examination of the biopolitical processes, technologies of domination and multiplicity of surveillance accompanying neoliberalism is needed to expose techno-​globalism’s mechanisms of post-​panoptic (synoptic) and banoptic control. This new ultramodern sign-​optic system of governmentality does not refer only to the management of political structures but also designates the way in which the conduct of individuals or groups might be directed (Foucault, 2008). The resulting neoliberal governance recognizes the need to make subjects more governable and interactively visible to prevent and pre-​empt deviance or crime so securitization efforts can be normalized. Instruments of bio-​digital power, such as radio frequency identification (RFID) implants, impose the liquid process of individualization, which places the focus onto individual personal responsibility for social or economic failure, delinquency, crime or violence (Bauman, 2000). The conditions required for creating newly responsibilized global citizens includes: (1) technologies of surveillance, which act as bio-​ power—​instruments of technology deployed to discipline and make individuals behave; (2) heightened individualism fostered through competition and linked to fear of cultural and economic non-​survival; and (3) discourse of moral absolutism tied to inevitability of the economization of the Social—suggesting no alternatives to neoliberal forms of marketization, choice and competition exist (Sellers & Arrigo, 2017, 2018a). RFID, which uses electromagnetic radio waves to automatically identify people, animals, or objects, has become perhaps the most ubiquitous computing technology in history. As such, RFID microchips allow for tagged people and goods to be automatically located through navigational support and for stored data on the chips to be retrieved and processed for numerous applications across several industries, both public and private. As an emerging crime control technology, RFID implants are geared towards rhizomatic post-​panoptic structures of control, which create new forms of everyday life surveillance, banoptic social sorting, the responsibilization of citizens, and new forms of ‘people-​making’ culture in coordination with the aims of the global pre-​crime society. Therefore, RFID technology is pivotal to the exercise of bio-​digital power necessary for normalizing and nurturing this crime control enterprise and its subsequent governmentality, whereby informational strategies and digital techniques employed by regulatory institutions to achieve full or hyper-​securitization worldwide may be actualized. This chapter initially provides an historical overview of the literature pertaining to the emergence of RFID and its evolving system

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components. Secondly, the chapter examines RFID’s numerous practical applications as a mechanism for global surveillance in the Internet of Things (IoT). As IoT devices, RFID implantable chips have the potential to track, monitor and collect vast amounts of data on citizens, which could significantly bolster hyper-​securitization aims of the pre-​crime society. Next, the chapter undertakes a theoretical analysis of the significance that RFID technology plays in the globalization of surveillance and the ‘creeping criminalization of everyday life’ (Presdee, 2001, p. 159). Lastly, the chapter concludes with a critique related to the liberty, privacy and citizenship concerns of RFID implementation and human chipping.

Overview of RFID’s historical emergence and system components During World War II, radar and radio research produced some of the earliest forms of RFID technology. Most notable was the creation of the Identification Friend or Foe (IFF) systems for military aircraft, which were long-​range transponder systems used by the British Royal Air Force to accurately identify Allied aircraft from the Luftwaffe during the Battle of Britain (Garfinkel, Juels & Pappu 2005; Roberts, 2006; Saleem et al, 2012). After the war, theoretical research emerged further exploring how point-​to-​point communication may be improved through the application of the theory and method of reflected power communication (Stockman, 1948). Stockman’s (1948) early work served as the theoretical foundations for developing RFID techniques, whereby electromagnetic energy (e.g. in the form of radio waves, microwaves, infrared radiation and ultrasonic waves) may be harnessed and utilized for the transmission of information between two objects (Stockman, 1948; Roberts, 2006, p. 19). Between the 1920s and early 1950s, a Russian physicist, Léon Theremin, further developed his musical invention, the theremin, which used antenna and radio waves to produce musical sound (Albrecht & McIntyre, 2005; Saleem et al, 2012). While working for the Russian NKVD (which later became the KGB), Theremin used early forms of RFID technology to create a resonant cavity microphone for espionage purposes (Albrecht & McIntyre, 2005; Saleem et al, 2012). In fact, the Russian intelligence services used it to eavesdrop on United States (US) Ambassador, Averell Harriman, in Moscow (Albrecht & McIntyre, 2005; Sellers & Arrigo, 2009). Thus, this murky past reveals that some of the first applications of RFID technologies originated out of efforts to aid the enterprises of warfare and espionage (Sellers & Arrigo, 2009).

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By the 1960s, some of the first prototype RFID systems became available commercially, such as Sensormatic’s anti-​theft devices, commonly referred to as electronic article surveillance (EAS) equipment in retail service industries (Garfinkel, Juels & Pappu, 2005; Roberts, 2006), which serves as the initial application of RFID for securitization purposes. Subsequent RFID technologies for the use in private and public industries were comprised of three primary components: (1) an RFID tag or chip; (2) a tag reader with an antenna and transceiver; and (3) a host system or connection to an enterprise system (Roberts 2006; Albrecht & McIntyre, 2005). The device layer of RFID tags, or chips, houses integrated circuitry, which allows them to store and process data contained in a small silicon computer chip (roughly the size of a grain of sand; with memory capacity ranging from 2 kilobytes to 64 kilobytes), which has a 96-​bit unique identifier number (Sellers & Arrigo, 2009; Fescioglu-​Unver et al, 2015). The flat, metallic microcoil in the device serves as an antenna, and when coupled with the integrated circuitry, this combination creates a transponder that enables the RFID tag to transmit its unique identifier number and any other information it has stored back to a RFID reader without requiring line-​of-​sight (Albrecht & McIntyre, 2005; Fescioglu-​Unver et al, 2015). Middleware, or the data integration layer of RFID systems, controls RFID readers, monitors communications between tags and readers using protocols, and manages the data gathered for processing (Saleem et al 2012; Fescioglu-​Unver et al 2015). Management of RFID data requires middleware to clean and filter the immense amount of data tags transmit and store it in databases to eventually be shared with the end user applications in the data integration layer of the system (Saleem et al, 2012; Fescioglu-​Unver et al, 2015). This final data integration layer of the system enables digital data sharing to multiple applications in which RFID data can be used for a variety of purposes, but primarily to automatically identify, track, trace, monitor and manage the movement of products, goods, animals or people (Saleem et al, 2012; Fescioglu-​Unver et al, 2015). To date, RFID tags are classified as passive, active or semi-​active depending on power supply (Fescioglu-​Unver et al, 2015). While active tags have their own power source, passive tags do not and must rely on a RFID reader to activate the tag in order to solicit a signal from it (Sellers & Arrigo, 2009; Fescioglu-​Unver et al, 2015). Semi-​active tags offer the features of both passive and active tags by possessing their own power source for running the internal circuitry, but they must still obtain power through the communication with a reader (Fescioglu-​Unver et al, 2015). RFID tags can be further classified by

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their data rewrite capabilities (e.g. from ‘read only’ to ‘write many-​read many’) and frequency band (Fescioglu-​Unver et al, 2015, p. 1370). The frequency categories are: low frequency (125–​134kHz with a range up to 10 cm), high frequency (13.56 MHz with a range up to 30 cm), ultra high frequency (856 MHz to 960 MHz with a range up to 10 meters), super high frequency (2.45 to 5.8 GHz with a range up to 100 meters) and microwave tags with ultra-​wide band technology function at 10 GHz and have a signal range of up to 200 meters (Saleem et al, 2012; Fescioglu-​Unver et al, 2015).

Practical applications RFID has four broad usage categories, including: (1) electronic article surveillance (EAS), (2) portable data capture, (3) networked systems, and (4) global positioning systems (GPS; Roberts, 2006). As mentioned previously, one of the first commercially available applications of RFID was EAS for anti-​theft in retail stores (Garfinkel, Juels & Pappu, 2005; Roberts, 2006). RFID tags can be attached to clothing or other products to trigger alarms when the goods leave the store if they are not properly deactivated at the point of sale (Garfinkel, Juels & Pappu, 2005; Roberts, 2006). Portable data capture refers to capacity for RFID sensor tags to employ contactless sensing and wireless information transfer to monitor object temperature, humidity, pressure, movement (seismic), radiation levels and other observable conditions affecting an object (Roberts, 2006; Cui et al, 2019). Another example of portable data capture RFID technology would be wearable or implantable healthcare devices that monitor glucose level, blood pressure, intraocular pressure and heart rate in a patient (Cui et al, 2019). Networked systems applications used fixed position RFID readers to track the movement of tagged objects, such as inventory tracking in supply chain management or E-​Z Pass monitoring for highway toll collection (Garfinkel, Juels & Pappu, 2005; Roberts, 2006). Lastly, positioning systems, coupled with RFID tags, utilize GPS and geographical informational systems (GIS) to automatically locate tagged or chipped objects, vehicles, animals or people (Garfinkel, Juels & Pappu, 2005; Roberts, 2006). Additionally, RFID is considered as the foundational technology for the Internet of Things (IoT; Wu and Li, 2017). The IoT is a developing global Internet-​based information architecture that simplifies the exchange of goods and services by using auto-​identification and sensor technology, such as RFID, to enhance the synchronization of data and real-​time information visibility in order to prevent the disappearance of tagged goods, animals or people through constant monitoring,

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tracking and quality assurance (Weber, 2015; Wu and Li, 2017). As IoT devices, RFID technology collects data, which is often aggregated with other forms of data, and it is subsequently sent through a router to a communication device (e.g. Wi-​Fi or cellular) that transfers the data to a cloud server where it is processed and later retrieved by end users to interpret and evaluate the data for multiple purposes (Weber, 2015; Wu and Li, 2017). Given its broad usage capabilities, RFID technologies are considered perhaps ‘the most pervasive computing technologies in history’ and ‘one of the most promising technological innovations to increase visibility and improve efficiency’ (Roberts, 2006, p. 18; Cao et al, 2017, p. 2100). Its practical applications are vast and will now be briefly reviewed.

Manufacturing and supply chain management Today’s competitive global manufacturing industry requires more timely, precise and reliable real-​time manufacturing data, especially on the job-​shop floor, where complex machining operations and manufacturing processes require accurate on-​site data so managers can monitor production procedure in order to maintain proper functionality of equipment, products, workers and raw materials to prevent unnecessary losses or accidents (Liukkonen, 2015; Cao et al, 2017). RFID technology’s contactless automatic identification and digital data collection capabilities enable production managers to effectively monitor static and dynamic information related to machine status, workforce situations, part locations, urgent order arrivals, material shortages and unexpected changes to order deadlines or quantities (Liukkonen, 2015; Cao et al, 2017). Moreover, RFID applications in manufacturing are optimal for operating real-​time traceability systems to enhance supply chain management and quality control (Liukkonen, 2015; Cao et al, 2017). Deployment of RFID in supply chain management has been heralded as the ‘holy grail’ of inventory management in the supply network for major corporations (Garfinkel, Juels & Pappu, 2005, p. 35; Cao et al, 2017). Wal-​Mart, Tesco and even the US Department of Defense have adopted RFID for supply chain management (Roberts, 2006; Fescioglu-​Unver et al, 2015). Individualized RFID tags can be affixed to products and tracked from packaging at the factory to delivery at distribution centers around the world by truck, boat, train or airplane and eventually be used to monitor sales and stock inventory at the retail store level (Garfinkel, Juels & Pappu, 2005; Roberts, 2006; Liukkonen, 2015; Cao et al, 2017). RFID tags are also used in fisheries and for

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livestock management, and many countries, including Australia, New Zealand, the European Union (EU) and the US have national animal identification systems, which use RFID to track and monitor animals raised for human consumption to better ensure food safety and quality control (Foster & Jaeger, 2008; Fescioglu-​Unver et al, 2015). Intelligent packaging incorporates RFID sensors to detect, communicate and monitor the conditions of packaged foods so complete product history information can be stored on packaged meat labels (Foster & Jaeger, 2008; Fescioglu-​Unver et al, 2015). Ideally, future development of RFID will aid in digital life cycle monitoring of products from their conception, through design, to manufacture, distribution and consumption or disposal (Liukkonen, 2015). Furthermore, ‘smart-​shelves’ equipped with their own RFID technology can alert store management of misshelved products, automate real-​time inventory updates to warehouses for expedited resupply shipping, and simplify quality control for recalled products and food safety protocols (Garfinkel, Juels & Pappu, 2005, p. 35; Sellers & Arrigo, 2009). Consequently, the tracking of products by RFID technology also permits the tracking of customer behavior through the monitoring of their consumption habits (Sellers & Arrigo, 2009; Landmark & Sjøbakk, 2017). Such monitoring can include logging favored products purchased in grocery stores and linking this information to loyalty card programs, or enabling ‘smart fitting rooms’ that capture customer behaviors, such as product consideration in order to offer garment and style recommendations in real time (Sellers & Arrigo, 2009; Landmark & Sjøbakk, 2017, p. 847). Eventually, corporations would like to know everything about consumers from the moment they enter a store in order to tailor marketing messages to individual customer needs or desires (Zuboff, 2015; Landmark & Sjøbakk, 2017).

Healthcare systems and the pharmaceutical industry Rising international medical concerns over aging populations, sedentary lifestyles, obesity rates, chronic diseases (e.g. cardiovascular disease, hypertension, and diabetes) and global pandemics (e.g. COVID-​19) have led to many in the healthcare fields seeking innovative technologies to improve patient safety, quality of care and reduce costs, while minimizing human error (Hu et al, 2015; Pérez, González & Dafonte, 2016; Yoshikawa et al, 2019). The system architecture of an RFID-​based healthcare monitoring system includes four components: (1) tagged objects (e.g. patients, physicians, nurses,

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a tagged personal digital assistant, medicines or surgical instruments), (2) RFID information capture and delivery, (3) the patient-​aware contexts querying system, and (4) the medical information central system (Hu et al, 2015). Patients can wear a smart RFID tag, which would possess a unique identifier, an electronic medical record for the patient, and directive information for medical guidance, such as how to take medication properly (Hu et al, 2015; Pérez, González & Dafonte, 2016). These tags can help identify patients, update patient status, match blood samples, manage medical devices (e.g. surgical tools or wheelchairs) and even help prevent infant abduction or locate patients with dementia who may wander from the premises (Pérez, González & Dafonte, 2016; Yoshikawa et al, 2019). Doctors, nurses and other staff can use portable, handheld devices with RFID reader-​enabled equipment to digitally retrieve patients’ information actively or through stationary readers placed in corridors or embedded in the rooms’ environment (Hu et al, 2015; Pérez, González & Dafonte, 2016). Once a patient’s information is captured, it can be delivered to a centralized medical information database where doctors can access the patient’s information (Hu et al, 2015). In addition, the patient-​aware contexts querying system employs wireless sensor networks, positioning systems and wireless body area networks to monitor and track a patient’s environment (e.g. temperature and humidity), location and physiological vital signs (e.g. body temperature, blood pressure, glucose level, etc.; Hu et al, 2015; Pérez, González & Dafonte, 2016; Cui et al, 2019). As such, RFID-​based healthcare systems strive to comprehensively track and monitor the patient life cycle from admission to a hospital, through examination, during the course of patient care, after treatment while undergoing recovery, and the subsequent discharge and billing of the patient (Hu et al, 2015). A real-​time RFID monitoring middleware system has been proposed to track patients with mental illness at healthcare wards, or in their homes, so as to enhance observation treatment and custody management (Abel, 2016). It is not too farfetched to envision similar approaches being proposed to monitor patients with COVID-​19, and to augment population surveillance and contact tracing during the ongoing global pandemic. In fact, some in the medical and cyber security fields are already requesting that RFID tags, with their IoT capabilities, be implemented in robust contact-​tracing programs and multi-​layer architectures to enforce adherence to infection control standards during the COVID-​19 pandemic (Gupta et al, 2020; Mehta et al, 2020). RFID sensor technology provides a rapid, real-​time

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system for tracking all points of contact, and it can be subsequently analyzed to notify those in close contact with a positive case so they can be directed to testing and/​or isolation (Gupta et al, 2020; Mehta et al, 2020). However, in order for an automatic hands-​free RFID tracking system to be ideally utilized, it would likely entail the costly endeavor of tagging all patients exhibiting symptoms of COVID-​19 infection who seek medical treatment at hospitals, as well as all medical personnel, healthcare staff, and medical equipment that may come in contact with novel coronavirus patients (Gupta et al, 2020; Mehta et al, 2020). Without such coverage, it is possible that the RFID system will leave gaps in contact tracing; thus, the effectiveness of such a system is contingent upon its comprehensive application (Mehta et al, 2020). Full implementation of RFID tracing systems in hospitals presents more than just logistical concerns. Without proper privacy protocols and policies that limit and de-​identify the data collected on patients and personnel, there is the potential for sensitive data to be gleaned by unauthorized entities, especially if the data is stored or transmitted in cloud-​based platform where data breaches could occur (Gupta et al, 2020; Mehta et al, 2020). Recently, the US Food and Drug Administration (FDA) urged the pharmaceutical industry to adopt RFID in order to combat drug counterfeiting (Roberts, 2006; Sellers & Arrigo, 2009; Pérez, González & Dafonte, 2016). RFID tags assist the FDA in collecting data to enforce regulatory controls and reduce drug theft or counterfeiting by helping to properly authenticate FDA approved medicines dispensed by pharmacies (Roberts, 2006; Pérez, González & Dafonte, 2016). As a result, RFID tracking and monitoring of pharmaceuticals can aid FDA officials in swiftly identifying, isolating and reporting suspected counterfeit drugs, while also enhancing the expediency of drug safety recalls (Sellers & Arrigo, 2009; Pérez, González & Dafonte, 2016).

Transportation Initial applications of RFID for vehicles were for automobile immobilizer systems, which utilize passive RFID tags within the car key that is authenticated by the steering column, thus authorizing vehicle operation (Garfinkel, Juels & Pappu, 2005; Sellers & Arrigo, 2009). For security purposes, these tags housed in automobile key fobs are typically factory programmed and cannot be rewritten in the field, and some versions have an added layer of cryptographic communications between key and steering column to prevent auto theft (Garfinkel, Juels & Pappu, 2005; Sellers & Arrigo, 2009). Similarly, highway authorities

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have turned to RFID to provide secure, automatic toll collection (e.g. E-​Z Pass) for travelers who frequently pay tolls on daily commutes, which is especially useful for trucking (Garfinkel, Juels & Pappu, 2005; Sellers & Arrigo, 2009). With global populations continuing to grow, the world has seen a rapid expansion in automobile usage and the severe traffic congestion and collision-​based injuries and fatalities that accompany this increase (Njord et al, 2006; Qu et al, 2019). In response, governments in the EU, China, Japan and the US have begun to adopt, or carefully consider, implementation of intelligent transport systems (ITS), which are based on RFID electromagnetic induction-​based vehicle identification systems (Njord et al, 2006; Qu et al, 2019). The purpose of ITS is to provide urban traffic control, parking lot management, congestion warnings, collision prevention, vehicle identification, speed management and enforcement strategies, and severe weather condition and hazard warnings (Njord et al, 2006; Qu et al, 2019). Earlier implementation of ITS was hindered by problems associated with RFID tag collision, which is when multiple RFIDs exist in a reading range and interfere with each other making it difficult for readers to discern which tag belongs to a particular vehicle (Fescioglu-​ Unver et al, 2015; Qu et al, 2019). However, a new efficient tag identification algorithm, the RTCI-​DFSA, can be applied to ITS in order to rapidly detect vehicles moving at high speeds on expressways and improve the functionality of RFID-​based intelligent vehicle identification systems (Qu et al, 2019). Additionally, a fusion tag serialization identification method was established to reduce the loss rate of vehicle tags and enhance vehicle identification (Qu et al, 2019). Future RFID-​based ITS applications could greatly advance real-​time vehicle tracking and monitoring across varying types of roadways in order to ease congestion, locate stolen vehicles and give priority to emergency vehicles (Al-​abassi et al, 2019). Actually, research is underway that incorporates prediction algorithms, based on a hidden Markov model inference algorithm, along with RFID sensor devices and GPS to create a system capable of predicting the navigation path of a vehicle based on data from driver’s habits (Malekian et al, 2016). Furthermore, RFID-​based ITS systems can be used by law enforcement to implement smart prepaid traffic fine procedures that identify the vehicle in violation and automatically charge the fine to the driver’s digital balance while sending a text message to driver’s phone number on file notifying the person of their pending traffic fine (Al-​abassi et al, 2019). Other RFID applications extend to ‘eEnabled’ airplanes, which

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would use on-​board RFID tags and readers to connect with varying ground systems to enrich navigation, logistics and access control during flight (Wu and Li, 2017).

School securitization The hyper-​vigilant response to media-​driven moral panics associated with perceived increases in serious school-​based violence (e.g. school shootings) has resulted in the unprecedented increase in surveillance technologies in educational systems around the world (Sellers & Arrigo, 2017; Taylor, 2017; Sellers & Arrigo, 2018a, 2018b; Rahman et al, 2019). As a result, RFID embedded identification cards for students, educators, administrators and staff have revolutionized automatic access control, automatic attendance counting, and overall school security mechanisms (Sirichai et al, 2011; Taylor, 2017; Rahman et al, 2019). For example, students and school officials can wear wireless non-​ contact RFID identification badges, which will permit them entry through security gates at entrances to school grounds, as well as access to buildings and rooms (Sirichai et al, 2011; Taylor, 2017; Rahman et al, 2019). Additionally, these RFID badges and scanners use a global system for mobile communication (GSM) through an IoT connection to cloud servers, via the Internet, in order to contact security personnel, school administrators and parents by automated short message service (SMS) on mobile devices (e.g. smart phones) to immediately alert these parties about a child’s attendance, absence, or if an unauthorized person is attempting to gain access to the school (Sirichai et al, 2011; Taylor, 2017; Rahman et al, 2019). A similar RFID-​based IoT process can be mounted on school buses to notify school administrators and parents, by way of text (SMS) message, as to whether the children caught the bus and arrived at school in the morning and when the bus dropped them back off at home at the end of the day (Taylor, 2017; Rahman et al, 2019). Individualized student data can also be stored on a cloud database through the GSM module of the RFID system after it has been read and processed through Arduino Uno microcontroller programs (Rahman et al, 2019). Basically, RFID identification systems in schools will make it possible for students to be tracked and monitored from their homes to the school bus, from the bus to the classroom, and from school to the bus ride home in an effort to prevent truancy and any associated deviant behavior (Taylor, 2017; Rahman et al, 2019).

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Cashless electronic payment RFID tags are being used as credit-​card-​like payment tokens that contain a unique serial number, which can be retrieved by a reader and sent over a network and remote computer to debit a consumer’s personal bank account (Garfinkel, Juels & Pappu, 2005; Sellers & Arrigo, 2009). Texas Instruments’ Speedpass was one of the earliest versions of this technology, which was developed for pay-​at-​the-​ pump systems that used RFID key fobs to authenticate ID and debit customer accounts automatically (Garfinkel, Juels & Pappu, 2005; Sellers & Arrigo, 2009). RFID-​enabled debit and credit cards, or contactless smart cards, use radio frequency identification for making secure payments (Lacmanović, Radulović & Lacmanović, 2010). EuroPay, MasterCard and Visa that developed Europay, Mastercard and Visa (EMV) authentication protocols for contactless smart cards (Lacmanović, Radulović & Lacmanović, 2010). Now major credit card companies market their own version of ‘wave and go’, ‘touch and go’ or ‘tap and go’ credit cards, such as MasterCard’s PayPass, Visa’s PayWave, Discover’s Zip or American Express’ PayExpress (Lacmanović, Radulović & Lacmanović, 2010, p. 33). Contactless chip cards are ideal for processing secure and cost-​ effective payments in circumstances where merchants are required to process large quantities of low value transactions, such as fast food restaurants, convenience stores or transport terminals (Sellers & Arrigo, 2009; Lacmanović, Radulović & Lacmanović, 2010). These cards are also appealing for remote or unattended payment situations, including vending machines, toll roads or parking kiosks (Lacmanović, Radulović & Lacmanović, 2010). Other contactless payment systems use near field communication (NFC, e.g. Apple Pay, Google Pay, FitBit pay, etc.) that can be integrated into mobile devices (Lacmanović, Radulović & Lacmanović, 2010). Cashless electronic payment with RFID-​enabled debit and credit cards provides speed, convenience, durability, reliability and flexibility, which mean these smart cards are quite appealing to consumers (Sellers & Arrigo, 2009; Lacmanović, Radulović & Lacmanović, 2010). Furthermore, as the COVID-​19 pandemic continues, consumer demand for contactless payment options is likely to rise. However, it is important to note that smart cards also create a digital transaction record with financial institutions and corporations that log and trace purchases, returns and exchanges of goods and services, which can further be used to understand and predict consumer behavior or prevent fraud (Sellers & Arrigo, 2009; Zuboff,

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2015). The anonymity of cash currency does not capture the digital footprint that RFID-​enabled smart cards do (Sellers & Arrigo, 2009).

Criminal justice applications As IoT devices, RFID sensor tags could potentially be used in smart crime detection systems for preventive policing, which would also employ CCTV surveillance systems and facial recognition technologies (Sellers & Arrigo, 2009; Byun, Nasridinov & Park, 2014). Citizens, law enforcement officers, correctional officers and even incarcerated offenders could be fitted with wearable, or implantable, body-​centric RFID sensor tags that would measure varying biological states (e.g. heartbeat, respiration or internal body temperature) of a person (Sellers & Arrigo, 2009; Byun, Nasridinov & Park, 2014). The sensors on body-​centric RFID chips can also track user location through GPS in real time, which enables CCTV and facial recognition technologies in the area to activate in order to better document and assess accurate emotion detection to determine if a law enforcement officer or correctional officer is in a high-​stress situation (e.g. encounter with criminal suspects at scene of a crime; Sellers & Arrigo, 2009; Byun, Nasridinov & Park, 2014). Theoretically, such a system could also be used by law enforcement to locate missing persons, kidnap victims, runaway youth and abducted children (Sellers & Arrigo, 2009). In institutional corrections, the Guardian RFID corrections system is a personnel management tool, as well as real-​time inmate tracking, cell checking, security monitoring and record keeping system that creates a digital record to automate tasks and workflow management (Halberstadt & La Vigne, 2011; Johnson, 2011; Cynthia, Priya & Guptha, 2018). Exclusion zones can be created with the RFID system to alert officers when certain inmates are in proximity to prohibited locations to prevent fights (especially between rival gangs), sexual assaults and other unauthorized activities (Halberstadt & La Vigne, 2011). In community corrections, RFID-​fitted anklet transponders have been used for electronic compliance monitoring of offenders under house arrest, and GPS surveillance anklets were later implemented to track offenders when they move beyond their homes with sensor capabilities that can track a person to within 5 to 15 feet (Nellis, 2006). Now, subdermal RFID implantable chips could replace external GPS surveillance anklets that currently track and monitor pretrial defendants, probationers, parolees and released sex offenders and allow them to avoid some of the direct stigma associated with

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wearing external electronic monitoring anklets, because they will be invisible to others and undetectable by the offender (Rosenberg, 2008; Henne & Troshynski, 2013). In addition, subdermal RFID chips are more difficult to tamper with and would significantly aid in the digital registration and surveillance of sex offenders required by Jessica’s Laws (Rosenberg, 2008; Henne & Troshynski, 2013). According to the International Civil Aviation Organization (ICAO), RFID is already embedded in e-​passport books and e-​passport cards for more than 490 million citizens from over 100 participating states to enhance securitization efforts worldwide (ICAO, 2011). These RFID chips store the citizen’s biographical information, as well as a digital photograph, biometric information of the passport’s owner, and a cryptographic signature (ICAO, 2011). National ID cards (e.g. Real ID enhanced driver’s licenses) and e-​passports, as ‘mobile identifiers’, automatically evoke surveillance, and the concerns over security and citizenship that follow (Amoore, 2008, p. 23; Lyon, 2010). In a globalizing world, risk threats materialize from multiple uncertainties, especially those that are perceived to present unknown dangers, such as irregular immigration, refugees and international terrorism (Sellers & Arrigo, 2016; Lyon, 2010). Such national ID systems may permit a global surveillance system to emerge that offers interoperability through ‘governing by identity’, whereby national identity and citizenship become mechanisms in securitization efforts aimed to prevent and pre-​empt crime (Zedner, 2007; Amoore, 2008, p. 23; Lyon, 2010). Thus, RFID embedded e-​passports or national ID cards empower border control and federal intelligence agencies with the ability to render travelers ‘visible, identifiable, and locatable’ (Amoore, 2008, p. 28; Lyon, 2010).

Human implantation As discussed earlier, RFID chips have been implanted into animals for both health and commercial reasons (Troyk, 1999; Foster & Jaeger, 2008). Digital Angel Corporation and its subsidiary, Verichip Corporation, developed the first implantable RFID chip for human use (Foster & Jaeger, 2008; Sellers & Arrigo, 2009). Human implantable chips consist of a glass tube about the size of a grain of rice that encapsulates the RFID microchip, circuitry and microcoil transponder, and it can be inserted just beneath the skin in a person’s hand or near the triceps on the back of one’s arm (Albrecht & McIntyre, 2005; Sellers & Arrigo, 2009). Enthusiasts of human ‘biochipping’ continue to grow in numbers primarily because of the utter pragmatism, expediency and

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convenience such technology promises (Brown, 2019; Walt, 2019). The allure of no longer needing to rely on bulky sets of keys or numerous plastic cards to accomplish the mundane tasks of one’s daily life is quite seductive (Brown, 2019; Walt, 2019). Currently, Biohax International is dominating the market of implantable RFID chips for humans (Brown, 2019; Walt, 2019). Roughly 4,000 people in Sweden have volunteered to be chipped, because ‘biohacking’ their bodies permits them to now unlock their homes, access office buildings, open office doors, gain access to their cars, start their cars, access their gyms, pay for train fare, log onto their computers, pay for items in vending machines, use photocopiers, provide an address for bitcoins and verify identity with a simply wave of one’s hand (Brown, 2019; Walt, 2019). Chipped individuals can even share information on social media sites (e.g. LinkedIn), by merely touching a person’s smartphone (Walt, 2019). In the US, Wisconsin-​based technology company, Three Square Market, recently claimed to have chipped 673 people voluntarily, including 85 of its own employees for personal data retention and security access (Walt, 2019). NewFusion, a Belgian technology and marketing company, is also creating an ‘opt in’ voluntary chipping program for their employees to use for secure access to buildings and computer systems (Rodriguez, 2019). In the past, companies, such as PervCom and Humanyze, helped major corporations like Amazon and Bank of America incorporate RFID sensor technology to track employees, monitor safety and measure productivity (Rodriguez, 2019). Recently, Biohax International partnered with Verisec to develop an electronic-​identity platform that would allow RFID biochips to store identification documents (e.g. passports and driver’s licenses), sense biological states for clinical data and be used for regular electronic payments anywhere (Walt, 2019). So no more lost keys, misplaced ID cards or forgotten wallets. RFID can give a person the peace of mind in knowing all these things are in one place, the microchip in one’s hand. Thus, the human body is the new platform for RFID applications, enabling people to become digital in a digital world (Walt, 2019).

Theoretical analysis In a pre-​crime society, or an ultramodern era, technologically advanced and sophisticated cultures become forward-​looking and focused on the logics of security (Zedner, 2007; Ashworth & Zedner, 2015; McCulloch & Wilson, 2015). Previously, crime was conceived

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principally as harm or wrongdoing committed by individuals or groups, which was followed by reactive responses from the criminal justice apparatus (Zedner, 2007). For a pre-​crime society, crime is perceived as inevitable so this traditional temporal perspective is reorganized to forecast and prevent crime before it occurs through calculation, risk assessment, surveillance, pre-​emptive policing, crime mapping, crime analytics and digital tracking and monitoring of citizens all in the pursuit of securitization (Zedner, 2007; Ashworth & Zedner, 2015; McCulloch & Wilson, 2015). In this society, the activities of risk-​ avoidance and threat analytics represent governing modes of human interaction (Beck, 2009). Technology is pivotal to normalizing and nurturing this crime control enterprise and is increasingly important to both the function and our understanding of the justice process (Zedner, 2007; McCulloch & Wilson, 2015). Additionally, security becomes a commodity to be sold for profit and protection transforms into a public good (Zedner, 2007). Thus, the logic of security has less to do with responding to, prosecuting or punishing crime; instead, it seeks to demand earlier interventions, reduce opportunity structures, target harden and enhance surveillance before the commission of a crime (Zedner, 2007; Ashworth & Zedner, 2015). However, such securitization comes at a cost (Ericson & Haggerty, 2008); specifically, the spheres and domains of everyday life are increasingly subjected to over-​criminalization and over-​policing by the growing surveillance state (Presdee, 2001). Neoliberal globalization is intimately connected to security politics of both the pre-​crime society and the new post-​panoptic dynamics emerging from the complex governmentalities that run between the state and the market, especially in the wake of the post-​9/​11 war on terror (Gane, 2012; McCulloch & Wilson, 2015). Now state governments seek to increase security by strengthening technologies and information-​gathering on individuals belonging to ‘risky’ or ‘suspect’ groups as they are pressured to think and act pre-​emptively to emerging global and local threats to security (Zedner, 2007; McCulloch & Wilson, 2015). In the past, classical economic liberalism acknowledged a relationship between the state and the market in which market freedoms allow exchange to determine the value of goods and services, and the utility and power of government was limited (Foucault, 2008; Gane, 2012). Under this arrangement, the goal of government was to exert ‘control, constraint, and coercion’ to guarantee the freedom of the market and the free exercise of property rights (Foucault, 2008, p. 67; Gane, 2012). Panoptic modes of surveillance served as disciplinary measures upholding conditions of freedom under

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classical economic liberalism (Foucault, [1977], 2008; Gane, 2012). However, disciplinary societies marked by panoptic models of liberal governmentality were short-​lived (Deleuze, 1995; Bauman, 2000; Gane, 2012). The neoliberal restructuring of global capitalism continued to promote a laissez-​faire culture limiting the governmental power of the state to intervene in the market or entrepreneurial activities of individuals (Gane, 2012). However, global neoliberalism also rolled out ultramodern forms of governmentality that operate through novel mechanisms of surveillance aimed at infusing market principles of competition, personal accountability and audit culture into all spheres of social and cultural life (Bauman, 2000; Foucault, 2008; Gane, 2012). As such, the state is to be marketized in its totality, whereby it justifies itself to the market by promoting new regimes of accountability (Gane, 2012). Contemporary neoliberalism exerts a ‘new system of domination’ through ‘control mechanisms’, because unlike fixed disciplinary institutions of the past, techniques of power in the digital age of control society require computer-​based systems of electronic tagging (i.e. RFID) ‘to make sure everyone is in a permissible place’ (Deleuze, 1995, pp. 181–​82). As unbound market forces of consumerism are unleashed by way of liquid modernity’s process of individualization of power and politics, newly responsibilized citizens are seduced into willingly embracing these mobile forms of synoptic surveillance that can track or fix ‘dividuals’ in real time and space (Deleuze, 1995; Bauman, 2000; Gane, 2012). RFID not only allows vertical surveillance but also horizontal surveillance where individuals and groups gather information on each other, as well as self-​surveillance where people purposefully monitor and regulate themselves (Gane, 2012; Nemorin, 2017). Thus, structural top-​down surveillance is simultaneously interlaced with individual bottom-​up surveillance (Boyne, 2000; Lee, 2015). This contemporary ‘surveillant assemblage’ is rhizomatic (like a tree’s root system) because it coalesces systems of surveillance by combining practices and technologies into an integrated whole (Haggerty & Ericson, 2000). The information collected from the dataveillance of citizens permits ‘data doubles’ to be developed for profiling purposes (Lewis, 2003). Thus, this surveillant assemblage functions by abstracting human bodies from their territorial settings and relocating them into discrete informational flows that are subsequently reassembled into ‘data doubles’ to be viewed, measured, described, categorized, classified, sorted and ranked in order to determine potential dangerousness, risks, threats or hazards that may impede securitization efforts (Deleuze & Guattari, 1994; Haggerty

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& Ericson, 2000; Sellers & Arrigo, 2017). Therefore, the control produced from the pre-​crime society enables power to be modulated through passwords and codes that allow individuals to pass through the ‘mesh’, or database, which is the key ‘instrument of selection, separation and exclusion’ that opens and closes by varying degrees to authorize access to some while incapacitating others (Deleuze, 1995, pp. 178–​79; Bauman, 1998, p. 51; Bigo, 2008). The previously mentioned array of practical applications for RFID reveals the everyday conditions of digital surveillance that permeates citizens’ lives across the globe, as well as the appeal of convenience, expediency, simplification and efficiency they promise. The usage capabilities of RFID are expanding into virtually everything, creating industries of dataveillance that generate cultures of control. These global mechanisms of surveillance extract personal data fragments from the daily activities of subjects and expose the intimacies of their social lives and actions to scrutiny from a myriad of observing entities through increasingly innovative ways (Smith, 2012). Nevertheless, how are people so easily seduced into allowing physical spaces and the privacy of their own bodies to become embedded with sensor devices that will detect human activities to create a digitized reality of human existence? To understand the current phenomenon surrounding human implantation of RFID, one must investigate the complex sociocultural relations of the Quantified Self movement and how it helps to facilitate the transformation from liberal (panoptic) to neoliberal (post-​panoptic) governmentalities in a globalizing world (Gane, 2012; Lupton, 2016). The Quantified Self movement promotes a ‘surveillant mentality’, in which responsibilizing initiatives enacted by social institutions, corporations and governmental bodies foster a culture of dataveillance whereby self-​exposure and transparency become socially and culturally desirable and precautious discretion and confidentiality are trivialized (Smith, 2012, p. 5; Lupton, 2016). This movement originates from the emerging concept of digitized ‘self-​tracking’ and ‘lifelogging’, where individuals use digital technology to collect personal data for documenting certain aspects of their lives to facilitate self-​reflection and self-​care as a means to improve their lives (Lupton, 2016, p. 102). However, initial forms of ‘private’ self-​tracking, which were voluntarily self-​initiated by individuals for personal reasons, have become diversified by ‘function creep’ in which the collection and analysis of one’s personal data through self-​tracking practices are now encouraged and implemented in numerous social contexts and institutions beyond mere personal reasons, as a product of the

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neoliberal audit culture (Lupton, 2016, p. 103; Gane, 2012). ‘Pushed’ self-​tracking deviates from ‘private’ self-​tracking’s motivations in that inducement for participating in self-​imposed dataveillance is in response to encouragement from an external source, such as concerned parents or school officials wanting to monitor children’s learning and predict future achievement outcomes or employers using financial incentives to promote workplace health, employee morale and productivity (Lupton, 2016, p. 108). Additionally, insurance companies may urge customers to partake in digital self-​tracking to monitor driving behavior or health, which might lower their calculation of risks and result in lower premiums (Lupton, 2016). ‘Communal’ self-​tracking refers to a growing concept of ‘quantified us’, where a community of self-​trackers publically shares their data on social media platforms to cultivate collaborative motivation, support or friendly competitiveness among fellow self-​trackers (Lupton, 2016, p. 108). Communal self-​ tracking incorporates additional notions of participatory democracy, citizenship and community (Lupton, 2016). Conversely, ‘imposed’ self-​tracking is steadily becoming an expectation in various institutional settings, especially in the workplace where several companies across banking, technology, manufacturing, pharmaceutical and healthcare industries are mandating employees to wear RFID badges with sensor technology to record sound (including tone of voice and who they speak to, and duration), geolocation, physical movement and even biological metrics (e.g. heart rate) to collect data on worker habits and efficiency in efforts to reduce costs (Moore & Robinson, 2016; Lupton, 2016, p. 110). Coercive, ‘imposed’ self-​tracking is also occurring in schools with the issuance of contactless RFID badges to monitor students, as well as RFID-​ based GPS monitoring of incarcerated inmates, probationers, parolees, recovering addicts and adolescents under the custody of criminal justice, addiction treatment and family law agencies (Lupton, 2016). Lastly, ‘exploited’ self-​tracking refers to the legal, or illegal, repurposing of individuals’ personal data for the financial benefit of other interested parties, such as retailers seeking to profit from monitoring consumer habits and preferences or cyber-​criminals stealing data for fraudulent or blackmailing purposes (Lupton, 2016, p. 111). In fact, RFID technology is prone to basic cloning and counterfeiting security attacks that pose a threat to privacy of individuals and organizations, which may include violating location privacy, identity theft, corporate espionage, denial of service, spoofing, computer virus susceptibility and cracking (criminal hacking) of support systems or databases (Roberts, 2006; Sellers & Arrigo, 2009). Of course, the state can also ‘exploit’

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self-​tracking data for surveillance reasons and to promote the new systems of control and securitization under the pre-​crime society. In the digital age, mass surveillance of citizens is a role embraced globally by corporations, private businesses and governmental intelligence organizations (Lee, 2015). The vast amounts of data collected on citizens can be used to create profiles and Strategic Subject Lists that sort people into ‘suspect’ groups in need of further monitoring, immediate control or exclusion (Lewis, 2003; Ferguson, 2017; Sellers & Arrigo, 2017). If emergent patterns in the data suggest substantial risk to order and safety, then a subject could be pre-​ emptively incapacitated (Lewis, 2003; Ferguson, 2017). These banoptic surveillance techniques aid in determining who warrants additional surveillance in order to sort those who merit inclusion from those who warrant exclusion (Bigo, 2008). These practices embody new forms of social sorting and people-​making culture. Therefore, the Quantified Self movement acts as the sociocultural mechanism needed to interactively and competitively seduce individuals into becoming willful participants in the post-​panoptical governmentalities of the pre-​crime society that fosters permanent vigilance (i.e. normalized and diversified surveillance), clinical captivity (i.e. neoliberal governance) and societal dis-​ease (i.e. hyper-​securitization) through the widespread adoption of RFID implants (Gane, 2012; Sellers & Arrigo, 2017). Consequently, RFID technology presents opportunity for the governing logics of this surveillant assemblage to be systematized and for the pre-​crime society to flourish globally.

Conclusion In 2020, China’s Social Credit Score System is expected to become functionally operational, and it will utilize mass surveillance, facial recognition technology and big data analysis to socially sort and rank citizens based on their daily behaviors and social interactions, especially deviant or unlawful activities (Ma, 2018). This single unified system is intended to standardize the assessment of citizens’ and businesses’ economic and social reputation through a system-​wide social credit score (Ma, 2018). The value of a person’s social credit score can fluctuate based on the monitored behaviors one engages in on a daily basis. For example, reckless driving, jaywalking, quarreling with your neighbor and any other behaviors deemed antisocial, criminal or disorderly will devalue one’s social credit score and lead to punishment (Ma, 2018). Punishment may include, banning a person from flying or

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taking a train, reducing one’s Internet speed, banning one’s children from the best schools, preventing one from promotion, and being publically shamed (Ma, 2018). Otherwise, good behaviors such as, donating blood, donating to charity or volunteering for community services will increase the value of one’s social credit score and the subsequent perks that follow, such as discounts on energy bills, better interest rates or more matches on dating websites (Ma, 2018). This system is the epitome of ‘societal dis-​ease’ whereby the values of prediction, precaution and pre-​emption are preeminent, and the production of a responsibilized citizenry through hyper-​securitization and the training of bodies through bio-​digital control are inescapable (Arrigo, Sellers & Sostakas, 2020). RFID biochips would revolutionize such a system’s tracking and monitoring capability, and it is not difficult to perceive widespread adoption of such systems along with the proliferation of human implanting across nation states. Liberty and privacy would be affected considerably. Historically, citizens engaged in a careful balance when weighing human desires for liberty and privacy against security from threats, both real and imagined (Sellers & Arrigo, 2009). However, the post-​9/​11 world experienced a shift wherein optimal freedom and liberty were severely compromised for the objective of containing risk, exerting control over ‘suspect’ groups and preventing threats to safety (Sellers & Arrigo, 2009). How much liberty should populations surrender in return for security gained, especially when privacy is recast as a safety problem, synonymous with risk, which is only solved through increased surveillance (visibility)? The rhetoric promoting RFID human implantation is strategic, seductive and compelling, particularly for growing populaces desiring immediate and convenient resolutions to social problems and everyday burdens. People consistently and predictably sacrifice quality for convenience. Thus, it is becoming gradually clear that not much thoughtful consideration is being given to the current decisions regarding how risk calculations should weigh individual privacy and collective liberty against the invasiveness of RFID securitization. Regardless of recommendations for industry self-​regulation, governmental legislation or even ‘kill switch’ functions that disable RFID tags after consumer purchase (Turri, Smith & Kopp, 2017), what incentive truly exists that could dissuade the state and corporate actors from seizing complete control over technologies that offer them total dominion over the citizenry? Arguments for human implantation are enticing to many, especially when this technology is increasingly integrated into practically everything and everywhere, and some cultures have already replaced their wallets and key chains

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with smartphones. At some point, the smartphone also becomes too cumbersome in comparison to RFID biochips. Likewise, the concepts of citizenship, state sovereignty and the rights to full membership to society are being reevaluated as the torrents of neoliberal globalization reshape the world (Sellers & Arrigo, 2016). Globalization produced increased flows and networks of activity, interaction and exercise of power, which have also resulted in a re-​ emergence of nationalism, geopolitics and a hardening of state power (Lyon, 2010). The mechanisms of control by way of the assemblage of technologies of domination present a new social sorting logic wherein national citizenship again becomes the tool by which individuals are either included or excluded (i.e. rendered stateless, risky or dangerous; Lyon, 2010). Because without control over the movement of peoples and national citizenship, governments ultimately fear that the fortress of the nation-​state system might crumble in the currents of globalization (Schinkel, 2009; Sellers & Arrigo, 2016). The resulting hegemony does not further an ethic of citizenship whereby human rights and dignity are tied to humanity and advance human connectedness. Instead, it perpetuates the hermeneutics of suspicion (citizen-​as-​suspect) that promote forms of human relating exemplified through harms of reduction and repression produced by cultures of control and industries of dataveillance (Arrigo, Sellers & Sostakas, 2020). References Abel, E.E. (2016). Ubiquitous computing: An assistive surveillance on in and out patients with mental illness via RFID. British Journal of Mathematics & Computer Science 17 (3): 1–​15. Al-​abassi, S.A.W., Al-​bayati, K.Y.A., Sharba, M.R.R. & Abogneem, L. (2019). Smart prepaid traffic fines system using RFID, IoT and mobile app. Telkomnika 17 (4): 1828–​37. Albrecht, K. & McIntyre, L. (2005). Spychips: How Major Corporations and the Government Plan to Track Your Every Move with RFID. Nashville, TN: Nelson Current. Amoore, L. (2008). Governing by identity. In C.J. Bennett & D. Lyon (eds.) Playing the Identity Card: Surveillance, Security and Identification in Global Perspective. New York, NY: Routledge (pp. 21–​36). Arrigo, B.A., Sellers, B.G. & Sostakas, J. (2020). Pre-​crime, post-​ criminology, and the captivity of ultramodern desire. International Journal of the Semiotics of Law 33 (2): 497–​514. Ashworth, A. & Zedner, L. (2015). Preventive Justice. Oxford, UK: Oxford University Press.

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Afterword: ‘Pre-​Crime’ Technologies and the Myth of Race Neutrality Pamela Ugwudike

In these closing remarks, I wish to foreground the contribution of this text to the study of pre-​crime culture and associated ‘hyper-​ securitization’ technologies. I also wish to highlight an emerging agenda in this field, which focuses on the racial implications of data-​driven AI technologies fueling the growth of the pre-​crime culture. In terms of this timely volume’s fundamental contribution, it certainly provides a solid foundation on which future theorizations and empirical analysis of ‘pre-​crime’ technologies can build to broaden current understanding of their cultural, social, legal and ethical dynamics. To take these a step further, the nexus of the technologies and racial justice is a key challenge that deserves urgent interdisciplinary scrutiny. Indeed, the importance of interdisciplinarity in this field cannot be overstated, primarily because it can provide insights into the societal impacts of the technologies, building on themes distilled from the humanities, the social sciences, computer sciences and other fields. This is evident in the growth of university departments offering courses in science, technology and society (STS) studies. Specifically, an exploration of how pre-​crime technologies and racial justice intersect requires critical analysis of key interrelated logics legitimizing or at least providing the impetus for the mass proliferation of the technologies. I conceptualize the logics as: neutrality, neoconservative and neoliberal logics (see also Ugwudike, 2020). The

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importance of unraveling these rationalities cannot be overstated in the current digital age. As Marc Schuilenberg persuasively argues in Chapter 2 of this volume, data-​driven algorithms are using patterns in large-​scale data to visualize and construct the social world in particular ways while operationalizing governance strategies in an increasing array of contexts. Pat O’Malley and Gavin Smith pick up this theme in Chapter 3, in their analysis of the nexus of pre-​crime and control via a ‘preventive justice’ model that emphasizes risk-​reduction on the basis of algorithmic forecasts of future probabilities. Parts III and IV of this volume also address this issue albeit with greater focus on how states are mobilizing the technology for surveillance and securitization, driven by ‘big data’ analytics, and enabled by particular scientific models and political imperatives. The impact of the algorithms on key aspects of social life has been described as constitutive of ‘algorithmic governance’, which is a mode of governance that is exploiting the benefits of the technological innovations enabling the analysis of large-​scale data for commercial use, staff recruitment, risk prediction in justice systems and other purposes, all of which exercise some form of power and control over people’s lives. ‘Algorithmic governance’ is also inherently technocratic since it involves the ‘machine-​ like’ specialization of discrete tasks to enhance the efficiency of governance techniques (Danaher et al, 2017). A further justification for investigating the logics on which the technologies are built and applied is that their potential to artificially inflate the risk ratings allocated to certain minorities including black people, provoking the digital racialization of risk, deserves considerable attention. As I have argued elsewhere, the digital racialization of risk ‘refers to the overprediction of recidivism risks associated with racialized groups, particularly black people, and the concomitant ossification of racial ideologies that depict this group as “dangerous” and “risky” ’ (Ugwudike, 2020). The digital racialization of risk exposes affected groups to higher risks of criminalization than others. Therefore, recognizing and remedying this problem has become particularly pertinent in the wake of the Black Lives Matter protests that have highlighted the problem of racially biased policing and the need for criminal justice reform in a number of jurisdictions, particularly the US. Here, I focus on the data-​driven algorithms animating what the editors of this volume rightly conceptualize as ‘pre-​crime analytics’, and operationalizing risk-​focused governance. I demonstrate how key logics underpinning some of the algorithms intersect with the digital racialization of risk. With the advent of a ‘digital age’, advanced variants

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of the technologies have emerged, with some possessing artificial intelligence capabilities.

Neutrality logics As I have also noted elsewhere (Ugwudike, 2020), the data-​driven algorithms now informing decision-​making, predictions, surveillance practices and other governance activities are ostensibly neutral in so far as they do not explicitly refer to sensitive characteristics such as race and gender, as defined by national and international anti-​ discrimination laws of which the Equality Act of England and Wales 2010 represents an example. However, this is a neutrality logic that is increasingly being called into question by a large corpus of theoretical and empirical studies that indicate that the systems are neither gender neutral (e.g. Hamilton, 2019) nor race neutral (e.g. Angwin & Larson, 2016; Ugwudike, 2020). In Chapter 12 of this volume, Terry Kupers underscores this point in a discussion about the application of such technologies in custodial institutions and the ways in which algorithmic depictions of prisoner violence, though ostensibly scientific, are racially biased in that they conflate problems such as danger, disease and disorder with racial difference. Indeed, studies now show that the technologies can inadvertently perpetuate stereotypes and trigger the digital racialization of risk as is the case when predictive algorithms overpredict the recidivism risk of black people compared with other groups and expose black people to unwarranted criminal justice intervention (Angwin & Larson, 2016; Hao & Stray, 2019; Lum & Isaac, 2016). Specifically, the studies reveal how data choices can bias algorithmic outputs and produce disparate outcomes. For example, in justice systems, some data-​driven algorithms that predict locational or individual risk rely on administrative data1 such as arrest datasets that can embody racially biased decisions. This is a design choice that is implicated in biased algorithmic outputs. To illustrate this problem, the predictor variables commonly used by the generic predictive algorithms now applied internationally for risk of recidivism prediction include family circumstances and antisocial attitudes (e.g. Hamilton, 2015). Predictor variables such as these, which are selected on the basis of subjective choices and principles that set the criteria for criminogenic or non-​criminogenic family circumstances, can disadvantage minorities. For example, the idea that an individual is more criminogenic than another because of a history of parental imprisonment would disadvantage black people given their over-​ representation in criminal justice statistics across several jurisdictions

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where such technologies are applied (Ministry of Justice, 2017; Bureau of Justice Statistics, 2018). Furthermore, data variables that differentiate groups according to ‘attitudes to law enforcement’2 would similarly disadvantage minorities given the long history of racially biased policing and negative interactions between both parties. Moving away from risk of recidivism technologies, predictive policing algorithms that rely on predictor variables such as locational arrest rates can disadvantage certain minorities, again particularly black people who tend to reside in deprived areas with high policing activity (for an example in England and Wales, see Office for National Statistics, 2011). This places them in close proximity with police officers, with a higher chance of police intervention than other groups. Indeed, studies of predictive policing algorithms in the US show that the technologies that rely on policing data for predictions tend to identify inner-​city areas heavily populated by black people as higher risk locations than others (e.g. Lum & Isaac, 2016). These brief examples illustrate how data choices and predictor variables can operate as proxies for race despite the ostensible neutrality of predictive algorithms. In doing so, they can foment the digital racialization of risk by increasing the likelihood that the areas mainly populated by black people will attain high risk scores and be profiled as chronically criminogenic. Notwithstanding these well-​documented problems (see also Ensign et al, 2018), technologies created using advanced mathematical and computer science methods, are likely to be viewed as ostensibly scientific ‘value neutral’ tools and credible sources of criteria for categorizations and governance. It is also worth considering how forms of use, particularly problems relating to racially biased application of data-​driven algorithms further undermine any notion of the tools’ neutrality. Structured tools such as the OASys risk assessment tool applied in the UK, allow practitioners to contextualize risk assessments and effect a clinical override of algorithmic risk scores. But there is evidence that professional judgment can be biased (Ansbro, 2010) and discretionary override on the basis of welfarist concerns is often not exercised in favor of minorities (Chappell et al, 2012). Yet risk prediction technologies and processes are ostensibly neutral. The concept of algorithmic superiority captures the widely held belief in the neutrality of technologically derived knowledge (see, Logg et al, 2018). Nevertheless, the discussion so far shows that given their socio-​technical composition the creation and application of data-​ driven systems do not occur in a vacuum. Subjectivities or personal choices determine their foundational theories, data configurations, algorithmic models and forms of use. Fortunately, critical empirical and

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theoretical work in this area is evolving into a large corpus of research from diverse disciplines such as criminology (Hannah-​Moffat, 2018; Ugwudike, 2020) legal studies (Starr, 2014) as well as computer and data sciences (Hao & Stray, 2019). Together this critical body of work is calling into question the perceived neutrality of the technologies.

Fusion of risk-​focused penality, neo-​conservatism and neoliberal logics To understand how data-​driven algorithmic technologies foment the digital racialization of risk, it is also useful to critique their theoretical foundations, not least because some of their underpinning theories employ discursive frames that can racialize risk. For example, researchers have designed machine learning models that can differentiate between criminal and ‘normal’ features, resurrecting the field of physiognomy that has been discredited for its pseudoscientific claims about links between human attributes (for example facial features), racial difference and risk of criminality (e.g. Wu & Zhang, 2016). Similarly, the generic risk of recidivism technologies commonly used in jurisdictions such as the UK and US rely in part on astructural socialization theories rooted in neoconservative logics that essentialize socio-​economically deprived minorities by ascribing racialized immanent qualities including criminality to them (e.g. Murray, 1990). Socialization theories worth considering in this context include those that trace the etiology of crime to deficient bonds with significant others and institutions that can inculcate societal norms and requisite social skills. Rooted as they are in Western conservative ideals including beliefs about the proper structure of normative or conventional institutions such as the family, the technologies can be deemed insensitive to cultural diversity. The problem of cultural insensitivity means that certain minorities can be misidentified as high-​risk/​pre-​criminals because their profile is inconsistent with Western norms (Maurutto & Hannah-​Moffat, 2005). Andrew Day (this volume) provides an insightful account of this dimension of the digital racialization of risk in his analysis of the socio-​political contexts of risk assessment. Added to the impact of socialization theories on risk of recidivism technologies, other studies suggest that predictive policing algorithms based on the near repeat thesis can foment biased predictions. The core assumption of this thesis is that a successful crime event typically sparks other spatially and temporally proximate crimes (Perry, 2013) due to the offender ’s knowledge of the location as well as their perception

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THE PRE-​CRIME SOCIETY

that the potential benefits of offending outweigh the costs. Therefore, predictive policing algorithms that are driven by this thesis stand the risk of consistently predicting crime risks in the same locations on the basis of near repeat logics. Studies have indeed shown that such predictive algorithms are prone to feedback loops whereby the new crimes that police observe when dispatched to an area are fed back into the algorithm, triggering further crime risk predictions in the same areas (example, Ensign et al, 2016). This problem has been noted when such algorithms are deployed in deprived, over-​policed areas that are heavily populated by certain minorities such as black people and it exposes them to over policing and higher risks of criminalization than other groups (example, Lum & Isaac, 2016). What these suggest is that, to understand the capacity of predictive algorithms to foment the digital racialization of risk, it is important to consider the role of their underpinning theories or inscribed rationalities. The embeddedness of predictive algorithms in risk-​focused neoliberal logics must also be considered in future studies of the ‘pre-​crime culture’. Indeed, the aforementioned neoconservative logics underpinning predictor variables have synergies with neoliberal ideals of individualism and minimal state intervention in social welfare provision. Thus, the neoliberal logics reinforce neoliberalism’s minimization of structural inequalities and this explains why they exclude structural deficiencies such as entrenched inequalities from their etiological analysis. In doing so, they obfuscate the need for structural-​level solutions. Instead, their proposed solutions are typically myopic and tend to emphasize punitive regulation rather than structural reforms. Illustrating this and also highlighting the neoliberal orientation of the technologies, governmentality scholars have longed argued that actuarial assessment tools (many of which have since evolved into data-​driven predictive technologies) offer governments a means of regulating and controlling groups whose circumstances do not reflect neoliberal ideals (e.g. Rose & Miller, 2010). In doing so, the scholars draw attention to the nexus of rapid technological development and neoliberal governance. Central to this is the tendency of the technologies to ‘responsibilize’ individuals by holding them accountable for addressing their social and welfare needs while minimizing the state’s role. This mode of governance bears the hallmarks of Garland’s (2001) ‘responsibilisation’ thesis, which he developed in his analysis of the penal cultures that emerged in shift away from post-​war expansionism and the rehabilitative ideal on both sides of the Atlantic. With this mode of governance, groups labeled as lacking neoliberal ideals of self-​ regulation and self-​sufficiency can be depicted as ‘risky’ and deserving

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of punitive risk-​focused intervention, a theme that is captured by David Palazzi in Chapter 4, in his analysis of the ‘cyber-​construction’ of certain groups as the risky ‘other’ requiring governance and control. Such risk-​focused profiling and penal intervention constitute modes of governance in that they are the means by which individuals are held accountable for how well they accomplish the risk-​reduction role imposed on them. In their seminal analysis of the rise of this mode of risk-​focused governance, Feeley and Simon (1992) conceptualize the risk-​focused management of minorities, primary black and Hispanic groups who mainly populate deprived inner-​city or urban areas in the US, as a new penology that emerged in the 1970s. They describe this mode of governance as the ‘managerial task that provides one of the most powerful sources for the imperative of preventive management in the new penology’.

Labeling and self-​fulfilling prophesies So far, we have seen that despite their facile neutrality, some of the technologies bolstering pre-​crime penality and governance are capable of fomenting the digital racialization of risk by depicting some minorities, particularly black people, as riskier than others. A harmful consequence of this is that, in itself, the digital racialization of risk can encourage the labeling and profiling of affected minorities and create a self-​fulling prophesy whereby excessive profiling artificially inflates criminalization rates, which in turn heighten risk scores. This problem can affect algorithms used for predicting recidivism risks and crime hotspots (e.g. Lum & Isaac, 2016). Kupers (Chapter 13 this volume) comments on this potential for predictive algorithms to provoke outcomes such as labeling and self-​fulling prophesies. It is a social problem that calls to mind the tenets of labeling theories and their emphasis on how negative labels, including those applied by the justice system trigger harmful effects, whether or not the labels are spurious (e.g. Becker, 1963). In sum, it is clear from the foregoing that when considering future directions for the study of pre-​crime culture and technologies, the ways in which they intersect with racial justice and broader social justice deserve critical scrutiny. Notes 1

2

Administrative datasets can comprise linked data from interactions with criminal justice services such as the court, police, and probation services, as well as other public authorities. See (Hamilton, 2015) for a list of some of the commonly used predictor variables.

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References Angwin J. & Larson, J. (2016). Bias in Criminal Risk Scores Is Mathematically Inevitable, Researchers Say. [online] Available at: https://​ www.propublica.org/​ a rticle/​ b ias-​ i n- ​ c riminal-​ r isk-​ s cores-​ i s-​ mathematically-​inevitable-​researchers-​say. Ansbro, A. (2010). The nuts and bolts of risk assessment: when the clinical and actuarial conflict. Howard Journal of Criminal Justice 49 (3): 252–​68. Becker, H. (1963) Outsiders: Studies in the Sociology of Deviance. New York, NY: Free Press. Bureau of Justice Statistics (2018). Prisoners in 2016. [online] Available at: www.bjs.gov/​content/​pub/​pdf/​p16_​sum.pdf. Chappell, A.T., Maggard, S.R. & Higgins, J.L. (2012). Exceptions to the rule? Exploring the use of overrides in detention risk assessment. Youth Violence and Juvenile Justice 11 (4): 332–​48. Danaher, J., Hogan, M., Noone, C., et al. (2017). Algorithmic governance: Developing a research agenda through the power of collective intelligence. Big Data and Society 4 (2): 1–21. Ensign, D., Fr iedler, S.A., Neville, S., Scheidegger, C. & Venkatasubramanian, S. (2018). Runaway feedback loops in predictive policing. Paper Presented at the Machine Learning Research. Conference on Fairness, Accountability, and Transparency 81: 1–​12. Feeley, M. & Simon, J. (1992). The new penology: Notes on the emerging strategy of corrections and its implications. Criminology 30: 449–​74. Garland, D. (2001). The Culture of Control. Oxford: Oxford University Press. Hannah-​Moffat K. (2018). Algorithmic risk governance: Big data analytics, race and information activism in criminal justice debates. Theoretical Criminology 1–​18. Hao, K. & Stray, J. (2019). Can you make AI fairer than a judge? Play our courtroom algorithm game. MIT Technology Review. [online] Available at: https:// ​ w ww.technologyreview.com/ ​ s / ​ 6 13508/​ ai-​fairer-​than-​judge-​criminal-​r isk-​assessment-​algorithm. Hamilton, M. (2015). Risk-​needs assessment: Constitutional and ethical challenges. American Criminal Law Review 231: 236–​39. Hamilton, M. (2019). The sexist algorithm. Behavioral Sciences & the Law 37 (2): 145–​57. Logg, J.M., Minson, J.A. & Moore, D.A. (2018). Algorithm Appreciation: People Prefer Algorithmic to Human Judgment. Harvard Business School, Working paper 17–​086. Lum, K. & Isaac, W. (2016). To predict and serve? Significance 13: 14–​19.

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Maurutto, P. & Hannah-​Moffat, K. (2005). Assembling risk and the restructuring of penal control. British Journal of Criminology 46: 438–​54. Ministry of Justice (2017). Statistics on Race and the Criminal Justice System 2016: A Ministry of Justice publication under Section 95 of the Criminal Justice Act 1991. London: Ministry of Justice. Murray, C. (1990) The emerging British underclass, Institute of Economic Affairs Health and Welfare Unit, Choice in Welfare Series, No 23. [online] Available at: http://​www.civitas.org.uk/​pdf/​cw33. pdf. Office for National Statistics (2011). 2011 Census analysis: Ethnicity and the Labour Market, England and Wales. [online] Available at: https://​ www.ons.gov.uk/p​ eoplepopulationandcommunity/c​ ulturalidentity/​ ethnicity/a​ rticles/e​ thnicityandthelabourmarket2011censusenglandan dwales/​2014–​11–​13. Rose, N. & Miller, P. (2010) Political power beyond the state: Problematics of government. British Journal of Sociology 61 (1): 271–​303. Starr, S.B. (2014) Evidence-​based sentencing and the scientific rationalization of discrimination. Stanford Law Review 66: 803–​72. Ugwudike, P. (2020). Digital prediction technologies in the justice system: The implications of a ‘race-​neutral’ agenda. Theoretical Criminology. https://​ j ournals.sagepub.com/ ​ d oi/ ​ a bs/ ​ 1 0.1177/​ 1362480619896006. Wu, X. & Zhang, X. (2016). Automated Inference on Criminality using Face Images. [online] Available at: https://a​ rxiv.org/​abs/​1611.04135v1.

491

Index References to figures appear in italic type; references to endnotes show both the page number and the note number (231n3). A Abrahamsen, R.  235, 237 academics, and big data use  416–​18 accountability  and automated risk assessment  185–​6 of the police  213, 214, 239–​40 private prisons  144 and responsibilization  488–​9 Ackerman, S.  283 active GPS tracking  326 actor-​network theory  95 actuarial justice  see risk assessment and actuarial justice Adam Walsh Act (AWA) 2006 (US) 318–​20, 325 Adams, I.  214 advertising, targeted  260–​1 Afghanistan, drones  433, 439 African Americans  and disenfranchisement  391–​2, 397 Jeffersontown murders  87–​8 see also race/​racism Agamben, G.  84, 85–​6, 87, 89, 168, 403 agent-​provocateur  273 Aggarwal, N.K.  94 AI-​based support and monitoring system (AI-​SMS)  352 Albert, M.  238 Alcatraz  86, 96n9 algorithmic governance  484 algorithmic skin  256, 262–​3 Alston, Philip  445 Al-​Alwi, Moath Hamza Ahmed  97n11 Amazon, facial recognition software  216 American Probation and Parole Association (APPA)  345, 349, 358 American Psychiatric Association (APA)  135, 136 Amoore, L.  xvii, 263, 468 analytical intervention  260

Anckarsäter, H.  141 Andrejevic, M.  232 Angola Three  309–​10 Anonymous (hacking group)  217 Anti Money Laundering/​Counter Terrorism Financing (AML/​ CFT)  236 anti-​plagiarism software  261–​3 antidepressants  130, 133, 137–​8, 139 antipsychotic medication  140 antisocial behaviors  76 Antisocial Personality Disorder (ASPD)  296, 305–​7 Aotearoa  see New Zealand architecture of discipline  44, 53 Arizona, electronic monitoring (EM)  329 Armstrong, A.  300–​1 Armstrong, G.S.  329 Arrigo, B.A.  308–​9, 373, 374 Arthur Liman Public Interest Program, Yale Law School  300 assemblage theory  37n10 Asset (assessment tool)  235 Association of State Correctional Administrators  300 AstraZeneca  140 atomism  129–​30, 145–​6 Attention Deficit Hyperactivity Disorder (ADHD)  137 Audit Commission (UK)  279 Augé, M.  164 Augur, H.  115 Austin, R.  394 Australia  anti-​plagiarism software  261–​3 high and low policing  233 international sharing of intelligence  277 risk assessment from indigenous perspective  186, 189–​93

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THE PRE-​CRIME SOCIETY

school digital surveillance  114 speeding offenses  75 Switching on Darwin program  77–​8 Automatic Number Plate Recognition (ANPR)  232 Azeni, H.  144–​5 B Babuta, A.  232, 241 Bachelard, G.  156, 170 Bacon, M.  166, 167 Bagaric, M.  356–​7, 359–​60 Bagshaw, E.  78 bail  182 Baldwin, J.  20 Bales, W.  300 Balkin, J.M.  27 Ball, J.  283 Ball, K.  111–​12, 243 banning powers  43–​4, 48, 49, 52, 474–​5 banoptic control  34, 456, 474 Bark (school safety company)  112 Bartollas, C.  155 Baudrillard, J.  24 Baylor medical system  134 B.C. Bombers  273–​4 Beccaria, C.  46 Becker, G.S.  270, 279 Beer, D.  239, 242 behavior modification  56, 263, 352 Benjamin, W.  447 Bennett, C.  399 Bennett Moses, L.  233 Bentham, J.  116, 163, 299, 375 Berger, P.  20 Bergson, H.  161 Bernstein, R.  157 Bersot, H.Y.  18 Best, S.  25 Big Brother Watch  114, 115 big data  409–​26 authenticity of  413–​14 benefits of  409–​12 challenges of  410, 413–​14, 418–​25 changes to data processing techniques  411 characteristics of  411 and civil liberties  425 and consent  419, 420–​1 contact-​tracing apps  421–​2 and criminological inquiry  416–​18 cybersecurity risks and implications  418–​20, 423 data shareholders framework  423 definition of  409, 411 and error bias  423–​4 and ethics  419–​20, 423 materiality and geography to  239

misinterpretation of  419 and policing  228, 232–​3, 239, 240–​3, 415–​16, 423–​4 privacy issues  418–​19, 420–​3 and private sector  414–​16, 423 racial bias  423–​4 user power over own data  422–​3 see also sex offender monitoring Big Data Research and Development Plan (US)  411 Bigo, D.  228, 230, 231, 232, 239, 241 Binney, W.  281 bio-​power  55, 167, 443 see also radio frequency identification (RFID) Biohax International  469 biometrics  215, 256–​7, 341–​2, 468 see also facial recognition technology Bittner, E.  46 Bjerkeset, O.  144 Black Lives Matter protests  217, 446 Blewett, L.  140–​1 blogs, big data from  418 Blood Alcohol Content (BAC) levels  68–​9 BlueLeaks  217 Bluetooth  421–​2 body-​worn cameras (BWCs)  213–​14, 215 Boitel, C.  141 Bonelli, L.  228, 230, 231, 232, 241 Bonta, J.  181, 193–​4 Border Agency (UK)  236 Bourdieu, P.  169, 228, 231, 234–​5, 236–​7, 238, 241, 242 Bourgois, P.  167, 168 Bowker, G.C.  263 boyd, d.  252 Bratton, William  207–​8 Brayne, S.  239, 240, 243 Bring Your Own Device schemes  114 British Security Industry Association  210 Brodeur, J.P.  229, 230, 233, 272 broken windows policing  207–​8 Brown, G.R.  215 Brown, M.  xxi, 191, 192 Bruce, Catherine  274 Brunson, R.K.  208 BRUSA Agreement (British United States of America Agreement)  276–​7 Brynjolfsson, E.  414–​15 bureaucracy/​bureaucratic field  164, 206–​7, 231, 234–​8, 401 Burnap, P.  416 Burris, S.  48 Bush, George W.  396–​7, 438 Bush, Jeffrey  87–​8 Butler, J.  441 Button, D.M.  334 Byfield, N.P.  206

494

Index

C California  data privacy rights law  421 electronic monitoring (EM)  326–​7, 327–​8, 329, 331 risk assessment court case  185–​6 cameras  body-​worn cameras (BWCs)  213–​14, 215 CCTV  77, 115, 118, 210–​11, 214–​15, 234, 254–​6, 284 dashcams  212–​13, 215, 215 drones  445–​7 mass surveillance of  283 in schools  115–​16, 118 speed cameras  70–​5, 76, 77 see also police dataveillance and cameras Cameron, H.  253, 256, 257 Cammett, A.  393 Canada  correctional risk assessment  181 international sharing of intelligence  277 national security intelligence  273–​4, 276, 281 Royal Canadian Mounted Police (RCMP)  273–​4, 276 sex offender registry and notification (SORN)  333 Canadian Security Intelligence Service (CSIS)  276 Canguilhem, G.  263 Cao, W.  460 capable guardianship logic  317 capital logic  21–​2 captivity  17–​18, 20, 22, 23, 34–​5, 309 Carey, Z.  239–​40 Carrington, K.  xx Carvin, S.  440 Casella, R.  107, 110, 120 Castel, R.  63–​4 CCTV  law enforcement use of  210–​11, 214–​15, 234 mass surveillance  284 in schools  115, 118 Switching on Darwin program  77 young people’s experience of  115, 118, 254–​6 Center for the Study of Pathologically Violent Individuals, UCLA  304–​5 Central Intelligence Agency (CIA) (US)  275, 283–​4, 439 Chamayou, G.  434, 438, 439, 442, 445 Chamberlain, A.W.  329 Chan, J.  233 Chavis, K.N.  209 Chen, H.  94

Chen, M.  409 Children’s Internet Protection Act (US)  113 China, social credit system  78, 114–​15, 474–​5 Choi, H.  252 Choi-​Kain, L.W.  128 Church Committee (1976) (US)  269, 274–​6, 277–​8 CIBA  137 cinematic shock  91–​5 citizenship  476 see also disenfranchisement civil death, concept of  389–​90, 395–​6 Clarifying Lawful Overseas Use of Data (CLOUD) Act (US)  xxii–​xxiii Clarke, R.  111, 203, 250 closed-​circuit television  see CCTV Cloud, W.  169 CMS (Centers for Medicare and Medicaid Services)  138–​9 cognitive assemblages  444 Cohen, J.E.  xviii COINTELPRO  275–​6 Collective Shop Ban  43–​4, 49 Colorado, electronic monitoring (EM)  330 commercial organizations  see private sector commodification of suffering  see mental health problems communists, and intelligence services  273, 275–​6 Community Care Behavioral Health Organization (US)  139 Community Mental Health Act 1963 (US)  142 community-​based policing  207–​8, 279–​80 companies  see private sector Connecticut v. Doe (2003) (US)  317 Connell, R.  xx, 191 constitutive criminology  19–​20 contact-​tracing apps  421–​2, 462–​3 contactless payment systems  466–​7 contractual governance  48 control power  49–​51, 53–​4 control society  3, 4, 34, 45, 49–​51, 55–​6, 257, 259 control society and pre-​crime  63–​78 dangerousness and risk  63–​7, 69 and mass preventive justice and control  69–​75 from pre-​crimes to risk crimes  67–​9 public resistance  72–​5 Cook, A.  273 Cooke, K.  284–​5

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Cormier, C.A.  188 Cornell, D.  19 Couey, John  324 Council of State and Territorial Epidemiologists (CSTE)  136 Counter-​terrorism and Security Act 2015 (UK)  113 counterterrorism  see terrorism COVID-​19 pandemic  contact-​tracing apps  421–​2, 462–​3 and radio frequency identification (RFID)  462–​3 use of drones  446–​8 Crawford, A.  229 Crewe, D.  158 crime control field  235 Criminal Investigations Department (CID) (UK)  274 criminalization of everyday life  11, 34 critical algorithm studies  240 critical data studies  239, 242 Crocker, A.G.  143–​4 Cubellis, M.A.  322–​3 Cudmore, R.  321 Cukier, K.  240 customer behavior  236, 237, 461, 473 cybercrime  417, 420 cybersecurity  and big data  418–​20, 423 and radio frequency identification (RFID)  473 D dangerous driving  66–​7, 68, 72, 76 dangerousness and risk  63–​7, 69 Dante, E.M.  327 Darwin, Australia, universal surveillance  77–​8 dashcams  212–​13, 214, 215 Daskal, J.  xxii, xxiii data doubles  34, 37n10, 263, 374, 471 data shareholders framework  423 datafication  250–​1 dataism  251 dataveillance, concept of  111, 203–​4 dating sites  415, 418 Davis, M.  52 de-​vitalization  17, 36n1 Debord, G.  23, 33 Décary-​Hétu, D.  418 deconstructionist philosophy  27 deep learning  216 deinstitutionalization (mental health care)  141–​2, 143, 144 Deleuze, G.  1–​2, 18, 33, 34, 37n10, 45, 49–​51, 54, 55, 57, 69, 71, 116, 252–​3, 257, 259, 471 delinquent personality  119–​20

Deloitte  348 Demetriou, J.  355–​6 DeMichele, M.T.  328–​9 Dencik, L.  239–​40 Department of Homeland Security (US)  280 depression  130, 132–​3, 137–​8, 139–​40, 146 Derrida, J.  27, 56 Descartes, R.  160 Diagnostic and Statistical Manual of Mental Disorders (DSM)  DSM-​IV  132 DSM-​IV-​TR  128, 132 DSM 5  128, 131, 132, 133, 136, 145, 306 Dick, P.K  1, 2, 105, 108, 110 Dickey, B.  144–​5 Digital Angel Corporation  468 digital divides/​inequalities  365–​9, 377 research evidence of  370–​3 digital guardianship  423 digital skills  importance of  365–​6, 367–​8 training in  365–​6, 368–​73, 377–​9 Director of the Office of Homeland Security (US)  280 disciplinary architecture  53 disciplinary power  47–​50, 52–​3 (dis)continuities  19, 20 disenfranchisement  389–​403 African Americans  391–​2, 397 as civil death  389–​90, 395–​6 enforcement of  398–​9, 400–​1 felon disenfranchisement law  390–​2 impact of  391–​2, 402–​3 impact of restoring voting rights  394, 395 importance of voting  390 as pre-​crime control  393–​4 as public shaming  394 and racial bias  391–​3, 397 and surveillance  398–​402 vagaries of exclusion  400–​2 and voter fraud  396–​8 (dis)identities  19, 20 dividuals  59, 69–​70, 252–​4, 257, 263–​4 domestic violence, and risk assessment  186 Doyle, D.J.  184 drink-​driving  65–​9 and in-​vehicle cameras (IVCs)  212–​13 drones  433–​49 in biopolitical regime  442–​5 civilian casualties  433, 438, 441 and COVID-​19 pandemic  446–​8 development and technology of  435–​8

496

Index

domestic law enforcement  445–​7 intelligence, surveillance and reconnaissance (ISR)  436–​7, 439 and international law  439–​42, 445 just war tradition (JWT)  440–​2 lethal strikes  433, 437, 438, 439, 441–​2, 442–​5 military-​aged male (MOM) concept  441 and non-​state actors  448 operators of  435–​6 pattern-​of-​life (POL) analyses  442–​5 personality strikes  444–​5 power without vulnerability  439–​40 precision ethics narrative  442 and re-​ordering of global power  438–​42 signature strikes  445 surveillance  445–​8 wide-​ranging use of  433–​4 drug testing  168 drug use industry  see substance misuse surveillance dynamic nominalism  240 dystopia  179–​80 E e-​passports  256–​7, 468 education sector  see school digital surveillance; universities Edwards, M.  83 egoism  131 Eisenberg, A.  347 elections  see disenfranchisement electronic article surveillance (EAS)  458, 459 electronic monitoring (EM)  50, 323–​34, 341–​60 and data analytics  349–​53, 354–​9 and home confinement  346 immediacy of  343–​5 implications of  331–​3 issues with  328–​30, 333–​4 origins and logic of  323–​6 predictive analytics  350, 351, 352–​3, 354–​5, 356–​60 and private sector  345–​6, 348, 349–​51, 354–​6, 359 and punitiveness  346–​9, 356–​7, 359–​60 and recidivism  330, 334 role of National Institute of Justice (NIJ)  349–​53 for sex offenders in US  323–​34 state models of (US)  326–​8 types of  326, 341–​2 and violations  326, 329, 344–​5, 355, 357 Eli Lilly  130

environmental design, and crime prevention  44, 53 Ericson, R.  37n10, 47, 263 Esposti, S.D.  203–​4, 250, 255, 260 EU Committee on Civil Liberties, Justice and Home Affairs  277 Ewald, A.  400–​1 expressive individualism  130 F Facebook  114, 204, 258, 260–​1, 418, 419 facial recognition technology  and deep learning  216 and drones  447 and mass surveillance  283, 284 and racial bias  215–​16, 301–​2, 423–​4 in schools  115 in shops  49 and speed cameras  77 Switching on Darwin program  77–​8 and police video surveillance  214, 215 young people and dataveillance  256–​7 Fair Labor Standards Act (US)  134 Fan, M.D.  217 Fazel, S.  187 FBI Data Intercept Technology Unit  283 Federal Bureau of Investigations (FBI)  275, 283 Feeley, M.  50, 72, 235, 489 felon disenfranchisement  see disenfranchisement Ferguson, A.G.  108, 203, 208–​9, 215, 216 field theory  see policing, pre-​crime and surveillance fields of struggle  227–​8, 230 finalization  17, 36n1 fines, speeding offenses  71, 73, 74, 76 Finnish Schools on the Move  115 First Steps Act 2018 (US)  348 Fitzgerald, R.  186 Five Eyes (FVEY)  276–​7 Florida  electronic monitoring (EM)  324, 327 felon disenfranchisement  391, 393 voter fraud  397 Flynn, N.  12n5 Foley, James  83–​4 Foreign Intelligence Surveillance Act (FISA) 1978 (US)  278, 282 Foreign Intelligence Surveillance Court (FISC) (US)  278, 282 formal indifference  117 Foucault, M.  18, 34, 70, 295, 449 and governmentality  116, 230 and panopticon  299, 308, 375 and power  28, 45–​50, 52, 53, 54, 55, 443

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THE PRE-​CRIME SOCIETY

Guardian, The  238, 283 Guattari, F.  18, 37n10 Gunderson, J.G.  128

Fox, R.  76 Franklin, Benjamin  299 Freeman, B.C.  329 Freiberg, A.  72 Fromm, E.  12n2, 22, 31–​2 Fund, J.H.  397 G G2 Research  354 Gad, C.  109 Gaggle  112, 113 Galbraith, K.  168–​9 Galindo, Jesus  144 Gane, N.  116–​18 Garland, D.  49, 235, 488 Gates, K.  232 GEO  354 Geosatis  354, 355–​6 German, K.  83 Gillies, C.  190 Gilliom, J.  237 Girard, R.  162–​3 global neoliberalism  470–​6 Global Positioning System (GPS) tracking  contact tracing apps  421–​2 radio frequency identification (RFID)  459, 464, 467, 473 see also electronic monitoring (EM) God  death of  157–​9, 171 existence of  160 and violence  162–​3 Goel, S.  188 Goffman, E.  193 GoGuardian  112 Goldman, R.  344 Google  112, 114, 204, 370, 378, 414, 419, 420–​1 Government Communications Headquarters (GCHQ) (UK)  237, 283 government databases, in schools 114–​15 governmentality, typology of  116–​18 Grady, Torrey Dale  325–​6 Grady v. North Carolina (2015) (US)  325–​6 Graham, H.  179–​80 Graham, T.  186 Granfield, R.  169 Granroth, J.  260–​1 Green, B.  353 Greenwald, R.  441 Gregory, D.  434, 436, 439 Gregory, T.  441 Griffin, R.  98n17 Guantanamo Bay, Cuba  86–​7, 97nn10–​11

H Hacking, I.  240 Haggerty, K.  37n10, 215, 263 Hall, N.  110 Hanich, J.  92–​3, 94–​5 Hansen, L.  109 Hanson, R.K.  334 happiness  131, 145–​6 Hardt, M.  18 harm reduction approach (drug treatment)  166–​8 Harman, G.  95 harms of reduction  35, 36n4 harms of repression  35, 36n4 Harris, A.J.  321 Harris, G.T.  188 Harvard University  323 Hayles, N.K.  444 Health Maintenance Organization Act 1973 (HMO) (US)  134, 135 Health Partners  139 healthcare  see mental health problems healthcare systems, and radio frequency identification (RFID)  461–​3 Heaton, H.I.  350–​1 Heidegger, M.  159–​60, 162 Help America Vote Act 2002 (HAVA)  398 Henry, S.  19 hermeneutical narrative, meaning of  155–​6 see also substance misuse surveillance Herodotus  129 high policing  233, 273–​4, 279 Hintz, A.  239–​40 Hobbes, T.  46 Hogg, R.  xx home confinement  346 Hood, J.  209, 215–​16 Hooper, M.K.  205 Hoover, J. Edgar  275–​6 human microchipping  456, 468–​9 Human Rights Watch  78 hybrid GPS tracking model  326 hyper-​realists and reification  23–​5, 33 hyper-​securitization  11, 34, 375–​6 hypernudges  56 I ID systems  468 identity  governing by  468 as primary ground for coercive interventions  119–​20

498

Index

image-​objects  22–​3 images of war  81–​2 Impero  113 in-​vehicle cameras (IVCs)  212–​13, 214, 215 indigenous peoples, and risk assessment  186, 188–​93 individualism  130–​2 industrial capitalism  21–​2, 33 information civilization  33, 35 innocence  negation of  90–​5 pre-​existing  87 insurance companies, and mental healthcare  127–​9, 132, 135, 138–​40, 145–​6 pay-​for-​performance  138–​40, 146 Integrated Security Units (Canada)  281 Integrated Threat Assessment Centre (Canada)  281 intelligence agencies  see national security intelligence intelligence-​led policing (ILP)  279–​81 intelligence, surveillance and reconnaissance (ISR), drones 436–​7, 439 intelligent transport systems (ITS)  464 INTELLITRACK software  354 International Association of Chiefs of Police (IACP)  212–​13 International Civil Aviation Organization (ICAO)  468 International Data Corporation (IDC)  411 Internet of Things (IoT)  115, 459–​60, 462, 465, 467 interrogation practices  86–​7 Isin, E.  239 ISIS  83 J Jacob Wetterling Act 1994 (US)  316 Jankélévitch, V.  170–​1 Jeffersontown murders, Kentucky  87–​8 Jessica Lunsford Act (2005) (US) 324–​5, 468 Jewkes, Y.  368, 376, 377 Joh, E.E.  240 Johnston, L.  229–​30 Joint Enterprise Defence Infrastructure (JEDI)  286 Judeo-​Christian gospel  156, 157, 161, 162 Jung, J.  188 juridical-​political form of power 45–​6, 47–​8 just war tradition (JWT)  440–​2 Justice Policy Institute  331

K Kant, I.  159–​61, 172n3, 172n8 Keebler, G.  182 Kelling, G.L.  205–​7 Kempa, M.  48 Kennedy, S.  xxi Kent Police (UK)  233 Kentucky, Jeffersontown murders  87–​8 Kerner Commission  206 Khalid Sheikh Mohammad  97n11 Khan, F.  366 Kindervater, K.H.  436–​7 King, R.  309–​10 Kitchin, R.  242, 253 Kleinman, D.L.  238 Knight, V.  179 Konikoff, D.  186 Korody, Amanda  273–​4 L labelling  and digital racialization of risk  489 and the pre-​criminal student  120 and substance misuse  160 Lacan, J.  26 Latour, B.  95, 98n15, 444 Latzer, B.  348 Law Enforcement Management and Administrative Statistics (LEMAS) survey  212 Lea, J.  237 Leclair, M.C.  143–​4 less eligibility  163–​4, 166, 167, 169 liberal individualism  130–​1 libertarian Marxism  22 license plate readers (LPRs)  211–​12, 214 Lin, Z.  188 Lippens, R.  158 Looney, A.  170–​1 low policing  233, 272 lucidity of the excluded  242–​3 Luckmann, T.  20 Lukács, G.  20, 36n5 Lunsford, Jessica  324–​5 Lupton, D.  263 Lyng, S.  158 Lyon, D.  228, 239, 399 M Mallett, C.A.  107, 141 mandatory drug testing (MDT))  168 Manning, P.K  205 manufacturing and supply chain management  460–​1 Marion, J.-​L.  160, 171 markets  see neoliberalism; private sector Martin, M.S.  143–​4 Martin, Trayvon  96n5

499

THE PRE-​CRIME SOCIETY

Marwick, A.  252 Marx, K.  21–​2, 25, 33, 157 mass de-​carceration  308 mass monitoring and big data  see sex offender monitoring mass preventive justice  69–​75 mass shootings  89 Massachusetts, electronic monitoring (EM)  328 master discourse  26, 27 Mastracci, S.  214 Mathiesen, T.  118 Mattelart, A.  281 Matthews, R.  158 Mauer, M.  391–​2 Mayer-​Schönberger, V.  240 McAfee, A.  414–​15 McAlpine, D.  140 McCulloch, J.  105, 106–​7, 109, 110, 119, 120, 244n5 McDonald Commission (Canada)  276 McJunkin, B.A.  325–​6 McLuhan, M.  1, 2 McNamara, T.  186–​7 McQuade, B.I.  233 Mears, D.  300 medication, mental health issues  127–​8, 130, 133, 135, 136–​8, 140 Melville, William  273 mental health problems  127–​47 access to care  140–​1 as a commodity  129, 132–​5 and criminal justice system 141–​2, 143–​5 and cultural assumptions  129–​32 and deinstitutionalization  141–​2, 143, 144 deliberate misdiagnosis  127–​9 and incarceration  127, 141, 143–​5, 165, 293–​4, 306 and insurance companies  127–​9, 132, 135, 138–​40, 145–​6 mental health surveillance  136–​41, 146 outcomes of current system  142–​5 pay-​for-​performance  138–​40, 146 and quality measures  146 see also substance misuse surveillance metaphysics of presence  31 methadone  167–​8 Metropolitan Police, London  272–​4 Metropolitan Police’s Special Irish Branch  273 metropolitan thinking  xx MI5 (UK)  283–​4 Miah, A.  115 Microsoft  112, 282, 286 military action  see drones

Miller, J.  208 Miller, W.  158 Milovanovic, D.  17, 19, 20 Minnesota Multiphasic Personality Inventory (MMPI)  299 Minority Report, The  108–​10 mission creep  109–​10, 112, 120, 472 Mittelstadt, B.  188 mnemotechnical system  56 Monaghan, J.  281 Monahan, J.  185 Monahan, T.  237 Moore, M.H.  205–​7 Mor, Y.  108 Morris, J.  179–​80 Morselli, C.  418 Moss, Stirling  66 Mossman, D.  183 Mothers Against Drunk Driving  212 Mr Big sting operations  274 Mustaine, E.E.  322 N National Alliance for the Mentally Ill (US)  143 National Center for Health Statistics (US)  138 National Center for Missing and Exploited Children (NCMEC) (US)  113, 317 National Crime Agency (NCA) (UK)  236 National Institute of Justice (NIJ) (US)  343, 349–​53 National Institute of Mental Health (US)  140, 142, 304 National Mental Health Act 1946 (US)  142 National Police Chiefs Council (NPCC) (UK)  241 National Pupil Database (UK)  114 National Security Act 1947 (US)  274, 275 National Security Agency (NSA) (US)  275, 277–​8, 282–​4, 286 national security intelligence  269–​87 BRUSA Agreement (British United States of America Agreement)  276–​7 counterintelligence  272–​6 curtailing of mass surveillance  285 and detective work  270, 274 early problematizations of  271–​2 as evidence in criminal justice system  284–​5 high policing  273–​4, 279 historical context  269–​71 intelligence-​led policing and integration  279–​81

500

Index

international sharing  276–​7 parallel construction  285 and private sector  286 search and seizure  282 signals intelligence  276–​9, 281–​5 targets of surveillance  282 and terrorism  280–​1 negation of innocence  90–​5 Negri, A.  18 neo-​conservatism  487, 488 Neocleous, M.  57 neoliberalism  3 neoliberal globalization  470–​6 and policing  231–​2, 235, 236–​7 responsibilization and individualism  488–​9 and school digital surveillance  116–​21 see also private sector Netherlands  see security society neutrality of algorithms  485–​7 New York City Police Department (NYPD)  207–​8, 233 New Zealand  algorithms and public services  179 international sharing of intelligence  277 risk assessment from indigenous perspective  182, 189–​93 NewFusion  469 Newman, S.  63, 77 Nicholls, T.L.  143–​4 Nietzsche, F.W.  36n7, 157–​9 non-​consummate offences  65 non-​places  156, 164, 170 Norris, Z.  310 nudging  56, 250, 255, 263 Nuechterlein, P.  158–​9 Nuttall, John  273–​4 O Obama. Barack  411, 439 object oriented ontology  95 Offender Assessment System (OASys)  235, 486 Office of the Attorney General (US) 346 Ogbonnaya-​Ogburu, I.F.  368–​9 Oleson, J.  109 Olver, M.E.  180 Omand, G.  274 Omnilink  354 Omori, M.K.  331 one per cent doctrine  119 online target hardening  423 ontotheology  159–​61, 168, 170, 171 OPTIC NERVE program  283 Orwell, G.  12n2 Owusa-​Bempah, K.  186

P PacifiCare Behavioral Health  139 Page, J.  232, 238 Pakistan, drones  433, 438, 439, 441 panoptics  34, 47, 51, 53, 116, 299, 375, 470–​1 Papson, S.  344 parallel construction  285 parole  and Antisocial Personality Disorder (ASPD)  306 and digital divides/​inequalities  371 and electronic monitoring (EM)  328–​9, 331, 345, 349, 358 and racial bias  302 and risk assessment  295–​7, 304, 306–​7 Pascarella, M.  98n16 passive GPS tracking  326 passports  256–​7, 468 Patient Protection and Affordable Care Act 2010 (ACA) (US)  134, 135 pattern-​of-​life (POL) analyses  442–​5 pay-​for-​performance  138–​40, 146 payment systems, electronic  466–​7 Payne, B.K.  328–​9 Peel R.  272 People v. Chubbs (2015), California  185–​6 permanent state of emergency  85–​6, 89 Person of Interest (TV series)  359 Pfohl, S.  2 pharmaceutical industry  130, 135, 137–​8, 140, 463 Phillips, A.J.  393 physiognomy  487 Pickering, S.  105, 106, 110, 244n5 Pike, L.  274 Pilgrim, D.  170 Pirzada, K.  366 plagiarism  261–​3 pleasure  131, 145 poetic space  156, 170–​1 police/​policing  and big data  228, 232–​3, 239, 240–​3, 415–​16, 423–​4 community led  207–​8, 279–​80 high policing  233, 273–​4, 279 intelligence-​led  279–​81 low policing  233, 272 Metropolitan Police (UK)  272–​4 and national security intelligence  271–​ 6, 279–​81, 285 New York City Police Department (NYPD)  207–​8, 233 paradigm shift  229–​30 political era of  205–​6 professional era of  206–​7, 209

501

THE PRE-​CRIME SOCIETY

Royal Canadian Mounted Police (RCMP)  273–​4, 276 and social order  46–​7 three eras of policing (US)  205–​9 see also police and dataveillance cameras; policing, pre-​crime and surveillance; predictive policing police dataveillance and cameras  203–​17 accuracy of information  215–​16 benefits of  216–​17 and bias  215–​16 body-​worn cameras (BWCs)  213–​14, 215 CCTV  210–​11, 214–​15 concept of dataveillance  203–​4 and counterterrorism  208–​9 criticisms of  211, 214, 215–​16, 217 and deep learning  216 embracing of technology  209–​10, 214–​15 historical context  205–​9 license plate readers (LPRs)  211–​12, 214, 215 in-​vehicle cameras (IVCs)  212–​13, 214, 215 see also police/​policing; policing, pre-​crime and surveillance; predictive policing Police National Computer (PNC) (UK)  232 Police National Database (PND) (UK)  232 policing, pre-​crime and surveillance  227–​44 and actuarialism  232 and big data  228, 232–​3, 239, 240–​3 crime control field  235, 238 fields of struggle  227–​8, 230 future research  241–​2 high and low policing  233 neoliberalism  231–​2, 235, 236–​7 paradigm shift in policing  229–​30 politics of pre-​crime  231–​4 private security officers  234 relationship between pre-​crime, surveillance and policing  228–​30 space of competing agents  241 state-​initiated responsibilization  234–​8 and surveillance subjects  242–​3 technological field of expertise  238–​40 see also police/​policing; police dataveillance and cameras; predictive policing political era of policing  205–​6 Popay, William S.  272–​3 post-​crimes  65–​6, 233–​4 post-​criminology  34

power  to banish  52 bio-​power  55, 167, 443 control power  49–​51, 53–​4 disciplinary power  47–​9, 49–​50, 52–​3 as harm  18, 32, 36n4 psychopower  54–​6 sovereign power  45–​7, 52 pre-​crime (general)  concept of  105–​6, 108–​11, 229 cultural perspective  106, 120 epistemology of  33, 34 ethic of  34 expanding category of  107 ontology of  33, 34 techno-​realist perspective  105–​6, 107, 110, 111–​21 pre-​crime society  229, 332–​3 predictive analytics  and electronic monitoring (EM)  350–​60 and policing  108–​10, 228–​32, 240, 242 school surveillance  111, 113–​16 predictive policing  108–​9, 229, 231–​3 and big data  415–​6, 423–​4 and electronic monitoring (EM)  343 feedback loop  240, 488 and power  47, 54, 57–​8 predictive analytics  108–​10, 228–​32, 240, 242 and racial bias  298, 486, 487–​8 see also police/​policing; police dataveillance and cameras; policing, pre-​crime and surveillance PredPol  233 Prescott, J.J.  325–​6 Presdee, M.  3, 34, 457 Prevent strategy (UK)  229, 238 PRISM program  204, 282–​3, 284 prison form  18 prisons/​prisoners  and control society  50 drug testing in  168 mental health issues  127, 141, 143–​5, 165, 293–​4, 306 officers’ racial bias  302–​3 private sector  144 and radio frequency identification (RFID)  467–​8 revolving door of crime  165–​6 and substance misuse  165–​8 video visitations  369 see also disenfranchisement; electronic monitoring (EM); reentry and rehabilitation; risk assessment and actuarial justice; supermax prison isolation

502

Index

privacy agreements/​issues  and big data  418–​19, 420–​3 and contact-​tracing apps  421–​2, 463 and mass state surveillance  283 and police camera surveillance  211, 214, 215, 217 and returning citizens  373, 375, 376, 378 and RFID technology  463, 473, 475 and school surveillance  117, 121 and young people  251–​2, 254, 259–​60, 261 privacy fatigue  252 private sector  and accountability  144 and big data  414–​16, 423 corporate secrecy  242 creating demand  238–​9 and digital skills training  369–​70 and electronic monitoring (EM)  345–​6, 348, 349–​51, 354–​6, 359 formal indifference  117 insurance companies  127–​9, 132, 135, 138–​40, 145–​6 national security intelligence  286 pharmaceutical industry  130, 135, 137–​8, 140, 463 and police practice  238–​9 prisons  144 private security officers  xx, 234, 244n4 and radio frequency identification (RFID)  459, 460–​1, 469 and risk assessment software  186 school digital surveillance  106, 110–​11, 112–​13, 116–​18, 120–​1 and state-​initiated responsibilization  236–​7 and technological field of expertise  238–​9 see also neoliberalism private security officers  xx, 234, 244n4 probation  and crime control field  235–​6, 237 and electronic monitoring (EM)  297, 328–​9, 345, 349, 358, 376 and substance misuse  164–​5, 166 problem-​oriented policing  207–​8 Proceeds of Crime Act 2002 (UK)  236 professional era of policing  206–​7, 209 prosthetic surveillance  115 protests  74–​5, 217, 285, 445–​6 psychologists, and risk assessment  187–​8, 295–​7, 306–​7 psychopolitical power  56 psychopower  54–​6 psychosurgery  304

public notification, sex offender registry and notification (SORN)  318, 319–​23, 320–​3 public opinion  electronic monitoring (EM)  330 license plate readers (LPRs)  211 sex offender registry and notification (SORN)  321–​2 public resistance  mass preventive justice  72–​5 mass surveillance  285 protests  74–​5, 217, 285, 445–​6 public spaces, controlling  43–​4, 51–​6 Pugliese, J.  444, 445 Pushing Change (UK)  171 Q quantified child  256, 262–​3 Quantified Self movement  472–​4 quasi-​criminal law  48 quasi-​police  76 Quetiapine  140 Quinsey, V.L.  188 R race/​racism  and big data  423–​4 and criminal tendency  301–​2 and digital inequalities  368 digital racialization of risk  484–​9 and disenfranchisement  391–​3, 397 and drones  441 facial recognition technology  215–​16, 298, 301–​2, 423–​4 and hyperpolicing  206–​7 myth of race neutrality  483–​9 and parole  302 and predictive policing  298, 486, 487–​8 and recidivism  300, 302, 485–​6, 487 and risk assessment  186, 188–​93, 299, 300–​3, 484–​9 self-​fulfilling prophecy  303–​8, 489 and solitary confinement  298, 299–​303 Stop, Question, and Frisk (SQF)  208, 298 and surveillance systems  298 US criminal justice system  392 race neutrality myth  483–​9 radicalization  92–​5, 98n16, 98n18, 109, 113, 238 radio frequency identification (RFID)  342, 345, 455–​76 and citizenship  476 criminal justice applications  467–​8 electronic article surveillance (EAS)  458, 459 electronic payment systems  466–​7 emergence and components of  457–​9

503

THE PRE-​CRIME SOCIETY

healthcare and pharmaceuticals  461–​3 human implantation  459, 467, 468–​9 and Internet of Things (IoT)  415, 459–​60 liberty and privacy vs security  474–​6 manufacturing and supply chain management  460–​1 practical applications  459–​69 and pre-​crime  469–​74 and school securitization  465 and self-​tracking  472–​4 as surveillant assemblage  471 theoretical analysis  469–​74 and transportation  463–​5 Rafiq ur Rehman  433 random breathalyzer test (RBT)  69 Rather, D.  144 recidivism  and electronic monitoring (EM)  330, 334 and mass de-​carceration  308 and race  300, 302, 485–​6, 487 and risk assessment  164, 181–​4, 186, 189, 192–​3, 296, 307 and sentence length  307 sex offenders  321, 322–​3, 330, 332–​4 and solitary confinement  300, 307 recovery  19–​20, 156 discovery model  170–​1 as non-​place  163–​6 as ontotheology  159–​61 reconceptualisation of  170–​1 recovery capital  168–​9 and substance misuse  168–​9 reductionism  129–​30 reentry and rehabilitation  365–​79 digital divides/​inequalities  365–​6, 367–​73, 377 digital skills training  365–​6, 368–​70, 377–​9 and electronic monitoring (EM)  345, 348, 349, 352, 353, 358 importance of digital skills  365–​6, 367–​8, 371–​2, 375, 377–​9 mass surveillance and hyper-​securitization  375–​6 pre-​crime and dataveillance  373–​5 and privacy issues  373, 375, 376, 378 and private sector  369–​70 research evidence  370–​3 and Scandinavian prisons  308 and solitary confinement  306, 308, 310 rehabilitation  see reentry and rehabilitation reification  concept of  20, 36n5, 36n6 and hyper-​realists  23–​5, 33

and Marx  21–​2, 25, 33 and the Situationists  22–​3, 25, 33 Rekognition facial recognition software  216 rendition  86–​7, 97n10, 97n11 Renzema, M.  330 reoffending  see recidivism Responsibility to Protect (R2P)  437 responsibilization  234–​8, 488–​9 retrotopia  180 returning citizens (RCs)  see reentry and rehabilitation Rice, M.E.  188 Rich, E.  115 Richey, P.G.  83 Ricoeur, Paul  156, 161 Rigano, C.  353 Right on Crime, Texas  348 risk  concept of  78n1 digital racialization of  484–​9 and society of captives  308–​9 and substance misuse  163–​5 see also control society and pre-​crime; risk assessment and actuarial justice; risk assessment in supermax prisons; risk society thesis risk assessment and actuarial justice  179–​95 and consent  185–​6 correctional `best practice’  192 correctional risk assessment  181–​4 and culture  184, 186, 187–​93, 194–​5, 487 ethics and politics of  184–​9, 191 and fairness  186–​7 Indigenous peoples  186, 188–​93 lack of accountability  185–​6 limitations of actuarial tools  183–​4, 184–​9, 194–​5 more holistic view  194–​5 predictive accuracy of  188 and race  186, 188–​93, 299, 300–​3, 484–​9 and stakeholder involvement  185, 194–​5 Western world approach  187, 188, 191, 192 risk assessment in supermax prisons 294–​7, 308–​9 and racial bias  299, 300–​3 and self-​fulfilling prophecy  303–​8 risk society thesis  17–​37 cultural forces of risk currency  29, 32 hyper-​realists and reification  23–​5, 33 and interdependent forces of reification  25–​32

504

Index

and jurisprudential forces of reification  25–​32, 29 linguistic forces of risk currency  29, 30–​1 Marx and reification  21–​2, 25, 33 material forces of risk currency  29, 31–​2 and offenders  18–​19 power’s diffusion  27–​8 and problem of reification  19–​25 and psychoanalytical forces of reification  25–​32, 29 Situationists and reification  22–​3, 25, 33 subjectivity as politicized  26 symbolic forces of risk currency  29, 30 in ultramodern age  32–​5 and the unconscious  26–​7, 30 road toll  66, 73 Roberts, C.M.  460 Roberts, G.  170 RoC*RoI  182 Roots, E.  144 Rotterdam, and spaces of security  43–​4, 51–​6 Rowan, K.  140 Royal Canadian Mounted Police (RCMP)  273–​4, 276 Ruckenstein, M.  260–​1 Rudin, C.  185–​6 Ruppert, E.  231, 238, 239, 242 S Sadowski, J.  54 Scandinavian prisons  308 scapegoating  162–​3, 168–​9, 172n10 schizophrenia  140 Schlanger, M.  300 school digital surveillance  105–​22 classroom management software  113–​14 connections between crime and schools  107, 118–​19 cultural perspective  120 devices used  111–​16 extent of use of  111, 113 government databases  114–​15 Internet of Things (IoT)  115 and neoliberal governmentality  116–​18 potentialities and dangers of  121–​2 and the pre-​criminal student  118–​21 and private sector  106, 110–​11, 112–​13, 116–​18, 120–​1 and radicalization  113 and radio frequency identification (RFID)  465 scrutiny of online work and behavior  112–​14 social control  110

student indifference to  121 student resistance to  118 surveillance cameras  115–​16 techno-​realist perspective  119–​20 school-​to-​prison pipeline  107, 118–​19 Schrijvers, J.  162 scopic regime  433, 441, 443, 449n1 search and seizure  282, 424 Seaver, N.  240, 242 SecureAlert  354 security society  43–​58 and concept of security  57 and control power  49–​51, 53–​4 and disciplinary power  47–​50, 52–​3 interventions  51–​6 psychopower  54–​6 and risk  51 and sovereign power  45–​7, 52 urban security  43–​4, 51–​6 Seddon, T.  166, 167 selective exclusion  52 self-​fulfilling prophecy  303–​8, 489 self-​medication  144–​5, 146 self-​recognition  92–​5 self-​tracking  472–​4 Seroquel  140 Seto, M.C.  143–​4 sex offender monitoring  315–​34 collateral consequences of  323 cost of  331 data collection standards  318–​20 data gathering  317–​20, 326, 328–​30 data storage issues  329–​30 electronic monitoring (EM)  323–​34 evaluation of  333 implications of  331–​3 issues with  328–​30, 333–​4 law enforcers’ opinion  322–​3 origins and logic of SORN  316–​17 and pre-​crime society  332–​3 and privacy  325–​6 public opinion  321–​2 public sharing of data  318, 319–​23, 333–​4 and recidivism  321, 322–​3, 330, 332–​4 and risk assessment  183, 187 sex offender registry and notification (SORN)  316–​23, 331–​3 state models of  326–​8 workload issues  328–​30, 333 sex offender registry and notification (SORN)  316–​23, 331–​3 Sex Offender Registration and Notification Act (SORNA) (US)  318–​20 Shade, L.  117 Shapiro, A.  389

505

THE PRE-​CRIME SOCIETY

Shaw, I.G.R  439 Shearing, C.  44, 48, 229–​30, 233 Shiffman, J.  284–​5 Shineman, V.  395 shopping malls, CCTV  234, 244n4 shops, Collective Shop Ban  43–​4, 49 Shover, N.  243 Sieh, E.  163–​4 sign-​exchange-​values  24–​5, 29, 30–​1 signals intelligence  276–​7, 281–​5 Simon, J.  50, 72, 235, 489 Singh, R.  117 Situationists, and reification  22–​3, 25, 33 Skeem, J.  188 Skinner, B.F.  359 Sloan, L.  416 Smart Cities movement  77 smartphone monitoring  284, 347, 348–​9, 352–​3, 358 Smith v. Doe (2003) (US)  317 Snapchat  259 Snowden, Edward  204, 237, 282 social capital  169 social contract  46 social credit system  78, 114–​15, 474–​5 social imaginary  129–​32, 145–​6 social media intelligence (SOCMINT)  233–​4 social order  46 socialization theories  487 societies of control  see control society; control society and pre-​crime society of captives  17, 308–​9 solitary confinement  see supermax prison isolation Sontag, S.  81–​2, 89 Southern Criminology  xx–​xxii, 192 sovereign power  45–​7, 52 Sozzo, M.  xx Sparta Rotterdam football club  44, 48 Special Branch (UK)  273 Special Operations Division (SOD), US Drug Enforcement Agency  285 spectacle  22–​3, 442 speed cameras  70–​5, 76, 77 speeding offenses  66, 69–​72 and public resistance  72–​5 and revenue raising  73, 74, 76 Spinoza, B.  47 Squires, P.  237 Star, S.L.  263 state of emergency  85–​6, 89 state of exception, and terrorism  81–​99 and cinematic shock  91–​5 concept of state of exception  85–​7 and negation of innocence  90–​5, 98n15 and non-​state actors  87–​91 permanency of  89

video images  82–​5, 92–​4, 96n7, 96n8 zones of indifference  85, 87–​9, 90–​1 Static-​99 actuarial tool  183, 190 Steadman, H.  185 Steinsbekk, A.  144 Stenson, K.  230 Stewart, C.A.  193 Stiegler, B.  55–​6 Stockman, H.  457 Stoddard-​Dare, P.  141 Stop, Question, and Frisk (SQF)  208, 298 Strachey, J.  157–​8 street furniture  44, 53 strict liability offenses  65–​7 structured professional judgment (SPJ) risk assessment tools  184 Student Safety Company  112 substance misuse surveillance  155–​73 and austerity  169 and co-​morbidity  144–​5 death of the God of metaphysics 157–​9, 171 and discovery as poetic space  170–​1 harm reduction approach  166–​8 less eligibility  163–​4, 166, 169 middle class addicts  169 and prisoners  165–​8 recovery approach  168–​9 recovery as non-​place  163–​6 recovery as ontotheology  159–​61 use of psychoactive substances  161–​3 Sue, S.  188 suffering as a commodity  see mental health problems supercharged digital exclusion  368, 377 supermax prison isolation  293–​311 effect of solitary confinement  293–​4, 302–​3, 309 life inside  293–​4 post-​release effect of  309–​10 problems with risk assessment  298–​9 and racial bias  298, 299–​303 risk assessment and technology  294–​7 self-​fulfilling prophecy  303–​8 surveillance  297–​9 use of technology  294 supply chain management  460–​1 surveillance, concept/​definition of  203, 228–​9, 297–​9 surveillance capitalism  xviii, 2, 12n5, 33, 35, 109, 121 surveillance creep  109–​10, 112 surveillance slack  112 surveillant assemblage  37n10, 230, 471 Suskind, R.  119 Suspicious Activity Reports (SARs)  236 synoptic/​synopticon  34, 118, 471

506

Index

T Tadros, V.  78n1 targeted advertisements  260–​1 Taylor, C.  129, 131, 132 Taylor, S.R.  350 techno-​rational capitalism  22–​3 techno-​realist perspective  105–​6, 107, 110, 111–​21 technological incarceration (TI)  356–​7 terrorism  as driver of pre-​crime measures  236 and intelligence  269, 280–​1 and logic of pre-​crime  109 and police dataveillance  208–​9 radicalization  92–​5, 98n16, 98n18, 109, 113, 238 video images  82–​5, 92, 94 see also state of exception, and terrorism Terrorism Act 2000 (UK)  236 Terry stops  208 Tewksbury, R.  322 Texas, electronic monitoring (EM)  348 Theremin, Léon  457 thin blue line  46 Thompson, J.B.  228 Threat Operations Center (NTOC), NSA  286 Three Square Market  469 Tokaji, D.P.  398 Torrey, E.F.  142 torture  86–​7 total information awareness  xix, 271, 281, 286 Track Group  354 traffic calming  71 traffic regulation  see drink-​driving; speeding offenses tranquilization  162 transnational data exchange  xxi–​xxiii, 276, 286 transportation and radio frequency identification (RFID)  463–​5 transpraxis  36n7 TREASUREMAP program  284 Treatment Advocacy Center (US)  142 Turner, S.F.  331 Turnitin  261–​3 Twitter  112, 414, 416, 418, 419, 424 U UCLA Violence Center  304–​5, 307–​8 Ugwudike, P.  164 UK Ministry of Justice  165 UN Declaration on the Rights of Indigenous Peoples (2007)  193 unconscious  26–​7, 30 United Kingdom  CCTV  118, 210

international sharing of intelligence  276–​7 mass surveillance  283–​4 Metropolitan Police  272–​4 national security intelligence 272–​4, 276–​7 rate of imprisonment  165–​6 school digital surveillance  113, 114–​15, 118 and substance misuse  166–​7, 168–​9, 171 see also policing, pre-​crime and surveillance United States  big data  411 and culture  191 Guantanamo Bay  86–​7, 97nn10–​11 international sharing of intelligence  276–​7 mass surveillance  281–​5 national security intelligence  274–​8, 280–​6 New York City Police Department (NYPD)  207–​8, 233 risk assessment and actuarial justice  185–​6 school digital surveillance  112, 113, 114 and transnational data flows  xxi–​xxiii see also disenfranchisement; electronic monitoring (EM); mental health problems; police dataveillance and cameras; reentry and rehabilitation; sex offender monitoring; supermax prison isolation United States Congress, drone attacks  433 Universities  anti-​plagiarism software  261–​3 CCTV  254–​5 unmanned aerial vehicles (UAVs)  see drones UPSTREAM program  282–​3, 284 US Bureau of Justice Statistics  143 US Drug Enforcement Agency (DEA)  285 US Food and Drug Administration (FDA)  462–​3 US Supreme Court  electronic monitoring (EM)  325–​6 Guantanamo Bay, Cuba  97nn10–​11 sex offender registry and notification (SORN)  317, 320 USA FREEDOM Act 2015  285 USA PATRIOT Act 2001  215, 280 Ustun, B.  185–​6 V Van Camp, N.  56 Van der Steene, S.  179

507

THE PRE-​CRIME SOCIETY

Van Dijck, J.  251 Vander Schee, C.  256, 263 VanNostrand, M.  182 Verdery, K.  96n3 video images  state collection of  282–​3 and terrorism  82–​5, 92, 94 video surveillance  accuracy of information  215–​16 body-​worn cameras (BWCs)  213–​14, 215 CCTV  77, 115, 118, 210–​11, 214–​15, 234, 254–​6, 284 concerns about  216–​17 and deep learning  216 drones  445–​7 in-​vehicle cameras (IVCs)  212–​13, 214, 215 large array of police capability  214–​15 license plate readers (LPRs)  211–​12, 214, 215 video visitations (prisons)  369 viewer society  118, 121 Virilio, P.  47, 50 Vollmer, A.  206, 274 voluntary drug testing (VDT)  168 voter fraud  396–​8 voting rights  see disenfranchisement W Wacquant, L.  228, 231, 235, 244nn2–​3 Walby, K.  281 Walker, S.  206–​7 war images  81–​2 Ward, T.  193 warfare  see drones Warren, Elizabeth  135 Washington Post, The  282 waterboarding  86 wearable technology  55, 256–​7, 341–​2 web scraping tools  417 websites, big data from  417 Weeping Angel program  283–​4 welfare state, and surveillance  235–​6, 237, 243 Wener, R.E.  193 will to power  156, 158, 159

Williams, M.C.  235, 237 Williams, M.L.  416, 424 Williamson, B.  256, 262–​3 Wilson, D.  106–​7, 109, 119, 120 Wilson, O.W.  206, 274 Wingate, Judge Henry  389 wiretapping  277 Wolfe, V.  95n1 Wolfson, P.  170 Wong, S.C.P.  180 Wood, J.  44 Woodfox, A.  309–​10 workplaces  CCTV  255 radio frequency identification (RFID)  469, 473 Wright Mills, C.  12n4 X XKEYSCORE  284 Y young people and dataveillance  249–​64 and algorithmic surveillance  260–​3 ambivalence towards  251–​2 and biometric and wearable technologies  256–​7 concept of dataveillance  250–​4 and datafication  250–​2 and dividuation  252–​4, 257, 263–​4 and privacy protection  251–​2, 254, 259–​60, 261 research methodology  252 and spatial surveillance  257–​60 and visual surveillance  254–​6 see also school digital surveillance Youth Risk Behavior Surveillance System (YRBSS) (US)  114 Yunkapoorta, T.  xxiv Z Zedner, L.  109, 229, 233, 240, 373–​4, 393 Zehfuss, M.  442 Zimmerman, George  96n5 Žižek, S.  159, 163, 168 zones of indifference  85, 87–​9, 90–​1 Zuboff, S.  33, 115, 117, 121

508

Majid Yar, Lancaster University

“This impressive collection of original essays is an essential critical guide to the transformations of crime control shaped by surveillance, dataanalytics and the diverse technological innovations of the pre-crime society.” Lucia Zedner, University of Oxford

Brian G. Sellers is Associate Professor of Criminology and Criminal Justice at Eastern Michigan University.

We now live in a pre-crime society, in which information technology strategies and techniques such as predictive policing, actuarial justice and surveillance penology are used to achieve hyper-securitization. However, such securitization comes at a cost – the criminalization of everyday life is guaranteed, justice functions as an algorithmic industry and punishment is administered through dataveillance regimes. This pioneering book explores relevant theories, developing technologies and institutional practices and explains how the pre-crime society operates in the ‘ultramodern’ age of digital reality construction. Reviewing pre-crime’s cultural and political effects, the authors propose new directions in crime control policy.

E DITED BY BRUCE A. ARRIGO AND BRI AN G. SELLER S

Bruce A. Arrigo is Professor in the Department of Criminal Justice and Criminology at University of North Carolina at Charlotte.

TH E PRE- C RI ME SOC I E T Y

“A wide-ranging, up-to-date and dynamic exploration of surveillance, power and social control in contemporary society. Essential reading for those interested in technology’s role in the responses to crime.”

ISBN 978-1-5292-0525-1

9 781529 205251

B R I S TO L

@BrisUniPress BristolUniversityPress bristoluniversitypress.co.uk

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THE PRE- CRIME SOCIET Y CRI M E , CU LTU RE AND CONTROL IN THE U LTR A MODERN AG E EDITED BY B RUCE A . A RRIGO A N D B RI A N G . S ELLER S FO RE WO RD BY IAN WARREN