Science, Technology and Society: An Introduction 9783031083051, 9783031083068, 3031083059

Table of contents :
Contents
About the Authors
List of Figures
List of Tables
1: Introduction: Why Do We Need to Rethink Science?
1.1 The Re-emergence of Scientism
1.2 A Complementary Vision
1.3 Science as a Humanist Enterprise
References
Part I: From the Philosophy of Science to the Social Studies of Science
2: Gnoseology: The Foundations of Human Knowledge
2.1 Language and Reality: Arbitrary Relationship?
2.1.1 The Role of Language
2.2 Classifications: Concepts and Terms
2.3 The Three Spheres of Knowledge: Saying, Doing, Thinking
2.3.1 The Sphere of Thought
2.3.1.1 Is There Such Thing as Universal Concepts?
2.3.1.2 Oral Cultures Versus Written Cultures
2.3.2 The Sphere of Language
2.3.2.1 Facts as Material-Symbolic Phenomena Guided by Theory
2.3.3 The Sphere of Action
2.4 Tacit Knowledge: Its Role in Everyday Life and in Science
References
3: Epistemology: The Foundations of Scientific Knowledge
3.1 Neo-positivism
3.1.1 Reductionism
3.1.2 A Denotative Theory of Meaning
3.1.3 The Verification Principle
3.1.4 The Concept of Scientific Law
3.1.5 Induction
3.1.6 The Legacy of Neo-positivism
3.1.6.1 We Are Not a Mouse Weighing 80 kg!
3.2 Popper’s Realism and Critical Rationalism
3.2.1 Falsifiability
3.2.2 Science on … Stilts
3.2.3 Political Liberalism
3.2.4 The Critique of Induction
3.2.5 The Demarcation Criterion
3.2.6 Rationality as Critique and Discussion
References
4: Society in Science
4.1 The Critiques Levelled Against Popper
4.2 Science Revisited: Norwood R. Hanson
4.2.1 Abduction
4.3 The Social Dimension of Science: Thomas Kuhn
4.3.1 The Critiques of Kuhn and of His Legacy
4.4 Freed Science: Paul K. Feyerabend
4.5 Common Sense in Science
4.6 Scientific Knowledge and Common Sense Knowledge: A Circular Relationship
4.7 Deconstructed Science: Metaphors, Metonymies and Analogies
4.7.1 Each Name (Common or Scientific) has a Metaphorical or Analogical Origin
4.7.2 The Initial Baptism
4.7.3 The Influence of Metaphors
4.7.4 Metaphors and Ideologies
References
5: The Advent of the Studies of Science and of Technology
5.1 The Advent of the Sociology of Science: Robert K. Merton
5.2 The Edinburgh School “Strong Programme”
5.3 The Experimental Method: Cultural Assumptions and Deviance
5.4 Mathematics and Logics as Social Institutions
5.4.1 The Empirical Programme of Relativism
5.5 The Strong Programme....Reinforced: Bruno Latour
5.5.1 The Actor-Network Theory (ANT)
5.5.2 Culture and Nature
5.6 A Summary
5.6.1 Realists
5.6.2 Critical Realists
5.6.3 Soft Realists
5.6.4 Constructivists
5.6.5 Relativists
References
Part II: Main Themes in STS
6: The Boundaries of Science
6.1 The Problem of Demarcation
6.1.1 Essentialist Approaches: Falsificationism, Institutionalised Ethos and Paradigmatic Consensus
6.1.2 The Constructivist Hypothesis and Boundary Work
6.2 Drawing and Redrawing the Boundaries of the Scientific Community
6.2.1 The Royal Society at the Start of the Seventeenth Century and the Problem of Testimony
6.2.2 Modern Times
6.3 Science Situated: From the “View from Nowhere” to “Truth-Spots”
6.3.1 The Hospital and the Segmented Human Body
6.3.2 The Laboratory
References
7: Science Behind the Scenes
7.1 Experiments
7.1.1 The Experimenter’s Regress
7.2 Facts, Black Boxes and Ships in Bottles
7.3 Laboratory Studies and Epistemic Cultures
References
8: Scientists, Experts and Public Opinion
8.1 Expertise: A Status Attributed to a Group
8.1.1 An Increasingly Blurred Boundary
8.2 The Communication of Science
8.2.1 Public Understanding of Science and the Information Deficit Model
8.2.2 From Public Engagement to Citizen Science
References
9: Science and Technology: Two Sides of the Same Coin
9.1 The Emergence of Technology Studies
9.2 From Technological Determinism to the Social Shaping of Technology (SST)
9.3 The Social Construction of Technology (SCOT)
9.4 Actors and Artefacts in the Actor-Network Theory (ANT)
9.5 The Ecological Approach to Technology
9.6 Sociotechnical Imaginaries and the Sociology of Expectations
References
10: Science, Technology and Gender
10.1 Women in Science
10.2 The Construction of Gender and Critical Empiricism
10.3 The Standpoint Theory and Situated Knowledge
10.4 Gender and Technology
References
Part III: Contemporary Fields of Inquiry
11: Environment
11.1 The Cultural Construction of Nature
11.2 Climate Change
11.3 Anthropocene
References
12: Digital Societies
12.1 Algorithms
12.2 Digital Sociology and Its Methodological Challenges
12.3 Artificial Intelligence
References
13: Medicine and Biotechnologies
13.1 Medicalisation, Normalisation and Biopolitics
13.2 The Human Genome Project
13.3 Biotechnology and Synthetic Biology
References
14: Five Challenges for the Future
14.1 Multispecies Ethnography
14.2 Agriculture
14.3 Science and the Senses
14.4 Risks, Disasters and Resilience
14.5 The Personalisation of Medicine: From Pharmacogenomics to Self-Tracking Tools
References
15: Conclusion
References
References
Index

Citation preview

SCIENCE, TECHNOLOGY and SOCIETY AN INTRODUCTION

GIAMPIETRO GOBO VALENTINA MARCHESELLI

Science, Technology and Society

Giampietro Gobo • Valentina Marcheselli

Science, Technology and Society An Introduction

Giampietro Gobo Department of Philosophy University of Milano Milano, Italy

Valentina Marcheselli Department of Sociology and Social Research University of Trento Trento, Italy

ISBN 978-3-031-08305-1    ISBN 978-3-031-08306-8 (eBook) https://doi.org/10.1007/978-3-031-08306-8 © The Editor(s) (if applicable) and The Author(s), under exclusive licence to Springer Nature Switzerland AG 2022 This work is subject to copyright. All rights are solely and exclusively licensed by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors, and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Palgrave Macmillan imprint is published by the registered company Springer Nature Switzerland AG. The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland

To the new generation of STS students

Contents

1 Introduction:  Why Do We Need to Rethink Science?���������������������������  1 1.1 The Re-emergence of Scientism�������������������������������������������������������  2 1.2 A Complementary Vision�����������������������������������������������������������������  4 1.3 Science as a Humanist Enterprise�����������������������������������������������������  5 References �������������������������������������������������������������������������������������������������  6 Part I From the Philosophy of Science to the Social Studies of Science   7 2 Gnoseology:  The Foundations of Human Knowledge���������������������������  9 2.1 Language and Reality: Arbitrary Relationship?�������������������������������  9 2.1.1 The Role of Language ��������������������������������������������������������� 13 2.2 Classifications: Concepts and Terms������������������������������������������������� 15 2.3 The Three Spheres of Knowledge: Saying, Doing, Thinking����������� 18 2.3.1 The Sphere of Thought��������������������������������������������������������� 20 2.3.2 The Sphere of Language������������������������������������������������������� 24 2.3.3 The Sphere of Action����������������������������������������������������������� 26 2.4 Tacit Knowledge: Its Role in Everyday Life and in Science ����������� 29 References ������������������������������������������������������������������������������������������������� 32 3 Epistemology:  The Foundations of Scientific Knowledge��������������������� 35 3.1 Neo-positivism ��������������������������������������������������������������������������������� 35 3.1.1 Reductionism����������������������������������������������������������������������� 38 3.1.2 A Denotative Theory of Meaning����������������������������������������� 39 3.1.3 The Verification Principle����������������������������������������������������� 40

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3.1.4 The Concept of Scientific Law��������������������������������������������� 40 3.1.5 Induction������������������������������������������������������������������������������� 41 3.1.6 The Legacy of Neo-positivism��������������������������������������������� 42 3.2 Popper’s Realism and Critical Rationalism ������������������������������������� 44 3.2.1 Falsifiability������������������������������������������������������������������������� 44 3.2.2 Science on … Stilts ������������������������������������������������������������� 46 3.2.3 Political Liberalism ������������������������������������������������������������� 46 3.2.4 The Critique of Induction����������������������������������������������������� 46 3.2.5 The Demarcation Criterion��������������������������������������������������� 48 3.2.6 Rationality as Critique and Discussion ������������������������������� 49 References ������������������������������������������������������������������������������������������������� 50 4 Society in Science������������������������������������������������������������������������������������� 53 4.1 The Critiques Levelled Against Popper ������������������������������������������� 54 4.2 Science Revisited: Norwood R. Hanson������������������������������������������� 57 4.2.1 Abduction����������������������������������������������������������������������������� 60 4.3 The Social Dimension of Science: Thomas Kuhn ��������������������������� 62 4.3.1 The Critiques of Kuhn and of His Legacy��������������������������� 72 4.4 Freed Science: Paul K. Feyerabend ������������������������������������������������� 74 4.5 Common Sense in Science��������������������������������������������������������������� 79 4.6 Scientific Knowledge and Common Sense Knowledge: A Circular Relationship ������������������������������������������������������������������� 81 4.7 Deconstructed Science: Metaphors, Metonymies and Analogies����� 82 4.7.1 Each Name (Common or Scientific) has a Metaphorical or Analogical Origin�������������������������������������� 83 4.7.2 The Initial Baptism��������������������������������������������������������������� 84 4.7.3 The Influence of Metaphors������������������������������������������������� 86 4.7.4 Metaphors and Ideologies ��������������������������������������������������� 87 References ������������������������������������������������������������������������������������������������� 89 5 The  Advent of the Studies of Science and of Technology ��������������������� 91 5.1 The Advent of the Sociology of Science: Robert K. Merton ����������� 91 5.2 The Edinburgh School “Strong Programme”����������������������������������� 93 5.3 The Experimental Method: Cultural Assumptions and Deviance����� 94 5.4 Mathematics and Logics as Social Institutions��������������������������������� 96 5.4.1 The Empirical Programme of Relativism�����������������������������100 5.5 The Strong Programme....Reinforced: Bruno Latour�����������������������101 5.5.1 The Actor-Network Theory (ANT) �������������������������������������107 5.5.2 Culture and Nature���������������������������������������������������������������109

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5.6 A Summary���������������������������������������������������������������������������������������111 5.6.1 Realists���������������������������������������������������������������������������������112 5.6.2 Critical Realists �������������������������������������������������������������������113 5.6.3 Soft Realists�������������������������������������������������������������������������113 5.6.4 Constructivists ���������������������������������������������������������������������113 5.6.5 Relativists�����������������������������������������������������������������������������114 References �������������������������������������������������������������������������������������������������117 Part II Main Themes in STS 121 6 The  Boundaries of Science�����������������������������������������������������������������������123 6.1 The Problem of Demarcation�����������������������������������������������������������124 6.1.1 Essentialist Approaches: Falsificationism, Institutionalised Ethos and Paradigmatic Consensus�����������124 6.1.2 The Constructivist Hypothesis and Boundary Work �����������126 6.2 Drawing and Redrawing the Boundaries of the Scientific Community���������������������������������������������������������������������������������������132 6.2.1 The Royal Society at the Start of the Seventeenth Century and the Problem of Testimony�������������������������������132 6.2.2 Modern Times����������������������������������������������������������������������133 6.3 Science Situated: From the “View from Nowhere” to “Truth-Spots” �����������������������������������������������������������������������������������135 6.3.1 The Hospital and the Segmented Human Body�������������������136 6.3.2 The Laboratory���������������������������������������������������������������������138 References �������������������������������������������������������������������������������������������������144 7 Science  Behind the Scenes�����������������������������������������������������������������������147 7.1 Experiments �������������������������������������������������������������������������������������147 7.1.1 The Experimenter’s Regress�������������������������������������������������148 7.2 Facts, Black Boxes and Ships in Bottles�������������������������������������������151 7.3 Laboratory Studies and Epistemic Cultures�������������������������������������156 References �������������������������������������������������������������������������������������������������161 8 Scientists,  Experts and Public Opinion �������������������������������������������������163 8.1 Expertise: A Status Attributed to a Group�����������������������������������������163 8.1.1 An Increasingly Blurred Boundary �������������������������������������164 8.2 The Communication of Science�������������������������������������������������������169 8.2.1 Public Understanding of Science and the Information Deficit Model���������������������������������������������������170 8.2.2 From Public Engagement to Citizen Science�����������������������173 References �������������������������������������������������������������������������������������������������177

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9 Science  and Technology: Two Sides of the Same Coin �������������������������179 9.1 The Emergence of Technology Studies���������������������������������������������180 9.2 From Technological Determinism to the Social Shaping of Technology (SST)�������������������������������������������������������������������������182 9.3 The Social Construction of Technology (SCOT)�����������������������������184 9.4 Actors and Artefacts in the Actor-Network Theory (ANT) �������������187 9.5 The Ecological Approach to Technology�����������������������������������������190 9.6 Sociotechnical Imaginaries and the Sociology of Expectations�������192 References �������������������������������������������������������������������������������������������������197 10 Science, Technology and Gender�������������������������������������������������������������201 10.1 Women in Science���������������������������������������������������������������������������201 10.2 The Construction of Gender and Critical Empiricism �������������������205 10.3 The Standpoint Theory and Situated Knowledge���������������������������207 10.4 Gender and Technology �����������������������������������������������������������������210 References �������������������������������������������������������������������������������������������������213 Part III Contemporary Fields of Inquiry 217 11 Environment���������������������������������������������������������������������������������������������219 11.1 The Cultural Construction of Nature ���������������������������������������������220 11.2 Climate Change�������������������������������������������������������������������������������222 11.3 Anthropocene���������������������������������������������������������������������������������227 References �������������������������������������������������������������������������������������������������230 12 Digital Societies�����������������������������������������������������������������������������������������233 12.1 Algorithms �������������������������������������������������������������������������������������235 12.2 Digital Sociology and Its Methodological Challenges�������������������238 12.3 Artificial Intelligence ���������������������������������������������������������������������241 References �������������������������������������������������������������������������������������������������245 13 Medicine and Biotechnologies�����������������������������������������������������������������249 13.1 Medicalisation, Normalisation and Biopolitics�������������������������������253 13.2 The Human Genome Project�����������������������������������������������������������255 13.3 Biotechnology and Synthetic Biology �������������������������������������������259 References �������������������������������������������������������������������������������������������������262

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14 Five  Challenges for the Future ���������������������������������������������������������������265 14.1 Multispecies Ethnography �������������������������������������������������������������265 14.2 Agriculture �������������������������������������������������������������������������������������268 14.3 Science and the Senses�������������������������������������������������������������������272 14.4 Risks, Disasters and Resilience�������������������������������������������������������274 14.5 The Personalisation of Medicine: From Pharmacogenomics to Self-Tracking Tools���������������������������������������������������������������������277 References �������������������������������������������������������������������������������������������������280 15 C  onclusion�������������������������������������������������������������������������������������������������285 References �������������������������������������������������������������������������������������������������289

References�����������������������������������������������������������������������������������������������������������291 Index�������������������������������������������������������������������������������������������������������������������315

About the Authors

Giampietro Gobo , Professor of Sociology of Science and Methodology of Social Research at the University of Milan (Italy), deals with scientific controversies on health issues, particularly on immunisation policies. His books include Doing Ethnography (2008), Qualitative Research Practice (co-edited with C. Seale, J. F. Gubrium and D. Silverman, 2004), Constructing Survey Data: An Interactional Approach  (with S.  Mauceri, 2014) and  Merged Methods: A Rationale for Full Integration (with N. Fielding, G. La Rocca and W. van der Vaart, 2022).  

Valentina Marcheselli  is a post-doctoral Research Fellow at the Department of Sociology and Social Research, University of Trento, Italy. Her research interests include the social construction of science and technology, the social dynamics of interaction and coordination in interdisciplinary contexts, cognition and embodiment in the fields of astrobiology and planetary science.

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List of Figures

Fig. 2.1 Fig. 2.2 Fig. 2.3 Fig. 2.4 Fig. 4.1 Fig. 4.2 Fig. 4.3 Fig. 4.4 Fig. 5.1 Fig. 5.2 Fig. 5.3 Fig. 6.1 Fig. 6.2 Fig. 6.3 Fig. 6.4 Fig. 6.5 Fig. 6.6

Same word (verbal signifier) and different meanings�������������������������16 Same image (visual signifier) and different meanings�����������������������17 The relationship between thought, language and action���������������������19 The blind men and the elephant ���������������������������������������������������������26 The reversal of images in the retina ���������������������������������������������������57 Gestalt psychological tests�����������������������������������������������������������������70 The tower experiment�������������������������������������������������������������������������79 Bacteria under the microscope�����������������������������������������������������������84 The layering of statements ���������������������������������������������������������������103 Fuzzy syllogisms�������������������������������������������������������������������������������106 Nature-Culture continuum�����������������������������������������������������������������111 The School of Athens by Raffaello ���������������������������������������������������140 Philosopher in Meditation by Rembrandt�����������������������������������������141 The Anatomy Lesson of Dr. Nicolaes Tulp by Rembrandt—1632 ���141 The Anatomical Theatre of Padua 1584�������������������������������������������142 An Experiment on a Bird in the Air Pump by Joseph Wright of Derby �������������������������������������������������������������������������������������������142 A photograph of Albert Einstein�������������������������������������������������������143

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List of Tables

Table 2.1 Table 3.1 Table 3.2 Table 4.1 Table 4.2 Table 4.3 Table 5.1

Concepts of abortion in the main religions���������������������������������������14 A syllogism���������������������������������������������������������������������������������������47 Other syllogism���������������������������������������������������������������������������������48 Types of causes���������������������������������������������������������������������������������59 The syllogism of adduction���������������������������������������������������������������61 Fundamental concepts of Kuhn’s thought�����������������������������������������63 Summary of the positions on the nature of science������������������������111

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Introduction: Why Do We Need to Rethink Science?

Over the past two decades, we have witnessed a revival of neo-positivism, a philosophy of science that had been heavily scaled down in the late 1950s. In fact, the 1960s and 1970s saw the emergence of relativist and constructivist approaches which in some ways demythologised science by showing how cultural and social aspects pervade scientific practice. Today, however, we notice (not without a degree of concern) a revival of a neo-­ positivist conception of science. It is, in part, the result of the success of “analytical” (logical and formal) philosophies over “continental ones”1 (psychoanalysis, Marxism, phenomenology, post-structuralism, post-modernism, etc. that aspire to holistic or more general theories, to concepts of broader applicability and to greater caution in accepting the conclusions of scientists). There are several signs of this return of a neo-positivist nature. Examples include the widespread use in public discourse of expressions such as “natural”, “objective”, “factual”, “real truth”, “evidence-based”, “anti-scientific”, “pseudoscience”, “conspiracy theories”, “fake news”, “post-truth” and so on. A constellation of terms intended to provide a reassuring vision of science, conceived as an  In literature, these so-called philosophical currents were mainly formed on the European continent, especially in Germany and France. Instead, the so-called analytical philosophy would develop in England and in the United States. However, this distinction seems, from a theoretical perspective, somewhat coarse and geographically inaccurate. In fact, on the one hand, it would be an exaggeration that emphasises the extreme positions of the two currents, while on the other, given the continental origin also of analytic philosophy itself (with Frege, Wittgenstein, Carnap, the logical positivism of the Vienna Circle, the logical empiricism of Berlin and the Lwów-Warsaw School of logic), the geographic distinction seems to have little relevance. 1

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2022 G. Gobo, V. Marcheselli, Science, Technology and Society, https://doi.org/10.1007/978-3-031-08306-8_1

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e­ nterprise with precise boundaries and unequivocal results, demonising divergent thoughts. However, this vision ignores an ineradicable contradiction present in our society. In fact, on the one hand, there is a relentless drive, a frantic search for new certainties, and on the other, we are increasingly condemned to live in a “risk society” (Beck, 1986) and in a “society of uncertainty” (Bauman, 1999). In this unsolvable tension, with its related anxieties and fears, it can perhaps comfort the reassuring neo-positivist proposal, which promises a method for distinguishing facts from opinions, objectivity from subjectivity and scientific truths from beliefs, manipulations or lies. However, in this perspective, social and scientific contentions (e.g. on climate change, biotechnologies, electromagnetic pollution, complementary and alternative medicines, animal testing, vaccinations, etc.) instead of being critically addressed tend to be concealed or censored and divergent opinions stifled. The consequences are manifold: a return to a naïve and caricatured vision of science, the reappearance of a certain dogmatism, major obstacles to freedom of thought and to those who express methodical doubt and critical thinking, the systematic de-legitimisation (and, sometimes, media pillory) of non-aligned thinkers added to an overconfidence in technology. However, the most worrying effect is the polarisation of points of view, that is, the reduction of the complexity and multiplicity of positions (on a single issue) to only two: scientific and anti-scientific, rational and irrational, for or against. So, whoever challenges an accepted and prevalent theory (mainstream) is disqualified as being incompetent, or worse a denier, a conspiracy theorist or a pseudoscientist.

1.1 The Re-emergence of Scientism Scientism refers to that intellectual stance, originating from neo-positivism, according to which scientific knowledge must be the foundation of all knowledge in any domain, including in ethics and politics. This position has been criticised by many, both conservative and progressive thinkers. One of the first critics was the Nobel laureate in economics (1974) and Austrian naturalised British sociologist Friedrich von Hayek (1899–1992). In his Scientism and the Study of Society (divided into three parts, published respectively in 1942, 1943 and 1944) he contested application of the methods of the natural sciences to the study and resolving of problems relating to social institutions and to the community. Thereafter, Karl Popper (1902–1994), referring to Hayek himself, glimpsed the presupposition of totalitarianism in the methodological dogmatism typical of scientism. According to Popper, science progresses not only rationally but also with the help of other forms of thought such as, for example, metaphysics. Furthermore, the philosopher was

1.1  1.1 The Re-emergence of Scientism

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also sceptical about the possibility of arriving at any certainty in the scientific field without renouncing the search for truth, which is instead the presupposition of his critical rationalism. Finally, Popper argued the inconsistency of concepts such as the, greatly invoked, scientific method as an alleged objective criterion for evaluating a theory: …no scientific method exists in any of these three senses: […] there is no method of discovering a scientific theory; there is no method of ascertaining the truth of a scientific hypothesis, that is, no method of verification; there is no method of ascertaining whether a hypothesis is ‘probable’, in the sense of the probability calculus. (Popper, 1956-57, p. 6)

Other philosophers, such as Hilary Putnam (1992) and Tzvetan Todorov (2001), have also criticised the dogmatic support for the scientific method and the belief that (true) knowledge is only that which can be counted, measured and quantified (as Galilei and Descartes instead hypothesised). As if to say, if you can’t count then it doesn’t count. This is precisely the opposite of what Albert Einstein considered, who (apparently) in his office at Princeton University displayed the following maxim: “Not everything that can be counted counts and not everything that counts can be counted”. Among the progressives, Max Horkheimer (1895–1973) and Jürgen Habermas have long fought scientism, considered as a cultural phenomenon that is the child of modern Western civilisation. But perhaps the most bitter opponent of scientism was the philosopher Paul Feyerabend (1924–1994). Although he started out at a young age from scientism, he later became convinced that science is “an essentially anarchist enterprise” and does not deserve any exclusive monopoly in the “knowledge trade”. The scientist drift, then, leads to consider that any topic (scientific, social, political, ethical, etc.) should only be addressed by the “experts”, the only ones with the correct knowledge to tackle problems and solve them. Consequently to lament the fact that politicians listen too little to scientists and experts, prefiguring technocratic governments as being most suited to the task. Beware, however, that the scientist attitude is often also linked to scholars and researchers who are singled out as charlatans, impostors and pseudoscientists. In fact, they too consider their opponents ignorant, incapable or worse in the pay of industry and multinationals. In other words, both factions are often scientists and neo-positivists.

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1.2 A Complementary Vision Several studies exist that have documented how science has influenced and still continues to influence society. Other texts argue that science must be disseminated more effectively and scientists must learn to communicate with public opinion (e.g. the Public Understanding of Science movement). Yet other volumes show how science is permeable to the needs of the market and how scientific research is conditioned by multinational companies and enterprises. Finally, there are also numerous authors who believe that science must consider the demands of public opinion and listen to the proposals put forward by civil society and nonexperts. While recognising the importance of all these approaches, this text nevertheless seeks to focus on two other aspects (complementary, therefore, to those indicated above): on the one hand, how society (and public opinion) has influenced and still continues to influence science and scientific research; from this perspective the (initial) foundations of science would lie in common-sense beliefs and in the related ideologies. On the other hand is how sciences are, first and foremost, a social and cultural activity. These two aspects, despite the claims of scientism, cannot be removed from scientific activity and recognising them would make science more human, moral and useful to humanity. Recalling the lesson, now partially forgotten, of the “new philosophy of science” (Hanson, Kuhn, Feyerabend, M. Polanyi) and emphasising the importance of the social studies of science, our aim is to present a more balanced view of science while acknowledging its specificity. We also intend to shed light on its nature as a human enterprise, rooted in the spirit of the times. This historicisation and socialisation should not be considered as negative aspects, but merely as an inevitable process, inherent in any human enterprise (without exception). The purpose of the book is therefore to prepare students (and readers in general) to approach science and technology from a historical and sociological perspective, treating them as cultural and collective enterprises. It is only through the appreciation of this social character and the framing of science within human practice that a more balanced relationship (and a more tolerant attitude towards a range of opinions and assumptions) will be restored—to the benefit of both society and of science itself.

1.3  1.3 Science as a Humanist Enterprise

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1.3 Science as a Humanist Enterprise The purpose of this text is to reaffirm a humanist vision of the scientific enterprise and an approach to the sciences that Latour (2010) refers to as “scientific humanism”. According to this approach, science, nature and society are not separate entities but hybrids, entities constantly interrelated in an intermittent movement: society incorporates nature and nature incorporates society. It is not a question of being “relativist” (where everything is socially determined or negotiable). Indeed, as Latour (1991) writes, trying to use society to explain science assumes and reinforces this separation. In other words, it is not possible to be constructivist with nature and realistic with society, using it as a platform for one’s own analyses of scientific practice. Society cannot be just the starting point for explaining a contention or the deus ex machina that resolves it. In fact, “the ozone hole is too social and too narrated to be truly natural; the strategy of industrial firms and heads of state is too full of chemical reactions to be reduced to power and interest […]. Is it our fault if networks are at the same time real like nature, narrated as discourse, collective like society? We must follow them […] they are like the Kurds under the rule of the Iranians, Iraqis and Turks (they slip across borders to get married, and they dream of a common homeland that would be carved out of the three countries which have divided them up)” (Latour, 1991, p. 6). It is therefore necessary to be half relativist and half realistic. As Collins and Pinch (1993) lucidly write, science is a controversial activity: on the one hand, it provides us with the means to cure the sick; on the other, it produces the treacherous poison caused by nuclear accidents; on the one side, it offers us improved living conditions and on the other the risk of death due to the side effects of a drug. Science is therefore similar to a Golem, a creature of Jewish mythology, neither good nor bad in itself, but powerful and potentially dangerous, a meek giant with the propensity to go mad at any time and spread terror. Only in this way is it possible to understand this powerful but imperfect (and therefore human) creation that we call science, learning to love the clumsy giant for what it is. We wish to thank Gino Boriosi, Enrico Campo, Andrea Falcon, Niccolò Guicciardini and Renato G. Mazzolini for their valued suggestions on some of the topics in this book. Although the book is the result of a joint effort, Chaps. 1, 2, 3, 4, 5 and 15 are formally attributed to Giampietro Gobo and Chaps. 6, 7, 8, 9, 10, 11, 12, 13 and 14 to Valentina Marcheselli. The last access to the Internet pages mentioned in the volume took place in January 2022.

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1  Introduction: Why Do We Need to Rethink Science? This book was funded by the Department of Philosophy “Piero Martinetti” of the University of Milan, under the Project “Departments of Excellence 2018–2022” awarded by the Ministry of Education, University and Research (MIUR), and by the Department of Sociology and Social Research of the University of Trento, under the Project “Departments of Excellence 2018–2022” awarded by the Ministry of Education, University and Research (MIUR).

References Bauman, Z. (1999). In Search of Politics. Polity. Beck, U. (1986). Risikogesellschaft. Auf dem Weg in eine andere Moderne. Suhrkamp. (transl. Risk Society: Towards a New Modernity. London: Sage). Collins, H. M., & Pinch, T. (1993). The Golem. What Everyone Should Know about Science. Cambridge University Press. Latour, B. (1991). Nous n’avons jamais été modernes. Essai d’anthropologie symétrique. La Découverte. (transl. We have never been modern. London: Simon and Schuster, 1993.) Latour, B. (2010). Cogitamus: six lettres sur les humanités scientifiques. La Découverte. Popper, K. (1956-57). Realismus und das Ziel der Wissenschaft. (transl. Realism and the Aim of Science. London: Hutchinson,1983.) Putnam, H. (1992). Renewing Philosophy. Harvard University Press. Todorov, T. (2001). Imperfect Garden: The Legacy of Humanism. Princeton University Press.

Part I From the Philosophy of Science to the Social Studies of Science

2

Gnoseology: The Foundations of Human Knowledge

Gnoseology (from the Greek γνῶσις “knowledge” and λόγος “speech”) refers to the critical study of the foundations of human knowledge, essentially understood as the product of a relationship between the knowing subject and the known object. You may wonder why it was decided to include the fundamentals of human knowledge in a book dedicated to reflecting on the fundamentals of scientific knowledge. The reason is, at the same time, both simple yet complicated. Simple because, as we shall see later on (see Sect. 4.6), there is an indissoluble link between these two types of knowledge; complicated because few people choose to acknowledge this link: both the social actors (the so-called common people), who are in awe of the sciences, and the scientists, who believe they possess special knowledge. To adequately address this intricate matter, it will therefore be beneficial to continue a step at a time.

2.1 Language and Reality: Arbitrary Relationship? Many people (and among them several scientists) believe that there is actually a direct and natural relationship between a referent (e.g. a thing or an object), the meaning we attribute to it (the concept) and the word we use to name it (the term). Let’s look at, for example, the word “house”. Upon hearing it, the listener imagines a house (referent) with a series of characteristics or properties (windows, doors, roof, etc.) that, in their entirety, represent the concept of house. However, the notion lies in the head (thought) of the speaker, the word in their mouth (language) and the object in reality. There are therefore at least three distinct levels. Conversely, most people believe that type of dwelling can only be called “house” or, similarly, © The Author(s), under exclusive license to Springer Nature Switzerland AG 2022 G. Gobo, V. Marcheselli, Science, Technology and Society, https://doi.org/10.1007/978-3-031-08306-8_2

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that “house” can only be that particular object, referring to nothing else. Continuing with this thought process then, a construction made with perishable materials such as wood, foliage, leather or fabric can only be called a “hut” and a house carved into the rock must necessarily be called a “cave”. In other words, there is belief in the existence of a natural link between the term and the referent and that the three levels are actually one and the same. Your reaction might be: “well, isn’t that actually the case?” No, it isn’t and neither has it been through history. In ancient Greece, precisely between the fifth and fourth centuries BC, the philosopher Democritus supported a very different thesis, called “conventionalist”, which can briefly be summarised in four distinct points (see Marradi, 1994, p. 157): 1. There are different things which are designated by the same name (or word). 2. Sometimes the opposite is true: the same thing is designated with different names (this is the case with languages). 3. The name of a thing can change and often. 4. There are multiple ways in which names are related to things. Aristotle, instead, was firmly convinced that the link between thing and concept was natural (see Sect. 2.2), while the link between word and concept was conventional. The Aristotelian position, which outlines a “realist” conception, heavily influenced Scholastic philosophy, or rather medieval Christian philosophy. The standpoint of Thomas Aquinas, its most distinguished exponent, was that the word was the perfect reflection of the thing. Over the centuries we have witnessed an authentic escalation of the realist position that has now become the dominant epistemological one, today more than ever, even if there was a brief period dominated by postmodernism,1 in which it momentarily wavered. Some might think that this discussion is nothing more than an intellectual play on words, a philosophical game of those who have too much time on their hands. After all, reality is there right in front of us, just waiting to be grasped, described and studied. So let’s look at an example in Box 2.1.

 Postmodernism is an intellectual movement that developed between the mid- to late twentieth century. It has spanned philosophy, the arts, social sciences, architecture and literary criticism and is generally characterised by scepticism, irony or rejection of the great narratives and ideologies of modernism, often questioning various assumptions of the rationality proclaimed by the Enlightenment. 1

2.1 Language and Reality: Arbitrary Relationship?

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Box 2.1  The Felling of the Twin Towers

The 11th of September 2001 is a tragic date. The Twin Towers, which stood out against the New York skyline, were struck by two planes that had been hijacked by members of Al-Qaeda, an armed Islamic fundamentalism organisation. Following the fire that broke out internally, the two towers then went on to collapse. A few days later, in the upper echelons of politics and in the mass media, a debate arose: was it an “act of terrorism” or an “act of war”? On the surface it would seem a purely nominalistic question. Yet, the problem of how to refer to it, what name (term) to give to that event (referent) and what meaning (concept) to attribute to it seemed anything but trivial. The definition of the event was not a simple intellectual exercise but would have considerable practical ramifications and would heavily affect the reality of the events that were to follow. If it had, in fact, been called an “act of war”, with the United States being one of the members of the defensive alliance called NATO (North Atlantic Treaty Organisation), art. 5, according to which member states undertake to consider an armed attack perpetrated by any state against them as an act of aggression against all members, the other member states, including England, France, Germany, Italy and so on would also have entered the war. If, instead, it had been called an “act of terrorism”, the United States would have had to respond to this event single-handedly. As you can appreciate, there is a huge difference, almost an exaggeration, with significant consequences following on from an apparently simple decision on the name with which to label an event. And this is just the start. The Towers were insured buildings. Compensation is established by the type of contract entered into and the type of clauses it includes. In this case the Towers were “only” insured against terrorist acts, not against acts of war. So choosing one definition of the event over another would therefore determine certain practical consequences. So are you still convinced that names are simple labels that are applied to things (that exist out there, regardless of the names) and that it is things themselves that produce names, following Thomas Aquinas’ train of thought? ◄ The illiterate peasants of Uzbekistan (a Central Asian region of the former Soviet Union) who participated in the psychometric tests of the Russian psychologist in the early 1930s, Aleksandr R. Lurija (1974), when presented with a geometric figure such as a circle and asked what they saw, responded “a clock”, “the moon” or “a sieve”. When instead a literate person saw a square in a certain figure, they perceived it as “a door”, “a house” or “a mirror”. So which set of answers was

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c­ orrect? Both, because it is the concepts we have in our mind that induce or influence us to see things a certain way. Things are not self-evident. Classroom Exercise

Look at this image. This was filmed during student demonstrations in Hong Kong in the summer-autumn of 2019.

Who do you think the participants are? What would you call them? What name would you choose? 1. Demonstrators 2. Objectors 3. Activists 4. Rebels 5. Protesters 6. Troublemakers

2.1 Language and Reality: Arbitrary Relationship?

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Well, despite this vast choice, the Hong Kong government decided to classify them as “rioters”. Unfortunately, due to the legislation of that country, a “rioter” risks up to 10 years in prison.

2.1.1 The Role of Language Language does not therefore seem to refer directly to the real world or to the metaphysical one. As we have just seen, essentially, there does not therefore seem to be a direct or natural relationship between a linguistic expression (a word or a term) and the referent (the extra-linguistic reality); in the same way, there does not seem to be a natural relationship either between a concept and its referent or between the concept and the relative term, as the Swiss linguist Ferdinand de Saussure (1857– 1913) argued. What connects them is an extended construction process that we can call socio-cognitive. The connection between the linguistic expression and the object then becomes purely conventional. However, we often forget the artificiality of this link and consider it natural; that is, we forget the role of the socialisation processes through which adults educate children to combine these three distinct levels (concept, term and referent), teaching for example that the wolf is bad, or meat is good, parents scold children for their own good and opinions are passed off as truth. The problematic nature of this relationship (usually considered “natural”) only becomes evident in controversies or in situations where there is a discussion or a dispute conducted involving (at least) two opposing points of view. In these cases the cultural and social constructed nature of the concepts is shown with particular emphasis. Let’s take the example of abortion. Is it a murder or a surgical operation? Is the foetus a human being or an embryo? Is the embryo a full-fledged human being or a zygote (a “simple” cellular organism)? The question, in addition to being tragically complicated, is practically unsolvable if to answer it we follow an approach that is based purely on reality or facts. If we look at Table 2.1, which compares the definitions of abortion and foetus present in the main religions, we can see that they differ significantly and any disputes on the matter could continue ad infinitum.

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Table 2.1  Concepts of abortion in the main religions CATHOLICISM Formally prohibited in the name of respect for human life from conception. Collaborating in an abortion is a sin sanctioned by excommunication.

PROTESTANTISM They are divided. The Lutheran and Reformist Churches justify abortion stating the dangers for women while Evangelicals are always against it.

JUDAISM According to the sages of the Talmud, the embryo does not have a life of its own until the fortieth day. Once this period has elapsed, abortion represents a grave infringement. Nevertheless, rabbis retain the power to judge on a case-by-case basis. ISLAM Tolerated by Islamic law (sharía) until the 120th day; according to the Koran, only at that moment does the spirit (mithaq) descend into the foetus. Thereafter, abortion is only granted when the mother’s life is at risk. BUDDHISM Discouraged as an offence to life and to the cycle of reincarnations. Different traditions debate whether the foetus is an actual or potential human being, which would authorise abortion in the first few months of pregnancy.

2.2 Classifications: Concepts and Terms

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2.2 Classifications: Concepts and Terms Some might argue that the reality outside of us is unique and it is only the meaning (concept) that we attribute to it that changes. To respond adequately to this objection, let us try to understand the role of classifications. By now it should be clear that concepts are not snippets of reality but instead fragments both of experiences (Marradi, 1984, pp.  9–10) and of other concepts transmitted by tradition and by schooling or learned by studying, listening, reading and so on. As Schütz (1953, p. 13) states, with the concept of stock of knowledge at hand, […] only a very small part of my knowledge of the world originates within my personal experience. The greater part is socially derived, handed down to me by my friends, my parents, my teachers and the teachers of my teachers.

For example, in our culture, we have the concept of “Martian” although most people are convinced that Martians do not exist and have never met one (experience).2 Yet the concept exists. So tradition (common sense) and school play an important role, perhaps greater than experience, in the formation of concepts. Moreover, from this example we can see how concepts (as well as classifications) are neither true nor false; there is nothing inherently wrong with them, but they simply exist or they do not (in a given culture) regardless of the belief in the existence of their referent. Concepts and classifications are nothing more than heuristic tools, devices for the discovery of phenomena. In other words, they are ways to show things, to highlight interesting aspects of a phenomenon. However, each classification has at least two limitations: 1. On the one hand, it simplifies reality [“it reduces complexity”, Bruner et  al. (1956) would say]; 2. On the other, it highlights a number of aspects of a phenomenon to the detriment of others. Hence, classifications are never exhaustive, in the sense that there is always something that is excluded. There will always be some phenomena that are recalcitrant to a given classification, which will not be well explained by it or included in the classification. As the Italian political scientist Giovanni Sartori used to say,  The Austrian philosopher Alexius Meinong (1853–1920) had already proposed the theory of non-existent objects. This theory is based on the fact that it is possible to think of an object, such as the golden mountain, even though such an object does not exist in the external world. 2

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classifications are conceptual containers, not accounting tools. Therefore, they are not required to capture and include every phenomenon, but only to identify, recognise and characterise. Concepts can be personal (experience) or collective (common sense). The latter are the sedimentation of collective knowledge and memories, archives of the way in which a community conceives, describes and decodes referents in a network of shared symbols and interpretative practices. Concepts are communicated both verbally and non-verbally: verbally through words (terms) and non-verbally through multiple signs or signals (blushing as a sign of the concept of “embarrassment”, the exhaled puff as an indication of the concept of “boredom”). Terms play a fundamental role in everyday life and in science because they are the first thing we encounter in a communication. In fact, terms are the first things we hear (words) or see (signs). In reality, concepts would be more important than terms, but they have a flaw, let’s say: they are neither heard nor seen. Let’s look at some examples (Figs. 2.1 and 2.2). As we can see, we have the same term or image that relates to four to six different concepts. We are therefore faced with a polysemy, an uncertainty or ambiguity, which can sometimes be a source of misunderstanding. Even in science. In fact,

stopping of work for protest to hit (e.g. a person) strike

to light (e.g. a match) a bargain (i.e. to reach) to cause someone to feel sympathy, strike a chord. to occur (e.g. bad luck strikes)

Fig. 2.1  Same word (verbal signifier) and different meanings

2.2 Classifications: Concepts and Terms

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death poison danger (due to high voltage) pirate

Fig. 2.2  Same image (visual signifier) and different meanings

even if the context in which the term is pronounced (or the image displayed) significantly reduces situations of ambiguity by specifying their meaning, situations of semantic uncertainty are nevertheless not rare.3 In general, we can say that there are many more concepts of terms, not solely for the reason just described but also because certain concepts (emotions, sensations, forms of pain, states of discomfort or illness) are not expressible, or at least they are not fully expressed. Have you ever said “I can’t find the words…”? Here then is one case. And not because you are not educated or refined enough in your choice of words, but because certain things are unspeakable, they have not yet found an adequate term. Indeed, “the conceptual heritage of a society is immeasurably larger than the terminological heritage of the language that that society speaks” (Marradi, 1984, p. 22). So why are terms more important? Because the defect of concepts (not hearing oneself and not seeing oneself) is more “serious” than their innumerable advantages (such as, for example, giving meanings to words).

 Think of expressions such as “flexibility in work”, “university evaluation”, “modernise society”, “technological innovation”, “de-bureaucratise” and so on and of the many semantic differences, misunderstandings and conflicts they can lead to. 3

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Exercise: Words Construct Reality

Watch the movie Malcolm X by the director Spike Lee (1993). Go to Chaps. 9 and 10 (roughly between minutes 1.08.00–1.11.00, when the protagonist talks with a companion in the prison courtyard. Observe the reality-creating power of the words “black” and “white”. So what then is the purpose of concepts? If we abandon a strong idea of reality, concepts take on an even more important role because they allow us to interpret, understand and construct reality. In fact, from a radically phenomenological point of view, in spoken language we do not find words but only noises, which culture transforms into words, that is, into containers of meaning/sense. So on these pages we do not find words but only ink on paper which is transformed into words by your knowledge and skills and ultimately by social conventions. Recognising a sign such as ink, paper or noise also seems to be a construction activity. Our observational activity (both as members and as social scientists) thus appears as a construction, an attribution of terms to object referents. In this complex process, concepts and more generally classifications play a privileged role. In fact, classifications do something more than concepts: they relate concepts and link them together in a network, a generally coherent whole. If they then order them by creating hierarchies between concepts, they are transformed into taxonomies, that is, hierarchical representations (Marradi, 1990). At this point we have all the elements to address a topic we have already mentioned: the three distinct spheres of knowledge.

2.3 The Three Spheres of Knowledge: Saying, Doing, Thinking We can hypothesise that knowledge is distributed in three different spheres that are constantly interlinked (see Fig. 2.3). This semiotic triangle is undoubtedly not new and recurs several times in the literature. At least since, starting from the early years of the twentieth century, the English writer and linguist Charles Kay Ogden (1889–1957) and the English literary critic and teacher Ivor Armstrong Richards (1893–1979) published the book The Meaning of Meaning (1923), in which they proposed considering language as a triangle at whose vertices a particular function was placed (symbol, thought and referent). In the same period what was also subsequently formed (because in the meantime the two authors had already died) was called the Sapir-Whorf hypothesis, published posthumously in 1956 with the significant title Language, Thought, and Reality.

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LANGUAGE (terms)

C

THOUGHT (concepts)

B

ACTION A

(referents)

Fig. 2.3  The relationship between thought, language and action

Although apparently similar, the two proposals diverge significantly: the first follows an ontological approach,4 while the second follows a gnoseological view. In fact, considering the referent of the sign as an object (as do Ogden and Richards) risks undermining a constructivist conception of the sign (see De Mauro, 1967), redirecting us to a (pre-Saussurian) conception that is denotative of language. The function of this is a “description” of the facts of the world, instead of thinking of language as an autonomous, conventional structure, with a connotative function. In other words, it constructs the facts of the world (as we have seen in the example of the Twin Towers). It was in fact a realist conception that the Swiss linguist and semiologist Ferdinand de Saussure (1857–1913) and

4  Many scholars, including Karl R. Popper (1972), a philosopher of science of Viennese origins, have followed the ontic approach of Ogden and Richards. Popper’s next step was to argue that not only language but all knowledge could be considered as distributed in three distinct worlds: subjective experiences or mental states, statements and physical objects (the third world where, in a confused manner, a little of everything is placed: logical contents of books, libraries, memories of computers, theoretical systems, problems and problematic situations, arguments, books, newspapers and letters, and in a general sense all the products of the human mind, such as tools, institutions, works of art, myths and fiction, institutions, our way of life, our intentions and our purposes, etc.).

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then the Austrian philosopher, engineer and logician of language Ludwig Wittgenstein (1989–1951) strongly objected to. Let us therefore examine the characteristics of the three spheres of knowledge, following the approach proposed by Marradi (1994).

2.3.1 The Sphere of Thought This sphere contains concepts. As we have seen, a concept is a snippet of experience, tradition and schooling but definitely not of reality. The concept has no meaning, as is often mistakenly heard, but is a meaning (Marradi, 1994, p. 144). This distinguishes it from the term (or word) which instead is a linguistic entity (sphere of language). Only the term has a meaning. In the example above, the term “strike” has at least six meanings, each of which depends on the context (sphere of action) in which the term is presented. In theory concepts (for example of solidarity, honesty, morality, etc.) could be specific and subjectively different for each person. If so, we will have as many concepts of “honesty” as there are inhabitants of the Earth. However, in practice this does not happen because concepts are not things that we individually possess but instead are ideas that we borrow or rent from our reference group. It can of course happen that someone individually invents new concepts, especially in the field of science but for the concepts of everyday life, the contribution of each individual seems to us, in most cases, to be very difficult to establish (Marradi, 1984, pp. 20–1). Furthermore, concepts have movable boundaries and blurred outlines and as such are not perfectly superimposable. Finally, and more importantly, concepts are also cognitive categories, that is, tools that allow us to orient ourselves in daily life, to perceive events, to grasp differences and to recognise. Concepts drive us to make cognitive progress; they make us go from “looking” to “seeing”. Indeed, as the US cognitive anthropologist Stephen A. Tyler puts it, there is no inherent quality in an object that forces us to ­perceive it exactly that way (1969, p.  7). To return to the example of the Twin Towers, there is nothing in that event that forces us to call it an “act of terrorism” or an “act of war”: the expression (set of terms) that will be chosen and the related concept that will be the result of negotiations between the social actors appointed to assign a name (term) and a meaning (concept). In the words of Whorf: “the world is presented in a kaleidoscopic flux of impressions which has to be organized by our minds” (1956, p. 169).

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This is one of the main reasons why cultures and languages were created. If reality were self-evident, we would all speak the same language and think the same way because reality would impose itself on our perception. Instead there are multiple languages. Why is the same referent, for example, our prehensile organ, called “hand” by the English, “mano” by the Italians, “ruka” in Czech and “el” by the Turks? But let’s continue with concepts.

2.3.1.1 Is There Such Thing as Universal Concepts? We are Kantianly convinced that “time” and “space” are given facts, that is, they pre-exist to us; that there is a “reality” external to us, made up of “facts”; that human beings possess an “ego” and a “self”, with an “identity”, with their own “individuality”; that they are endowed with a “memory”, a “mind”; that they act driven by “intentions” or as a consequence of “causes”. And in all the phenomena that we observe we are able to identify their “subjective” and “objective”, “concrete” and “abstract”, “voluntary” and “involuntary”, “internal” and “external”, “animated” and “inanimate” components or aspects, the “part” and the “whole”. Any of us could happily subscribe to these claims. Yet scholars of ancient cultures or of African and Asian peoples have discovered that not everyone thinks this way; therefore the list just made would not concern (universal) characteristics of human beings, but it is a list of beliefs of a particular system of thought: the modern Western idiom. In fact, in the ancient Greek culture between the twelfth and eighth centuries BC, the one described to us by Homer, the concepts of “subjective” and “objective” do not seem to exist. The thing, τὸ πρᾶγμα (the factual), is never conceived as an object, that is, something that stands in front of a thinking subject who objectifies it, which reifies the surrounding world. Only starting from the eighth century BC, with Hesiod and later with Archilochus and Sappho, did the first “rough” concepts of subjectivity and individuality seem to appear. However, they never refer to an individual but to a collectivity. These authors sing and evoke the feelings of love, joy and hate of a humanity, not of a specific or particular person. What was represented in the theatre were the stories of mythical characters who embody ­ characters (Agamemnon represented the villain, Hector the brave, Achilles the invincible warrior, etc.), not actual people. It was no coincidence that the actors performed wearing a single mask, which was always the same for all the characters. It was not even conceivable that an actor could change character during the performance. When Euripides introduced changes of character into the tragedy, he attracted heavy critique from Aristotle (see The Poetics) and from

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the Athenian Comedians as the custom was for the tragedy to only include figures with immutable characters. And neither did the internal/external antinomy that Homer describes seem to be present in the Greek culture. The concepts of “personality” and of “self” appeared strange to the ancient Greeks, who did not even seem to have a unified conception of the body; they did not see it as a whole object but only perceived the arms, necks, legs, feet and torso and described them as separate objects. The Greeks have a suitable term for the body seen as skin, body surface and pigmentation which is cros; “soma” instead indicates the body as a corpse, dead, lifeless and abandoned by the psyche (the breath of life), and in Homer’s works, it is never used to refer to the living (Snell, 1946, p. 7).

2.3.1.2 Oral Cultures Versus Written Cultures The US scholar of oral and religious cultures Walter J. Ong (1912–2003) states that the notion of the existence of a separation between interior and exterior became popular with the dawn of writing (sixth century BC) and was definitively established only after the invention of printing (approximately 1450). In fact, when information circulated only orally, it was inside the mind of the individual and in collective memories: a group only knew what it was able to remember. With the advent of writing, however, information could be found outside the memories of individuals, in written texts. Aristotle himself invented the treatise and the first school (now you know who to blame!). Then with the affirmation of the press, information becomes further traceable to an object outside the mind: the book. The concepts of “internal” and “external” therefore do not seem to be present in the conceptual heritage of oral cultures. Similar findings were determined by the French anthropologist and missionary Maurice Leenhardt (1878–1954) who studied (1947) the Canaki of New Caledonia (a large island of Melanesia), by Lurija (1902–1977) who studied a number of populations of Uzbekistan and by many other scholars. The same is valid for the concept of “intentionality”. In the Western language there is the belief that people have the ability to make decisions, to choose a course of action. Reading the passages of Homer we realise instead that for the ancient Greeks the concept of “self-determination” does not seem to exist; that is, it does not seem conceivable that a person would act autonomously also because the ­ancients did not seem to possess the concept of “will” or even that of “freedom” and “necessity”. The decision is for them an event that comes from outside: it is Athena who stops Achilles (and not the latter who refrains from slaying Agamemnon); it is Zeus, the Erinyes and Moirai (destiny) who strike Achilles with madness; it is always the gods who make the person dream or think (Snell, 1946;

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Dodds, 1951). The human being in the Greco-Homeric idiom seems two-­ dimensional (only their height and width are described) without thickness or depth. In fact no character in the Iliad sees, decides, thinks, knows, is afraid or remembers in their psyche (Jaynes, 1976). The introduction of the three-dimensional perspective seems to be an effect of the advent of writing (Ong, 1982), with the preference of sight (a sense favoured by writing) over hearing (a sense favoured by orality) (McLuhan, 1962). Similarly, in the Melanesian language the concept of the human being as an autonomous agent who can enter and exit a social relationship does not seem conceivable. Leenhardt (1947) states that the Melanesian is not aware that they possess an autonomous self and cannot experience themselves as an isolated individual, delimited by a body independent of their social relations to the point that if they are removed from the village, and therefore lose their role in society, they no longer exist socially. The Melanesian considers himself or herself to be nothing more than a social being and suffers deeply at no longer being one, consequently even allowing him- or herself to die. Similar observations are also made by the British physician and ethnopsychiatrist of South African origin John C. D. Carothers (1903– 1989) comparing the indigenous illiterate with those that were literate. We could continue showing the artificiality, the arbitrariness and conventionality of many other concepts (time, space, cause, abstract and concrete, memory and mind, etc.) considered universal, biologically innate in human beings and present in reality. This is not the purpose of this book. However, from these accounts of hermeneutic philology and anthropology we can draw the following conclusion: these concepts have become the cornerstones of the modern Western idiom in such a pervasive and all-encompassing way that they have been hypostatised. In other words, from foundations of (a particular) mindset they have been mistakenly transformed by us into foundations of reality. Some might argue that the differences in language and thought are due to the environment in which a culture has developed. For example, Filipinos do not have the concepts of winter, autumn and spring (probably not even the terms) but “only” of summer and the rainy season; an inhabitant of the Amazon rainforest does not have the concept of season because there the climate is always the same; similarly the linguistic concepts of a Mayan from a flat area of the Yucatan would revolve around this particular and familiar type of geographical area and similarly for an inhabitant of a mountainous zone. Hence the classifications and conceptual organisation of an individual would be caused by the physical environment. But this sort of determinism does not explain many other phenomena.

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2.3.2 The Sphere of Language Let’s take colour recognition as an example. It would seem that colour is a property of objects: artichokes are green, blood is red, coal is black and so on. Yet the Dani of New Guinea divide, and therefore distinguish, the colours into “cold” and “warm”: the former denotes black, blue and green and the latter denotes white, yellow and red (Berlin & Kay, 1969). The Dani are not an exception. Some peoples distinguish only three basic colours (from which the gradations derive), while others only four. The boundaries between these colour ranges differ from culture to culture. The Viennese psychologist Heinz Werner (1940) noticed confusion between blue and green in various European cultures. If you happen to have a son/ daughter or brother/sister who is much younger than you, you may remember their initial difficulties in attributing the “right” colour (as we perceive it) to various objects. A sign that, once again, there is nothing inherent in the object that forces us to call it by that name. In addition, the physical environment does not seem to influence the perception of colours. It follows that not only are terms, and more generally language, conventional, but that language affects our perception. As the famous US ethnologists and linguists Edward Sapir (1984–1939) and Benjamin Lee Whorf (1897–1941) stated, it determines the way in which a certain culture perceives the world (Whorf, 1956). The theory of linguistic determinism, after a period of decline, has more recently been revived by the so-called Neowhorfians, scholars5 who through experimental tests have proposed new arguments in support of the initial hypothesis of Sapir-Whorf. Therefore, following Wildelband (1894), Rickert (1899), Weber (1922), Rorty (1979) and systems theorists, we could conceive of reality as disorder, chaos, turbulence and nebula—an opaque referent without precise boundaries and classifications as attempts to bring order and make sense of a reality that has no intrinsic meaning. An imposition on a reality that is increasingly more complex than classification. So there is no autonomous reality, independent of classifications and, ultimately, of an observer.

2.3.2.1 Facts as Material-Symbolic Phenomena Guided by Theory Speaking of his dog, Alfred Schütz (1953, p. 8) said:

 Chinese cognitive scientist Fei Xu, Belarusian cognitive scientist Lera Boroditsky, US psychologist Susan Carey, US neuroscientist and linguist Peter Gordon and Dutch linguistic anthropologist Stephen Levinson. 5

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“I look at him as my friend and companion Rover…without a special motive, not induced to look at Rover as a mammal, an animal, an object of the outer world, although I know that he is all this too”. Therefore, “strictly speaking, there are no such things as facts, pure and simple…. They are, therefore, always interpreted facts …. This does not mean that, in daily life or in science, we are unable to grasp the reality of the world. It just means that we grasp merely certain aspects of it, namely those which are relevant to us either for carrying on our business of living or from the point of view of a body of accepted rules of procedure of thinking called the method of science.” (ibid., p. 5)

In other words, our mentality assembles reality (see Box 2.2). Box 2.2  Facts as Theory-Driven: The Case of the Economic Value of a Job

The New Economics Foundation (NEF) is a group of 50 economists, known for bringing issues such as international debt to the agenda of the G7 and G8 in the 1990s. Some time ago they also proposed linking salaries to the contribution of well-being that any job brings to the community. As a result, the NEF calculated the economic value of six different jobs: three very well paid and three very low paid. In its conclusions, the NEF counter-intuitively puts bankers at the bottom of the rankings, because they drain companies and cause damage to the global economy. This is the result of a new approach to assessing the value of work, going beyond the vision of how much a profession is paid and (conversely) evaluating how a profession contributes to the well-being of the entire society. The essential point of the NEF is that there should be a direct link between how much people are paid and the value their work generates for society. For this purpose, the NEF invented a way to calculate this value and thus determine the relative remuneration. Following these principles, the NEF quantifies differently the social, environmental and economic impact and the contribution of the work performed by the different professions, ultimately affirming that the least paid jobs are the ones most useful to society. For example, by comparing refuse collectors with tax advisors, the former contribute to the safety of the environment, while the latter harm companies by doing their utmost to make their customers-taxpayers pay less tax (see https://neweconomics. org/2009/12/a-­bit-­rich). ◄ This example, from the many that can be used, highlights how facts are always material-symbolic constructions. So researchers are like a group of blind men (from a Hindu tale) who have never come across an elephant before and who learn and conceptualise how it is made by touching it (Fig. 2.4). Each blind person feels a different part of the elephant’s body, such as the side or the tusk. Then  the people describe the elephant based on their (partial) experience; however, their descriptions end up being in complete disagreement as to what in fact an elephant actually is.

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Fig. 2.4  The blind men and the elephant

They even come to suspect that the others are being dishonest and come to blows. The moral is that humans tend to project their partial experiences onto reality, thinking they have perceived the whole truth.

2.3.3 The Sphere of Action Someone might ask alarmed: so the environment in which we live has no value at all? Is it all an invention? First, speaking arbitrarily does not mean that we can wake up one morning and decide that there are eight days in the week and that the day is made up of 25 hours. A person can of course think this, but must then convince others and change the organisation of time. Arbitrary does not mean “as you wish”. It simply means that reality is constructed, with effort and lengthy negotiations, by human beings who limit (for better or for worse) the indiscriminate proliferation of concepts. Second, knowledge is not entirely in people’s heads (thought) or in their words (language): it is also in the environment, which is the stage on which actions are played out. As US engineer and cognitive scientist Donald A.  Norman (1988, pp. 6–7) writes, much of our daily knowledge resides in the world, not inside our heads. In fact, people rely on the position and arrangement of objects, on written

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texts, on the information possessed by other people, on the artefacts of society and on the information transmitted in and by culture. So there is a great deal of information out there in the world, not inside our heads. Anyone who strums a musical instrument will undoubtedly forget how to play a tune or a melody played long ago. They will have then found the chords by putting their hands on the keyboard of a piano or on the strings of a guitar: the hands “moved by themselves” (Sudnow, 1978); they were in some way independent of thought. The same can be said for the words of a song: starting to sing it, perhaps several times, the forgotten words slowly come back to mind, concatenating with those we already remember. Similarly, the anthropologist Clifford Geertz (1962) recalls that the child counts on their fingers before counting “in their head”. Knowledge therefore lies in the three spheres. Sometimes it is language that influences perception; in other cases it is thought that influences it; at other times it is action that modifies thought and language. In fact, classifications are also constituted for practical purposes. For example, the German classical Greek scholar and philologist Bruno Snell (1896–1986), to explain the fact that the Greek-Homeric idiom is devoid of concepts referring to abstract entities such as “man” and “animal” (Homer speaks only of “this man named Achilles”, “this dog or horse”), unlike the classical Greek idiom in which there is a distinction between the concept of “abstract” and “concrete”, argued that the different structure of thought was linked to the type of activity to which the two peoples were dedicated. Similarly, even the primordial Latin idiom had enormous difficulty in expressing concepts referring to abstract objects; the Romans, practical men dedicated to wars, did not at that time have an entrenched use for writing and therefore did not even possess a true literature. Furthermore, Snell points out that the Latin language lacks the article, essential to connote abstract objects; the Latin language proliferates only in demonstrative, personal, possessive pronouns, all useful for indicating concrete objects; the purpose of these pronouns is to compensate for the absence of the article. After the deportation to Rome of many Greeks (writers, teachers, educators, writers, playwrights, etc.), the Latins also learned to create a literature that initially emulated the Greek one. Despite this, the Latin idiom still has difficulty in translating the Greek article and scholars strive as best they can with very long periphrases. For example, to translate to agathon (the Good) Cicerone must use “id quod bonum (re vera) dicitur”. Professional activities (fishermen, farmers, military personnel, etc.) and those prevalent in our own community therefore also have an influence on thought and language: the nomads of the Sahara have dozens of terms to designate the camel. The Argentine gauchos have more than 100 words for the various types of horse. The Bantu of subequatorial Africa have more than 50 terms for the various types of palm. The Eskimos do not have a general concept of snow but at least six or seven different terms. Italians have dozens of words to classify coffee (see panels 2.1 and 2.2).

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Panel 2.1: Worldwide

Panel 2.2: Italy

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2.4 Tacit Knowledge: Its Role in Everyday Life and in Science

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Although thought, language and action communicate incessantly, nevertheless three distinct spheres remain. In fact, action is not limited to classifications. This is the critique of cognitive anthropology or ethnoscience and of psycho-sociological research on social representations that reveal stable and recurrent mental patterns or cognitive patterns within a social group or organisation. They believe that culture is found in the minds and hearts of the actors. According to this perspective, culture can be described through the reconstruction of categories, taxonomies and systematic rules that allow competent behaviour. But as the US anthropologist Clifford Geertz (1926–2006) (1973, p. 11) critically notes, using a brilliant analogy, “a Beethoven quartet […] no-one would, I think, identify it with its score, with the skills and knowledge needed to play it, with the understanding of it possessed by its performers or auditors”. Similarly “to make a trade pact in Morocco, you have to do certain things in certain ways (among others, cut, while chanting Quranic Arabic, the throat of a lamb before the assembled, undeformed, adult male member of your tribe) and to be possessed of certain psychological characteristics (among others, a desire for distant things). But a trade pact is neither the throat cutting nor the desire, though it is real enough” (ibid., p. 12). Just as the music is not in the score and the score is not the music, so society does not identify with its rules. The rules, the categories and the maxims neglect the context of the action, that is, the fact that a sentence is always uttered in a context and we cannot attribute to it a greater generality, valid in all situations. Also because, as we have seen in Sect. 2.2, classifications are never completely exhaustive, they are unable to include everything that happens in reality. The fact that there are always exceptions, events that do not fit perfectly into the cognitive categories at our disposal, on the one hand documents that social actors are capable of addressing new situations, not codified by their classifications, and on the other hand that concepts change under the impulse of the creative capacity that allows us (at times) to escape the constraints of thought, language and the environment.

2.4 Tacit Knowledge: Its Role in Everyday Life and in Science Every reasoning, every sentence and every action is based on tacit knowledge: a wealth of knowledge (possessed by human beings) essential for understanding and acting. Its peculiarity lies in being an elusive, implicit, nebulous knowledge. It is difficult to verbalise because it is unconscious, embedded in people’s practices more than in their minds. In fact, they use it without giving it importance. Somewhat

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like water for fish and air for all other living beings: everyone uses tacit knowledge (and especially experts) even if they don’t know they have it. And this is its main paradox: it is essential, vital for the accomplishment of an action and enormous in its quantity, but whoever uses it does not notice and does not consider it important: “A body that easily descends stairs uses extremely complex mechanical, physical, electronic, chemical, optical knowledge, instilled in it over millions of years of evolution: so complex that we do not know even the hundredth part in detail” (Gallino, 1995, p. 66). As Marradi exemplifies, “our tacit knowledge also allows us, for example, to lean enough to take a certain bend on a bicycle or motorbike at a certain speed without falling to the ground or going off at a tangent; yet, as Michael Polanyi points out […], we don’t have the faintest idea of the mathematical function that links our inclination to our speed and to the radius of the curve; and so on” (2003, p. 331). What is even more surprising is that it allows an individual to adapt (unknowingly) to a wide range of specific situations. Its unconscious aspect (still) represents an authentic mystery. In fact, for several psychoanalysts (Freud, 1916–1917; Jung, 1938–40; Fromm, 1951) intellectual operations take place in our unconscious (e.g. in dreams) that are far superior to those we are capable of in the waking state. US psychoanalyst and physician Brian Weiss (1996, p. 17) even noted that in a state of hypnosis or trance “patients are able to speak portions of languages they have never learned, or have never even heard, in their current lifetime […] an ability, which is known as xenoglossy” or to discuss complex atomic phenomena and related physical theories that they had never studied. This happens to such an extent that it provides proof (from his point of view) of reincarnation in many lifetimes. The fact of knowledge being unconscious is one of the reasons why it does not appear in interviews, research reports or manuals; instead we learn by imitation, through short conversations at work and by participating in activities. It is practical knowledge, a mixture of knowledge and technical skills. It is the know-how as opposed to know-what. In fact, those who hold it to a greater extent (the experts) look down upon those who do not have it, such as novices, apprentices, recruits, new students and so on who perhaps are fresh from study and expounding novel notions, but without practical experience. Being tacit, the only way to find out is to observe the experts as they work and talk or to ask them for explanations as a neophyte, as someone who is perfectly ignorant of the subject; at that moment, Latour and Woolgar (1979) state (speaking of scientists) the expert stands up, even changes their tone of voice and speaks with emphasis. On what basis does tacit knowledge operate? To understand this, let us consider an example cited by Marradi (2003):

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• “Frank threw a stone (TO) against a window (T) and broke it; Joseph threw a glass (TO) against the wall (T) and broke it” (Parisi, 1989, p. 237). • Although their syntactic structure is identical, everyone would interpret without hesitation that in the first case the target (T) broke and in the second the thrown object (TO) broke. ◄ Chomsky (1957) called this ability “linguistic competence”, to make these inferences extremely quickly without even knowing why. And as it is unconscious, Chomsky (1980) considers it impossible for it to be acquired through learning in the first few years of life and argues that it is innate and that language training is only necessary to activate it and direct it to this or that specific language.6 This competence operates through processes that, over the centuries, have variously been called: “intuitive induction” by Aristotle, “categorisation” by cognitivist psychologists and “typing” by Schütz (1932, 1959). As we will see in the following pages, tacit knowledge also plays a fundamental role in scientific practice. The first to have extensively documented it was the Hungarian philosopher, economist and chemist Michael Polanyi (1958, 1962, 1966). He noted how “an art which cannot be specified in detail cannot be transmitted by prescription (…) It can be passed on only by example from master to apprentice [this is why it] tends to survive in closely circumscribed local traditions. This is why it tends to survive in restricted and localised circles” (Polany, 1958, p. 55). This is what the British sociologist of science Harry Collins discovered several years later (see Sects. 7.2 and 7.2.1). In research on the duplication (by some scientists) of a laser in laboratories other than the original one where it was previously invented by other scientists, he discovered (Collins, 1974) that the articles in scientific journals, as well as the most detailed illustrations and instructions for mimeographed use, were not sufficient to reproduce the model in other laboratories because different interpretations are possible even of the simplest and clearest prescriptions (Collins, 1983, p. 276). Hence some laboratories sent their researchers to gain direct experience at the original laboratory. Only at that point, returning to their respective locations, were these researchers able to exploit the accumulated knowledge, providing the necessary instructions to build the new laser. Of course, none of the scientists interviewed gave any importance to the role of experience, that is, of informally acquired knowledge.  “Similar theses had already been supported by Descartes (1628), by the logicians of Port Royal (Arnauld and Lancelot, 1660; Arnauld and Nicole, 1662), by the Cartesian Cordemoy (1688) and by von Humboldt (1836)” (Marradi, 2003, p. 235). 6

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Exercises

Exercise 1 Take a pen and paper. Find a classmate. Together choose any term and, separately, try to see how many referents (and related concepts) are connected to it. Then compare your results. Exercise 2 Work on the concept of “sister”: how many referents have you been able to find? Exercise 3 Repeat what you did in Exercise 2, but choose a sentence and see how many meanings it can have. For example “take it up” can mean: (a) (b) (c) (d)

“Pursue the matter” as in take it up with the relevant authorities; “Shorten” as in take up that curtain; “Physically elevate” as in take it up to the top floor; “Remove” as in take up the carpet.

Further Reading • Bowker Geoffrey C., Leigh Star Susan (2000); • Marradi Alberto (1990); • Roth Wolff-Michael (2005). Check Your Preparation

What is a concept? What is a classification? What is a taxonomy? What is a term? Are there multiple terms or concepts? Why?

References Berlin, B., & Kay, P. (1969). Basic Colour Terms. Their Universality and Evolution. University of California Press. Bowker, G. C., & Leigh, S. S. (2000). Sorting Things out. Classification and Its Consequences. The MIT Press.

References

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Bruner, J. S., Goodnow, J. J., & Austin, G. A. (1956). A Study of Thinking. John Wiley & Sons. Chomsky, N. (1957). Syntactic Structures. Mouton & Co. Chomsky, N. (1980). Rules and Representations. Behavioral and Brain Sciences, 3(127), 1–61. https://doi.org/10.1017/S0140525X00001515 Collins, H.  M. (1974). The Tea Set: Tacit Knowledge and Scientific Networks. Science Studies, 4(2), 165–186. https://doi.org/10.1177/030631277400400203 Collins, H.  M. (1983). The Sociology of Scientific Knowledge: Studies of Contemporary Science. Annual Review of Sociology, 9(1), 265–285. https://doi.org/10.1146/annurev. so.09.080183.001405 De Mauro, T. (1967). Introduzione. In F. De Saussure (Ed.), Corso di linguistica generale. Laterza. Dodds, E. R. (1951). The Greeks and the Irrational. University of California Press. Fromm, E. (1951). The Forgotten Language. An Introduction to the Understanding of Dreams, Fairy Tales, and Myths. Rinehart. Gallino, L. (1995). Il gioco delle rappresentazioni culturali di scopi e referenti dell’azione nella mente dell’attore. In P. Borgna (a cura di), Corpi in azione. Sviluppi teorici e applicazioni di un modello dell’attore sociale (pp. 63–88). Rosenberg & Sellier. Geertz, C. (1962). The Growth of Culture and the Evolution of Mind. In J.  Scher (Ed.), Theories of the Mind (pp. 713–740). The Free Press. Geertz, C. (1973). The Interpretation of Cultures. Basic Books. Jaynes, J. (1976). The Origin of Consciousness in the Breakdown of the Bicameral Mind. Houghton Mifflin. Jung, K.  G. (1938–40). Psychology of Yoga and Meditation: Lectures Delivered at eth Zurich, 6. : Princeton University Press. Latour, B., & Woolgar, S. (1979). Laboratory Life. The Construction of Scientific Facts. Sage. Leenhardt, M. (1947). Do Kamo. La personne et le mythe dans le monde mélanésien. Gallimard. Lurija, A.  R. (1974). Ob istoricheskom razvitii poznavatel’ nykh protsessov. Izdatelstvo “Nauka”. (transl. The Cognitive Development: Its Cultural and Social Foundations. Harvard: Harvard University Press, 1976). Marradi, A. (1984). Concetti e metodo per la ricerca sociale (3rd ed. accresciuta). Giuntina. Marradi, A. (1990). Classification, Typology, Taxonomy. Quality & Quantity: International Journal of Methodology, 24(2), 129–157. https://doi.org/10.1007/BF00209548 Marradi, A. (1994). Referenti, pensiero e linguaggio: una questione importante per gli indicatori. Sociologia e ricerca sociale, 43, 137–207. Marradi, A. (2003). Il ruolo della conoscenza tacita nella vita quotidiana e nella scienza. In F. Lazzari & A. Merler (Eds.), La sociologia delle solidarietà. Scritti in onore di Giuliano Giorio. FrancoAngeli. McLuhan, M. (1962). The Gutenberg Galaxy: The Making of Typographic Man. The University of Toronto Press. Norman, D. A. (1988). The Psychology of Everyday Things. Basic Books. Ong, W. J. (1982). Orality and Literacy. The Technologizing of the Word. Methuen & Co. Parisi, D. (1989). Intervista sulle reti neurali: cervello e macchine intelligenti. il Mulino. Polanyi, M. (1958). Personal Knowledge: Towards a Post-Critical Philosophy.

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Polanyi, M. (1962). Tacit Knowing: Its Bearing on Some Problems of Philosophy. Review of Modern Physics, 34(4), 601. https://doi.org/10.1103/RevModPhys.34.601 Polanyi, M. (1966). The Tacit Dimension. The University of Chicago Press. Popper, K. (1972). Objective Knowledge: An Evolutionary Approach. Oxford University Press. Rickert, H. (1899). Kulturwissenschaft und Naturwissenschaft. J. C. B. Mohr. Rorty, R. (1979). Philosophy and the Mirror of Nature. Princeton University Press. Roth, W. M. (2005). Making Classifications (at) Work: Ordering Practices in Science. Social Studies of Science, 35(4), 581–621. https://doi.org/10.1177/0306312705052102 Schütz, A. (1932). Der sinnhafte Aufbau der sozialen Welt. Springer. (transl. (1953). Common-­ Sense and Scientific Interpretation of Human Action. Philosophy and Phenomenological Research, 14(1), 1–37. https://doi.org/10.2307/2104013) Snell, B. (1946). Die Auffassung des Menschen bei Homer. In B. Snell (Ed.), Die Entdekkung des Geistes. Studien zur Entstehung des europäischen Denkens bei den Griechen. Vandenhoeck & Ruprecht. (transl. The Discovery of the Mind. Oxford: Blackwell, 1953). Sudnow, D. (1978). Ways of the Hand: The Organization of the Improvised Conduct. Harvard University Press. Tyler, S. A. (1969). Cognitive Anthropology. Holt Rinehart & Winston. Weber, M. (1922). Gesammelte Aufsätze zur Wissenschaftslehre. Mohr. Weiss, B. (1996). Only Love Is Real. Grand Central Publishing. Werner, H. (1940). Comparative Psychology of Mental Development. International Universities Press. Whorf, B. L. (1956). In J. Carroll (Ed.), Language, Thought and Reality: Selected Writings of Benjamin Lee Whorf. The MIT Press. Wildelband, W. (1894). Geschichte und Naturwissenschaften. Rector speech at Straßburg.

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Epistemology: The Foundations of Scientific Knowledge

The word epistemology means the critical study of the basic aspects, validity and limits of scientific knowledge. The term, coined in 1854 by the Scottish philosopher James F. Ferrier, over the years has come to assume a variety of meanings. It has also become synonymous with “philosophical perspective” as there is more than one type of epistemology, depending on the conception that scholars actually have of reality and of the role played by concepts and terms. To start with, we can state that many of the aspects argued regarding classifications, tacit knowledge and the functions of thought, of language and of the actions of everyday life (see Chap. 2) are also applicable to science. “But then how”, you might ask, “can a scientist be classified as just any other person?” Well, they cannot actually. A scientist is a different person in the same way that a plumber is different from a carpenter or a surveyor is different from an accountant. With a little patience and reading through to the end of this chapter, this statement will not seem so far-­ fetched.

3.1 Neo-positivism Comparing a scientist to a carpenter would no doubt be considered quite an insult for many scientists and philosophers (while carpenters would undoubtedly be glad to hear of the comparison). Such a reaction of astonishment or disbelief has very deep roots. We don’t know exactly how deep as the concept of science is, on balance, fairly recent (see Box 5.2). In fact, Galilei would never have considered himself to be a “scientist” (a term invented by William Whewell in 1833). Instead, the concept of reality had a huge influence on a certain type of epistemology, namely © The Author(s), under exclusive license to Springer Nature Switzerland AG 2022 G. Gobo, V. Marcheselli, Science, Technology and Society, https://doi.org/10.1007/978-3-031-08306-8_3

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positivism, that developed during the second half of the nineteenth century. The roots of nineteenth-century positivism then led to the birth of neo-positivism. Neo-positivism (1900–1951) was a manifold cultural movement that influenced reflection on science for over half a century, until the start of the 1950s.1 Ludwig Wittgenstein (author of the Tractatus logico-philosophicus of 1921), the philosopher, logician, mathematician Bertrand Russell and the members of the so-called Vienna Circle are considered to be leading exponents of neo-positivism. Obviously, during this period other philosophical perspectives proposed by the mathematician, science historian and philosopher Federigo Enriques (1906) in Italy; by the philosopher, science historian, physicist and mathematician Pierre Duhem (1906); by the science philosopher Gaston Bachelard (1934) in France; and by the microbiologist and philosopher Ludwig Fleck (1935) in Poland were also at odds with each other. Despite this, neo-positivism was the dominant perspective at that time. Its heyday was around 1930 with the Vienna Circle, a group of scholars that, among others, included the German physicist and philosopher Moritz Schlick, who is considered the founder and main creator of the movement, the German philosopher and logician Rudolf Carnap, the mathematicians, logicians and philosophers Gottlob Frege (German), Kurt Gödel (Austrian) and Alfred Tarski (Polish) and the Marxist sociologist, economist and philosopher Otto Neurath (Austrian).2 The development of the movement (highly organised both from an editorial perspective with journals, series and encyclopaedias and from a communication point of view with conferences, international symposia and congresses) ground to a halt with the advancing of Nazism; in fact, many of the leading exponents (as Jews threatened by persecution) fled to the US. Neo-positivism is also known by the name of “logical empiricism” or “logical positivism”.3 Empiricism and logic are two fundamental terms that define the epistemological orientations of this movement. Empiricism is that Anglo-Saxon tradition which was taken forward by Francis Bacon (1561–1626), its forerunner, and by Thomas Hobbes (1588–1679), John Locke (1632–1704) and David Hume (1711–1776). It considers the following:  Forerunners of this movement, among others, are indicated (and not always entirely correctly) including the German physicist Ernst Mach (1838–1916), the Austrian physicist, mathematician and philosopher Ludwig Eduard Boltzmann (1844–1906), the German philosopher and psychologist Hermann Brentano (1838–1917) and the Austrian philosopher Alexius Meinong (1853–1920). 2  Despite sharing the same intellectual perspective, the authors are also very different from each other, whose positions are not always compatible or whose positions are not always compatible or superimposable. 3  Even if the term positivism is rejected by Carnap. 1

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–– Experience is the primary source of knowledge (knowledge can only come about from experience, that is from what occurs with immediacy. –– The study of nature is the privilege of an empirical science. –– Induction is the main form, or structure of thought, of scientific reasoning. –– Perception and observation of phenomena are direct, without any previous theoretical influences. –– The correct approach of the scientist is to tackle the topic of study without any preconceived ideas: they must ensure a tabula rasa of the theories available and in circulation and of the values and ideologies so that their observation is not influenced or distorted by them. –– The critique and rejection of metaphysics must be clear as its statements (propositions) are not true and therefore make no sense (meaning). –– The world is created from a set of single “elementary” facts. –– The principle of causality is a metaphysical, or perhaps pre-scientific, principle that does not fall within scientific reasoning. In keeping with English empiricism, and in particular with Hume, it is argued that what we see and observe is only a succession of phenomena or events, not the creation of some by others. For logical empiricists, even the principle of determinism,4 which underpins the principle of causality, does not form part of science. This type of empiricism is called logic because it is based on a careful logical analysis of scientific claims through recourse to philosophy. Even if, according to this school of thought, philosophy is not a science (but only a minor discipline that cannot contribute knowledge), in any case it plays an important role: that of inviting a reflection on the language of science, that is on its syntax or logical rules that guide the construction of scientific findings. If instead philosophers intended to produce knowledge, they would alternatively deviate towards metaphysics. Instead, the role of philosophy is “only” to develop an activity with the aim of clarifying ideas, concepts and the method of science. In other words, philosophy is logical. The task of logic is to check the truthfulness or falsity of statements. This is what Schlick, the former Wittgenstein5 and then Carnap mean when they refer to logical analysis of scientific language. Carnap (1934, p. 279) in fact states: “Apart from the questions of the individual sciences, only the questions of the logical analysis of

 Principle that stems from a philosophical conception with a marked mechanistic character, according to which each phenomenon or event of the present is necessarily determined by a historic phenomenon or event. 5  We say former Wittgenstein because thereafter he radically distanced himself from the initial positions expressed in Tractatus. 4

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science, of its sentences, terms, concepts, theories, etc. are left as genuine scientific questions. We shall call this complex of questions the logic of science”. Finally, according to neo-positivists, it is necessary to achieve a greater unification of science that is still too fragmented into many disciplines that fail to communicate with each other and to create a singular method for science as a common base for all the disciplines. For this purpose, its proponents brought out a publication called Journal of Unified Science and two series of monographs that in 1938 converged to become the Library of Unified Science; the same year saw the publication of the International Encyclopedia of Unified Science. Succinctly summarised, there are five fundamental pillars of logical empiricism: the concepts of reductionism, meaning, verification, law and induction.

3.1.1 Reductionism According to the former Wittgenstein, everything is a fact, including words and statements. Therefore, if we are in the presence of truth, then consequently facts and words harmonise; this takes place because the statement expresses the reality, it is a reflection of it. In other words, there is an isomorphism between the structure of the fact and the structure of the statement. Consequently, we must consider as true statements (genuine) only those that allow us to establish a direct relationship between language (propositions) and the empirical reality (the facts). Only true statements have meaning and vice versa statements that have meaning are therefore true. The empirical reality, the world, consists of (and therefore is completely described as) a set of “elementary” or basic statements: the so-called “atomic propositions or protocol sentences” (Carnap, 1932/33). These are observational, concrete and direct statements (sentences), such as “patient no.18, 6 o’clock, temperature 37.5 °C” or “my body sees red”, which can be translated into the statement: “body C is now seeing red”. These statements do not require confirmation as they refer to the data of the senses and do not refer to other statements. Protocol sentences are useful as a basis for all statements of science that are often more complex, in the sense that they are constructed (like pieces of Lego) using various elementary statements. However, states Wittgenstein, there is a problem: in scientific tests there are many more statements than the elementary ones. This therefore means that we are presented with a certain number of statements that are somewhat redundant, perhaps even completely false. The former Wittgenstein is determined to remove every non-empirical statement. But, how can this be achieved? Schlick and then Carnap argue that to establish whether a statement is true (that it therefore

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has meaning) we need to deconstruct it in reverse, through subsequent definitions based on logical transformations and reduce it until only words appear in it whose meaning is no longer defined but solely demonstrated. As such, with the aid of logic, we would need to somehow scrupulously define things and show how complex statements are constructed starting from elementary ones. There is no way to understand the meaning of a statement (in other words to discover if it is true) if not progressively reducing it, through the correct application of logical rules, to ostensive definitions that guide us directly to the experience. This approach therefore guides us towards a reduction of all levels of reality to focus on just the one, the physical-natural aspect: there is nothing but a class of objects which are physical events. As a result we find ourselves faced not only with a logical reductionism but also with a methodological one, essentially reducing all the sciences into one singular discipline and so, essentially, any type or level of scientific language can be translated into the language of physics (physicalism).6

3.1.2 A Denotative Theory of Meaning In the example of the destruction of the Twin Towers (see Box 2.1) we saw how naming that event a terrorist attack or an act of war could actually make a huge difference. In the perspective presented in Chap. 2, names have a connotative meaning, in the sense that they connote (create) certain properties or characteristics.7 Instead, the neo-positivists, Frege in particular, and many modern-day ­scientists argue that names have a denotive meaning; in other words they appoint a referent (object) that already in itself exists. Names do nothing else but reflect reality, recording it. So, if the statements are true, they denote the truth; if they are

 In social sciences, this position has led to the rejection of mentalism and an embracing of behaviourism. Behaviourism rejects the use (for example) of concepts of intelligence, intention, interpretation and so on, to explain human behaviours because concepts (being in the mind) cannot be observed. Behaviourism only focuses on actions, only on observable entities. If in the context of biology all the phenomena of life can be described and explained through physical and chemical laws, in the sphere of psychology, behaviourism theories consider that all the psychic and mental processes must necessarily be reduced to behaviours and must therefore be expressed in neurophysiological terms. 7  If we are consistent with a constructivist approach, we should use the term “attributes” instead of “properties” or “characteristics”. In fact, the properties are elements possessed by the referent (therefore an objectualist position), while the attributes are elements attributed to the referent by an observer. Added to this is the fact that different observers could attribute different elements to the same referent. 6

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false, they denote falsehood. Russel also, while making several changes and placing various limitations on Frege’s theory, would continue to pursue a theory denotative of meaning. The former Wittgenstein also supported this position.

3.1.3 The Verification Principle The third cornerstone of neo-positivist epistemology sees in ostensiveness (demonstrating) the only possibility of verification. Reference is made to possibility and not to tout court verification, because the latter is reached at a subsequent time, once the reduction has occurred. In fact, an elementary statement only has meaning if the rules (logics) of its derivation from protocol statements are clear, in other words if the path to be taken to verify it is known. The principle of verifiability, as a control criterion of the meaning of scientific statements, is the starting point to weaken metaphysical theses and in general all false statements. Schlick therefore theorises the two neo-positivism pivots: (1) the reduction of propositions to statements that (2) permit the possibility of verification. As the basic units of the world are elementary experiences (Carnap, 1928) and that for all sciences there is a single and certain foundation, which is experience, verification has a clear road ahead.

3.1.4 The Concept of Scientific Law Now let us take a look at the penultimate cornerstone of neo-positivism: the concept of scientific law. According to Carl Gustav Hempel, German mathematician, logician and philosopher, the task of scientific research is to discover regularity in the seemingly disordered flow of events and therefore to enucleate a set of general laws for the purpose of prediction and explanation, to make sense of it all. According to Hempel (1952/58), explaining and predicting are two activities that share the same structural logic. The scheme of scientific argumentation is, in fact, called hypothetical-deductive or nomological, in order words the search for nomos (which in Greek means “laws”). Hempel therefore corrects the inductivist position of neo-positivism of the 1930s, against which even Popper would conduct a full-scale battle. The model of hypothetical-deductive reasoning consists of a set of statements  on individual events (particular) and a set of laws (general) that explain these individual events. A scientific law is a universal statement that affirms a constant relationship, simple or statistical, between properties. For example, the statements “all metals are conductors of electricity” and “the probability of a newborn being male is 50%” are

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statements of laws. However, the universality is a necessary but insufficient requirement (a condition). Other conditions are also required to be able to affirm that it in fact relates to a law. Second, it is essential that every single part of a statement is verifiable and has successfully passed verification tests or that it is deducible from other laws or theories that have been successfully verified. There is, however, one problem: neo-­ positivists realise that much scientific progress has also come about through laws without observable or ostensible referents, laws relating to hypothetical or theoretical entities (in other words, objects, events, attributes, which cannot be perceived by the senses or be directly observed, such as quanti or qualia). To resolve this problem, Hempel distinguishes empirical generalisations (wood floats in water, metal sinks) from actual theories (laws in the strictest sense). Even if both are verifiable, empirical generalisations are the result of an ascertainment; theories, instead, are the product of a law because the latter indicates a necessary relationship between events or properties of which the regularity relationship is stated. Therefore, empirical generalisations only characterise the initial stages of a science; then when it develops, it produces laws that are used to understand hypothetical entities: magnetic fields, energy, space, weight, force, mass, speed and so on. Consequently, the vocabulary of a science is split into two classes: observational and theoretical terms. Finally empirical generalisations are different from theoretical laws because the former have a limited field of validity (where reference is made solely to water, wood and metal); furthermore, within this field, there are always a number of exceptions: for example, empty metal spheres float while metals found in another shape, with a greater specific weight, in general tend to sink (ibid., p.  54). Formalising it with the language of logic, empirical generalisations can be represented in the following way: ∃x (Px→Qx), where ∃ means “for some”, while for the laws ∀x(Px→Qx) where ∀ means “for all”.

3.1.5 Induction Regarding this concept, the positions of neo-positivists are the most uncertain. Initially they considered that induction was the guiding structure of scientific reasoning. But later Carnap (on this point agreeing with Popper) changed this position, assigning to deduction the role of protagonist and to induction a secondary role. He also agrees that scientific discoveries do not take place through induction. However, Carnap considers (and this is the reason that grounds him in neo-­positivist ideology) that how theories are formed is an irrelevant problem. What instead is

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important is how they can be justified, how they can be validated; in this case induction, with its logical rules, plays a fundamental role. Expressed otherwise, for Carnap the logic of induction is the expression of rationality; the scientist must accept the most probable hypotheses (instead Popper, as we shall see shortly, argues the opposite: it is the most improbable hypothesis that must be pursued). The logic of induction therefore maintains a direct relationship between experience and theory. Hans Reichenbach, German philosopher of science, also makes a valid contribution on this point, arguing that there is a clear distinction between the context of the discovery (the psychological, social, political and economic reasons that come into play in each scientific discovery) and the context of the justification, in other words the inductive procedures used to give basis and validity to the same discovery. According to Reichenbach (1951), the two contexts vary in that they are governed by different logics; in the context of the discovery, dissimilar logics are active (and permitted); in that of justification, the only logic that has credence is of the inductive type.

3.1.6 The Legacy of Neo-positivism The positions of logical empiricism may be considered by some to be splitting hairs, also in light of the highly philosophical, excessively formalised and even somewhat convoluted language with which they are discussed. They are positions that appear philosophically almost entirely outdated. And yet most modern-day scientists continue to be (practically) inspired by neo-positivism. Just think of how much the word “verify”8 is still widely used among scientists or the emphatic tone with which the words “facts” and “data” are uttered. Or how diffuse and dominant the reductionist logic in natural sciences is, which assimilates living material to the inanimate type, biology to physics and to mechanics, one animal species to another, ignoring the specificity of each species and the actual complexity of natural phenomenon. This reductionist culture guides, for example, research on genetically modified organisms (OGM) or animal experimentation; rodents, dogs, cats and monkeys are considered biological models for the human organism, ignoring the numerous differences that (in metabolism, in genetics, in physiology, in ­immunology, etc.) are found between one species and another. The critique levelled against such studies is not so much based on the call to simplify the phenomena; in

 Paradoxically, this term, with its Latin roots, made up of verum (true) and facere (make, render) seems more akin to a constructivist epistemology. 8

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fact, reducing complexity is a cognitive, as well as a practical, need that is linked to the limits of our reasoning ability. The critique instead focuses on the validity of the use of the animal model. In other words, it is as though the sociologist, to study hierarchies or the relations of power in organisations, should take the hive as a model.

3.1.6.1 We Are Not a Mouse Weighing 80 kg! A recent case concerns vitamin E: for many decades it has been widely promoted and sold as an adjuvant for fertility, for the nervous and muscular system. Today it is agreed that it is only essential for mice and not for human beings; in fact, if the food of mice lacks this vitamin, they experience severe deficiencies whereas if it is absent in the food of humans, no visible damage is evident. The French molecular toxicologist, Claude Reiss (2004), who for years studied the evolution of AIDS, documented the unreliability of experiments on animals: take, for example, the chimpanzee, the closest species to humans of those normally used in the laboratory. The chimpanzee is completely immune to AIDS: the virus has no effect on it. Instead, for example, with the Ebola virus, their physique behaves like ours. How, therefore, can a test on another species be validated when their reactions vary each time from ours? According to Reiss, the reductionist culture that guides the experimentation of products on animals (an indication of which is given by the term “clinically tested” stated on the pack) involves the occurrence each year in France of the hospitalisation of around 1,300,000 persons suffering from the detrimental effects of medicinal drugs. Similarly, in the US, 100,000 people die each year because of adverse reactions from such drugs, considered completely harmless in tests on animals. Drug reaction illness, from an epidemiological and statistical perspective, is (depending on the years) the fourth or fifth most frequent cause of death. In 1998 JAMA, one of the most important medical journals in the world, published two pieces of research that documented how 52% of drugs marketed in the US had caused serious adverse reactions, essentially leading to death, the risk of death or permanent disability. For this reason, it is important to extensively study neo-positivism and its scientistic ideology. However, neo-positivists have also asked relevant and undoubtedly very thought-provoking questions: which are the criteria to distinguish scientific knowledge from other types of knowledge (metaphysics, religion, ethics, aesthetics, etc.)? How is science progressing? How are scientific theories developed? How can we control the values and ideologies of scientists (as they are human beings) so that they do not contaminate scientific knowledge? How can we defuse ­arbitrariness and subjectivity? How can we construct a neutral and objective science? Through which method? What are the elements that characterise scientific reasoning (as

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distinct from other reasonings)? What are the tasks of science in modern-­day times? What are the tasks of philosophy? Does science have a place in political, moral and social issues or should it avoid them? These are just some of the issues that logical empiricism addresses and places at the centre of contemporary reflection and debate. After all, if we started this book by focusing analytically on the difference between concepts and terms, this is also a stance attributable to the neo-positivists. However, at the same time other authors, while starting from the same questions, will provide different if not opposite answers. One of these is Popper.

3.2 Popper’s Realism and Critical Rationalism The intellectual training of Popper developed in a cultural climate dominated in fact by neo-positivism. He then began to study logic and methodology (even if he essentially remains a philosopher) and taught at the London School of Economics from 1946 to 1969, the year in which he retired, with a spell of nine years that he spent in New Zealand. While not being of English origin, due to his intellectual merits, he was appointed a baronet by the Queen. His reflection was in fact prompted by the questions posed by Viennese logical empiricism. Contrary to what was considered for a long time, Popper had never been a positivist and even less so a member of the Vienna Club. Conversely, his philosophy was in open controversy with logical empiricism and indeed he himself states, in Replies to My Critics and in Autobiography, that he was the artificier of his own undoing. Similar to the logical empiricists, Popper poses the problem of how to strictly outline the guidelines of scientific reasoning, which he (like them) considers rational: in fact, both for the neo-positivists and for Popper, science is first and foremost rationality. However, to this problem the author provides a response that is diametrically opposed to that presented by logical empiricists.

3.2.1 Falsifiability According to Popper, the role of experience has been overestimated. In fact, the task of experience is neither to give meaning to propositions (or statements) nor to verify them. The author, in his critique of neo-positivism, argues that the principle of verifiability, if applied literally, results in us denying the possibility that s­ cientific laws are verifiable. In fact, what the scientists do when they verify is to focus on single events, in other words, on particular facts. However, the laws are universal

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statements. As such, how can a particular event verify a general statement? There is, therefore, a clear contradiction: no single statement of experience can guarantee the truth of a universal statement. Popper’s example (1934, p. 4) is well known: “no matter how many instances of white swans we may have observed [experience], this does not justify the conclusion that all swans are white”. To be able to say “all”, the scientist would have had to have actually seen them all, that is, to have experienced each of them. But this is impossible from a practical point of view. So do we need to dismiss the hope of finding universal laws and instead be satisfied with constructing statements that are valid but only locally? Some post-Popper scholars would answer yes to this question (see Chap. 4). Instead, Popper does not deny this possibility but shrewdly turns the verificationist approach around: while a very large number of cases drawn from practical experience are never able to demonstrate the validity of a universal assertion, in any case even just the one case is sufficient to highlight its falsity. Let us look at an example. The universal law “all metals conduct electricity” cannot be verified. However, if we find even just one case in which this does not occur, the assertion loses its universality and it would therefore be necessary to review its scope. According to Popper, it is impossible to justify the validity of a universal theory by means of experience, even for purely practical reasons: we would need to find all the pieces of metal existing on this earth and check whether each of them conducts electricity; this would involve a huge number of resources, time, specialist personnel and so on, with the risk that perhaps some pieces of metal might be overlooked and therefore not be verified. Science does not proceed by experience and verifications, as the neo-positivists state (and how most contemporary scientists still think), but by hypotheses and falsifications or rather by Conjectures and Refutations, also the title of his most important work, the one that made him famous (Popper, 1963). However, in Popper the experience is not completely devalued, but takes on a different role from that afforded to it by the logical empiricists. Subsequently Carnap would turn his back on the notion (illusory and impractical) of verifiability, instead replacing it with that of “degree of confirmation”: a scientific hypothesis can never be verified, but only confirmed (supported, sustained) by empirical evidence. Popper therefore persuades his colleagues that experience has the task of falsifying a theory, in other words of finding that particular case in which what was envisaged by the statement is not evident to our senses. So does this mean that the scientist must adapt to working in a world without certainties? Not exactly. Of course, there will be certainties. So, if we can never conclusively know if our theory is true, we can instead know, with a certain degree of confidence, if our theory is false.

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3.2.2 Science on … Stilts The scope of Popper’s statements does not end with the important but finite critique of the concept of verifiability but has implications of a more general scope. The first of these implications has to do with the building blocks of scientific knowledge. Popper introduces the notion, unknown to neo-positivists, of the fallibility of science: scientists can in fact make mistakes and fail to see the truth; they can never be assured that their theory is true. Hence, Popper is a proponent of the idea that the theories are plausible, that is, merely an approximation to the truth and not a reflection of it. This does not necessarily imply a sceptical or relativistic conception of science, but only the idea that science does not rest on absolute and constantly stable foundations, but instead on a somewhat slender base; so thin in fact that even one case could bring into question a theory that has been accepted for decades or even centuries. Science is therefore a stilt house, a construction of fragile materials which rests on stilts, not a castle forged on rock.

3.2.3 Political Liberalism The second implication of Popper’s philosophy is a liberal conception, both of science and of society. In fact, his philosophy goes beyond the limited scope of science and also has reflections in political thought. The author argues that if from a theoretical point of view assertions and theories can be continually questioned, the practical condition that guarantees this possibility is that there is a science (and consequently also a society) that is free-minded, open to critique, not set in its ways or in stone, and, as such, therefore willing to continually question itself. According to Popper, this type of science is only possible in a democratic and liberal society, but undoubtedly has no place in a totalitarian society (Nazi, fascist, communist, theocratic, etc.).

3.2.4 The Critique of Induction By replacing the criterion of verifiability with that of falsifiability, Popper deals another fell swoop to neo-positivism as it removes the falsifiability of an aspect that is particularly dear to logical empiricists: that of being able to attribute significance (meaning) to statements, that is, to discover and separate true statements from false ones, such as tautologies, syllogisms and pseudo-scientific propositions. In fact,

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according to neo-positivists, verification paved the way for the discovery of false statements (therefore without meaning) even if they seem true from a logical perspective. In other words, verification compensated for the flaws of logic and became a resource to draw on when the latter was in difficulty. Let’s look at the examples (see Table 3.1). Nobody would have anything to object to these three statements. Now let’s look at these three examples (Table 3.2). Even if logically flawless, we perceive that there is something amiss in these conclusions even if we cannot explain why. Logical empiricists used to say that this was the time to introduce verification. Through the inductive method and experience, it would reveal nonsense and therefore the falsity of statements that from a logical-formal point of view seemed true because they followed a certain rigorous path (apparently). The problem stems, therefore, from the fact that logic only deals with the form (the structure) of an expression and not with its content. Popper criticises this representation of the problem of induction and of the meaning. He retains that induction is a logically unjustifiable process, psychologically impossible and epistemologically irrelevant. Indeed, scientific discovery does not proceed by induction; rather it advances by: –– Deductions, that is moving from one idea to another (contrary to the conception of the scientific mind as a tabula rasa) and not from one experience to another; –– Falsifications, in the sense that the only valid conclusions are those that come about from disproof or falsifications of theories, not from their verification for which Popper (1935, Chap. 11) leans towards the concepts of “corroboration” and “confirmation” of a theory; –– Trial and error, therefore also randomly; –– Following the most improbable hypotheses (and not the most probable ones as Carnap argued). The scientist differs from the layman because of their r­ eluctance to follow the most commonly trodden path, the idea closest to hand, the most convenient solution.

Table 3.1  A syllogism A Major premise (or rule)

B Minor premise (or case)

All metals are conductors of electricity

Copper is a conductor of electricity

C Conclusion (or result) Copper is a metal

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Table 3.2  Other syllogism A Major premise (or rule) All metals are conductors of electricity Adults smoke The human being eats salad

B Minor premise (or case) Water is a conductor of electricity I smoke The goat eats salad

C Conclusion (or result) Water is a metal I am an adult The goat is a human being

3.2.5 The Demarcation Criterion The implications of the philosophy of Popper are therefore very productive and continue to evolve. Another of these involves the demarcation criterion. The author argues that falsifiability is not a criterion to establish meaning (or the truth of statements); in other words falsifiability does not replace verifiability and should not fulfil the same function. Popper considers that scientists should not worry whether the theories they are working with are true or false. This preoccupation that had kept logical empiricists awake for many a night is a useless concern because scientists will never be able to be assured of the certainty of their theory. As, at any time or in any part of the earth, a contrary case could bring it tumbling down; the scientist is never sure that their theory (which seems to work) is true. The fact of being right for much of the time in the face of critiques and with all the possible counterexperiments does not necessarily mean they will stand the test of time forever. Our theories, states Popper, are always temporary. They are not true, but simply those that are most appropriate for our purposes and that persisted up until then. Therefore, falsifiability is only a demarcation criterion, of separation between the statements of science and those of pseudo-sciences or of metaphysics, not a criterion to ascertain the truth of scientific statements. What then is the difference between science and pseudo-sciences? According to Popper, a statement is scientific when it is presented, from the point of its formal structure, in such a way that it can be falsified, that is disproved, criticised and debated. For this reason, again according to Popper, psychoanalysis, Marxism (historical materialism), astrology and palmistry, as well as sociology, psychology and history, are pseudo-sciences because they do not present their statements in a way that they can be refuted. How can the Oedipus complex be falsified? Did Freud express it in such a way that it could be disproved? This doesn’t mean that propositions (assertions and statements) of pseudo-sciences make no sense, that is without meaning, as the logical empiricists strenuously argued—simply that their statements are not scientific. They belong, let’s say, to the private realm of individual

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preference. From a psychological perspective, they can be an important source of inspiration but must not be confused with actual science.

3.2.6 Rationality as Critique and Discussion One of the last implications of Popper’s theory concerns the role of rationality. According to the author, presenting our ideas in such a way that they can be refuted means being receptive to critique and agreeing to follow a transparent and rational way of proceeding. He in fact affirms that “critique is the best synonym of rational” and rationality is the foundation of scientific activity. He apparently also appears to be open mind in terms of pseudo-sciences and does not put down non-scientific statements. Instead, Popper (1934) says that it is, at times, also possible to learn something very interesting from a pseudo-scientific or metaphysical theory. Only that science has a rational basis while the other stances do not. Exercises

Exercise 1 In  geometric optics rays of light propagate in a straight line. This is presented as a general law. Now, instead, discover which particular conditions are necessary for this to happen. Also describe (consulting a text on optics or physics) the situations in which this law is not applicable. Exercise 2 Consider the following syllogisms. All forks have four teeth All rivers have a bed Grass is mortal

My grandfather has four teeth I have a bed Men are mortal

My grandfather is a fork I am a river Men are grass

What’s the problem here? Where’s the error? What is a “grass syllogism” and who invented this expression? Why is it important to recognise the correct value of logical connectives and quantifiers? Exercise 3 According to Popper, applying the demarcation criterion, astrology and alchemy are not sciences. However, Keplero made astrological predictions and Galilei produced horoscopes on commission, convinced that the stars could determine the choices of individuals. Furthermore, Tycho Brahe, Boyle and Newton were also alche-

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mists. So much so that Newton’s interest in alchemy cannot be separated from his contributions to science: if he had not believed in the occult idea of action at a distance, through the void, he probably would not have developed his theory of gravity. Moreover, he spent September of each year immersed in alchemy-­ related experiments, whose preferred metal is mercury. His nervous exhaustions and eccentricity were then attributed to psychic and neurological symptoms of poisoning induced by mercury. In support of this, after his death, his body was exhumed and a high concentration of mercury was in fact found in his hair, probably because of the numerous alchemy experiments he had conducted. Can we now then say that these scholars were not scientists? What does this way of reasoning remind you of?

Further Reading • Musgarve (1993) • Nagel (1961) • Popper (1956–57) Check Your Preparation

1. What are “elementary statements”? 2. What are empirical generalisations and how do they differ from theories? 3. What legacy has neo-positivism left us with and why is it important to study it? 4. What is the difference between verifiability and falsifiability? 5. What is the purpose of the demarcation criterion?

References Bachelard, G. (1934). Le nouvel esprit scientifique. PUF (transl. The New Scientific Spirit. Beacon Press, 1985). Carnap, R. (1928). Der logische Aufbau der Welt. Weltkreis. (transl. The Logical Structure of the World. University of California Press, 1967). Carnap, R. (1932-33). Über Protokollsätze. Erkenntnis, 3, 215–228. (transl. On Protocol Sentences. Noûs 1987, 21(4), 457–470. https://doi.org/10.2307/2215667). Carnap, R. (1934). Logische Syntax der Sprache. Springer (transl. The Logical Syntax of Language. Routledge & Kegan Paul, 1967.) Duhem, P. M. M. (1906). La théorie physique: son objet et sa structure. Chevalier et Rivière. (transl. The Aim and Structure of Physical Theory. Princeton University Press. 2nd. ed., 1991).

References

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Enriques, F. (1906). Problemi della scienza. Zanichelli. (transl. Problems of Science. The Open Court Pub. Co. 1914). Fleck, L. (1935). Entstehung und Entwicklung einer wissenschaftlichen Tat- sache. Einführung in die Lehre vom Denkstil und Denkkollektiv. Benno Schwabe. (transl. Genesis and Development of a Scientific Fact. Chicago University Press,1979.) Hempel, C.  G. (1952). Fundamentals of Concepts Formation in Empirical Science. University of Chicago Press. Musgarve, A. (1993). Common Sense, Science and Scepticism: A Historical Introduction to the Theory of Knowledge. Cambridge University Press. Nagel, E. (1961). The Structure of Science: Problems in the Logic of Scientific Explanation. Harcourt, Brace & World. Popper, K. (1934). Logik der Forschung. Springer. (transl. The Logic of Scientific Discovery. Basic Books, 1959). Popper, K. (1956–57). Realismus und das Ziel der Wissenschaft. (transl. Realism and the Aim of Science. Hutchinson,1983.) Popper, K. (1963). Conjectures and Refutations. Routledge and Kegan Paul. Reichenbach, H. (1951). The Rise of Scientific Philosophy. University of California Press. Reiss, C. (2004). Science Based Toxicology: A New Strategy for Toxic Risk Assessment in the 21st Century. Animal Aid.

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Society in Science

Popper’s theorising has enjoyed much success and can still be considered the predominant version of the philosophy of science. However, its supremacy is not without its critics. Other perspectives vie to affirm an alternative epistemology of science. These perspectives, despite their diversity and, at times, even mutual indifference, share the same goal: to show the social dimension of science or, to use a happy expression of the philosopher of science Mary Hesse (1988), “socializing epistemology”. At least three generations of scholars belong, to varying degrees, to this wide and varied philosophical-cultural movement: –– The 1950s saw the contributions of the US  philosopher and logician  Willard Van Orman Quine (1908–2000), the latter Wittgenstein, the US philosopher Wilfrid Stalker Sellars (1912–1989), the British philosopher Stephen Edelston Toulmin (1922–2009) and the US philosopher of science Norwood Russell Hanson (1924–1967). –– In the 1960s it was the turn of the US physics historian Thomas Kuhn (1922– 1996) and the philosophers of science Paul K.  Feyerabend (1924–1994, Austrian) and Mary Hesse (1924–2016, British). –– The 1970s and 1980s were dominated by the British sociologists Barry Barnes, David Bloor and Harry M. Collins, the US  historian Steven Shapin and the French philosopher Bruno Latour. From a cultural perspective, one of the main innovations is represented by the type of preparation attributed to some of these: their eclectic group includes not only logicians or philosophers but also historians and social scientists who, reflecting on science, would introduce a historical

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and social dimension, hitherto unknown and even considered of no ­importance by the logical empiricists. The 1990s and following years saw the emergence of a number of authors (some also with a background of studies or doctorates in physics, chemistry, engineering, etc.) that gave a greater impetus to technology as an integral part of science. At one time, technology was considered a simple application aspect, an activity on the periphery of science, playing a merely supportive role. Authors such as MacKenzie and Wajcman (1985) and Pinch et al. (1987) instead demonstrated how technology has for some time now been the driving force of scientific knowledge and has therefore played a fundamental role in discoveries and in the construction of new visions.

4.1 The Critiques Levelled Against Popper If the theories of Popper eclipsed neo-positivism, he still had not elaborated on the reasons that produced it. Other authors, more numerous and better than him, contributed to his waning, which took place in the 1950s, spear-headed by Quine, the latter Wittgenstein, Sellars, Toulmin and Hanson. However, whilst defeated from a philosophical perspective, logical empiricisms continued to enjoy a strong influence in the natural sciences. Starting from the 1960s, various critiques were also levelled against the Popperian approach, by both his own pupils such as Feyerabend and Lakatos (defined as post-Popperians) and philosophers, historians and sociologists of subsequent generations, whose views were motivated by contemporary thinkers as Popper but who had remained marginal, such as Pierre Duhem (1906) and Ludwig Fleck (1935). Despite the theory of falsification and the principle of refutation being very clear and seemingly convincing, they are considered to be not particularly realistic (a hard pill to swallow for a critical realist such as Popper) for three reasons: 1. The role assigned by Popper to experience (see Sect. 3.2.1) is still excessive: for example, the axis of the Earth is not something that we can readily perceive unlike the actual Earth that we walk on. And yet it is an accepted fact. Furthermore, there are a number of scientific theories that have been modified or even discarded even though they continue to explain the phenomena for which they had originally been created and (more importantly) in relation to which the famous “countercase” had never appeared which would have put an

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end to it. The falsification of a theory appears, from a pragmatic perspective, as the result of competing theories in which one prevails, not so much on the basis of factual evidence but due to other reasons that Popper and the logical empiricists would have labelled with horror “non-scientific”. 2. For a theory to be falsified, scientists first need to introduce it into a falsification project and then receive it into the family of scientific theories. However, if some disciplines such as astrology, alchemy, psychoanalysis, Marxism and so on are downgraded to pseudo-sciences even before being introduced into a falsification project, consequently their statements will never be able to be put to the test. In other words, scientists often display a prejudicial, anti-falsification approach that really should have no place in science, at least in the idealised one of Popper and of the logical empiricists. 3. As a result, the falsification procedure is much less objective than first initially thought, as its application is dependent upon several decisions (subjective) made by scientists that are jealously gatekeepers of science. With the rising tide of such critiques, in the 1970s Popper turned his back on the dogmatic falsificationism he had advocated in the early 1930s, replacing it with a seemingly more receptive and tolerant attitude that he calls critical rationalism. In this, the refutation of theories is more akin to a process of theoretic discussion while moving away from an automatic and almost mechanical process, as defined by falsification in the strictest sense (see Box 4.1). Second, Popper’s critics also attach his demarcation concept (see Sect. 3.2.5). The apparently objective decision to draw a boundary line between science and pseudo-science in reality hides the identity of those who make this distinction, where they actually become a sort of authority, giving scores and deciding who is good and who he is bad, who does science and who does not. The danger that lies within this apparently objective activity is essentially the arbitrariness that this criterion seeks to oppose: it is no coincidence that Popper (as a youth with mild socialist tendencies, and then a staunch liberal) disqualifies Marxism, branding it adverse political thought, in the same way that official medicine has scorned homoeopathy. Even if in a subtler and more prudent form, and perhaps against the intention of the same Popper, the criterion of demarcation however has in its genes an authoritarian potential and ends up playing the same role performed by that of “meaning” of the neo-positivists (see Sect. 3.1.2) that ruled out, as it made no sense (and was therefore not true), a whole set of disciplines.

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Box 4.1 The Attitude of Scientists When Faced with a (Popperian) Counter­ example

When the detector Opera, located in the Gran Sasso laboratory near L’Aquila (Italy), recorded the transit of neutrinos fired by the CERN (Conseil Européen pour la Recherche Nucléaire) of Geneva (located approximately 730 km away) and discovered that they had arrived 60 nanoseconds earlier than expected, it was a huge surprise because this actually meant that they had travelled at a speed faster than light. However, the overwhelming majority of physicists were sure that it had been a blunder (as in fact it had been: a defective connection with a consequent measuring error). As Andrew Pontzen and Hiranya Peiris (2010) argue, Bayesian statistics show that (alone) the anomalies in the data are not such as to call for drastic revisions. What is required is a plausible theory. In other words, science does not work as Popper states: one isolated case is simply not enough if on the other hand there are hundreds or thousands of experiments that show the opposite. ◄ Third, The Logic of Scientific Discovery (title of the first book published in 1934) that Popper presents us is not a description about scientific evolution (as he argues) but a normative and prescriptive theory about science. Expressed otherwise, the logic of falsification, the critical rationality, the criterion of demarcation and the freedom of research are the characteristics that, according to Popper, should be rooted in a science. He therefore confuses reality with his own agenda, Is and Ought: a sort of scientific idealism. In fact Popper was never intent on describing the everyday scientific practice, but instead his focus was merely on “heroic” or ground-breaking science, that of Galilei, Keplero, Einsteinz and Bohr. Finally, the representation of science as a house on stilts appears barely credible. Even if Popper encourages scientists not to worry about the truth of their theories (see Sect. 3.2.5) because it is unfathomable, it is a far-fetched idea to think that such an approach is, from a psychological point of view, sustainable for the scientists, who instead need to rigorously believe in the truth of their theories and in the robustness of their methods. The absence of such a believe would otherwise lead to the risk of apathy and the loss of dedication, passion and tenacity.

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4.2 Science Revisited: Norwood R. Hanson Hanson was a very eclectic character, whose life was filled with many complex and stimulating activities: he played trumpet in an orchestra, was a marine and fighter pilot during the Second World War, an amateur boxer and illustrator of the comic version of Homer’s Iliad and often enjoyed bike rides out on his Harley-Davidson. He died young, aged only 42 years old, after crashing his single-engined monoplane and with ten books still to be completed. His most famous book, Patterns of Discovery, was published in 1958. The author argues that if logical empiricists and Popper have described the scientific process in that way, this depends on the fact that they concentrated on the “finished product” of science, that is, on the theories of physics that are now widely accepted and consolidated. Instead, to adequately understand scientific processes, it is necessary to study them in fieri, therefore turning our attention to blossoming areas of science, those that are developing. In fact, the classical disciplines are no longer recognised as fields of research but only places for the exchange of knowledge. Hanson revisits a number of basic concepts of logical empiricism such as those of “observation”, “fact” and “theory”. On the subject of observation, he emphasises that seeing is not a passive activity of contemplating the world, a simple retinal reaction, as the neo-positivists considered, but “an experience”. It is people that see, not their eyes. It is not possible to localise vision in the sight organ also because in the retina, images are upside down, and therefore, if we actually followed our eyes, we would see the world upside down (see Fig. 4.1). So what is involved then? The brain and prior knowledge. The former turns the images upside down, thus acting as a go-between for sight and perception. The lat-

Fig. 4.1  The reversal of images in the retina

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ter directs, focuses and orientates. Observation is not therefore a direct activity but is shaped by the brain and by prior knowledge. Hanson invites us to consider optical illusions. Based on the results of Gestalt psychological research,1 he argues that to see (and therefore to recognise) certain forms and objects in confused figures, it is first necessary to have experienced them, to be familiar with them, within a context of theoretical and practical knowledge. Hanson states (1958, p. 19): “seeing is a ‘ theory-laden’ undertaking. Observation of x is shaped by prior knowledge of x”. Physics is not a discipline based on elementary experiments and a repetitive sequence of perceptions. Physics is a way of thinking the world. If physics worked in the way described by the neo-­positivists, there would be no novelties, changes or innovations. Instead, it would be the case that a scientist would see in familiar objects that which no one had ever seen before. The novelty is introduced by the scientist, not by the object being observed. As the Brithish philosophers Toulmin and Goodfield (1965) documented, all the facts that the English naturalist Charles Darwin used as proof for his theory of evolution were already known before he began to use them. They were already out there. Other naturalists were interested in fossils, many years before Darwin, and most of the birds and animals had been discovered by other travellers. The way in which Darwin contributed was his radically new method of reordering (gestaltically) these data. Furthermore, Hanson points out that in order to be able to describe an event, scientists need a language. In other words, what they describe is not merely the product of what they see but also the terms that they have available to describe what they see. Hanson (1958, p. 35) wonders: “if my language is made up of only the following terms: one, two, three, few, many, then how can I possibly convey the concept that that St John’s Tower has four spires?” For which the formation of a concept x in a language that is not expansive enough to express x is always going to be difficult, if not even impossible.

 Gestalt psychology is a movement of thought that gained popularity between 1910 and 1920, led  by psychologists of perception, such as the Germans Wolfgang Köhler (1887– 1965) and Kurt Koffka (1886–1941), and by the Czech Max Wertheimer (1880–1943). Gestalt, in German, means organic or animate form: when we observe a referent, we don’t perceive the details but only the whole figure (form). Furthermore, the same details can be combined in such a way as to form different figures. The perception is therefore a global vision, total and entire, of a referent. The first person to use the term Gestalt was the Austrian philosopher Christian von Ehrenfels (1859–1932). In 1890 he wrote “the whole is more than the sum of its parts”. Therefore, the parts do not have intrinsic properties but can only be understood starting from the organisation of the whole, its Gestalt. 1

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An example comes from the French naturalised Russian science historian and philosopher Alexander Koyré (1939) who studied the Galilei error relating to the law of falling bodies. In 1604 Galilei suggested the notion that the speed of a body in free fall grows in proportion to the distance travelled from its starting point. When he takes the speed as a function (squared) of space (in this case height) rather than time, as physicists do nowadays when they say that speed is the space travelled by a body in the time of one second, of which the formula: v =

d Distance (or space travelled ) = , that is, speed t Time taken

Galilei (and before him Benedetti, Leonardo and many others, and after him Cartesio) adopts that position simply because it was cognitively, at the time, the most apparent for a variety of reasons. (a) It conformed to the “impetus theory”, generally accepted and based on the experience of engineers who used it when excavating wells. (b) We used the concept of geometric progression and more generally algebraic notation, which, although not preventing correct reasoning, in any case makes it difficult. (c) At distances of 20–30 metres, the differences with respect to times could not be seen and the precise mathematical calculations were far too complex. Prior knowledge therefore plays a fundamental role that obscures the conception (neo-positivist) of the ostensivity of facts. To show how this works, Hanson examines the concept of cause and the idea (already objected to by Hume and by the entire subsequent empiricist tradition) of the causal chain as a succession of simple events, one after another. For example, the death of a person involved in an accident (see ibid., p.  54) may be attributed to various causes depending on the perspective of the observer (see Table 4.1). Table 4.1  Types of causes

Causes Multiple haemorrhage Negligence on the part of the driver Defect in the brake block construction The presence of tall shrubbery at that turning

Explanations Physician Barrister Carriage-­builder Civic planner

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Only the prior knowledge of each social actor feeds into the scenario to attribute a cause that cannot be deduced from the event itself. In other words, we only have an explanation of the event x if we can insert it into a system of concepts that is also relative to other referents, because “a completely novel explanation is a logical impossibility. It would be incomprehensible” (ibid., p.  54) for our interlocutors. Hanson concludes that “what we refer to as ‘causes’ are theory-loaded from beginning to end. They are not simple, tangible links in the chain of sense experience, but rather details in an intricate pattern of concepts (p. 54) [...]Seeing what causes […] requires more than normal vision […]: we must learn what to look for” (p. 58) and where to look. Moreover the causes cannot be visual data because no sensorial piece of data can by itself be labelled as a cause or effect. The distinction between cause and effect depends uniquely on the theory. If to explain the origin of rain the meteorologist says: “the atmospheric disturbance originates near a stack of clouds; the cloud is an electrostatic generator and, as such, the ice crystals in it produce, by mutual friction, electric charges whose separation in turn produces a concentration of positive charges on the one side and negative on the other and the electric field grows between them”, what appears to be a causal chain is nothing more than a deductive chain. Each step follows on from the previous one not as a ring of a chain but as an implication. They are therefore details within a scheme (Gestalt), a system, a plot.

4.2.1 Abduction Similar to Popper, Hanson also criticises the inductive model as a realistic account of scientific practice while also contesting the hypothetical-deductive model as both models can be found in scientific reasoning; in fact, on the one hand, inductivism is correct when affirming that laws are obtained as inferences from data, but is incorrect in suggesting that scientific reasoning is only a summary of data; on the other, the hypothetical-deductive model is correct in stating that it is laws that explain the data and not the other way round, but conceals the initial connection, as if inference only went in the one direction, that is, from the laws to the data. Instead the starting point for a discovery is often a question of reasonableness or intuition or inspiration or some other aspect. According to Hanson (referring to the US mathematician, philosopher, semiologist and logician Charles Sanders Peirce, 1839– 1914), the discovery is the product of an abduction, in other words a blend of induction and deduction, a cognitive process of producing a hypothesis in order to explain a number of observations.

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Table 4.2  The syllogism of adduction A Major premise (or rule): certain Phenomenon to be explained, result of an observation The patient died in five days

B Minor premise (or case): doubtful Explanation hypothesis Anyone who has lupus dies in five days (even if no one has carried out a census on all the lupus deaths)

C Conclusion (or result): probable A probable conclusion (derived from the minor premise) The patient has lupus

The notion of abduction was first proposed by Aristotle who distinguished it from both induction and deduction. With respect to the other two, abduction is however of lesser demonstrative importance: it indicates a syllogism in which the major premise is certain, the minor one is doubtful and the conclusion is only probable; it is therefore characterised by probability. Peirce considered abduction (extending its Aristotelian meaning) the first step in scientific reasoning, in which a hypothesis is established to explain a number of empirical phenomena (see the example in Table 4.2). Peirce would say that this conclusion is a surprising fact; it is not tautological (as is the case with deduction) or simply empirical (as in induction). In this way, we have expanded our knowledge as we know something more about the patient: before, we only knew certain aspects of the illness, while now we can even assume something about the patient. According to Peirce, abduction is the only form of reasoning that could increase our knowledge; in other words, it allows the ­hypothesising of new ideas, of guessing, of predicting. It is the basis of creative and non-­linear thought. According to Hanson, the scientist proceeds from one or several specific observations until reaching a general hypothesis that should explain both these and numerous other previous observations. Abduction is a process of generalisation that, as such, does not result in demonstrable conclusions and for which no rules exist that could guarantee the correctness of the hypothesis. This is a fairly standard practice because in the construction of theories, scientists are not guided by clear and simple methodological rules. Furthermore, the metaphysical aspect persists in each science (which is part and parcel of the same): the scientists see the needle approach the magnet but do not see the attraction. They see a body fall but do not see the gravity.

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Not all of Hanson’s theses are original. However, his forte was reviving theses that had disappeared or that had been forgotten. In fact, a long time before him, William Whewell (1794–1866), the English philosopher, mineralogist and science historian, in 1840 had argued that thoughts and things are closely entwined that they cannot be considered as individual concepts; as such, a fact is the joined combination of an event with an interpretation. Furthermore, Popper himself had already argued with inductivism stating, among other aspects, that the precept “observed!” is not even grammatically correct as the observation is always selective and needs to focus on a specific object (Popper, 1934). Finally the same Alexandre Koyré (1939) had pointed out the role played by previous knowledge. However, Hanson’s book appeared at a particular time, when the ideas of logical empiricists were in sharp decline. Thus, it was accepted as an alternative to both them and Popper, therefore contributing to establish, together with Kuhn and Michael Polanyi, a new philosophy of science, one that was more historical and less prescriptive and rationalist.

4.3 The Social Dimension of Science: Thomas Kuhn Four years after Hanson’s book, The Structure of Scientific Revolutions (1962), by Thomas S. Kuhn, was brought out, a work that would radically change the philosophy of science. The author had previously dedicated The Copernican Revolution, a volume published in 1957, to the subject of change and in particular to the innovations introduced by Copernican thought. The fresh idea introduced by Kuhn consists of describing science as a socially determined activity. Its perspective ­represents an authentic epistemological revolution,2 with respect to both logical empiricism and its conceptual apparatus (reductionism, verificationism, realism, inductivism) and regarding the latter Popper, that of critical rationalism and of soft falsifiability (see Sect. 3.2). However, despite making its appearance at the beginning of the 1960s, it would be some time before his theses were recognised, being eclipsed by Popperian philosophy, the dominant thought during that period. Kuhn’s conceptual network consisted, as always, of a mix of new concepts, (paradigms, incommensurability, crises of science, normal science, scientific revo However, the true precursor of this approach was Ludwig Fleck (1896–1961), held captive for many years in the concentration camps of Auschwitz and Buchenwald. According to Collins (2012, p. 421), Kuhn’s success was mainly due to the fact that he wrote in English while Fleck expressed himself in German. Furthermore, Fleck’s book (1935) was only translated into English 40 years later, in 1979. 2

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1. Paradigm 2. Incommensurability 3. Cognition as Gestalt (total, overall vision) 4. Crisis 5. Normal science 6. Scientific revolution 7. Cyclicity of scientific revolutions 8. Science as puzzle-solving 9. Scientific anomalies

lution, cyclicality of scientific revolutions, science as puzzle-solving, scientific anomalies—see Table 4.3) and of old concepts, borrowed from historians, from the psychology of Gestalt (cognition as a total vision), from Whorf (the language shapes the vision of the world), from Quine (with his critique of neo-positivism), from the Polish microbiologist and epistemologist Fleck and from Wittgenstein (as the same Kuhn declares in his Preface)—probably also from Hanson, to whom, however, no intellectual credit is recognised. Unlike the logical empiricists and Popper, who founded their arguments on logic and philosophy, Kuhn uses a historical approach, which enables him to focus on aspects that the former had been unable to grasp. In fact, as Hanson stated, the image of science (and unfortunately our own!) mainly stems from the study of textbooks, texts and school books which, however, have two main defects: on the one hand they are a rational and ex post construction of a scientific fact; on the other they are popular texts with a persuasive, pedagogical and normative purpose. It is as if we had set out to create a national culture from a tourist brochure or a language text (1962, p. 1). According to Kuhn, “the early developmental stages of most sciences have been characterized by continual competition between a number of distinct views of nature, each partially derived from, and all roughly compatible with, the dictates of scientific observation and method. What differentiated these various schools was not one or another failure of method—they were all ‘scientific’—but what we shall come to call their incommensurable ways of seeing the world and of practising science in it” (ibid., p. 4). However, in this initial phase, none of the competing conceptions of nature is able to construct a corpus of knowledge that is defined and accepted by all scientists. Kuhn however is not a relativist (see Sect. 6.1.1). Instead he argues that observation and experience must strictly limit the boundaries of permissible scientific knowledge, otherwise there wouldn’t be a science. However, observation, experi-

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ence and method alone are not able to determine a particular system of beliefs and as such “an apparently arbitrary element, compounded of personal and historical accident, is always a formative ingredient” (ibid., p. 4) in a scientific discovery. This situation, of competing of the coexistence of a variety of theoretical perspectives, at a certain point evolves, precisely when one of these alternatives, even for social and economic reasons (and not only intellectually or scientifically motivated) achieves an exclusive dominant position in the scientific sector in question. At this point, all the scholars of this sector unanimously assume a certain mode of seeing, understanding and explaining the problems in which the disciplinary sector was struggling. As a result, what was initially only one alternative of the many under consideration became the perspective shared by all. Kuhn calls this perspective, more popular than the others, paradigm. The imposition of one perspective over others, and therefore the creation of a paradigm, characterises the second phase of a discipline, that of its full scientific maturity. According to Kuhn, with the exception of mathematics, astronomy and of a number of specialisations such as biochemistry (which come about by division or by the merging of other disciplines), this is the typical way that science makes progress. But what exactly is a paradigm? The matter is much more complex and controversial than it seems because Kuhn is fairly ambiguous. In fact, the British linguist and philosopher Margaret Masterman (1965) argues that the author has presented no less than 21 different meanings of the term “paradigm” that can be summarised in three different groups: meta-paradigms, sociological paradigms and paradigms of artefact or of construction. This critique is accepted by Kuhn who then replaced the term “paradigm” with the more defined ones of “incommensurability” and “disciplinary matrix”. Broadly speaking we can say that a paradigm is: (a) A cognitive model, therefore a way of looking, that includes theoretical, methodological and ontological statements (i.e. assumptions relative to the nature of the reality); (b) The basis of a social practice, in other words a mix of theory and practice distributed and applied by an entire community of scientists that develop a shared language and a way of doing; and (c) A set of scientific accomplishments that provides models to the community of scientists, for example, problems and relative solutions which are then reported in textbooks and presented in class.

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A paradigm therefore consists of: –– A theory and a number of exemplary applications; –– An availability or receptiveness to any kind of further research; –– The absence of cognitive rivalry in the sense that researchers work to explore and extend the paradigm, not to replace it. The schools of thought in fact disappear and philosophical discussions are reduced, which are replaced by communications in specialist journals (ibid., p. 89). However, paradigms resolve only some problems, those considered most urgent, that become specimens known throughout the community. And, often, they resolve them incompletely and with various imperfections (see Box 4.2). A significant task of cleaning, refinement, resolution of residual ambiguities, study and expansion by scientists is therefore needed. The paradigm only indicates the direction (a promise of success, of results, of new applications), but the road stretches ahead. Or, to use another analogy, the paradigm represents the foundation of a house awaiting construction. Box 4.2 The Case of Optics: Three Paradigms

Kuhn (1962, pp. 12–14) reconstructs the historic events of optics. From ancient times to 1600, there was not just the one paradigm but instead various schools and subschools (Epicureans, Aristotelians, Platonists, etc.) that competed with one other: for some, light was a set of particles emanating from material bodies; for others a modification of the medium (air? vacuum?) that intervened between the body and the eye; for others still, light was the result of an interaction of the medium with an emanation from the eye. Each notion drew its strength both from a particular metaphysics and from the highlighting of a particular group of optical phenomena for which the theory was best able to offer an explanation. The first paradigm was affirmed between 1600 and 1700, the corpuscular theory of Isaac Newton (1642–1726), for whom light was an emission of physical ­corpuscles by light sources. Between 1800 and 1900, the Newtonian paradigm was undermined by a new paradigm produced from the theories of the British scientist Thomas Young (1773–1829), of the French engineer and physicist Augustin-­Jean Fresnel (1788–1827) and, above all, of the Scottish physicist and mathematician James Clerk Maxwell (1831–1879). The latter considers light an electrical and magnetic wave phenomenon, in other words electrical-magnetic radiations (non-corpuscular) emitted by matter (understood both in the sense of sources and of bodies) that strike the retina of the eye. In this vision, dark would be an absence of radiations. Light is therefore a wave movement, a propagation through cross waves. However, to propagate, waves need a support that is essential air. But what happens in a vacuum? He argues (craftily, according to

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Kuhn) that the support is given by the cosmic ether, a perfectly elastic and at the same time rigid fluid. The third paradigm took hold at the start of the 1900s due to the theories of the German physicist and initiator of quantum physics Max Planck (1858–1947) and of the German naturalised Swiss and US physicist Albert Einstein (1879– 1955). Both were awarded, at different times, the Nobel prize. This paradigm continues to be the dominant one and features a return to Newton’s theory: according to Einstein, light is made up of “quanta” (indivisible, granular and discrete packets of energy), which in the 1920s would be called “photons” by the US chemist Gilbert N. Lewis. These are both waves and corpuscular particles. There is in fact currently a dualistic theory (wave-corpuscle dualism) of light, which would therefore have a dual nature, both corpuscular and wave. The quantum theory of Einstein clearly explains the phenomena attributable to the action of light on metals and on material (for which the latter emits electrons). Maxwell’s theory, according to which light is constituted by electromagnetic waves, instead explains propagation well. ◄ Who is commissioned with this task? Kuhn responds with another concept: normal science. With this term he identifies the everyday life of science. Normal science is the daily work, long and continuous, performed within a paradigm, intended to improve the agreement between paradigm and nature (whose relationship, as we have by now already seen, is never particularly rich in explicit points of contact) and above all to formulate quantitative laws. This daily work, often tedious and repetitive, making scientists look like white collars, is carried out by persons gathered in work groups, who form networks of relationships, who are constantly in contact, who speak the same language and, above all, with their drive for precision and refinement of the theory, end up narrowing down their field of investigation, making their research ever more specialistic: definitely a, let’s say, “dry” area, as proposed by Kuhn. In fact, the fame gained by most scientists is not down to the innovative nature of their discoveries (actually quite rare) but to the precision and scope of the methods that they have developed within a paradigm to redefine previously known facts. In other words, states the author, normal science is a chain of puzzle-solving events that have been successfully solved. Through the analogy of the puzzle, the author sets out to show how normal science is a task requiring great patience, is slow and routine, requiring the adaptation of numerous elements (just like the tiles of a mosaic) that scientists still haven’t worked out how to insert but in relation to which they are convinced they have a solution. This certainty gives them the paradigm, in which they have a fierce conviction.

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Finally, scientific revolutions (at times), while questioning the previous paradigm, do not completely eliminate it. At least from a practical point of view. The Newtonian mechanical view, for example, despite being superseded, is still the most appropriate method of resolving numerous scientific problems linked to medium-sized material bodies; quantum mechanics and the theory of relativity, the most adequate instruments to study, respectively, very small bodies (sub-atomic) and enormous bodies (e.g. the planets) are not particularly useful in the case of everyday life objects and the errors of Newtonian mechanics would in any case be imperceptible. The mathematical calculations on which lunar space missions were based still actually use Newtonian mechanics. Many philosophers of science of the time (also including Paul Feyerabend) consider Kuhn’s proposal a little too simplistic and deterministic. However, the author, as a good historian, was well documented and his theory was very refined. He in fact affirmed that not all scientific discoveries take place in the paradigm (and consequently within normal science, after solving the puzzle). If the discoveries of the neutrino, of radio waves, of the missing chemical elements in the periodic table and so on were in some way envisaged by the paradigm, the discoveries of oxygen, electricity, x-rays and the electron instead had a radically different nature, comparable to an actual scientific revolution: there was no way they could have been predicted by an accepted theory (paradigm) and were therefore true surprises. How do scientific revolutions come about? Kuhn argues that science evolves through surprises. Underlying a scientific change (as also takes place in a revolution) is the perception of an anomaly, in other words the recognition that nature has, in some way, breached the expectations generated by the paradigm. The anomaly is the fundamental requirement for any change in a commonly accepted scientific theory. If we revisit the constitutive features (referred to above) of a paradigm, it would seem that its affirmation would obstruct any possibility of innovation: in fact, the rival schools vanish, a single thought (mainstream ideological conformism) takes hold, all the scientists of that disciplinary sector share the same ­language. And so, metaphorically, we find ourselves facing a dictatorship. However, normal science, as all dictatorships, always contains the seeds of change. This agent of change is an automatic mechanism, given (so to speak) by the expansionist aims of the paradigm. In fact as the paradigm gradually becomes increasingly solid (through the long and meticulous daily work of normal science), it aims to expand its domain with the production of laws which, by doing so, intend to become universal. The warning flags however go up as an inverted relationship exists between universality and explanation: the more a theory tries to become universal, the greater the number of phenomena that it is unable to explain. In other words, the greater its reach, the higher the number of anomalies it risks encountering. The

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more anomalies it encounters, the more tweaks and readjustments it has to invent to maintain its primacy. Until one day the patches are no longer enough and it turns out cheaper its replacement, which is not based on a solely cost–benefit economic analysis but on a social need: unresolved anomalies lead to discontent and cognitive uncertainty, a sort of infesting woodworm that in the long term destroys the paradigm because it weakens the trust of its advocate. Box 4.3 What Is a Discovery? The Case of Oxygen

According to Kuhn (among others), facts and interpretations, observation and conceptualisation, are not separate but are rather inseparably  intertwined. He demonstrates this when he refers to the “discovery” of oxygen (1962, pp. 53– 56), asking himself: who discovered it? When was it discovered? If the discovery was that type of event that is traditionally expressed, it wouldn’t be difficult to answer these two “simple” questions. In fact, things are much more complicated. Around 1770, at least three scholars, and many other chemists, obtained in the laboratory enriched air in a container, without even realising it: –– The Swedish pharmacist C. W. Scheele, who however published his articles after the discovery of oxygen was already widespread. So, he may have been the discoverer, but we just don’t know. He certainly had an exchange of correspondence with Lavoisier and could have influenced the latter. –– The English scientist and theologian Joseph Priestley collected the gas released by heated red mercury oxide. But he presented it as one of the many types of air; then in 1774 he called it nitrogen oxide and in 1775 instead stated that it was, instead, common air with little phlogiston. –– The French chemist, biologist, philosopher and economist Antoine-Laurent de Lavoisier. Performed experiments on the suggestions of Scheele after Priestley; in 1777 he reached the conclusion that it was in fact a separate gas, one of the two main constituents of the atmosphere, a conclusion that Priestly refused to accept. So, wonders Kuhn, who discovered oxygen? Not Priestly, because his oxygen samples weren’t pure (otherwise anyone who placed air into a bottle could state that they’d introduced oxygen); instead, in 1774 he believed he had obtained nitric oxide, a gas that however had already been known for some time; finally in 1775 he considered the gas obtained (that was oxygen) as deflogised air.

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However, not even Lavoiser was the discoverer of oxygen (even if his claim was more than founded). In fact, initially, in 1775, he identified the gas (oxygen) as the “same air”. It was only in 1776 and 1777 that he understood that it was in fact oxygen. However, throughout his life, Lavoisier continued to argue that oxygen was a principle of atomic acidity and that it formed with heat. These principles were then repudiated in the nineteenth century when Lavoisier was already dead and oxygen was already known (recognised). If it is not clear who discovered oxygen, do we at least know when it was discovered? Between 1774 and 1777. But it’s not known precisely when. So as such, the phrase “oxygen was discovered” is somewhat misleading because it gives the impression that it was a singular, one-off event, similar to seeing or touching. “Discovering”, however, is a complex and collective act that requires the recognition that something new exists as well as an understanding of precisely what it is. A practice of reciprocal accommodation between observation and theory. ◄ Therefore, what at the beginning seemed to be a fairly unimportant anomaly, an exception, over time, after much resistance begins to be considered an increasingly awaited phenomenon that undermines the paradigm and creates a different atmosphere that Kuhn refers to as “extraordinary science”. The anomaly is not, however, comparable to the  (Popperian) single negative instance or counter-­example that falsified the theory (ibid., p.  147). While the latter represented an obstinate response of nature, instead, according to Kuhn, the whole issue is played out within the paradigm: the anomaly is a missing piece of the puzzle, not a case of invalidation through an (external) interface with nature, a methodological idea typical of neo-positivism. In describing scientific revolutions, Kuhn uses (as an analogy) theories relative to political, religious and social revolutions. The change of the paradigm is not immediate but incubates in a pre-revolutionary phase that can in fact be quite protracted. This phase is marked by a significant theoretical unease of scientists due to the continuous tweaks that need to be made to the paradigm, by a psychological crisis, by the re-emergence of conflict and by incomprehensions among scientists and by the revival of the schools of thought. This crisis, greatly disseminated, is resolved with the revolution. Unlike Popper and neo-positivism, the factors that lead to scientific revolutions, present in the pre-revolutionary phase, are minimalistically rational (costs-benefits analysis, refutation principle) because to be present, they would pre-suppose a constant dialogue between the proponents of the waning paradigm and the advocates of the emerging one. However, the phenome-

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Fig. 4.2  Gestalt psychological tests

non of incommensurability does not permit this dialogue. Incommensurable means that the two paradigms are not comparable from a cognitive and rational perspective because taking a stance in one means not being able to perceive (or recognise) the things that someone else standing in their paradigm sees and vice versa. Look at the two images (a) and (b) of Fig. 4.2 used by Gestalt-oriented psychologists. What do you see in image (a)? A young or an old woman? And in image (b)? A rabbit or a duck? It is almost impossible to see both the shapes simultaneously. This is a prime example of cognitive incommensurability. A similar phenomenon takes place in scientific revolutions where it is not possible to sit on both sides of the fence. In fact, the adhesion to one paradigm is, to use a religious analogy, similar to a conversion, an act of faith, in which previous knowledge is reviewed in light of the new belief. Consequently, in science, the processes of knowledge accumulation are fairly rare and, in principle, improbable because a new perspective (the ­paradigm) completely restructures the previous knowledge: we see everything in a new light. Only “normal research” is cumulative (ibid., p. 96). Therefore, according to Kuhn, other factors promote a scientific revolution including:

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–– Aesthetic, in the sense that an elegant, beautiful and economical theory is preferred (the famous principle called Occam’s razor,3 for which out of two theories that explain the same things, it is appropriate to choose the most economical one, that is the theory that encapsulates fewer concepts). –– Cognitive, because scientists (and also human beings) are mentally conservative and prefer simple theories to complex ones, clear ones to confusing ones, certain to uncertain ones. –– Sociological, as it is usually young scientists, those who in terms of age were on the fringes of the paradigm, who bring innovation. Older scientists are too anchored to the waning paradigm and too famous to be able to take on board the new paradigm; furthermore, as the adhesion to a paradigm is similar to a conversion, in life usually you only have the one (assuming any happens at all); as such it is unlikely that scientists would change paradigm several times in the course of their professional career and so generally this is a realm of only the relatively young ones. –– Political-economical, because, as Luther in his protestant reform was supported by the German princes who sought to be politically and economically autonomous from the Roman pope, similarly in the same period Copernicus, a rich bourgeois from Krakow (whose case Kuhn studied in great depth and from whom he took many examples for his theory) was supported by the bourgeoisie, the new emerging class, representative of the ideals of freedom and pluralism. Kuhn emphasised that a revolution not only changes the way of seeing nature but also the criteria with which we: (a) Judge certain subjects admissible or non-admissible (hence the always negotiated and renegotiated boundary between science and metaphysics); (b) Consider acceptable and legitimate the solutions proposed; (c) Admit the existence or not of the referents being discussed; (d) Assign validity or not to the experiments presented, or faith in certain techniques, procedures and methodological rules.

 William of Ockham (1288–1347), English theologian, philosopher and religious Franciscan. 3

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4.3.1 The Critiques of Kuhn and of His Legacy The debate that followed Kuhn’s book (1962 and the relative critiques) would lead the author to partially review his position that was expressed in the important Postscript, inserted in the second edition of the book (1970). In it, Kuhn tends to reduce the role of scientific revolutions, to circumscribe the presence of large discontinuities in the history of science and to limit the concept of paradigm. The latter, as we have seen, is reduced to a disciplinary matrix consisting of beliefs, symbolic generalisations, models and analogies, values, examples and so on that the members of a scientific community (of a scientific discipline) need to master to be accredited as members. A number of critics have pointed to the excessive emphasis directed towards the discontinuity that would exist between one paradigm and another through a revolution. In this regard, the US historian of physics (of German-Austrian origin) Gerald Holton (1978) pointed out that there is a set of knowledge (that he calls thèmata) that persists despite the changes of paradigm and the existence of apparently incommensurable competing theories. These are pre-comprehensions, main principles (such as the conservation law) and concepts (such as that of infinite space) that can appear, disappear and be revived according to the trends of the time. As such, the pivot of scientific change would not be revolutions but micro-variations, according to an evolutionist selection model (Toulmin, 1970). As Andrea Cerroni (2002, p. 99) argues, the fact that the concept of mass in Einsteinian mechanics not being generally translatable in terms of Newtonian theory is obvious. But it is necessary to consider that Einstein imposed on his own theory that it should reduce in the previous one in cases in which it was well corroborated (classical limit). In addition, he obtained the physical meanings of the mathematical entities that appear in the equations that he was developing from a purely theoretical perspective, thanks to the imposition that in this limit these equations were reduced to Newtonian equations and that, therefore, those new physical entities were consistent with the well-known Newtonian quantities. The translation is therefore not only possible but is actually necessary by the subsequent theory.

Philosopher of science and of mathematics, the Hungarian Imre Lakatos (1922– 1974) proposes to resolve the conflict between the normative model of Popper’s science (whose falsificationism he considers too abstract and often not practised) and the descriptive one of Kuhn (where the concept of normal science, which extinguishes the different perspectives, seems more monopolistic than real). Lakatos (1970), instead, considers that various networks of scientists exist and

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conduct ­basic research. These gravitate towards groups of theories (that he calls “research programmes”) that differ slightly from each other. These groups of theories are constructed like a fortified city: they contain a core of conventionally accepted principles and hypotheses, together with a wall of other hypotheses, considered more susceptible to change as the programme evolves. The scientists involved in the research programme defend the theoretical core from falsification attacks, protecting it with a series of “auxiliary hypotheses” (a sort of protective belt), of “methodological rules” intended on the one hand to protect the fundamental aspects (negative heuristics) and on the other to indicate the development lines to be followed (positive heuristics). Finally the research programmes are separated into “progressive” and “degenerative”: the former focuses on the discovery of new phenomena, also through the invention of new auxiliary hypotheses whose confirmation would increase the empirical content of the theory (progressive problem shift); the feature of the latter is, instead, the multiplication of protective hypotheses (ad hoc) to protect the core, without increasing either the empirical content of the theory or the knowledge (degenerative problem  shift). In Lakatos’ (slightly baroque) model, science is therefore like a highly dynamic activity where alternative research programmes on the one hand compete with each other but on the other hand are in a continuity (and not in discontinuity) with the previous theories. He is convinced that the task of history is to create rational constructions for which the step from one theory to another (revolution, in the sense of Kuhn) is a rational step (progressive research programme). The vision of science that comes to light from the reading of Kuhn is a far cry from the idealisations of neo-positivists and different (even if not completely incompatible) from that of Popper. Without having to refer to the distinction between the contexts of the discovery and that of justification (see Sect. 3.1.5), science is a set of actual practices, without a clear methodology. Science thus becomes a very material undertaking, child of its own time and anchored in the ideology of the era. Its criteria and internal logics interact constantly with society. It is not a stand-­ alone body, an island, one separated from the social world, but a deeply political and social institution despite its peculiarities (in fact it is only in science that we have such an effective normalisation). Rationalism and critical realism therefore seem to be swept away by Kuhn’s passage. Yet something still remains unscathed. Feyerabend would then see to completing the work.

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4.4 Freed Science: Paul K. Feyerabend Feyerabend was essentially a philosopher and mutated through various intellectual phases. In the initial period of his intellectual production (from the end of the 1950s to 1961), he remained fairly faithful to the Popperian methodology. Later, starting from Explanation, Reduction and Empiricism, an article from 1962, and How to Be a Good Empiricist, published in 1963, Feyerabend began to move away from the Popperian vision, through one of his critiques, also based on historical studies, in defence of an approach of epistemological tolerance, entirely absent in the realist vision. Of course, the synchronicity of this second phase of Feyerabend with the publishing of Kuhn’s most famous book is plainly obvious to see. Finally, the third period, essentially the provocative, libertarian and anarchic phase that brought him worldwide fame, began at the start of the 1970s and reached its pinnacle in 1975, the year in which Against Method was brought out, a genuine manifesto, as denoted by the subheading: Outline of an Anarchistic Theory of Knowledge. Feyerabend argued that the position of logical empiricism, which might seem justifiable from a pedagogical point of view, is in fact very dangerous because it leads to a sort of methodological dogmatism and threatens to suppress the creative potentialities of human activity. Also because the main methodological principles of logical empiricism have already been refuted by the history of science. However, he does not fully agree with Kuhn’s position that he considers, in some ways, tainted with excessive determinism, mechanicism and historicism, while recognising “normal science” as a realist description of scientific practice. Another scholar, the German naturalised US biologist, naturalist, geneticist and historian of science Ernst Mayr (1904–2005), affirmed that the Kuhnian idea of non-accumulation of knowledge is too extreme. Revisiting the history of biology (that he considers ontologically different from physics), Mayr considers that accumulation can only be recognised in the long term while focusing in the short term it is easier to make mistakes in seeing cognitive revolutions. Perhaps revolutions are actually impossible: anyone who has studied the French revolution, the Russian revolution or the great changes brought about by the World Wars will have noticed that in history there is no such thing as clear-cut events, removed from the surrounding context. Instead, all the pre- and post-event periods are connected to each other by thin ties and by numerous elements of continuity. So essentially Kuhn may have fallen into an optical illusion.4  However, Kuhn emphasises that revolutions are only perceived as such by those actually inside the paradigm. The external observer (as someone belonging to other disciplines) instead sees the entire process as an accumulation. 4

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But, where Feyerabend excels is in the critique of the neo-positivists and especially of Popper. Of the former, he denies that experience need not be the only criterion of validity and of the latter that the methodology should not be unyielding. In other words, it is necessary to reject any general rule. Sometimes, for the purposes of science, it is healthy to ignore the protocols because it is only by doing so that a new theory can evolve. Therefore, even the (judged) metaphysical proposals have a right to citizenship: they are important because they contain a critical potential that is beneficial for science. As such, everything (myths, fairy tales, theories, etc.) is useful for the progression of science. So why do limits need to be set? Hence, says Feyerabend, a good empiricist will be a critical metaphysician, without dogmatic limitations, with a tendency towards theoretical pluralism: the more alternative theories are in circulation, the more chance there is that the one that prevails will be a well-grounded theory because it will have won the race against many competitors, rather than having played a match (rigged) with only a few select opponents. The abundance, even excessive, of theories helps paradigms to improve. In fact, the history of science shows us that the latter proceeds not so much through experience, but by means of the comparison between theories. And the more theories there are, the more beneficial the comparison is; because the most important properties of a theory (and also the prejudices related to it) are found by comparing and contrasting and not by analysis. Feyerabend urges the keeping of all theories, even those that are no longer compared, because no idea is ever examined in all its ramifications and therefore it is always possible that it may one day be useful again (see Box 4.4). Box 4.4 Scientific Theories Once More Become Contemporary: Life on Mars

If we could travel back in time and ask the question “does life exist on Mars?” scientists would have given us very different answers depending on when exactly during the last century the question was posed. For example, at the end of the nineteenth century, the Italian astronomer Giovanni Schiaparelli (1835–1910) had observed long straight tracks on the surface of Mars, which he interpreted as channels; he, and even more so his US colleague Percival Lowell (1855–1916), had believed that the channels were artificial and therefore proved the existence of a technologically highly a­ dvanced Martian civilisation (Lane, 2005). It was only a few decades later that the channels were shown to be optical illusions. In the mid-1960s the Martian skies were first visited by the US spatial probe Mariner 4 whose mission it was to photograph the surface of Mars and transmit images of a vast desert without water or vegetation. Even if the idea of the existence of a Martian civilisation had long since been dismissed, the hope of find-

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ing microbial life forms was still a fervent wish. Finding ourselves in the middle of the space race, this question seemed not only worthy of being explored, but in fact of fundamental importance for the future of humanity as a whole. For this purpose, in the 1970s, the Viking mission performed a number of experiments on Mars. One such experiment appeared to have detected the presence of metabolic activity in the soil. After many years of debate, this experiment was declared flawed (as at the time, not enough was known about the composition of the soil on which the experiment had been performed) and for many decades the question of life on other planets was relegated to the side lines (if not altogether entirely excluded from the scientific debate—see Dick, 1996). The notion of life on Mars seemed only a fantasy. Thirty years later, between the end of the 1990s and early 2000s, a series of discoveries apparently from markedly different fields of interest, such as the presence of microorganisms that live in extreme terrestrial  environments and the discovery of planets beyond our solar system (see Impey, 2010), then brought this subject back into the limelight. Today, the search for life elsewhere in the universe has become a priority for all space agencies and many experiments are underway or are at the preparatory stages to find an answer to this question. The red planet is no longer simply considered an arid and barren desert, but rather its description conjures up a lost paradise, a once fertile planet that has gradually become parched, transforming into the planet that we are now familiar with today. ◄ Furthermore, no theory is in agreement with all the facts; that’s normal and is in no way objectionable, because it is only if we are truly rigorous and precise that we can discover exceptions, or anomalies (as Kuhn would have put it). Theories that seem to be completely in agreement with all the facts only achieve this status because the procedures have been performed without due rigour. Moreover, if only perfect theories are admitted (as the logical empiricists would insist), then we would not actually have any theories at all! Much of the technical progress of the nineteenth century came about as a result of knowledge that was at best inadequate, and at worst, flawed. As such, referring to the English philosopher and economist John Stuart Mill and his essay On liberty (1859), it is only fair to hear everyone out, even those (considered) to be holding erroneous points of view. For this purpose Feyerabend (1975, p.  86ff) argues that if experience (as the logical empiricists state) or reason (Popper’s stance) were (and had been) the dominant criteria in the acceptance of theories, even Galilei would have been forgotten or remembered as a failure. In fact, the Italian astronomer built himself (by copying) a telescope which, however, he had not mastered the art of using correctly; he

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was not particularly familiar with the science of refractions or the areas of physical optics needed to understand telescopic phenomena; he was not even sure how to focus the instrument well, how to point it upwards towards the sky; in fact the public performances were not particularly successful because the people looked but didn’t see. Have you ever tried looking at a radiograph? The specialist sees lots of things, but laymen see only blurry images, confused figures and shapeless objects. In addition, the telescope did quite a good job of picking out objects on the earth (trees, mountains, etc.) but directed upwards towards the sky, the result was less than satisfactory because the senses of the onlookers were not trained for that type of perception. Finally, Galilei’s representation of the moon was completely incorrect also because his telescope conveyed images (considered) confusing and conflicting. The lesson that Feyerabend learnt from all this is woefully anti-methodological: experimental data are constantly contaminated by the prejudices of the scientist, by the techniques and technologies that they use, by the historical period they live in and by the beliefs of the time. As such, it would be senseless and somewhat irresponsible to assign solely to experimental data the task of evaluating the soundness of the theory. Science evolves through proselytism (Kuhn), ad hoc hypotheses carried along on the wave of emotions and also by means of a good pinch of irrationality. Essentially, there is no need to give too much credit to reason. If we have made such great strides in terms of scientific development, we can actually attribute this to the fact that the criteria of reason and of the methodological rules, as unique criteria, are defeated results. Also, because theories appear rational or irrational only after a number of years, when they are refined, smoothed out, adapted and shaped into rationality. If, at the time when they first emerged, we had evaluated them based solely on rational criteria, we would undoubtedly have discounted them. So, concludes Feyerabend, attacking reason is one of the inevitable presuppositions of empirical success. And Farewell to Reason (1987) is the meaningful title of one of his last books. Feyerabend in some ways slightly resembles Popper, whom he also hated, so much so that he called him “Al Papuni” (a name that recalls Al Capone) in epistolary exchanges with his colleague and friend Lakatos: like Popper, he was a liberal and was convinced that his theory had strong prescriptive, normative features instead of just being historical-descriptive, Kuhn-style. However, Feyerabend is the proponent of a radical, libertarian liberalism taken to its extreme consequences (anarchy and Dadaism). He went from embracing a moderate liberalism and from a permissive tolerance (“at times it is healthy to depart from the rules), precisely in his movement from the second to third phase of his thought, to the passionate persuasion to apply the counter-rules, to free ourselves from the monolithic rules

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invented and imposed by methodologists, to the idea that science can only be successful if anarchist progress is continuously applied. In other words, anarchism as a medicine for epistemology and for the philosophy of science. Box 4.5 Correct Discovery, Incorrect Explanations: The Wireless Telegraph System

In 1894 Guglielmo Marconi, physics student in Bologna, went to see his lecturer Augusto Righi, famous for his studies on electromagnetic radiations. Marconi announced: “Professor, with the electromagnetic waves that you discovered, I’ll create wireless telegraph from here to America”. Righi replied: “Don’t talk rubbish. Get out of here before I kick you out!” A short while after, a Paris newspaper interviewed, on the same subject, Henri Poincarè, the renowned theoretic physicist of the time. He replied ironically: “Does Marconi know that the earth is round or does he still think it’s flat?” In fact, electromagnetic waves propagate in a straight line. So, if perhaps they might be able to travel over a hill, there was no way they could manage the curvature of the earth. Intrigued by this theoretical impossibility, Marconi installed one antenna in Cornwall (UK) and one in Newfoundland (Canada). On 12 December 1901, he carried out an experiment and the signal reached Newfoundland. But, how was that possible? Due to the ionosphere (a band of the terrestrial atmosphere, consisting of gas) that acts like a mirror. As such, the wave emitted from Cornwall essentially moved in a straight line (consistent with Righi’s theory) but then reached the ionosphere where it bounced back towards the earth. But neither Righi nor Marconi was aware of the existence of the ionosphere, which was only confirmed in 1924. But then how did Marconi predict the phenomenon of electromagnetic wave defraction? Because he was...ignorant, in the sense that he believed (erroneously) that electromagnetic waves propagated in parallel to the earth’s surface. In fact Marconi had never taken a physics degree. But what he did achieve was the Nobel Prize for physics (in 1909). So it’s not always the case that those who know things get it right and those who don’t know them get it wrong. ◄

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4.5 Common Sense in Science Hanson, and above all Kuhn, widely demonstrated, with a number of historic examples, the social dimension of science. However, even the most receptive of scholars struggle to accept that science uses common sense; in fact it would be impossible without it. The same Feyerabend provides a historic example relating to the argumentations of Galilei that would be used to persuade his students, colleagues, friends and enemies (including the Danish astronomer Tycho Brahe) of the solidity of his theory on the motion of the earth. The opposite argument was based on experience and common sense. In fact, his opponents argued that if it were true that the earth moved, when we drop a stone from a tower, it should end its journey not at the foot of the tower (Fig. 4.3) perpendicular (trajectory A), but at a distance from the base of the tower (trajectory B). Galilei does not argue the sensitive content of experience (observation) but instead suggests that what is involved is in fact an optical illusion: the problem stems from the notion that human beings cannot distinguish relative motion (what they perceive) from absolute motion5 (what the Earth does). Therefore Galilei, according to Feyerabend, introduces a new language of observation and responds to the former optical illusion using other illusions, which however are already considered Fig. 4.3  The tower experiment

A

B

 The adjective “‘absolute”’ is quite misleading. We now know (from Einstein) that motion is always relative because it can only be studied with respect to a particular frame of reference, which in turn can be in motion with respect to another frame of reference. Absolute motion would only exist if there was an absolutely stationary frame of reference, but this sort of system does not exist. Even the so-called fixed stars are not actually fixed even if they appear to us to be stationary because of their vast distance from the earth (the closest is approximately 4.5 light-years away). 5

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such (by the common sense beliefs of the time) such as movement on a ship as it travels or inside a moving carriage. Galilei asks his opponents: how is it that the captain of the ship, despite being in motion, is able to draw a straight line on a sheet of paper? If things really worked as they (illusory) appear to us in the case of the tower, the captain would not be able to draw a perpendicular line but only an oblique one like the trajectory B. The same is valid if we draw when we are in a moving carriage. If a falling object could draw in the air the trajectory they are following, we would see that it is undoubtedly transversal. Unfortunately, this is not the case and so we cannot see it. However, it is also true that on the captain’s sheet of paper we should see a transversal line; again, this is not the case. From a practical perspective, Galilei converts an experience that, in part, opposes the idea of the motion of the Earth into an experience that, conversely, confirms it. All this is achieved by playing with common sense knowledge. For this reason Feyerabend states, exaggeratingly, that Galilei is a forger, someone who cheats using the “psychological tricks” (p. 65) of an illusionist: from the Gestalt perspective we can see that with a conceptual system (created around the idea of motion of the Earth) we see a certain thing while with another conceptual system (based on the idea of​motion) we see an alternative, even opposite, perspective. Even the observed phenomenon that is perceived by experience is the same. But that is not all. “Galileo’s trickery” (p. 68) is what emphasises the continuity between two perceptions, to give the impression that the second is only a continuation, an extension of the first. It is not necessary to change a way of thinking (Galilei wisely seems to be saying), something that many would have objected to, but merely to take a step forward into the same paradigm. Something that is a little easier to digest. Instead, what is involved is actually a deep-rooted change, the altering of an entire conceptual perspective: that of the fixity of the Earth. Galilei, concludes Feyerabend, “invents an experience that has metaphysical ingredients” (p.  76). Our experience is ultimately much more speculative than we are led to believe.6 Some might object that Galilei only used common sense beliefs to persuade his peers. However, his peers were scientists and what we have witnessed is a scientific discussion, not a bit of small talk at the pub. Even if science began as a liberation movement, it has become (argues Feyerabend) a tyrannical ideology. As

 Some historians and philosophers of science have criticised the reconstruction of Galilei made by Feyerabend. In their opinion, Galilei did not use these reasonings positively to construct his theory (the motion of the Earth, as Feyerabend argues), but negatively, to bring down the theory of the fixity of the Earth. In fact, he was also condemned for the latter notion. In other words, Galilei does not have a pluralist or possibilistic approach (both theories are plausible) but of open hostility towards the theory of adversaries. 6

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such, society must protect itself from an excessive influence of science and similarly from other ideologies. Furthermore, science does not deserve the privileged role in Western society it enjoys because there is no justification to assess scientific claims as being superior to those of other ideologies such as religions. Feyerabend imagines a “liberal society”, one in which all the traditions have equal rights with equal power-sharing. That is why science should be completely accountable to a democratic control: it is not only areas of scientific research that should be ­determined by popular elections but the assumptions and conclusions should also be overseen by a committee of laymen.

4.6 Scientific Knowledge and Common Sense Knowledge: A Circular Relationship The history of science is full of mutualistic influences between scientific and common sense knowledge. Have you ever wondered why the Swedish naturalist Carl Linnaeus defined nature as being divided into three kingdoms (animal, vegetable and mineral)? Probably because in Europe in the first half of the eighteenth century the monarchy was the dominant political power (moreover, in Sweden, as in a dozen European countries, it is still present) and the republic was a less frequent occurrence. Linnaeus and the first naturalists, basing their beliefs on an ancient anthropocentric image of the world, restored the natural sciences following on from Aristotle, proposing nature as an ordered “kingdom”, with its “generates”, its “species” and its “families”. A conception of reality that was politically, conservatively and cognitively static. Even the term “mammal”, which Linnaeus chooses to describe our species, is profoundly linked to common sense thinking (see Sect. 10.2). More than a century earlier, precisely in 1628, the English physician William Harvey published the book Exercitatio anatomica de motu cordis et sanguinis in animalibus in which he described blood circulation. The idea itself was not original; in fact it was fairly conventional; the Chinese in the third millennium BC, then the ancient Egyptians and subsequently Leonardo da Vinci, Miguel Serveto, Juan Valverde de Amusco, Andrea Cisalpino, Giordano Bruno and Robert Fludd in the sixteenth century had already made reference to the circular motion of blood within the body. In addition, in his book Harley Harvey compares the heart to the sovereign: the king (Charles I) is at the centre of the kingdom as the heart is at the centre of the organism. However, Harley Harvey takes it a step further and describes how the heart works similar to hydraulic bellows, with our wrist performing the function of a pump. The throbbing we perceive in our ears or in the groin is the rhythm

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of a machine. The heart is a pumping machine, a mechanical organ with its valves and spare parts. Is this a conclusion that could have been arrived at a century earlier? Probably not (even if the first description of a pump can be traced back to Archimedes in the third century BC) because pumps became popular in the seventeenth century and Harvey must surely have been aware of this tool as he wandered around the artisan workshops of the time.

4.7 Deconstructed Science: Metaphors, Metonymies and Analogies George Lakoff, a US linguist, considered the evolution of thought as a way of developing improved metaphors, the application of one area of knowledge to another, resulting in new perceptions and knowledge. The notions of the heart as a pump or of nature as a federation of distinct realms are quite simply metaphors. This may not denote implications, because we are under the impression that the metaphor is a simple way of stating, of representing or expressing a concept that would otherwise be difficult to communicate. However, metaphors, like metonymies and analogies, take on a much more serious stance. So serious in fact that many scientific concepts are considered nothing more than a reflection of them. A metaphor (from the Greek μεταφορά, “I transport”) is where a proper term is replaced with a figurative one, following a logical transposition of images. Every day we use expressions such as “the phone’s gone mad” (as if it were suffering from a serious mental problem), “summer’s gone” (as if it had departed), “a full moon” (as if it had filled up with something) and “I devoured that book” (as though I had eaten it). It is not that you cannot say about the book “I read it quickly, incessantly and compulsively”; it’s just that the metaphor using “devoured” is preferable, making it a more comfortable, vivid and expressive description: essentially metaphors communicate our thoughts more instantly and readily. Analogies (from the Greek ἀναλογία, “proportion”) are also rhetorical figures, but take another form. They describe a relationship of similarity between two objects or facts, which, however, in reality are different. This cognitive process essentially replaces the traditional relationship of comparing (using the word “like”) with that of identity, thus removing the “like”. For example, instead of saying “AIDS is like a plague”, it becomes “AIDS is a plague”. Note how these two apparently similar expressions have a different effect on us. In the former we are still aware of the two separate objects (AIDS and the plague); in the latter, however, it becomes one object (Marcheselli 2022). Analogies are used, by both layman and scientists, especially in the processes of discovery (Sect. 5.5), precisely when we

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have an idea (a concept) but not yet the proper term (see Sect. 2.2) or a satisfactory sentence, or when we have a term that is somehow lacking, because it is not specific to or is less appropriate than the concept we are seeking to express. Finally, metonymies (from the Greek μετωνυμία, “exchange of name”) are rhetorical figures that consist of reversing the roles of the referents, for example, using the name of the container for the content (“drink a bottle”), of the material for the object (“unsheath the iron”), of the symbol for the designated thing (“do not betray the flag”), of the place of production or origin for the thing produced (“a bottle of Chianti”), of the abstract for the concrete (“evade surveillance”), of the brand for the contents (“drink a Guinness”) and of the author for their product (“read Kant”).

4.7.1 Each Name (Common or Scientific) has a Metaphorical or Analogical Origin Not only are metaphors and analogies present in verbal expressions, but they also compose the essence of names. In other words, every name we use has metaphorical or analogical roots. In fact, given the fact that there is no direct link between language and reality (see Sect. 2.1), numerous cultures have sought to name phenomena and concepts that were still nameless in their own language. One straight-­ forward way to find out the metaphorical or analogical origin of names is to resort to etymology, essentially the study of the origin and history of words in a particular language, studying their phonetic, morphological and semantic evolution. In common language, for example, the name “two” (the number) has its roots in the idea of cutting or separating. The word “horizon” would mean “extreme circle”, referring to the line in the shape of an arc of a circle in which the sky and earth or sky and sea appear to touch each other. Sometimes the actual metaphorical origin (dating back thousands of years) is now lost to us or it is dubious or debatable, with various less probable hypotheses. The etymology of scientific names is easier to reconstruct because they are more recent. For example, in botany, aerides (a genus of orchid) takes its name from “air”, because these orchids draw nourishment from the air. The term “cell” is associated with the analogy that the English physicist, biologist, geologist and architect Robert Hooke (1635–1703) imagined between the microstructures he observed in cork, using a microscope that he himself had invented, and the small chambers (cells) that are common features of many monasteries. In physics, the “gluon”, an elementary particle that acts in the marked interaction between quarks, takes its name from glue, because it “glues” the quarks together, forming hadrons, such as protons and neutrons.

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Fig. 4.4  Bacteria under the microscope

In medicine, the Berlin anatomist W. Waldeyer coined the term “chromosome” in 1888 by combining two words of Greek origin: cromo (colour) and soma (body). He had noticed intensely colourable small bodies, which become evident in the cell nucleus during karyokinesis or mitosis. Then there is the term “bacterium” (from the Greek baktē´rion, “stick”)? Look at Fig. 4.4 and you’ll see why. And we could continue with “seismic swarm” in geology, DNA “editing” and “genome transcription” in genetics and so on. Sometimes, however, it is the name of the discoverer that is the basis for a scientific term (e.g. the Broca area) or a name is created in honour of someone [such as the mineral bridgmanite in honour of Percy Williams Bridgman, who was awarded the Nobel Prize in physics 1946 following his research on high pressures, or polonium, named in honour of Marie Curie’s country of origin (Poland)], again, of the place of discovery (such as the Fassaite and Fiemmeite minerals, discovered respectively in Val di Fassa and Val di Fiemme, both valleys in the Dolomites in Italy). Underlying all scientific terms there is therefore always a mixture of common sense knowledge and the relative ordinary language (see Gobo 1993).

4.7.2 The Initial Baptism It is also the case that the chosen name, again on a metaphorical or analogical basis, is subsequently found to be incorrect; yet it is not corrected despite the subsequent discovery of the error. This is the case of the word “Indians”, a name used by Christopher Columbus to describe the Amerindians, convinced that he had landed in the Indies (as the Far East was referred to at the time). Saul Aaron Kripke, US

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philosopher and logician, in his causal theory of reference, call this phenomenon “initial baptism”: a referent receives a name and it sticks forever more, even if it is later discovered that it was incorrect (Kripke, 1972). Again, this is also the case for scientific terms. For example, in botany, there is the “ginkgo biloba” (a very ancient tree from China, whose origins reach back 250 million years). It was probably called ginkgo due to an erroneous transcription of the Japanese name ginkyō by the German botanist Engelbert Kaempfer. This name was given to the species by Linnaeus in 1771, where he kept that erroneous transcription of the original name. The name of the species (biloba) instead stems from the Latin bis and lobus referring to the splitting into two lobes of leaves, assuming the shape of a fan. You cannot get more metaphorical than that! In chemistry the word “enzyme” was first used in 1878 by the German physiologist Wilhelm Kühne. He happened upon this word (in Greek ἐν ζύμῳenzýmō meaning “inside the yeast”) precisely because the belief was that such entities could only be found inside yeast cells. However, it was in 1897 that the German Eduard Buchner (Nobel Prize for Chemistry in 1907) discovered that fermentations also take place in the absence of live yeast cells. In physics, “atom” is a commonly used term and comes from the Greek ἄτομος (which, by means of the privative alpha, means “that it cannot be cut”). The term was coined by the Greek philosophers Leucippus, Democritus, Epicurus and so on, who suggested that matter was not continuous but instead consisted of minute particles which were the smallest existing entity that could not be further divided. Aristotle (fourth century BC), instead, objected to this theory, believing that instead matter was continuous and could in fact be infinitely divided into increasingly smaller particles equal to each other. This hypothesis persisted, as for many centuries the technology that would have been needed to validate it was not yet available. Well now it is known that the atom is not a-tom (inseparable), but is in turn composed of protons, neutrons, electrons, androns, six types of quarks, gluons and so on. Yet despite this revised knowledge, the (incorrect) name “atom” has persisted. In medicine, the words “vaccine” and “vaccination” have their origins in the Latin “vacca” (cow). In 1796, the British physician Edward Jenner named the procedure whereby material from bovine pox lesions was injected into patients. However, the preparation used to safeguard against human smallpox perhaps originated not from bovine but instead from equine smallpox (Schrick et al., 2017). This is proven following analysis in 1902 of the residues contained in the two smallpox vaccine vials produced by the pharmaceutical company H. K. Mulford of Philadelphia, Pennsylvania. They date back to a century after Jenner’s discovery but are still the oldest ever to be examined and contain DNA that is much more

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similar to that of equine  smallpox (although this does not exclude the fact that Jenner actually used cowpox).

4.7.3 The Influence of Metaphors Metaphors, metonymies and analogies are therefore not simple tools to produce scientific concepts but, in many cases, represent the core of the concepts themselves. US writer, philosopher and historian Susan Sontag (1933–2004) has demonstrated how medicine uses certain metaphors (1988, p. 9). It can be stated that: Modern medical thinking could be said to begin when the gross military metaphor becomes specific [and the conclusion is reached] that illnesses were caused by specific, identifiable, visible (with the aid of a microscope) organisms [...] Since then, military metaphors have more and more come to infuse all aspects of the description of the medical situation. Disease is seen as an invasion of alien organisms, to which the body responds by its own military operations, such as the mobilizing of immunological “defences”, and medicine is “aggressive”, as in the language of most chemotherapies.

In medicine, terms such as “fight” and “struggle” between globules, “war” on bacteria and viruses, “weapons” to “conquer” illnesses, microbes that “attack” (and are considered “enemies”, “invaders”, “threats”), “array of cells”, “antibodies”, “center of command of the immune system” and so on are used. Metaphors are therefore not neutral but reflect a particular view of the world, an ideology, shared by the scientists who use them. But that’s not all. Metaphors are not only passive tools, but instead reflect a way of thinking, becoming active tools, in the sense that they are the cornerstones (here’s another analogy!), continually producing and reproducing that way of thinking (see Gobo 1995). The Welsh scholar of organisations Gareth Morgan (1986) has shown how tacit and common sense metaphors found in the thinking of social scientists have influenced their subject matter. The organisation (a factory, an administration, a company) has been represented at various times over the centuries as a “machine”, an “organism”, a “brain”, a “system”, a “culture”, a “network”, a “political system”, an “asylum” and a “prison”, to name but a few. These metaphors have shaped the way of perceiving, considering and managing both phenomena and organisational problems, as well as the related solutions. It therefore appears clear how language has its own internal force, intrinsic (like matter), as names and speeches are activities, and additional constitutive of objects; that is, they play a performative role,

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already highlighted by the English analytical philosopher and linguist John Langshaw Austin with his theory of linguistic acts, expressively evoked by the title of his posthumous book How to Do Things with Words (1962). And so it seems reasonable to state that any type of knowledge (and that includes scientific knowledge) is not initially based on extra-linguistic elements but only on linguistic ones (see Sect. 2.1). The building blocks of the sciences would therefore not primarily be cemented in reality but rather in concepts and therefore in discourses. Theories are in fact discourses.7 As a result, “the notion of a general and unsurpassable situation of circularity that hinders any attempt at justification and self-foundation of scientific knowledge [...]. The only possible response to this condition of circularity is the reflective awareness of the circularity and the absence of foundations of scientific knowledge” (Zolo, 1988, p. 133).

4.7.4 Metaphors and Ideologies The English sociologist of science Bloor (1976, pp. 62–65), believing that theories of knowledge are a reflection of social ideologies, has shown the social images and metaphors that overarch the opposing theories of Popper and Kuhn. Popper’s vision of science dates back to the eighteenth-century Enlightenment, to the Anglo-­ Saxon and Darwinian theory of law. Focusing on the latter, science is involved in a struggle for survival, in which weak theories make way for strong ones. From the Enlightenment Popper makes use of an anti-authoritarian, egalitarian and universalist approach: science does not give in to any authority, of either reason or experience (both are untrustworthy in uncovering the truth). Furthermore, all men are equal; no individual speaks with greater authority than another; no one represents a privileged source of truth, and all claims must be subjected, none excluded, to critique and scrutiny following a procedure, one which Popper himself (1934, pp.  92–93) compares to that by which a jury reaches a verdict. Finally, all men belong to a single rational human race whose barriers and boundaries (such as those created by specialisations, languages and idioms) must be broken down to allow the free circulation of ideas. The protagonist, the discoverer of knowledge is the individual; the community (society) is nothing more than a set, a collection of individuals. Rationality and morality are ahistorical; they withstand the passing of  These considerations also receive the self-critique of logical positivism, initiated during the 1960s by Quine, also inspired by the nautical metaphor (which embodies an anti-foundation concept of knowledge) of Neurath (1921, p. 199): “we are like sailors who on the open sea must reconstruct their ship but are never able to start afresh from the bottom”. 7

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time. Finally, since the Enlightenment, thought has often been associated with change, reform and pedagogy with the aim of accommodating these ideas, Popper’s philosophy takes a highly prescriptive and moralistic stance. Kuhn objects (unconsciously) to the Enlightenment ideology with a romantic ideology, in which the human race is not minutely shattered into individuals but rather grouped into communities. Individuals, with their outlook and intellect, are not the rulers of the world but are instead dominated by the community of which they are part. The latter is in fact the bed of knowledge and significant experience. Moreover, not all scientists are equal and there are some (in terms of age, fame and resources) who garner more authority than others. Finally, perceiving normal science as a series of puzzles means, on the one hand, thinking of it as closed, inward-­ looking and self-governing, while on the other, seeing scientists as believers who have an unwavering faith in the fact that for every problem that exists there is always a solution. In conclusion, Bloor believes that social ideologies are so prevalent that they represent the constitutive nucleus of concepts and metaphors, which are reflected by them. Exercises

Games and Exercises: Metaphors • Go to https://www.etymonline.com/ and look for the metaphorical origin of the following words: character, energy, doubt. • Go to https://www.etymonline.com/ and look for the metaphorical origin of the following plants: azalea, daisy, gladiolus, orchid, tulip. • Go to https://www.etymonline.com/ and look for the metaphorical origin of the following diseases: mastitis, sclerosis, erythema. • Let’s now try to experience the metaphors that are (often) tacitly  used in social theories: 1. Form a group of three people; 2. Then choose an organisation that everyone is familiar with (e.g. the university); 3. Following Morgan’s (1986) approach, each group chooses one of the nine metaphors indicated by the author (see Sect. 4.7.3); 4. Then describe the life of the organisation (the actors, practices and rituals) through that metaphor; 5. Finally, bring the groups together and compare your descriptions. ◄

References

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Further Reading • Kuhn (1969) • Fleck (1935) • Lakoff (1987)

Check Your Preparation

1. “Seeing”, says Hanson, “is a ‘theory-laden’ undertaking”. What does this mean? 2. What is Gestalt and why is it relevant for the study of science? 3. The incommensurability principle. What does it mean and why is it important? 4. Why, according to Feyerabend, is Galilei a cheat? 5. What are metaphors, analogies and metonymies? Why are they so important?

References Austin, J. L. (1962). How to Do Things with Words. Harvard University Press. Bloor, D. (1976). Knowledge and Social Imagery. Routledge and Kegan Paul. Cerroni, A. (2002). Discovering Relativity Beliefs: Towards a Socio-Cognitive Model for Einstein’s Relativity Theory Formation. Mind & Society, 3(1), 93–109. https://doi. org/10.1007/BF02511869 Collins, H. M. (2012). Comment on Kuhn. Social Studies of Science, 42(3), 420–423. https:// doi.org/10.1177/0306312712436571 Dick, S. (1996). The Biological Universe: The Twentieth Century Extraterrestrial Life Debate and the Limits of Science. Cambridge University Press. Duhem, P. M. M. (1906). La théorie physique: son objet et sa structure. Chevalier et Rivière. (transl. The Aim and Structure of Physical Theory. Princeton University Press. 2nd. ed., 1991). Feyerabend, P. K. (1975). Against Method. Verso Book. Feyerabend, P. K. (1987). Farewell to Reason. Verso. Fleck, L. (1935). Entstehung und Entwicklung einer wissenschaftlichen Tat- sache. Einführung in die Lehre vom Denkstil und Denkkollektiv. Benno Schwabe. (transl. Genesis and Development of a Scientific Fact. Chicago University Press,1979.) Gobo, G. (1993), Class: stories of concepts. From ordinary language to scientific language, in “Social Science Information”, 32(3), 467–89. https://doi. org/10.1177/053901893032003003 Gobo, G. (1995), Class as metaphor. On the unreflexive transformation of a concept in an object, in “Philosophy of the Social Sciences”, 25 (4), 442–67. https://doi. org/10.1177/004839319502500402 Hanson, N. R. (1958). Patterns of Discovery: An Inquiry into the Conceptual Foundations of Science. Cambridge University Press.

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Hesse, M. (1988). Socializing Epistemology. In E.  McMullin (Ed.), Construction and Constraint: The Shaping of Scientific Rationality (pp.  97–122). University of Notre Dame Press. Holton, G. (1978). The Scientific Imagination: Case Studies. Harvard University Press. Impey, C. (Ed.). (2010). Talking about Life. Cambridge University Press. Koyré, A. (1939). Études galiléennes. Hermann. (transl. Galileo studies. Harvester Press, 1977). Kripke, S. A. (1972). Naming and Necessity. Harvard University Press. Kuhn, T. (1962). The Structure of Scientific Revolutions. University of Chicago Press. Kuhn, T. (1969). Postscript. In T.  Kuhn (Ed.), The Structure of Scientific Revolutions (pp. 174–210). The University of Chicago Press. (2nd ed. 1970). Lakatos, I. (1970). Falsification and the Methodology of Scientific Research Programmes. In I. Lakatos & A. Musgrave (Eds.), Criticism and the Growth of Knowledge (pp. 91–195). Cambridge University Press. Lakoff, G. (1987). Women, Fire, and Dangerous Things. What Categories Reveal about the Mind. Chicago University Press. Lane, K.  M. D. (2005). Geographers of Mars. Cartographic Inscription and Exploration Narrative in Late Victorian Representations of the Red Planet. Isis, 96, 477–506. https:// doi.org/10.1086/498590 Mackenzie, D.  A., & Wajcman, J. (1985). The Social Shaping of Technology: How the Refrigerator Got Its Hum. Open University Press. Marcheselli, V. (2022). The Exploration of the Earth Subsurface as a Martian Analogue. Tecnoscienza 13(1), pp. 25–45. Masterman, M. (1965). The Nature of a Paradigm. In I.  Lakatos & A.  Musgrave (Eds.), Criticism and the Growth of Knowledge, Proceedings of International Colloquium, The Philosophy of Science, 4. Cambridge University Press. Mill, J. S. (1859). On Liberty. John W. Parker & Son. Morgan, G. (1986). Images of Organization. Sage. Neurath, O. (1921). Anti-Spengler. In Neurath, O., Empiricism and Sociology. Vienna Circle Collection 1 (pp. 158-213). D. Reidel. Pinch, T., Bijker, W. E., & Hughes, T. P. (1987). The Social Construction of Technological Systems: New Directions in the Sociology and History of Technology. The MIT Press. Pontzen, A., & Peiris, H.  V. (2010). The Cut-Sky Cosmic Microwave Background Is Not Anomalous. Physical Review, D, 81(10), 103008. https://doi.org/10.1103/ PhysRevD.81.103008 Popper, K. (1934). Logik der Forschung. Springer. (transl. The Logic of Scientific Discovery. Basic Books, 1959). Schrick, L., et  al. (2017). An Early American Smallpox Vaccine Based on Horsepox. New England Journal of Medicine, 377(15), 1491–1492. https://doi.org/10.1056/ NEJMc1707600 Sontag, S. (1988). Aids and Its Metaphors. Farrar, Straus and Giroux. Toulmin, S. (1970). Physical Reality: Philosophical Essays on Twentieth-Century Physics. Harper and Row. Toulmin, S., & Goodfield, J. (1965). The Discovery of Time. Hutchinson. Zolo, D. (1988). Epistemologia riflessiva e complessità sociale. MicroMega, 1, 131–143. (transl. Reflexive Epistemology: The Philosophical Legacy of Otto Neurath, Boston Studies. In the Philosophy and History of Science. Kluwer Academic Press, 1989).

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Sociology of knowledge, whose founder was the German sociologist Karl Mannheim (1893–1947), may well have been predestined to herald the social studies of science. Mannheim (1929) instead excluded science and mathematics from the sociological explanation, removing the products of scientific knowledge from his analysis.

5.1 The Advent of the Sociology of Science: Robert K. Merton A decade later, with his PhD thesis (1938) on the role of protestant ethics in the advent of modern science in the England of the seventeenth century (explicitly referring to the work of Max Weber), the US sociologist Robert K. Merton (1910– 2003) opened this new sector of research. To be precise, a number of Russian scholars had already highlighted the social aspects of science: one of the most important was the physicist, philosopher and historian of science Boris Hessen, who had adopted a materialistic (Hessen, 1931) or, so to speak, externalist perspective in the study of the physics of Newton (Cerroni & Simonella, 2014). Merton was not indifferent to this perspective and had portrayed science as an institution, a cultural structure similar to the others. According to the author, the work of the scientist was guided by mores, in other words values, rules and standards of social (more than methodological) behaviour. Merton undertook a functionalist analysis, whose objective it was to discover the specific functions of certain standards that constitute the structures of science. For this purpose he outlined what would be the fundamental characteristics of the ethos of the scientists: as set © The Author(s), under exclusive license to Springer Nature Switzerland AG 2022 G. Gobo, V. Marcheselli, Science, Technology and Society, https://doi.org/10.1007/978-3-031-08306-8_5

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of prescriptions, preferences, precepts (reinforcements and sanctions) and imperatives that bind and guide their actions. These constitute the knowledge of the scientists, as evident from the interviews that Merton and his collaborators undertook during their research. In particular, regarding imperatives, Merton identifies the following four: 1. Universalism, where the contributions of scientists needn’t be evaluated based on their  personal or social characteristics (race, class, gender, religion or nationality); 2. Communism (that in the 1930s, in America, was still not a four-letter word), understood as a strong inclination towards collaboration and the giving up of intellectual property in exchange for recognition and esteem; 3. Disinterestedness, as science is of a public nature, it aspires towards verification and makes its results available to all; 4. Organised scepticism an attitude that is not only mental or personal but also classified as part of methodological rules. According to Merton, these four imperatives differentiate the scientific undertaking by other socially organised activities. However, from a careful examination, these imperatives are fairly generic and idealistic but hardly charactise science. In fact Merton’s legacy was not collected by the new generation of British social scientists (including Barry Barnes, David Boor, Henry M. Collins, Michael Mulkay, Nigel Gilbert, David Edge, Steve Woolgar) who, 30 years after Merton, would resume the quest of science. These instead are inspired by the work of the late Durkheim, that of The Elementary Forms of Religious Life (1912), by Mannheim and, in part, also by the same Kuhn. In their opinion, Merton only addressed the social context of science, adopting, so to speak, an outward perspective, while never going so far as to analyse the content of the scientists’ work. It was precisely on the latter that they focussed, countering the widespread prejudice, according to which although everything might seem socially determined, embodying the sign of the times, the content of scientific knowledge would be an exception. Instead, for them, scientific knowledge is social knowledge.

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5.2 The Edinburgh School “Strong Programme” Bloor (1976) and the colleagues of the Edinburgh University prepared in the mid-­ 1970s what would be the “sociology of scientific knowledge” manifesto. This, called strong programme, as it sought to be rigorous, implacable, coherent and ground-breaking, is based on four main radically prescriptive principles (ibid, p. 7). While not being clear cut, with some study, we can say that the study of science, in the words of Bloor, must be: 1. Causal, in other words addressing the conditions or causes that produce scientific beliefs. There may be many types of causes, not all social.1 2. Impartial, in explaining both reality and falsity, rationality and irrationality, success and failure; there is a diffuse approach according to which logical, true and rational knowledge does not require explanation: they explain themselves and feed themselves (ibid, p. 9). The idea is that only the things that fail or that are unsuccessful should explain themselves. Scholars have focused on these to explain the causes (psychological, sociological, economic, historical, etc.) of their failure. The sociology of knowledge instead must be impartial and not only be looking at errors and deviances but must explain normalities with the same theoretic instruments. 3. Symmetrical, in the sense that the same types of causes must be used to explain both true and false beliefs. It is not scientific to find for knowledge false social explanations (for example) and for true knowledge natural causes. Sociological language is not a language that can be used at will. 4. Reflexive, for which the sociological models of explanation must also be applied to sociology itself. What’s needed is consistency: if you criticise you must also be willing to be criticised, with the same conceptual tools. According to Bloor, scientific knowledge has (a) an eminently theoretical rather than empirical nature and (b) the theoretic component is not natural but social. As such, errors in science cannot be fully eliminated. Continuing along the way paved by the French sociologist and anthropologist Émile Durkheim (1858–1917), who theorised that in a society not all crimes can be eliminated and that it is therefore necessary to establish which it is acceptable to live with (preferably those that do not compromise the fundamentals of society), Bloor affirms that the choice of  The US science philosopher Larry Laudan (physics graduate) instead argues (in line with classical positivism and behaviourism) that the search for causes falls within the realms of metaphysics and theology. 1

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errors with which science accepts to live with is a social and not a scientific decision. There is never a clear distinction between normality and deviance, success and failure, rationality and irrationality, science and metaphysics; instead there is continuity because normality and deviance (and the other dichotomies, such as health and illness) are defined and are mutually redefined, at every historic moment and on extremely social bases. Exercise: Health and Illness

Research historically when and why some phenomena, long known and considered normal (at times also healthy), have become illness. Try with the following (now considered) illness: allergy, neurosis, stress, osteoarthritis, obesity, alcoholism, smoking, and so on. ◄

5.3 The Experimental Method: Cultural Assumptions and Deviance Even the methods used for knowledge are an intrinsically social product and thus, from their outset, have been imbued with a strong cultural and ideological component. Let’s take the experiment, the favoured tool of the scientific method, that requires that experience has a repeated, public, controllable character, respecting the Mertonian ethos. Even so, the experiment is not as old as the method but made its début at a particular historic moment, between the end of the sixteenth century and the beginning of the seventeenth century, attributable to Francis Bacon (1560– 1620) and Galilei (1564–1642), two contemporaries who are considered its inventors. However, the cultural climate that helped to promote its beginnings prevailed at least  150 years earlier, when the concepts of replicability and reproducibility began to appear and become popular, fuelled by the invention of movable type printing (by the German goldsmith and typographer Johann Gutenberg, between 1448 and 1454, refining tools and techniques that already existed and that he applied to printing). As we have already seen (see Sect. 2.3.1) a verbal culture (where there is no slavish repetition, but where each contributes something personal) would never have been able to conceive the experiment as the basis for science: it is instead the written culture that materialised the concepts of precision, making changing of the past difficult in light of the present and reducing the aspect of  arbitrariness. Later, printing and typography reinforced and strengthened the attributes of writing; if in writing it was still possible to make mistakes (the exceptions of the Latin language were probably due to copying errors made by the scribe

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monks), printing would go a long way to reducing these. As such, typographical practice technologically materialises repeatability/replicability, equality (the first copy is equal to the last), objectivity and controllability. However, even if the experimental method would eliminate a series of errors, it is not clear which errors it continues to allow, to perpetuate. One thing, however (at least in the eyes of those who hold a positivist view of science), is fairly disconcerting. Galilei, father of the experimental method, was the first to not always follow the procedure that he himself had indicated. In fact, according to some historians of science, some of his most important experiments might never have been performed, for example, the experiment of the tower of Pisa (carried out to disprove Aristotle’s theory on gravity), that it was said took place between 1589 and 1592, apparently never happened (Cooper, 1935). Even the experiment of the ship, performed to highlight the difference between absolute motion (of the earth) and uniform relative motion (that we don’t perceive), probably never even took place. Similarly, it is dubious as to whether the law of isochronism for a simple pendulum (Naylor, 1974) and the experiment of the inclined plane (to formulate the law of uniformly accelerated motion) actually took place (Koyré, 1953; Naylor, 1974). Regarding the latter, Galilei stated he had performed it in 1604 “for experiences replicated a hundred times” and described in minute detail the procedure that consisted of rolling a bronze sphere across a tilted plane three feet long, covered in “the shiniest parchment paper possible” (in other words a scroll made with sheep’s coat). However, a single sheep’s (or calf’s) coat would never have been able to cover the whole surface of the plane: at least two were required. These however would have needed to have been stitched together but this join would undoubtedly have slowed down the bronze ball and Galilei would have realised that the use of the parchment not only was of no help at all but in fact could actually have constituted a hindrance. If he truly had performed this experiment, he would have no doubt made a point of mentioning these details. As such, they were only “mental experiments”, an expression coined by the Danish physicist and chemist Hans Christian Ørsted (1777–1851), undoubtedly important conceptual instruments (used with great success in physics, economics, history, cognitive sciences, philosophy, etc.), but quite different from natural experiments. Newton, Einstein, Bohr and many others (according to Westfall, 1973) maintained that they had carried out experiments that in fact they hadn’t and simply manipulated their data to back up their theories. The history of science is a continuous, never-ending and recursive testimony of an enduring schizophrenic behaviour: on the one hand, binding methodological rules are affirmed, on the other they are transgressed hidden or unconsciously, for a series of psychological, social and organisational reasons.

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In conclusion, as we have seen, the boundary between deviance and normality (between correct and incorrect behaviours) is fleeting and continuously redefined, historically and socially. Furthermore, institutional pressures, ideology, blind faith in one’s own convictions, narcissism and so on can lead even a supposedly r­eputable scientist to (sometimes) tell lies. Without in any way diminishing their value. Obviously all of this involves great risk and danger. This, perhaps, is the deterrent. But Popper would say that we are invoking determinism and historicism. According to Bloor (as already for Popper, Kuhn, etc.) experience certainly has an important role, science is not indifferent to facts and scientific theories are not pure fantasy. However, science is highly more sensitive and influenced by the impositions of society than by experience; at times directly, for example in the case of the Manhattan project,2 more often indirectly, through acceptance of the prevalent visions of the world. Once again, following in the footsteps of Durkheim, Bloor compares (another analogy) science to religion. Similar to religion, science is essentially a “way of perceiving, and making intelligible our experience of the society in which we live” (Bloor, 1976, p. 51). Just as religion requires unwavering adhesion, it imposes a marked regulation of the behaviours of its followers, tends to distinguish the sacred from the profane (by which it is constantly threatened and towards which it instils rituals and behaviours to neutralise it) so science demands from its members faith in the scientific method, adhesion to its methodological rules and objects to metaphysics and pseudo-sciences. In the same way that religion is a product of social pressure, science is (in each of its phases) the product of a particular society.

5.4 Mathematics and Logics as Social Institutions Bloor is interested in that which is commonly referred to as disciplines of a binding nature that reflect unique and unchanging truths: mathematics and logics. His efforts reached the very heart (social) of mathematical knowledge. “The idea that there can be variation in mathematics just as there is variation in social organisation appears to some sociologists to be a monstrous absurdity” (Bloor, 1976, p. 107).

 In 1942 on the express request of the US government (and with the support of the UK and Canada) a team of a thousand scientists was formed (among the most important, including the Italian physicist Enrico Fermi) who, under the scientific direction of the US physicist Robert Oppenheimer, in the laboratories located near the US small town of Los Alamos (New Mexico), worked to implement war-oriented nuclear energy. Thus was conceived the atomic bomb. 2

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And yet the German philosopher, historian and writer Oswald Sprengler, in his very famous Decline of the West (1918), and Wittgenstein, in the challenging Remarks on the Foundations of Mathematics (1956), had hypothesised a connection between worlds of numbers and worlds of civilisations. The German mathematician, logician and philosopher Gottlob Frege, in Foundations of Arithmetic in 1884, had also argued that mathematics (unlike the position of John Stuart Mill presented in System of Logic) was not an inductive science, in the sense that it was not based on experience, that is on physical operations on objects. The idea of Mill could at best be pedagogically useful, in other words to teach children to learn mathematics through the handling of objects (pebbles, peppercorns, marbles, etc.). Frege argues that numbers do not equate to experience: who has even experienced zero (zero pebbles) or extremely big numbers such as 10,000,000,000? Experiencing one  thing doesn’t mean experiencing the number 1, says Frege. Natural numbers (0, 1, 2, 3, etc.) are used to count but do not identify what is in fact being counted. They actually have properties that are not found in the thing being counted (e.g. the odd or even), that cannot be seen or touched while the things to which they refer are seen and can be touched. It is similarly difficult to argue that “imaginary” numbers, such as 2i, that stem from the fact that it is not possible to calculate the squared root of a negative number, and “complex” numbers (produced from the sum of a natural part and an imaginary number, for example 5 + 2i) are abstractions obtained from real things. The mathematician Richard Dedekind, in his The Nature and Meaning of Numbers (1888), considered numbers free  creations of the human spirit, completely independent from reality and a direct consequence of the pure laws of thought. As the Italian mathematician Enrico Giusti (1999) points out, the objects of Euclidean geometry (straight, plane, length, area, circle, angles, etc.) do not come from the abstraction of real objects, external, independent of the observer, but from a process of objectification of procedures, of social practices that formalise human actions (how to trace a circle on the ground using a rope, etc.). Mathematics develops through the repeating of a sort of module that results in “fixing” and therefore creating mathematical objects. This takes place in three phases: at first, new instruments are introduced, methods of demonstrating that have originated from innovative ideas; these then become solutions to problems and at the same time objects of study; finally, if they are accepted, they take on their own objective existence. Bloor (1976, p. 102) also argues this: Weavers pick up the way that the pattern goes by watching and working with others. They can then function autonomously and apply and reapply the technique to new

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Of course mathematics is not created from experience and from perception (as Frege argues) but is invented. However, it is not simply an invention (a formal game, mental, purely subjective), detached from the surrounding reality because it is born of need, from an empirical manipulation. In other words, it is a social invention, a construction (therefore with a certain amount of arbitrariness) based on practices.3 Mathematical bodies therefore have the nature of ideal constructs that however find a foundation in an actual human practice that with time is consolidated and is generalised in the form of problem-solving. Bloor, therefore, on the one hand accepts Frege’s position while on the other he takes it to extreme consequences, criticising the same Frege and re-evaluating and correcting Mill (who had also discussed mathematics as a subjective, psychological reality): if numbers are not based on an empirical reality but on theoretical notions (highly processed, the finest and purest that the mind has ever managed to think up) where do these notions come from? If not from nature, then from culture: “the theoretical component of knowledge is precisely the social component” (ibid. 98). Bloor therefore starts, phenomenologically, to imagine an alternative mathematics (ibid, p. 108) in which the results of operations should systematically produce different results. In this apparently absurd idea, he takes comfort in Greek mathematics, where the number 1 was not considered a number. It was a monad, neither fully odd nor fully even; it was both, essentially “even-odd”, because it was considered a starting point, the generator of numbers (1 + 1 = 2; 1 + 1 + 1 = 3 etc.), both of even and of odd, for which he partook of both natures (ibid, pp.  111). Leaving Bloor to one side for a moment, but within this vision, it can also be argued that 1 is also the largest number because it contains all the other numbers; it is also the number with the highest number of relationships with the other numbers, because all the numbers start from it and can be broken down into the minimal unit that is 1. Finally 1 is the totality, the largest part: if you break up/cut 1 (e.g. a cake), the resulting parts (2, 3, 5, etc.) are smaller than the 1 whole or totality. And we have seen (see Sect. 4.2) that the number 2 comes (etymologically)  from “cut”.  Together with Bloor, one of the first people to bring social constructivism into mathematics was US’s Sal Restivo (1983a, 1983b). 3

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The mathematics of Pythagorean and, later, of Platonian thinkers was of the cataloguing type and echoed the classifications in use in everyday life. This “classificatory scheme symbolised society, life and nature [...]. The various types of number ‘stood for’ properties like Justice, Harmony and God” (ibid, p.  120). It was an applied mathematics, used for practical matters, radiating magic, as all the even numbers, and the number ten was related to health and cosmic order. A little like the numeric symbolism of the Bible where (for example) 3 was perfection (while the same, for the Mayans, was represented by 4). Four in Medieval times was considered a pivotal and solver number (there are four cardinal points, the main winds, the seasons, the lunar phases, the liberal arts of the quadrivium, the sides of the square to which the Earth is compared, as opposed to the triangle of the sky, symbol of the Trinity). Four is also the number of moral perfection and of the proportions of the human. Seven is the Buddhist number of completion. Bloor therefore found an alternative mathematics: “clearly if we do not recognise number mysticism as a form of mathematics at all then there is no question of it being an alternative [...] that it makes it tautological that there is no alternative mathematics” (ibid, pp. 121–2). “So mathematics has not a life of its own and a meaning of its own […] an intrinsic significance which resides in the symbols themselves awaiting to be perceived or understood” (ibid. 122). Bloor wonders: is the square root of 2 an irrational number (1.41421356237), as argued by contemporary thinkers, or is it actually not a number at all, as sustained by the ancient Greeks? There will be no proof to resolve the question because it involves incommensurable mathematical visions, whose “meanings [do not] reside in the marks on the paper or the symbolic routines of the computation itself” (ibid. 123). Certain conditions, in other words a collectively held system of classifications and meanings of a culture, have to be obtained before a computation has any meaning (ibid, p. 124). So the number is the role” (ibid. 101), a position that should not be confused with any object that plays that role. But if we are discussing roles, positions, then we find ourselves in the field of sociology and numbers can comfortably be defined as social instructions: “but if mathematics is about number and its relations and if these are social creations and conventions then, indeed, mathematics is about something social. In an indirect sense it therefore is ‘about’ society” (ibid. 105). Drawing on the conclusions reached by the philosopher of Latvian origins Jacob Klein, scholar of Greek mathematical thought, Bloor argues that “it is an error to see a single unbroken tradition of meaning attached to the notion of number [...] the continuity that we see in the tradition of mathematics is an artefact. It derives from reading back our own style of thought into the earlier work” (ibid, pp. 111–2).

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Up until then, the studies of science had been based on logical philosophical arguments or on historic examples. Starting from the second half of the 1970s a new phenomenon surfaced: a new generation of scholars (sociologists, anthropologists, linguists, ethnographers, philosophers, with a marked preference for empirical studies) has entered the laboratories, departments of researches, into the classes where science was being taught, into conferences where scientific communities take place. In other words, science began to be studied not only using the books, correspondence and documents of the time (as it is still appropriate to do even now) but also from within, observing and experiencing routines and the everyday life of scientists (see Sect. 6.3), with the aim of capturing science as it unfolded, observing it in the making and thus countering the mythical and sweetened image that is so widely perceived.

5.4.1 The Empirical Programme of Relativism During the same period, at Bath University (UK), Harry Collins, together with other colleagues, proposed a perspective for the study of science based on the proposals of the strong programme and on the philosophical arguments culled from Wittgenstein’s works, but what set it apart was preferring an empirical (rather than a historical) approach for the study of scientific knowledge production processes (Collins, 1974, 1981). This methodological proposal took the name of Empirical Programme of Relativism (EPOR) and focused, in particular, on the study of “scientific controversies”, the cases in which there is (especially in certain phases of the evolution of scientific knowledge) a controversy in the community of scientists. These controversies were analysed empirically by interviewing the scientists involved or by observing the research practices (Collins & Pinch, 1993). However, Collins rejects the idea that explanation should be causal and eschews explanation of the genesis of theories: only their reception can be accounted for. Their dispute analysis model is based on three stages: (1) demonstrating the “interpretative flexibility” of experimental data, that is that results lend themselves to various interpretations, that then generate controversies; (2) showing the local social mechanisms by which the closure of interpretative flexibility is effected; (3) linking the “local closure mechanisms” to wider social forces (Collins, 1981, p. 7). Collins illustrates these stages with a number of case studies. The Flexible Boundary Between Science and Pseudoscience

A symbolic piece of research of this programme was performed by Collins and Pinch (1979) and by Pinch (1979) in the second half of the 1970s. It involves the

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case of parapsychology, a discipline that addresses paranormal phenomena such as telepathy, the interaction between mind and matter and survival after death. The authors note that parapsychology uses rhetorics and procedures that are typical of mainstream science to gain acceptance as a new form of scientific knowledge. In fact, the methods adopted by parapsychologists, in an attempt to obtain recognition (by traditional science) for their discipline, include experimental techniques usually used by physicists and psychologists (e.g. double-­ blind experiments). Complementarily, the critics raised by the latter against parapsychology are not always based on criteria that stem from the scientific method (e.g. the rigour of procedures, the methods used), but instead on apparently non-scientific and philosophical reasoning, such as denying the validity of parapsychology itself because it deals with phenomena that are commonly associated with magic or with fantastic tales. As a result, conclude the authors, the distinction between science and pseudo-science doesn’t hinge solely on aspects linked to the correctness of the knowledge produced or on the correct application of the scientific method but also on a series of rhetorical and symbolic mechanisms intended to delegitimise parapsychology. ◄ In subsequent years, Collins progressively abandoned relativism to achieve, starting from the 2000s, a more realistic and less constructivist vision initiated by what he calls the “Third Wave” of STS (see 7.1.1 and Conclusion), in which he is the bearer of a normative stance based on the possibility of distinguishing between scientists and non-scientists, between who is competent and who is not.

5.5 The Strong Programme....Reinforced: Bruno Latour According to the French philosopher and anthropologist Bruno Latour, social studies of science that address the social production of a scientific fact still haven’t clearly demonstrated how the link between social context and scientific content is achieved. In other words, the strong programme (according to the cutting irony that characterises this scholar) is not strong enough. In some ways, it is the same Bloor (1976, p. 158) that recognises it at the end of his book: The shortcomings of the views developed here are, no doubt, legion. The one that I feel most keenly is that, whilst I have stressed the materialist character of the sociological approach, still the materialism tends to be passive rather than active. It cannot,

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I hope, be said to be totally undialectical, but without doubt it represents knowledge as theory rather than practice. The possibility for discovering the right blend seems to me to be there, even if it has not been realised.

For Latour (influenced by authors such as William James, Ludwik Fleck, Alfred North Whitehead, Michel Serres, Harold Garfinkel, David Bloor, Gilles Deleuze and Gabriel Tarde), it is an understatement to say that in scientific production there are social influences; in fact, the production of a scientific fact is itself entirely a social construction. This statement is documented through an ethnographic research that Latour performed at the Salk Institute, a California university research organisation located at La Jolla (San Diego), a cliff overlooking the ocean. This institute (named after the bacteriologist and virologist Jonas Edward Salk, inventor of a vaccine against poliomyelitis) is famous for its research on brain hormones and genome and because Renato Dulbecco, Nobel Prize winner for medicine, also worked on it. Latour entered the community of scientists of Salk and remained there for almost two years (from October 1975 to August 1977), in the same way that anthropologists entered an African tribe or a clan: with the same attitude of surprise and in an effort to suspend their (albeit minimal) scientific and epistemological knowledge. So what’s new about this method? Most of the social studies of science had been undertaken either through the study of controversies reconstructed on original documents or through interviews conducted with scientists. Latour instead set out to investigate what scientists do (during their work) and not what they say they do (a world away from scientific practice). Furthermore, his (challenging) task was to describe and explain, in a philosophical and sociological language, the production of a scientific fact that takes place in a biological and medical language. This work of translation is similar to that undertaken by the anthropologist who translates into social science events and behaviours that are produced in the language of natives. If we suspend our scientific knowledge (and it is fairly easy if we are ignorant of scientific matters), entering a laboratory we are of course in contact with a series of inscriptions. Using this term/concept (borrowed from the French philosopher Jacques Derrida) the authors introduce a semiotic4 (or semiological) twist in the social studies of science. Historically, inscriptions come about from stylised signs, symbols for commemorative requirements (e.g. sepulchral and honorary inscriptions, etc.) in an era before writing. What type of inscriptions, signs, do we find in

 A discipline that deals with the study of signs, and their interrelation (syntactics), their relationship with the meaning (semantics) and with actions (pragmatics). The founding father of this discipline is considered to be Charles Sanders Pierce (see Sect. 3.2). 4

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the laboratory? Tracks, notches, points, lines, recorded numbers, spectra, diagrams, peaks and slopes of curves, histograms and other graphical representations. Radically applying the naturalistic approach, the two authors ended up considering statements, words and signs as facts. Obviously they didn’t adhere to the positivist philosophy of the former Durkheim or to the positivist philosophy of the former Wittgenstein (see Sect. 3.1 and following); they only acquired a methodological precept from this that allowed them to see the laboratory as an inscriptions production system, created by inscription devices (laboratory machines and equipment that are constantly connected to a computer or to a printer that records n­ umbers, curves, etc.). Remaining faithful to their methodological task, the ethnographer, for example, does not look at experiments but only at daily, routine, normal inscription activities. These same substances, for which scientists have invented the strangest acronyms (e.g. tfr, thyrotropin releasing factor, to identify somatostatin) have an indirect existence because they are identified from tests performed by machines and not by scientists. Due to their mediated nature, say the two authors, it can be stated with some confidence that the substances are socially constructed. According to the theory of Latour and Woolgar (1979), the laboratory is a system of statements (assertions, affirmations) and inscriptions. There are five types of statements at a level that is higher than inscriptions and are distributed across various levels, depending on the degree of arbitrariness attributed to them by the community of scientists (see Fig. 5.1).

Statements 1 (conjectures or speculations) Statements 2 (tentative suggestions) Statements 3 (claims) Statements 4 (specialist facts) Statements 5 (taken-for-granted facts) Inscriptions Fig. 5.1  The layering of statements

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Contrary to Galilei’s arguments (that even today most scientists concur with), essentially that a statement is nothing more than a description of a fact, Latour and Woolgar are convinced that a statement is in itself a fact. The separation between statements and facts, argued by scientists, actually produces a concealing of the social production of facts: in the same way that a caress is not separate from the hand (that produces it), the fact is not independent of the statement. As stated in Sect. 2.3.2, reality is none other than an infinite and indistinct mass of events that doesn’t really have its own meaning; as such, the description of a fact, the naming of it, is not something that is accessory but is, to some extent, the fact. Therefore, scientists do not discover facts but write facts: they are writers who seek to convince their public of readers to accept their statements as facts, using aids such as “literary inscriptions” produced by machines. In other words, the laboratory is an organisation for persuasion through literary inscription. None of this is, of course, immediate: concepts are constructions that cover wide time spans, not notions thought up on the spot. In the classification of Latour and Woolgar (1979, pp. 75–80) the first statements (type 5) that we see are found at a level that is slightly higher than inscriptions and are relative to facts considered taken-for-granted. They are statements that never appear in discussions because they refer to facts considered obvious. They constitute tacit knowledge (which we have already covered in Sect. 2.4). The statements relating to obvious facts are followed by those (type 4) that concern specialist facts, essentially belonging to the disciplinary sector (e.g. the effects of certain reactions with certain substances). This also, second type of statements, is not referred to in controversies, but is instead cited as an acquired and essential reference and is commonly found in textbooks. It could be said that type 5 and 4 statements belong to “objective” facts. As indeed they are. Not in an ontological sense, but instead they are discursive and relational: according to Latour (2005), “objective” is a phenomenon on which we all agree and to which we offer no objection. At a level of greater arbitrariness are statements (type 3) that relate to non-­ definitive claims or assertions. These are statements that we find in papers, drafts or technical reports circulating in the laboratory and, as they are still not definitive, they are more affiliated to affirmations than to facts. Climbing the ladder of arbitrariness, we meet tentative suggestions,  type 2 statements. When they are spoken or written they are always accompanied by terms of phrase such as “what is generally known” or “what might reasonably be thought to be the case”, and so on, followed by names, dates, places, in other words

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modes that refer to laboratory work conditions, hypotheses on the development or the repetition of experiments that are used to obtain new inscriptions. Finally we meet conjectures or speculations, type 1 statements, set out at the end of articles or in private discussions. Latour and Woolgar state that statements are in continuous evolution. In fact a statement can change status (and therefore its facticity content) and move to another level, both ascending and descending the ladder of arbitrariness. The content of the statement changes with the addition or elimination of clarifications. For example if we add to the statement (of the type 2, that is a tentative suggestion) “the effects of somatostatin on the secretion of TSH” the clarification “have now been confirmed by laboratory X”, the statement becomes a type 3 one (a claim). Or, to take another example, a paper sent to a journal may contain, in the author’s opinion, type 2 and 3 statements; however if the referees consider them too arbitrary and premature (see, p. 84), their evaluation will transform them into type 1 statements (conjectures). A tug-of-war therefore ensues (possibly quite animated) between the referees (who argue that the matter only concerns conjectures) and the author of the paper who will act with the aim of moving their statements to a lower level, such as those of type 3 or even 4 (taken-for-granted facts). According to Latour and Woolgar, much of the work of scientists in the laboratory consists of performing operations on statements, adding or removing citations, improvements, proposals, combinations and so on, to lower their statements on the ladder of arbitrariness. In fact the last aim of the scientist (and also their hidden desire) is to produce a theory that is recognised by the community as a type 4 statement, that is a statement with or without few references to the specific situation or context in which the experiments are conducted in order to make it a statement that is a-­contextual, non-indexical, universal. At that point, the fact has been created but, simultaneously, the social reference that produced the fact has been hidden. Scientists are therefore engaged in a constant and recursive activity of fact-making (etymologically, “fact” stems from the Latin factum, past participle of the verb facere, that means to  make, to  create, to  put together); in reality, the objects of scientific study are socially constructed in laboratories and do not exist beyond the measuring instruments and experts that interpret them. A few years later, Latour (1996) would say that actually the “fact” is a “factish”, an indissoluble mixture of beliefs (fetishes) and knowledge (facts). For this reason, nature alone (and consequently the experiment, the evidence, rationality) cannot be produced to resolve scientific controversies. The theory of Latour and Woolgar also argues the character of reasonings (so far proposed) that lead to the scientific discovery. In fact it isn’t inductive or deductive reasonings (precise logical syllogisms) that guide research but analogies or fuzzy

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A=B Bombesin sometimes behaves like neurotensin B ------------------------------> C Neurotensin lowers temperature A -------------------------------> C Therefore bombesin decreases temperature Fig. 5.2  Fuzzy syllogisms

syllogisms of the type “A resembles B” or “A makes me think of B” or “A looks like B to me”, for example (Fig. 5.2). During research, scientists are guided by analogies; then, when their discovery has been accepted, they would say that it was a logical thing and rationally reconstruct ex-post a path that was anything but logical. Furthermore, replacing logic with analogy, the scientist ends up unconsciously hiding the context of production, transforming a tentative suggestion (type 2 statement) into a fact (type 4 statement). The laboratory is therefore the place both of the production and of the stabilisation of facts, the place where an order (fictitious, artificial, manipulated) is imposed on the disordered reality. In fact, wide disorder is always present and discoveries are the result of a long activity of bricolage (DIY), involving assembling confused ideas, fortuitous events, suggestions and refinements. In this regard, the US sociologist of science Michael Lynch (1985) documented how, in the public presentation of research findings, scientists don’t exhibit all their data but only a selection, to propose only the most persuasive aspects: for example they isolate and present graphs that show the curves that most support their theories; they clean up computer images; for the purpose of a projection, they ask their collaborators to choose with precision, from within a series of “dirty” slides, those which are least dirty. The purpose of these cleanups or refinements (say Latour, Woolgar, Bloor) is not only to obtain a compactness of the information but to conceal a scientist’s ideological design in the same way that religion tends to hide its internal contradictions.

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5.5.1 The Actor-Network Theory (ANT) In the early 1980s, the collaboration of the sociologists Michel Callon, Bruno Latour and John Law produced a theory5 that would go on to gain much popularity. It was presented as an attempt to overcome an anthropocentric view of social phenomena. As we have already seen, a statement or a scientific result is always at risk, in the sense that it might ascend or descend the ladder of randomness. As such, a taken-for-granted fact (statement 4), to be consolidated, really needs the support and cooperation of a whole series of supporters or allies, not only within but also from outside the laboratory. In this regard Latour (1984) reconstructs the case of Louis Pasteur (1822–1895), French chemist and biologist, creator of preventive vaccines. The existence of bacteria had already been a known fact since the second half of the seventeenth century, thanks to the microscope. In 1864 Pasteur discovered that all the ferments are produced by microscopic organisms called “microbes”6 (a term that etymologically and metaphorically means “small life”). Through his discovery, he constructed a new “microbic theory of fermentations”, which would revolutionise biology. Some years later (in 1881) he devised the anthrax vaccination (an infection that affects cattle and sheep, and sometimes also humans). In 1885 he invented the vaccine for rabies (a viral infectious disease) and pasteurisation, a procedure (named after him) to sterilise fermentable liquids. Inspired by the novel War and Peace by Lev Tolstoi (1865), Latour argued that Pasteur’s success wasn’t solely the product of his genius and it would not have been possible without a dense network of alliances and militias to support the “general” Pasteur. In fact he went to great lengths to persuade his peers of the robustness of his ideas. For example, many of his medical colleagues raised objections: they considered absurd both his explanation of infectious diseases and the hypothesis (essentially quite counter-intuitive) that it was possible to prevent them  through inoculation bacteria that cause the illness itself. It was in fact vets, the hygienist movement, the breeders and (even if it seems surreal) bacteria that helped Pasteur’s discoveries. But this argument wasn’t overnight and also required an intense and complex political activity by Pasteur because for each of the potential allies, he had to find a good reason for their support. As such, every time a category of actors entered the network (to support a scientific fact), the scientific statement or the technological artefact was readapted to maintain the interests of that category. A “translation”, a proposal/an attempt to persuade them that that scientific fact was  As Latour (2005) corrected, the ANT, more than a theory, is a method.  Today this term is considered too generic because it mixes different microorganisms, such as bacteria, viruses, protozoa, unicellular algae, fungi and so on. 5 6

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also in their interest, was taking place. What followed was then a sort of (military) enlistment in the ranks of the scientist. For this purpose Pasteur first convinced the breeders that to recover from anthrax they would need to go to his laboratory and reformulated his initial idea, shaped to their needs. He then managed to persuade the doctors who for 20 years had opposed him (his discoveries were actually finally accepted by the scientific community when he reached 60 years): their objections were based on the fact that the preventive vaccine bypassed them, significantly reducing their work (as there were many fewer ill people!) and created a competition with them and hygienists and vaccinators. However, when Pierre Roux, one of Pasteur’s closest collaborators, created a serum against diphtheria (a childhood plague typical of those years), doctors regained status as the serum was administered after a prior medical diagnosis, as if it were a drug. At this point, the translation was a fait accompli, serotherapy became part of medical practice and doctors and the Pasteur Institute had finally found some common ground. Latour therefore puts humans and non-humans (viruses, bacteria, etc.) on an equal playing field that he refers to as “actants” as they form part of a network that concurs (containing contrasts) in affirming or not a theory or an action that are always collective accomplishments (see Box 5.1). Box 5.1  Drug as an Actant

In the spring of 2017, in the state of Arkansas, there was a sudden increase in state executions. The prison programme envisaged the killing of eight persons by Sunday 30 April. But what lay behind this urgency? The executions would take place through a lethal injection of a cocktail of drugs, including Midazolam (the purpose of which is to anaesthetise and sedate the condemned), the use of which was set to expire that particular Sunday. In other words, the acceleration of executions was not attributed to the need to meter out justice but to use up any remaining stocks of the drug within the expiry date, after which the efficacy would be reduced, thereby prolonging the suffering of the condemned. Following the ANT, we can say that the drug (non-human actor) contributed to the decision of the prison authority as much as any other human actors. ◄ Critics (e.g. Bloor, 1999) argued that ANT is tautological, overly Machiavellian, deterministic and animist. However, at a conference held at Geneva University on 11 May 2011, Latour (to reject a simplistic reading of his work) stated: “if you want to remove Pasteur there would be no microbes. But if you think that Pasteur ‘constructs’ [...] his microbes one ‘piece after another’ then you haven’t quite understood what takes place in a laboratory. He makes his microbes be, that is, he is doing everything he can so that his microbes become autonomous and, as

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such, independent from him. The more he works and the more microbes are autonomous, the more he works and the more objective the microbes are”.

5.5.2 Culture and Nature Latour (1991) considers that the distinction between nature and culture is the result of an actual vision of modernity.7 In fact the author considers that traditional ­ecology is outdated, because nature is no longer something external (objective) damaged by human beings, the most invasive species. As such, from the epistemological point of view, modern, anti-modern and post-modern are similar because they all share the modern vision in which nature and culture are separate. So nature itself is the product of a political vision. Today, instead, a new actor has taken its place besides ecologists and politicians with quite different accomplishments: science. It in fact determines the disappearance of the distinction also between human and non-human objects (conceived in the seventeenth century) as there is an innumerable quantity of objects (however in constant growth), “hybrids” or “mixed” (or cyborgs as the feminist US philosopher Donna Haraway would say, see Sect. 10.3), in which the two worlds are constantly merged: frozen embryos, seeds and transgenic foods, whales fitted with collars connected to radio transmitters, silicone breasts and buttocks, contact lenses, synthetic crystalline lens inserted in cataract surgery, microchips implanted under the skin or in the brain, pacemakers, artificial hearts, facial plastics, arthroplasty, synthetic retinas and so on. These hybrids are the new collective actors, the new exteriorities, the new objectivities, which require a particular sociology (that of hybrids) and a new ecology that includes politics (political ecology). More generally the ANT considers that human behaviour cannot be distinguished (at least not analytically) from technological behaviour. Artefacts, plants, animals, organisations and human beings are deeply entangled and together produce a sociomaterial weave (see Box 4.2). Box 5.2  Sociomateriality

The concept of sociomaterial stems from research undertaken by the US feminist theorist Karen Barad (2003) on the work of quantum physicists and resumes that of material-semiotic reality also adopted by Haraway and by the ANT. Underlying both concepts is the idea that reality and practices are always  Classical modernity refers to that period in which we are seeing a growth in the centrality of the state-nation, the affirming of rationality in many areas of social life and an increase in technological innovation. This began in the second half of the 1700s with the industrial revolution and, later, the birth of positivism. 7

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the result of an assembly of matter and meaning that Barad refers to as “entanglement”: there is no social that is also not material and no material that is also not social. For this reason, according to Barad (1997), realism and social constructivism can co-exist without contradiction. ◄ On closer inspection, this proposal is a (beneficial, from our point of view) return to the Ancients (paradoxically, from the epistemological point of view, wiser than us), for which nature and culture were inextricable. In fact our civilisation has always lived side by side with science and technology, which the ancient Greeks referred to as episteme and techné, even if we have not always been aware of this link. A new approach to sciences, that Latour (2010) calls “scientific humanities”, may once again highlight the fact that sciences are human. Consequently, in the study of science, it is always necessary to simultaneously pose two questions: (1) how does society incorporate nature? and (2) how does nature incorporate society? What the scholar, through an exploration of discussions and written feedback of scientists, can observe and explore is only the intermittent movement of replacement and displacement, of association between things and people; not the construction of the former made by the latter. Latour, always controversially, typical of his character, does not side with the relativists (such as Collins or Bloor) as he argues that not everything is socially determined or negotiable, also because, in fact, many things are not renegotiated but stabilise and become natural. As explained in the Introduction, according to Latour (1991) using only society to explain nature (and science) actually means infringing the “symmetry principle” (see Sect. 5.2) proposed by the “strong programme” and, as a second consequence, accepting and reinforcing this division. Paraphrasing the author, if the ozone hole is too social to be considered a purely natural phenomenon, the political strategies are too full of embryos and stem cells to be able to reduce them to interests. We can’t conceive of Pasteur’s bacteria without considering the French society and politics of the nineteenth century or Edison’s light bulb without the American economy. The modern concept of family or those of life or of death ignoring assisted fertilisation techniques or human genome mapping. The micro/macro relationship is thus served. It is therefore necessary to be half relativist and half realist.

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5.6 A Summary As we have seen, at the end of the 1970s, there was a multi-faceted and divided spectrum of positions relating to nature and science. In fact it was so complex that it would be trivial (and even pedagogically dangerous) to reduce it to a (dichotomous) clash between realists and relativists. Instead, following Latour’s suggestion, it would be more correct to conceive this conflict as placed in a continuum (see Fig. 5.3 and Table 5.1), at whose extremes are found, on the one hand, those Language

Nature

Culture

[------------------------------------------------------------------------------------------] – Facts vs. interpretations – External reality independent of the observer

– Everything is socially determined – Everything is negotiable

Fig. 5.3 Nature-Culture continuum Table 5.1  Summary of the positions on the nature of science Realism Galilei Neopositivism Searle Weinberg P. Churchland P. S. Churchland

Critical realism Popper Lakatos Laudan Musgrave Putnam

Soft realism Fleck Hanson Kuhn

Constructivism Hesse Latour Knorr-Cetina Barad Haraway

Relativism Barnes Bloor Shapin Collins Woolgar Harding Pinch Pickering Yearly

Radical relativism Feyerabend

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for whom science is the mirroring of nature and, on the other, the advocates of a completely and radically relativist vision. More moderate and less radical positions are scattered within this continuum that shift within a pendulous movement between two opposing poles.

5.6.1 Realists Following this spatial analogy and accepting the risk of squeezing different positions,8 we can place at the first end the position of Galilei who argued that it is important not to confuse scientific truths (which are “things”) with names, which are conventional instruments to succinctly indicate things; names merely have a denotative function. The truths of science are not contaminated by the beliefs of the time because they are objective, impersonal. Science mirrors the nature, which is the exact opposite of culture: in fact modern science actually came about by creating a moat between the world of physical sciences and that of humanities. Searle (1996) more recently assumed this position that distinguishes two types of facts: 1. The “brute facts” (atoms, heart, mountains, etc.) that exist independently of our theories, representations or languages (used to describe them); 2. The “institutional facts” (wedding, football, money, laws, etc.) performatively constructed by persons, through the assigning of agency and intentionality by the observer. The latter are based on the former that are logically a priority. As such, social reality is based on the physical, chemical and biological reality. As argued by US’s Steven Weinberg, Nobel Prize winner in 1979, the main difference between the rules of nature and those of culture (e.g. those of the game of football) is that human beings do not create the former but only discover them. Human beings create (socially) only the languages to describe them; but they exist independently of languages.

 For example Patricia S. Churchland and Paul Churchland take different stances on matters relating to theories of the mind. 8

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5.6.2 Critical Realists In a contiguous, but much more mitigated position, we find the critical rationalists (Popper, Lakatos, Laudan, Musgrave, Putnam). These believe that science is an enterprise that is fundamentally different from any other human activity, especially given its relationship with a reality. While being fallible, never completely reaching the truth, striving ahead through trial and error, being (at times) influenced by politics and by ideologies (that however shouldn’t be involved), science is based on a method and on rules that make it, by far, the most rational and effective knowledge enterprise we have. In fact, while theories come and go, the scientific method par excellence (the experimental one, invented by Galilei) is still valid after 400 years. Even if slowly, at times with great difficulty, our scientific knowledge (which is a mirror of reality) becomes from day to day more precise and things are discovered (not constructed!) that existed but which we didn’t know about. To silence the constructivists or the relativists, they could ask them, using Laudan’s words: “did oil exist or not before it was discovered?” They could mock them with one of the famous jokes of the US comedian Groucho Marx: “Oxygen was discovered in 1770. It’s unknown how people were able to breathe before then”.

5.6.3 Soft Realists Taking a distant stance from strong realism we find Kuhn. However, according to Popper (1956-57, pp. XXXI–XXXV) Kuhn’s conclusions, beyond certain divergences, are essentially close to his. Only that he takes positions for an objective rational critique, while Kuhn (again using Popper’s words) falls into relativism. However Kuhn (1969, pp. 205–6) rejects the: mere relativism [...] [science is an activity used] to solve puzzles presented by nature [and] scientific development is, like biology, a unidirectional and irreversible process. Later scientific theories are better than earlier ones for solving puzzles [...] That is not a relativist’s position, and it displays the sense in which I am a convinced believer in scientific progress.

5.6.4 Constructivists We can place the constructivists (Hesse, Latour, Knorr-Cetina, Haraway, Barad) at the centre of the continuum. They do not have a pre-established position. On the one hand, Hesse (1987) argues that scientific theories, similar to some social habits, would in any case be developed (at least partially) by conforming to an external

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reality. The fact that a certain number of deadly illnesses have been reduced and controlled through the identification of something (e.g. a bacterium) that can be shown, would demonstrate the ability of humans to conform to an external reality and the success (the healing) would represent evidence of the success of an adaptation. And yet there would exist a biological basis of the perception that must refer, to survive, to real regularities of the world; the survival would be evidence of a success, the demonstration that not all the inductions and cognitive procedures are purely arbitrary or completely conventional. In other words, there is a reality that is independently accessible to the observer. However, again Hesse proposes radicalising the current philosophical and sociological approaches of science to consider epistemology itself an object of sociological analysis. Latour also, in the diatribe between realists and relativists on what performs the main role in determining the contents of science, refuses to sit either on the side of nature or on the one of society. For him, every description is half natural and half cultural, half realist and half relativist. Human beings produce (construction) objects (cultural  act), which then become autonomous from human beings and become external realities (nature) that then end up conditioning the action of human beings. The Irish chemist, physicist, inventor, theologian and naturalist philosopher Robert Boyle (1627–1691), for example, was the first to produce the vacuum, a situation that does not exist in nature. In 1659, aided by his colleague Robert Hooke, he constructed an air pump that was able to create a situation whereby he could predict the behaviour of gases (the law of Boyle and Mairotte). Boyle was aware that the experiment was an artificial practice and that the vacuum was an artifice. As such, according to Latour, the vacuum machine on the one hand is a human construction but on the other its presence changes human knowledge: it sits in the middle, at the crossroads between natural and social.

5.6.5 Relativists They don’t argue that there is no world, that scientific knowledge is illusory or a simple construction. Quite the opposite. They simply say (these also) that worlds are “constructed” and, as such, they exist: they exist as constructions, similar to a house after it has been built. For example the US feminist philosopher Sandra Harding argues that physics, chemistry, mathematics and logic bear the cultural “footprints” of their creators, no less than anthropology and history. So reality isn’t as compelling as realists claim. Otherwise we wouldn’t understand why, to explain

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the same phenomenon, contradicting theories persist instead of just the one. Of course, it’s not that there are dozens of theories being bandied around on the nature of light (merely two) and this means that reality does in fact play its role, however to a much lesser extent than imagined. For example the English sociologist, philosopher and historian of science Andrew Pickering, in his study on the construction of quarks, pointed to how scientific knowledge on elementary particles came about in relation to the type of techniques used and to the phenomena that these techniques highlighted. In this case, it’s not that we’ve had a new Gestalt that has restructured the observational field but instead only an accommodation and the taking of competing perspectives based on varying theoretical resources, interpretative practices and social negotiations. According to Pickering, realists are unable to grasp the positive message of relativism: there are different ways for human beings to perceive the world and for the world to be instilled in them. They act in a certain way and obtain certain powers; they act in a different way and acquire others. And vice-versa, one way gives them the old physics while another gives them the new one. One way gives them alchemy while another gives them chemistry. Therefore a reciprocal accommodation acts between cultural field and material world. The role of the social, argues Shapin (1982), is to pre-structure, not to preclude the choice of the scientist. Fleck (1935, p. 43) was the first to underline the fact that those who consider social dependence a necessary evil and an unfortunate human inadequacy which ought to be overcome fail to realize that without social conditioning no cognition is even possible. Indeed, the very word “cognition” acquires meaning only in connection with a thought collective.

As such, Bloor argues that relativism is not a monster to be afraid of but simply the opposite of absolutism. For this reason it is certainly preferable. The relativism of the strong programme (Sect. 5.2) is (only) a “methodological relativism”; in other words, it applies the requirements of symmetry and reflexivity to also study scientific knowledge. Additionally, it is not a destructive and iconoclastic relativism; rather, in some ways, it can be compared to the progressive epistemology of Popper and of his followers, as it doesn’t seek to dissolve the autonomy of practices and of scientific theories in a mere social conditioning. It would (…) be fatal only to the claim that knowledge depended exclusively on social variables such as interests […] a mono-causal story which denied a role for anything but social processes, i.e., the near meaningless claim that knowledge is ‘purely social’ or ‘merely social’ [...] But doesn’t the strong programme say that knowledge is purely

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social? Isn’t that what the epithet ‘strong’ means? No. The strong programme says that the social component is always present and always constitutive of knowledge. It does not say that it is the only component, or that it is the component that must necessarily be located as the trigger of any and every change: it can be a background condition. (Bloor, 1976, pp. 166–7)

However, recognising the autonomy of scientific theories from social conditioning doesn’t mean accepting tout court the independence of nature. Relativism, says Bloor (ibid, p. 159), means assuming that all knowledge is relative to the local situation of the thinkers who produce it: the ideas and conjectures that they are capable of producing; the problems that bother them; the interplay of assumption and criticism in their milieu; their purposes and aims; the experiences they have and the standards and meanings they apply. What are all these factors other than naturalistic determinants of belief (…)?

Are beliefs, Bloor wonders, ultimately conjectures? But “to see all knowledge as conjectural and fallible [as Popper does] is really the most extreme form of philosophical relativism” (ibid, p. 159). Exercises

Exercise 1: Role play (a) Form six groups, each of which is given the task of copying an approach or a school of thought, choosing from the following: Realism Critical realism Weak realism Constructivism Relativism Radical relativism

(b) Place in front of you a card with the name of the approach that the group is impersonating so that it is recognisable by the members of the other five groups; (c) Consider the following ten keywords: nature, culture, fact, evidence, reality, belief, objectivity, subjectivity, politics, science. Write each of these words on a small piece of paper; fold it up and place it in a container; (d) Take out the first keyword and start the debate assuming (and arguing) the theoretical position that you represent; (e) Continue in this way until all ten keywords have been used up; (f) Try, as far as possible, to use all your empathic skills to understand the system of values of your peers, putting yourself in their shoes. Science must become encounter and not clash.

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Further Reading • • • •

Bloor David (1999) Id. (2011) Latour Bruno (2005) Id. (1999)

Exercise 2: According to ANT (see Sect. 5.5.1 and later Sect. 9.4), viruses and bacteria (as actants or non-human actors) equally concur with humans in influencing and conditioning our lives. Thinking about the SARS-COV 2 virus and the syndemic we have experienced, how can ANT be applied? Discuss in class. Check Your Preparation

1. What are the differences between the sociology of science of Merton and that of Bloor? 2. How were the mathematics of the ancient world conceived? How do they differ from modern mathematics? 3. Why, according to Latour, is the “strong programme” not strong enough? 4. What is the ANT? 5. What does it mean to be half realist?

References Barad, K. (1997). Meeting the Universe Halfway: Realism and Social Constructivism Without Contradiction. In L. H. Nelson & J. Nelson (Eds.), Feminism, Science, and the Philosophy of Science (pp. 161–194). Kluwer Academic Publishers. Barad, K. (2003). Posthumanist Performativity: Toward an Understanding of How Matter Comes to Matter. Signs, 28(3), 801–831. https://doi.org/10.1086/345321 Bloor, D. (1976). Knowledge and Social Imagery. Routledge and Kegan Paul. Bloor, D. (1999). Anti-Latour. Studies in History and Philosophy of Science, 30(1), 81–112. https://doi.org/10.1016/S0039-­3681(98)00038-­7 Bloor, D. (2011). Relativism and the Sociology of Knowledge. In S.  D. Hales (Ed.), A Companion to Relativism (pp. 433–455). Wiley-Blackwell. Cerroni, A., & Simonella, Z. (2014). Sociologia Della Scienza. Carocci. Collins, H.  M. (1974). The Tea Set: Tacit Knowledge and Scientific Networks. Science Studies, 4(2), 165–186. https://doi.org/10.1177/030631277400400203 Collins, H. M. (1981). Stages in the Empirical Programme of Relativism. Social Studies of Science, 11(1), 3–10.

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Collins, H. M., & Pinch, T. (1979). The Construction of the Paranormal: Nothing Unscientific is Happening. The Sociological Review, 27(1_suppl), 237–270. Collins, H. M., & Pinch, T. (1993). The Golem. What Everyone Should Know about Science. Cambridge University Press. Cooper, L. (1935). Aristotle, Galileo and the Tower of Pisa. Cornell University Press. Dedekind, R.  J. W. (1888). Was sind und sollen die Zahlen? Vieweg Verlag (transl. The Nature and Meaning of Numbers. Essays on the Theory of Numbers. Dover, 1963.) Durkheim, É. (1912). Les formes élémentaires de la vie religieuse. Alcan. (transl. The Elementary Forms of the religious life. George Allen & Unwin Ltd.) Fleck, L. (1935). Entstehung und Entwicklung einer wissenschaftlichen Tat- sache. Einführung in die Lehre vom Denkstil und Denkkollektiv. Benno Schwabe. (transl. Genesis and Development of a Scientific Fact. Chicago University Press,1979.) Giusti, E. (1999). Ipotesi sulla natura degli oggetti matematici. Bollati Boringhieri. Hessen, B. (1931). The Social and Economic Roots of Newton’s “Principia”. In N. I. Buharin et al. (Eds.), Science at the Cross Roads: Papers Presented to the International Congress of the History of Science and Technology, Held in London from June 29 to July 3 (pp. 41– 101). Subsequently published Cass. 1971. Koyré, A. (1953). An Experiment in Measurement. Proceedings of the American Philosophical Society, 97, 222–237. https://www.jstor.org/stable/i357807 Kuhn, T. (1969). Postscript. In T.  Kuhn (Ed.), The Structure of Scientific Revolutions (pp. 174–210). The University of Chicago Press. (2nd ed. 1970). Latour, B. (1984). Les Microbes. Guerre et paix, suivi de Irréductions. La Découverte. (transl. The Pasteurization of France. Harvard University Press, 1988.) Latour, B. (1991). Nous n’avons jamais été modernes. Essai d’anthropologie symétrique. La Découverte. (transl. We have never been modern. Simon and Schuster, 1993.) Latour, B. (1996). Petite réflexion sur le culte moderne des dieux faitiches. Éditions Synthélabo, “Les Empêcheurs de penser en rond”. (transl. On the Cult of the Factish Gods followed by Iconoclash. Duke University Press, 2011). Latour, B. (1999). Politiques de la nature. Comment faire entrer les sciences en démocratie. La Découverte. (transl. Politics of Nature. How to bring the sciences into democracy. Harvard University Press, 2004). Latour, B. (2005). Reassembling the Social  – An Introduction to Actor-Network-Theory. Oxford University Press. Latour, B. (2010). Cogitamus: six lettres sur les humanités scientifiques. La Découverte. Latour, B., & Woolgar, S. (1979). Laboratory Life. The Construction of Scientific Facts. Sage. Lynch, M. P. (1985). Art and Artifact in Laboratory Science: A Study of Shop Work and Shop Talk in a Research Laboratory. Routledge and Kegan Paul. Mannheim, K. (1929). Ideologie und Utopie. Cohen. (transl. Ideology and Utopia, Routledge and Kegan Paul 1936). Naylor, R. (1974). Galileo and the Problem of Free Fall. British Journal of History of Science, 7(2), 105–134. https://doi.org/10.1017/S0007087400013108 Pinch, T. (1979). Normal Explanations of the Paranormal: The Demarcation Problem and Fraud in Parapsychology. Social Studies of Science, 9(3), 329–348. https://doi. org/10.1177/030631277900900303

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Popper, K. (1956-57). Realismus und das Ziel der Wissenschaft. (transl. Realism and the Aim of Science. London: Hutchinson,1983.) Restivo, S. (1983a). The Social Relations of Physics, Mysticism and Mathematics. Pallas. Restivo, S. (1983b). The Social Construction of Mathematics. Zentralblatt für Didaktik der Mathematik, 20(1), 15–19. Searle, J. R. (1996). The Construction of Social Reality. The Free Press. Shaping, S. (1982). History of Science and its Sociological Reconstructions. History of Science, 20(3), 157–211. https://doi.org/10.1177/007327538202000301 Spengler, O. (1918). Der Untergang des Abendlandes. Umrisse einer Morphologie der Weltgeschichte. Gestalt und Wirklichkeit, Wilhelm Braumüller. (transl. The Decline of the West. Knopf, 1926). Westfall, R.  S. (1973). Newton and the Fudge Factor. Science, 179, 751–758. https://doi. org/10.1126/science.179.4075.751 Wittgenstein, L. (1956). Remarks on the Foundations of Mathematics. Macmillan.

Part II Main Themes in STS

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In Chap. 5, we looked at how, during the 1970s and at the beginning of the 1980s, the Strong Programme in the Sociology of Scientific Knowledge in the English-­speaking world and the ANT on the Continent made a significant contribution to the establishment of a constructivist and relativist approach to scientific knowledge. The idea that the knowledge-making process is not the abstract accumulation of theories on the nature of the world, but an eminently social process, would then be consolidated in the  course of the next two decades, when the field of Science and Technology Studies (STS) would reach a progressive institutionalisation, at least in the UK, the US and France. Conversely, the discipline would become popular at a much slower pace in countries where the positivist and neo-positivist traditions still today play a predominant role. In these contexts, STS scholars have sometimes struggled to establish themselves outside the spheres of a few prestigious centres. In this second part, we will be taking a thematic approach to explore some of the fundamental articulations of the studies of science and technology. It is however important to emphasise that the expression Science and Technology Studies defines an extremely interdisciplinary field within which sociology, history, philosophy, anthropology, literature, gender studies, cultural geography and other disciplines intersect. For this reason, the examples that will be presented over the following pages will be extrapolated from these various disciplinary traditions, with their abundant mix of approaches and fields of research.

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2022 G. Gobo, V. Marcheselli, Science, Technology and Society, https://doi.org/10.1007/978-3-031-08306-8_6

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6.1 The Problem of Demarcation In every era it is possible to identify a certain number of forms of knowledge— religion, law, art, ideology and so on—that provide an interpretive framework to make sense of the world. As we already saw in Chaps. 3, 4 and 5, many thinkers, from Francis Bacon to Karl Popper, have wondered what are the features (or set of features) that set science apart from other forms of knowledge. The special role that is often assigned to science dates back, in the Western world, to the so-called period of the Enlightenment, when natural philosophy (the forerunner of what we now call “science”—see Box 6.1) was progressively imbued with an authority that exceeds that of any other cosmological system. It was at the height of this period that science became (and still is) the true protagonist of the narrations on the nature of the world. The problem of what—and above all if something—makes science different from other forms of knowledge has therefore become more pressing. The existing answers to this question fall into two large categories: • Essentialist approaches argue that science possesses certain features that make it a special form of knowledge and that clearly set it apart from any other knowledge systems. • Constructivist approaches, on the contrary, tend towards the idea that there are no universal and unique characteristics that (at any time) set science apart. According to this perspective, the authority of science is a rhetorical conquest based, depending on the era and context, on principles that might differ significantly from each other.

6.1.1 Essentialist Approaches: Falsificationism, Institutionalised Ethos and Paradigmatic Consensus The essentialist hypotheses, according to which a main characteristic of science exists and can be clearly defined, have been articulated in numerous variants. Following Thomas Gieryn (1995), we will examine three of them, formulated respectively by Popper (see Sect. 3.2 and in particular Sect. 3.2.5), Merton (see Sect. 5.1) and finally Kuhn (see Sect. 4.3). According to these three authors— despite the diversity of their positions—there are certain criteria that make it possible to distinguish, even retrospectively, what is properly scientific from what cannot be defined as such.

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Popper (1963) addressed this theme while examining the problem of induction. He argued that falsificationism could not only provide a valid alternative to verificationism but could also perform another fundamental role: that of drawing a boundary line between science and non-science. Merton (1973), instead, saw in the institutionalised ethos of science—in other words, the set of prescriptions that would guide the actions of each scientist—an alternative to Popperian falsificationism. According to Merton, it is the adhesion to the principles of universalism, communism, disinterestedness and organised scepticism that distinguishes proper science from other “deviant” approaches to ­knowledge and knowledge-making. The emblematic example of deviant science, according to Merton, was that practised by the Nazi regime, exercised in great secrecy and undoubtedly not for the good of humanity. As we have already seen in Sect. 5.1, the Mertonian position—ideological and normative—has been moved aside thanks to the many studies of history, sociology and anthropology of science that highlighted how the four Mertonian imperatives did not in fact guide the behaviour of scientists. Instead, in the everyday playing out, each principle is subjected to social interpretations and negotiations, and thus cannot be adopted as a parameter to define what counts as properly scientific and what is not. Kuhn marked, somehow, a watershed. Constructivists and relativists resumed the legacy of his book The structure of scientific revolutions, but Kuhn always distanced himself from both theoretical orientations. The solution to the boundary problem that he proposed was deeply essentialist as he identified in the incommensurability of paradigms (Kuhn, 1962; Sankey, 2017) a precise criterion to distinguish between science and non-science (Gieryn, 1995). According to Kuhn, within the disciplines that he does not consider as properly scientific (such as philosophy and sociology) a multitude of different and sometimes irreconcilable methods, concepts, theories and research questions can coexist. Instead in science, especially during the period of normal science, much of the community of scientists adheres to the same paradigm: in other words, they agree on the same basic principles and share the same interests, practices, instruments and so on. During a period of normal science, turning one’s back on the dominant paradigm means repudiating science itself. This paradigmatic consensus is thus the criterion that most effectively confirms the status of a discipline as not only mature, but also properly scientific. The three essentialist hypotheses just outlined do not merely propose a characterisation of science, but implicitly present a normative approach; in other words, they seek to define how science should be. The norms and the criteria that each of

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them identifies are used not only to certify the specificity of science, but also to explain what makes it superior to other forms of knowledge.

6.1.2 The Constructivist Hypothesis and Boundary Work The beginning of the 1970s witnessed the emergence of a growing interest in scientists’ everyday life and ordinary activities. It was in this context that the essentialist hypotheses proved to be increasingly problematic. On the one hand, it became clear that some of the characteristics proposed as typical of science might actually also be attributable to other activities considered non-scientific; on the other, it did not even seem possible to attribute these characteristics to science itself, when closely observed. The criteria proposed by the essentialist approaches, therefore, turned out to be inadequate. Thanks to these early sociological studies, not only the essentialist approaches to the demarcation problem were called into question, but the issue of demarcation itself began to appear almost paradoxical: if, from a theoretical perspective, the search for the definition of a criterion of demarcation between science and non-­ science had not been successful, from the opposite practical point of view the many social actors constantly resolve this problem, often without any confusion at all. In other words, in most cases—while not having an explicit and shared definition of what science is and what it is not—social actors juggle practical matters— such as the preparation of academic programmes or the provision of research funds—easily (Gieryn, 1983). This phenomenon is emblematic and invites us to a reversal of perspective. In the words of the British sociologist Barry Barnes (1974, p. 100), we should not seek to define science ourselves; we must seek to discover it as a segment of culture already defined by actors themselves […] It may be of real sociological interest to know how actors conceive the boundary between science and the rest of culture, since they may treat inside and outside very differently.

According to Barnes, the absence of a singular, universal and timeless criterion that sets science apart from the other types of knowledge does not mean that this distinction, in fact, is not somehow achieved or that it has no value. Instead, it has “great sociological interest” (ibid.) as, for those who are involved in scientific research as well as for the common citizen, how and where the boundary between science and non-science is defined has a whole series of social and economic con-

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sequences, such as the recognition of a profession, a certain authority in decision-­ making processes, to name but a few. It was the US sociologist Thomas Gieryn that reformulated the demarcation problem in social and pragmatic—instead of theoretical and abstract, as was previously the case—terms. According to Gieryn, what counts as legitimately scientific and what, instead, cannot be considered as such could not be determined beforehand as the boundary between science and non-science is the result of a continuous and challenging process of negotiation. Gieryn calls this process boundary work, or the process of “attribution of selected characteristics to the institution of science (i.e. to its practitioners, methods, stock of knowledge, values and work organization) for purposes of constructing a social boundary that distinguishes some intellectual activities as non-science” (Gieryn, 1983, p. 782). According to Gieryn, therefore, the problem does not concern what scientists do, whether in the laboratory or at their own desks. What matters is the narration of these activities that is produced when (even implicitly) the question “what is science?” is posed. There is no one answer to this question: instead, answers are articulated differently in different historical circumstances and discursive contexts. To appreciate what characteristics have been attributed to science as an institution over time, therefore, the sociological analysis should focus, on a case by case basis, on the responses formulated in each particular situation. There is a wide range of characteristics that can be attributed to science to describe its (supposed) uniqueness, depending on which intellectual or professional activity science is opposed to: for example, when science is contrasted with religion, it is often described as empirical and applied; instead, anyone who seeks to pronounce the superiority of science over engineering describes science as abstract and its activities as basic and pure, in other words not primarily aimed at an applicative purpose. When it is contrasted with art, its rigour is commended while when it is juxtaposed with mechanics, emphasis is placed on the creativity required in scientific research. But then, one might wonder whether science is abstract or empirical, applied or pure, certain or sceptical, useful or disinterested, precise or imprecise, deductive or inductive, systematic or the result of random discoveries, is it rigorous or creative? Gieryn would answer that science can be described in all these ways, depending on the circumstances. These characteristics in fact are flaunted from time to time depending on the various fields that science is juxtaposed to: pseudo-science, amateur science, ideology, popular science, politics, technology, management, religion, philosophy, art, crafts or social sciences, to name but a few. Science, therefore, does not enjoy a uniform character: the characteristics that are attributed to it are heterogeneous and, at times, contradictory, because there are many activities to which it is compared or contrasted (depending on the circumstances) in this continuous battle for intellectual authority.

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Gieryn (1995) illustrates the concept of boundary work by means of a cartographic metaphor1: just as national boundaries are decided (or imposed) after a negotiation between countries, so too the boundary that distinguishes science from other intellectual enterprises is the outcome of the negotiations between social actors. Furthermore, the boundary between science and non-science is maintained and reinforced thanks to the continuous recognition of its existence. The range of action of science is therefore not inscribed in nature just as geographical boundaries are not: even when they follow rivers or mountain ranges, they are never simply a geological issue, but a political one. In the same way, sociologists of science, according to Gieryn, need to be aware that the problem of demarcation does not find a solution in the methodology or logic of science and not even in its object of study, but in the very way in which science is described by the social actors. The distinction between science and non-science is a boundary that is drawn and maintained through a constant and endless work of negotiation, guided by the need to claim, expand, protect, monopolise, usurp, deny or restrict the cognitive authority of science. Boundary work is in fact nothing else but a battle for the intellectual authority that the “science” label, today, guarantees, as well as the derived credibility, prestige, power and material resources. What during one particular historical period is considered alien to scientific investigation can subsequently be integrated and become the beating heart of research and innovation (think for example of search for life on Mars, which in the space of seventy years has been considered, intermittently, science or science-fiction—see Box 4.4) or, conversely, studies deemed legitimately scientific in one time can be delegitimised and excluded from the boundaries of science later on (as in the case of phrenology, a popular discipline at the end of the nineteenth century and today completely delegitimised; the same also applies to astrology and alchemy). These boundaries, however, do not have to be redrawn every time because, as cartographers continuously produce new maps from existing ones, so boundary work activities can strategically draw on episodes of the past to legitimise the validity of a new representation of science. Obviously this in no way means that the boundaries of science “do not exist”, just as it would be absurd to argue that the boundaries of countries, being social constructions, do not exist. And yet, they are not “natural”. As institutions, they exist as long as they are accepted by most social actors. Once constructed and legitimated, they become real since the consequences for those who end up (often against their will) on one side or the other of the boundary are enormous.

 The map-mapping metaphor used by Gieryn (1995) was taken from Shapin and Schaffer (1985). 1

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Box 6.1  When Did Science Begin?

According to Popper (1972), science arises in the context of ancient Greek philosophical thought, when thinkers such as Plato and Aristotle placed a difference between episteme (knowledge based on logic, that searches for causes and that is self-founding—linguistically epistêmê comes from epi + istemi and means “standing alone”) and doxa (beliefs, which can be dogmatic since they are based on authority or opinions, whether true, false, credible or not). However, the approach to nature of these classical philosophers was still very far from the so-­called scientific method—experimental and quantitative—which was systematised only between the sixteenth and seventeenth centuries and which, according to some definitions, would give rise to science as we today ­understand it. In fact, according to some historians, the merit of this change should be attributed to a few illustrious figures such as Francis Bacon or Galileo Galilei (see Whitehead, 1920). This hypothesis, however, stems from an essentialist assumption, which holds that constitutive characteristics of science as a category of thought can be identified and remain unchanged over time. As we have seen in this chapter, however, science does not have fixed and immutable characteristics but, as an institution, it coincides with the community that reproduces its norms and in so doing brings it into being. Other scholars have tried to trace the genealogy of the terms “science” and “scientist”. Until the seventeenth century, the word scientia (which Aristotle referred to as epistêmê) simply meant knowledge. The study of nature instead fell under the expression “natural philosophy”. Natural philosophy included all those fields of research that we now call geology, astronomy, chemistry, optics, biology and botany but also philosophy and theology. Unlike modern science, natural philosophy was not based on experimentation, but on speculation and tradition. Anyone who investigated nature commonly identified themselves with the expression “natural philosopher” or, more rarely, “man” of science (in the past, the speculations on the world were mostly precluded to women). An example is Isaac Newton (1642–1726/7), considered by some as the figure through whom scientific revolution reached its culmination: he in fact titled his most famous work Philosophiæ Naturalis Principia Mathematica (1687). Even if these aspects of his work are today seldom mentioned, Newton not only laid the foundations of physics but also wrote extensively on theology, occultism and above all alchemy. The first instance of the word “scientist” in fact dates back to 1834 by William Whewell but its widespread use was not immediate.

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Lord Kelvin (1824–1907), more than three decades later, in 1867, still titled his work Treatise on Natural Philosophy. Today, however, there is a tendency to privilege the study of science as a set of practices (not of ideas!), and to rethink, therefore, the historical reconstruction that sees in the activities of Greek philosophers, so far removed from contemporary scientific practices, the foundations of scientific thinking (Bowler & Rhys, 2005). It is precisely here that the principle of boundary work comes to our assistance: we could say that science, as an institution, emerges when it begins to be recognised as a separate, distinct field and when scientists begin to identify themselves as such and then claim authority starting from the category of science. The institution of modern science goes hand in hand with the establishment of a certain organisation of institutions, practices and instruments. Based on this different stance on what science is, its beginnings might be traced back to the time of the Enlightenment, when the scientific method was systematised and science was institutionalised in organisations such as the Royal Society of London, l’Academie des Sciences of Paris or the Accademia dei Lincei in Italy. Attention, however: the principle of boundary work reminds us that the boundary between what is scientific and what is not changes over time because science is not a static and unchanging entity, but a system of practices located in its own social and cultural context. It is therefore wise not to attribute anachronistic characteristics to science but to remember its heterogeneous, multiple and composite development. To the question “when did science begin?” we should instead rephrase the question as “how do the knowledge-making practices that we today call science change?” The latter question in fact invites us to critically rethink continuity and change without resorting to easy simplifications. ◄ Like any social construct, the boundaries of science cannot be determined abstractly or a priori; as such, understanding how social actors are engaged in boundary work is an empirical problem, something to be discovered in the field through the study of specific cases of contention on what science is. The response given by social actors will be articulated differently each time. Box 6.2  Boundary Objects

The boundary between science and non-science, or between one discipline and another, is maintained through what we have defined as boundary work. At times these boundaries are contested and one of the opposing factions manages

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to turn the situation to their own advantage to the detriment of the other. At other times, these boundaries are not disputed, and all the social groups involved contribute to maintaining their own perimeter of action. And yet, even in this latter case, these boundaries do not make the communities impermeable or isolated from each other. In a famous essay, Susan Leigh Star and James R. Griesemer describe this process, taking as an example the coordinated efforts of naturalists and amateurs for the development of the Museum of Vertebrate Zoology in Berkeley, California. Despite having various skills and different purposes, these social actors manage to collaborate effectively thanks to the standardisation of samples, field notes, maps and so on, which Star and Griesmer call boundary objects. The various social groups in fact use the same standardised objects but with different purposes. In this way the work carried out by each of them is successfully integrated into a singular process while maintaining for each a different meaning and a different value (e.g. what appears to naturalists as a collection of data, for amateur collectionists is instead a pleasant stroll through nature). Boundary objects are objects which are both plastic enough to adapt to local needs and constraints of the several parties employing them, yet robust enough to maintain a common identity across sites. They are weakly structured in common use and become strongly structured in individual-site use. They may be abstract or concrete. They have different meanings in different social worlds but their structure is common enough to more than one world to make them recognizable, a means of translation. The creation and management of boundary objects is key in developing and maintaining coherence across intersecting social worlds. (p.393)

Science and technology are not the exclusive domains of scientists and engineers but in many ways and on many occasions they interface with other social groups. Boundary objects are objects (or concepts) specific enough to be always recognisable, but at the same time characterised by a flexibility that makes them usable in different fields. The study of these objects and concepts allows us to understand how scientific practice crosses the boundaries of the scientific community, making its boundaries permeable without, however, questioning its robustness. ◄

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6.2 Drawing and Redrawing the Boundaries of the Scientific Community Considering science as an institution with boundaries in continuous flux may perhaps seem completely counterintuitive and even risky. Since the time of the Enlightenment, science has proposed itself as objective knowledge, detached from socio-cultural conditioning, and it is precisely this aura of stability and universalism that makes science the privileged form of knowledge, at least in the Western world (Shapin & Schaffer, 1985). However, in Sect. 6.1, we saw that the characteristics that make science a “unique” knowledge are actually anything but unique. It might therefore be useful for us to challenge our perspective for a moment and turn our gaze to science at the end of the seventeenth century, a period in which it established itself as based on the experimental method.

6.2.1 The Royal Society at the Start of the Seventeenth Century and the Problem of Testimony In his famous article The House of Experiment in Seventeenth Century England, the American historian of science Steven Shapin examined the organisation of the then nascent British Royal Society, perhaps the most famous of the scientific societies established in the seventeenth century. The Royal Society, as the expression itself suggests, promoted the sharing of discoveries and observations with all members of the association, and discouraged experimentation conducted in solitude, which could be influenced by biases, prejudices or even the desire for personal gain. However, for practical reasons (such as the capacity of the venues where experimental activities would take place) only a few members of the society were able to take part in the experiments and an even smaller number of persons were able to travel to the remote places where naturalistic observations were made. The problem that the Royal Society encountered, which Shapin (1988) called the “problem of testimony”, was anything but abstract: how would it be possible to guarantee the credibility of experiments conducted in the presence of only few witnesses before the other members of the community? How would it be possible to validate observations and measurements to guarantee the transition from individual claim to collective knowledge? And, above all, who might be considered reliable and trustworthy? Shapin reports that a fair number of people took part in the Society’s scientific events: apart from the public, technicians, assistants and domestic staff also

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attended. And yet, only the gentlemen who were members of the Royal Society, according to the ethos of the time, were afforded the maximum credibility. Since they took part in these scientific endeavours without being remunerated, they were believed to be more honest in their judgement. Conversely, the technicians and assistants that handled the instruments, while essential for the conduct of the experiments, enjoyed no credibility as they were paid to perform their duties. To ensure a privileged access for the other members of the Royal Society, most demonstrations took place in the private mansions of the London aristocracy. These—while adapting, at least in part, to the new situations of use—offered already familiar and recognised codes of conduct which could be borrowed from the nascent experimental science. These residencies, in fact, boasted spaces for public receptions and the etiquette of the time required that gentlemen extended a generous hospitality towards members of the same social class. This etiquette (familiar to everyone at the time, without needing to be explicit) provided a cultural and conduct-based model to regulate access to the new experimental activities. The houses of the aristocracy were open to the members of the same social class, who therefore become the privileged public attending the experiments and offering their own testimony. Shapin shows that the physical environment and the associated social norms determined the contours and the rules of this emerging community of practitioners. The recognition of the social specificity of the context in which the demonstrations were performed created both limits that could not be passed and thresholds to be crossed. It was precisely the social organisation of the nascent institution that offered effective strategies and practical responses to this empirical need. The distribution of the credibility necessary to guarantee the reliability of the testimony followed the values of the English society of the time. Even during the Enlightenment—an era famous for having set out the ideal of an experimental practice guided only by reason, detached from time and from local specificities— science was in essence an activity that was in strong continuity with its socio-­ cultural context (Shapin, 1988; see Shapin & Schaffer, 1985).

6.2.2 Modern Times This historical example now allows us to observe contemporary science with fresh eyes and to ask ourselves: through which social and cultural mechanisms is science today imbued with the authority that characterises it? And under what conditions? The problem of testimony has certainly not disappeared: the scientific knowledge shared by many is in fact often formulated and evaluated by means of experiments

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carried out by only a few. What guarantees the credibility of these few individuals? The question that the first members of the Royal Society asked themselves is no less important today, even if today’s practices are oriented towards radically different solutions. First, today, unlike in the seventeenth century, scientific activities take place in purpose-built environments, specifically intended for experimentation and measurement; usually they are based in university departments and in industrial settings (e.g. pharmaceutical, IT companies, etc.), in dedicated research and development departments. The mixing of residential places and spaces dedicated to scientific practice, very common in the seventeenth century, would today be viewed at least with a degree of suspicion, if not disdain. Furthermore, inside laboratories (from large-scale facilities, such as particle accelerators, to small university laboratories), access is strictly regulated: with just a few exceptions, only those persons who actually work for that institution or who are trained within the institution itself (students, doctoral students and trainees) have access to it.2 Today, the hunt for research funds takes up a significant amount of time for any principal investigator and his staff. If in late seventeenth century England only those who self-funded their own experiments and were not paid enjoyed credibility, today instead, it can be stated with some certainty that quite the opposite is the case: a researcher who could not obtain funds and did not enjoy an affiliation with an institution would be considered an amateur, not a scientist. In fact, anyone who calls themselves an “independent researcher” (essentially someone who conducts research completely autonomously, without depending on academic institutes) is often looked upon with suspicion. Finally, once out of the laboratory, the data collected during the experiments are not handed down following chains of friendships, acquaintances and personal collaborations, but disseminated through well-coded literary genres, such as scientific publications (e.g. specialist journals whose credibility is guaranteed by the peer review process, Berkenkotter, 1995), conferences and reports. These organisational modes are some of the contemporary answers to the problem of testimony. Instead of basing credibility on wealth, as was normally the case in the late seventeenth century, scientists today acquire credibility through various other criteria and devices: academic qualifications, state exams, curricula, work-

 As we shall see in Chap. 7 (in particular in Sect. 7.3), the walls of laboratories and experimental spaces do not limit access solely to staff but also to nature itself. Within the laboratory, in fact, the chaotic and disordered pace of nature is filtered, so that only certain phenomena are actually allowed inside (Knorr-Cetina, 1995). 2

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wear and so on, that allow access to otherwise forbidden places and give those who possess them the credibility once only reserved for gentlemen. The parallel between two different moments in the history of science (the dawn of experimental science and the contemporary situation) highlights an important aspect that too often risks being overlooked: what today seems “normal” and “obvious” is only due to the fact that we live immersed in a context that presents them as such. Authority is a “licence” attributed by the community through conventions that have their roots in contiguity with the social context. It is precisely for this reason that the type of social organisation that guarantees authority to science today is neither better (in an absolute sense) than in the past nor stable over time.

6.3 Science Situated: From the “View from Nowhere” to “Truth-Spots” In the sociology of science, the interest in the epistemological importance of places to which scientific activities are ascribed is divided into various phases (Henke & Gieryn, 2008). Initially, positivists and rationalists thought that science was detached from the local geographical and cultural context as it was reaching towards an abstract and universal truth. According to this perspective the scientific method, thanks to rationality and logic, allowed science to realise what Thomas Nagel (1986) called “the view from nowhere”. His concern was how the individual scientists could distance himself from his personal perspective to embrace an objective vision of the world, in other words not dependent on historical and local circumstances. Since the start of the nineteenth century, we have instead witnessed the emergence of a whole series of historical case studies on the social and material conditions that characterise the places of science and, above all, on the change in the conditions of knowledge production over the course of history: the rooms in which the members of the Royal Society operated (Shapin, 1988); the agorá of Athens into which only adult and free men were invited to take part in the search for truth through public debate (Sennett, 1994); the cloisters of the medieval monasteries (Noble, 1992); renaissance study, in which solitude and contemplation were considered the necessary conditions to nurture the intellect (Ophir, 1991) and so on. These examples, and many more besides, express the shift in the conception of which places were best suited for the creation of legitimate knowledge. The spaces used for research, teaching, professional practice and experimentation are then studied from the point of view of the sociology of organisations as places that reflect the social configuration of science. Buildings, in fact, provide a

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“materialisation of the architecture of knowledge” (Galison, 1997, p. 785; Galison & Thompson, 1999): they are not merely empty spaces dedicated to certain activities rather than others, but “they convert the abstraction of ‘discipline’ into something more palpable, stable, and enduring” (Gieryn, 2002a, 2002b, p.  46). In a certain sense, “they discipline” the behaviour of who is present inside, offering possibilities and limits of action.

6.3.1 The Hospital and the Segmented Human Body Think, for example, of the spatial organisation of a hospital: the first thing that we will notice is the division of the building that reflects the division of the human body into apparatuses—the departments of cardiology, neurology and pneumology correspond, respectively, to the cardiac and circulatory apparatus, to the nervous system and to the respiratory apparatus. These units are, however, not simply separated from each other; they are organised spatially in such a way as to create privileged paths from some departments to others, spaces that can more easily be reached by the public (such as clinics for specialist appointments) and spaces more remote and more difficult to access (such as operating theatres). All these elements reflect in many ways the dominant conceptions of knowledge and of the practices of Western medicine, which is specialised, reductionist, non-holistic: the human body is segmented and distributed into various departments. The structure of the hospital also envisages a certain type of relationship between medicine and other spheres of social action. The possibility of including refreshment points near the hospital, for example, is evidence of the implicit recognition of the presence of family members and friends at the bedside of hospitalised patients. By observing the history of a building, we would therefore be able to reconstruct the intentions of the builders and which conceptions they translated into the “language” of bricks and concrete (see Box 6.3). However, if it is true that the type of building is both a resource and a limit to action, on the other it is also in continuous flux, undergoing never-ending changes and reinterpretations by social actors. According to Gieryn: Buildings stabilize social life. They give structure to social institutions, durability to social networks, persistence to behaviour patterns. What we build solidifies society against time and its incessant forces for change […] and yet, buildings stabilize imperfectly. Some fall into ruin, others are destroyed naturally or by human hand, and most are unendingly renovated into something they were not originally. Buildings don’t just sit there imposing themselves. They are forever objects of reinterpretation, narration and representation—and meaning or stories are sometimes more pliable

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than the walls they depict. We deconstruct buildings materially and semiotically, all the time. (Gieryn, 2002a, p. 35)

Buildings are therefore able to shape the activities that take place within their walls but at the same time they are reimagined and rethought precisely in light of these activities, in a continuous process of mutual construction. As in Giddens theory (1984): micro-events (action) and macro-phenomena (structure) mutually interact, creating society. Box 6.3  Physical Spaces and Conceptions of Science

In one of the very first studies on the places of science, the Scottish historian Owen Hannaway (1986) compared two sixteenth century constructions: Uraniborg, the castle built on the island of Hven by the Danish astronomer, astrologist and nobleman Tycho Brahe and the ideal house according to Andreas Libavius, German physician and chemist. The Uraniborg project was designed by Tycho Brahe himself when the king of Denmark granted him the concession of the small island of Hven to build an observatory. The facilities were designed to accommodate the astronomical instruments on the top floor and the forges and tools for alchemical practice in the basement. According to Tycho Brahe, astronomy and alchemy were two symmetrical and complementary systems of knowledge, and this concept was symbolically reflected in the very structure of the building he designed. In the precise description of the spaces of Uraniborg, only a few words are spent on the description of the private rooms and on those dedicated to servants and students. Tycho Brahe moved to the island of Hven in 1577 and remained there for 20 years. For the Danish astronomer, Uraniborg represented the possibility of living in isolation, away from the distractions of everyday life and political responsibilities to devote himself to contemplation and to the study of nature. When Tycho left the island of Hven, he set out in search of a new patron; for this purpose, he produced and distributed among the European aristocracy a text in which he described in detail not only his work, but also the castle-observatory he had built. It is precisely with this text that Libavius entered into dialogue—or perhaps it would be better to say into open controversy. According to Libavius, the practice of science should not be removed from social life; quite the opposite, the ideal dwelling for anyone seeking to devote themselves to the study of natural phenomena had to be at the centre of city life and should draw attention, both symbolically and physically, to the scientific activities taking place in it. Libavius in fact located the laboratories not in the basement, like Tycho, but on the ground floor, with large windows that offered

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good lighting and allowed outsiders to glance at what was taking place inside the laboratory. The spaces dedicated to chemistry, in Libavius’ house, were immediately adjacent to the rooms dedicated to public and private life, separated only by a wall and a door, symbol of a limit to be crossed as many times as possible. The practice of science in fact had to be accompanied by a life as a present pater familiae, as a responsible citizen and as a good friend. Andreas Libavius juxtaposed not only two buildings but the entire ideological and intellectual foundation of the practice of science, still emerging at that time. According to Hannaway, the laboratory, a place too often idealised and described with fixed characteristics, cannot in fact be identified solely with either an active practice (as in the case of Libavius) or with a contemplative one (so loved by Tycho Brahe). However, the material managerial and organisational aspect of the laboratory and its context can occasionally help us to understand how the scientific activity that takes place within it is positioned with respect to the rest of the social context. ◄

6.3.2 The Laboratory Special attention in these studies is dedicated to the laboratory, the archetypal place of contemporary science. Its standardised design allows scientific narrative to disregard its specificities which, in a certain sense, are removed from the narrative itself. Where is a laboratory located? What is its history? Who inhabits it? All these elements are expelled by scientific articles and by the presentations that scientists make of their own work—and this is only by virtue of the fact that their work takes place in one of these very special sites. If this were not the case, it would be difficult (perhaps impossible), for a scientist, to present his/her conclusions as “valid everywhere”. Gieryn (2002b) calls this phenomenon “the paradox of place and truth”: some places, which Gieryn calls “truth-spots”, produce a situation whereby the knowledge that is produced therein becomes placeless, in other words detached from any specific place and therefore purportedly “universal”. All scientific knowledge-claims have a provenance: they originate at some place and come from there. However, as they become truth, these claims shed the contingent circumstances of their making, and so become transcendent (presumably true everywhere, supposedly from nowhere in particular). Turning the argument around: scientific claims are diminished in their credibility as they are situated somewhere, as if their truthfulness depended upon conditions located only there. That is only half of the paradox. Not only do all putatively universal claims of science necessarily have a particular place of origin, but the place of provenance itself enables the transit of some claims from merely local knowledge to truth believed by many all around. The

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passage from place-saturated contingent claims to place-less transcendent truths is achieved through the geographic, architectural and theoretical construction of a “truth-spot” (i.e. the place of provenance). Place allows claims to escape place, to transcend its suffocating particulars; place achieve placelessness. (ibid., p. 113)

But what really happens inside laboratories? To find it out, sociologists of science must integrate the reports provided by scientists on their activities with the direct observation of the same everyday, mundane and routine activities. Thus, thanks to the sociological and anthropological studies of laboratories and laboratory activities, to the ethnographic observation of research practices and to a feminist literature ever closer to the world of technology (which we will discuss more fully in Sects. 7.3 and 10.4), reflections emerge which go beyond the institutional and organisational aspects of research activities and highlight how epistemological regimes are nothing other than the product of material and situated conditions. Two Exercises

Exercise 1, in class All these images (Figs. 6.1, 6.2, 6.3, 6.4, 6.5 and 6.6) convey different ideals of science and of knowledge: the importance given to the setting, the centrality of the scientist, the presence of a community, the style adopted and the purpose for which these works were created. In small groups, discuss these elements. Then find out a more modern representation of science and scientific activities (it can be a work of art, an image taken from an advert, a figure from an academic textbook, etc.). Where is it set? Finally, discuss what value these places have for the activities that take place within it. Exercise 2

Some contemporary disciplines are very recent and only came into being a few centuries ago—some are only decades old. Other disciplines, on the other hand, are very ancient. Even the oldest disciplines, however, are constantly changing institutions; the unfolding of new disciplines is not just a matter of knowledge “accumulation”, but it is about actually redefining old boundaries. In small groups, try to explore, for example, the history of medicine (also through the many resources that you can find online) and to compile a table with as many details as possible on the differences and similarities between contemporary medicine and that of the past. Do not ask yourselves what was/is properly “scientific” by today’s standards but focus instead on what was/is considered intellectually legitimate in the various eras and in the present.

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Fig. 6.1  The School of Athens by Raffaello

In particular, bear in mind three questions: 1. What are the basic characteristics of the figure of the doctor (are there any other names to indicate those who practice medicine)? 2. What are the fundamental problems of medicine? 3. What is the dominant approach to health and disease? Then discuss the tables you made in class.

Further Readings On boundary work • Gieryn (1983) • Ramírez-I-Ollé (2015)

Fig. 6.2  Philosopher in Meditation by Rembrandt

Fig. 6.3  The Anatomy Lesson of Dr. Nicolaes Tulp by Rembrandt—1632

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Fig. 6.4  The Anatomical Theatre of Padua 1584

Fig. 6.5  An Experiment on a Bird in the Air Pump by Joseph Wright of Derby

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Fig. 6.6  A photograph of Albert Einstein

On places of science • Gieryn (2018) • Kohler (2002) • Livingstone (2010) • Mol and Law (1994) Check Your Preparation

1. What is the “problem of demarcation”? In general, what do the essentialist answers tell us? 2. What is boundary work? 3. What does the “problem of testimony” consist of? 4. What guarantees credibility and authority to science today? And in the past? 5. What is meant by “truth-spot?

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References Barnes, B. (1974). Scientific Knowledge and Sociological Theory. Routledge. Berkenkotter, C. (1995). The Power and the Perils of Peer Review. Rhetoric Review, 13(2), 245–248. https://doi.org/10.1080/07350199509359186 Bowler, P. J., & Rhys, M. I. (2005). Making Modern Science. A Historical Survey. University of Chicago Press. Galison, P. (1997). Image and Logic. A Material Culture of Microphysics. University of Chicago Press. Galison, P., & Thompson, E. (1999). The Architecture of Science. The MIT Press. Giddens, A. (1984). The Constitution of Society: Outline of the Theory of Structuration. University of California Press. Gieryn, T. F. (1983). Boundary-Work and the Demarcation of Science from Non-Science: Strains and Interests in Professional Ideologies of Scientists. American Sociological Review, 48(6), 781. https://doi.org/10.2307/2095325 Gieryn, T. F. (1995). Boundaries of Science. In S. Jasanoff et al. (Eds.), Handbook of Science and Technology Studies (pp. 393–443). Sage Publications. Gieryn, T. F. (2002a). What Buildings Do. Theory and Society, 31(1), 35–74. https://doi.org /10.1023/A:1014404201290 Gieryn, T. F. (2002b). Three Truth-Spots. Journal of the History of Behavioural Sciences, 38, 113–132. https://doi.org/10.1002/jhbs.10036 Gieryn, T. F. (2018). Truth-Spots: How Places Make People Believe. University of Chicago Press. Hannaway, O. (1986). Laboratory Design and the Aim of Science: Andreas Libavius versus Tycho Brahe. Isis, 77(4), 584–610. Henke, C. R., & Gieryn, T. F. (2008). Sites of Scientific Practice: The Enduring Importance of Place. In E. J. Hackett et al. (Eds.), The Handbook of Science and Technology Studies (pp. 353–376). The MIT Press. Knorr-Cetina, K.  D. (1995). Laboratory Studies: The Cultural Approach to the Study of Science. In S.  Jasanoff et  al. (Eds.), Handbook of Science and Technology Studies (Revised ed., pp. 140–166). Sage Publications. Kohler, R. E. (2002). Landscapes and Labscapes. Exploring the Lab-Field Border in Biology. University of Chicago Press. Kuhn, T. (1962). The Structure of Scientific Revolutions. University of Chicago Press. Livingstone, D. N. (2010). Putting Science in Its Place: Geographies of Scientific Knowledge. University of Chicago Press. Merton, R. K. (1973). The Sociology of Science. Theoretical and Empirical Investigations. University of Chicago Press. Mol, A., & Law, J. (1994). Regions, Networks and Fluids: Anaemia and Social Typology. Social Studies of Science, 24, 641–671. https://doi.org/10.1177/030631279402400402 Nagel, T. (1986). The View from Nowhere. Oxford University Press. Noble, A. A. (1992). A World without Women: The Christian Clerical Culture of Western Science. Alfred A. Knopf. Ophir, A. (1991). A Place of Knowledge Re-Created: The Library of Michel de Montaigne. Science in Context, 4, 163–189. https://doi.org/10.1017/S0269889700000193 Popper, K. (1963). Conjectures and Refutations. Routledge and Kegan Paul.

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Popper, K. (1972). Objective Knowledge: An Evolutionary Approach. Oxford University Press. Ramírez-I-Ollé, M. (2015). Rhetorical Strategies for Scientific Authority: A Boundary-Work Analysis of “Climategate”. Science as Culture, 24(4), 384–411. https://doi.org/10.1080/ 09505431.2015.1041902 Sankey, H. (2017). Kuhn’s Changing Concept of Incommensurability. The British Journal for the Philosophy of Science, 44(4), 759–774. https://doi.org/10.1093/bjps/44.4.759 Sennett, R. (1994). Flesh and Stone: The Body and the City in Western Civilization. Faber & Faber. Shapin, S., & Schaffer, S. (1985). Leviathan and the Air-Pump: Hobbes, Boyle, and the Experimental Life. Princeton University Press. Shaping, S. (1988). The House of Experiment in Seventeenth-Century England. Isis, 79(3), 373–404. Whitehead, A. N. (1920). The Concept of Nature. Cambridge University Press.

7

Science Behind the Scenes

In this chapter, we will delve into the heart of laboratory studies with the aim of problematising the central core of science, a bit like Bloor when he chose mathematics, traditionally considered the purest and most abstract kind of knowledge, as his area of investigation. Similarly, laboratory studies focus on the elements that are more often regarded as the quintessence of scientific practice—“experiments”, “facts” and “data”—to reveal their social and cultural character.

7.1 Experiments The word “experiment” comes from the Latin experiri or literally “come into cognition by perceiving with the senses” and describes a sequence of operations through which natural phenomena are reproduced or simulated. As seen in Sect. 6.2, the centrality of experiments in the scientific method usually dates back to the first half of the seventeenth century. Experimental systems are often presented as situations within which nature is revealed to scientists. Outside of the laboratory, in fact, nature appears chaotic, disordered and confused; experiments are thus means to order, purify and control the natural phenomena in which scientists are interested. With great technical effort, experimental systems recreate artificial versions of these same phenomena. In the seventeenth century, this artificiality of experiments was cause of debate and perplexity (Shapin & Schaffer, 1985). According to scholastic philosophy, natural philosophy (precursor of what we today call science, see Box 6.1) was supposed to study phenomena already observable in nature. It is no coincidence that the science considered most “noble” was astronomy, as the celestial cycles (the © The Author(s), under exclusive license to Springer Nature Switzerland AG 2022 G. Gobo, V. Marcheselli, Science, Technology and Society, https://doi.org/10.1007/978-3-031-08306-8_7

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motion of the Earth around the Sun, the orbits of the planets, the seasons, the tides) repeat regularly and without the observer being able to intervene in any way. Experiments, instead, were considered demonstrative aids, but their artificiality made it difficult to believe that they could reveal natural phenomena in any reliable, solid and meaningful way. How, despite this opposition, has experimental science ­replaced the observations of natural philosophers? It was the alleged repeatability of experiments that vindicated the status of universality: an experiment had in principle to be reproducible by anyone, anywhere in the world, with the same results. As we have seen extensively (in particular in Chap. 3), the neo-positivist philosophy of science has forgotten the history of experiments, idealising them and attributing to them a linear relationship with the theory. It is only with the entry of sociologists and anthropologists into the laboratories that the local and contextual character of experiments has been rediscovered.

7.1.1 The Experimenter’s Regress In the 1980s and 1990s, a whole series of new empirical studies placed experiments at the centre of sociological reflection, thus highlighting the work of a large number of social forces and the demanding negotiations between different groups of practitioners about how experiments had to be performed and interpreted. The author who perhaps more than any other devoted himself to this topic is the British sociologist Harry Collins, thanks to his privileged relationship with the community of gravitational wave physicists. Collins observed this community from the end of the 1960s, when the US physicist Joseph Weber created the first prototype of a detector of gravitational waves, a physical phenomenon whose existence had been predicted more than half a century earlier by Albert Einstein’s theory of relativity. In line with the field equation—the fundamental equation of general relativity—the sudden change of mass of a body would produce ripples in space-time. According to Einstein, these wave perturbations must have been extremely diffuse in the universe but at the same time very difficult to detect because they were extraordinarily weak. The instrument Weber built in the basement of his department of the University of Maryland consisted of aluminium cylinders 2 m long and 1 m in diameter; at the passage of a gravitational wave, these cylinders would have registered its transit thanks to a variation of 10−12 mm (in proportion, it is as if the distance from the Sun to the nearest star varied by the diameter of a human hair—so to speak!). Weber had dedicated years of his career to the construction of these detectors, spending

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months in the laboratory and learning about each and every aspect of them down to the last detail. In the early 1970s, Weber published his initial results and claimed that he had recorded a first high flow of gravitational waves. Weber’s publication was immediately greeted with much scepticism. The results in fact contained a fundamental contradiction: although the confirmation of the existence of gravitational waves was evidence in support of Einstein’s theory, the intensity of the waves that Weber had recorded was instead much higher than expected and suggested, again according to the theory of relativity, that the universe had an extremely short life and this was considered, by the physics community, very unlikely. Here the first dilemma arises: had the theory of relativity been rejected or confirmed by Weber’s observations? According to Weber, the theory of relativity had been confirmed but required some adjustments in order not to provide highly improbable predictions on the life of the universe. The detractors of the experiment, on the contrary, maintained that the intensity of the gravitational waves recorded was simply incompatible with relativity and therefore Weber’s observations must have been flawed. In the attempt to disprove Weber’s data, over a few years half a dozen research groups constructed detectors similar to those of the University of Maryland, with the aim of repeating and invalidating Weber’s experiment. And so it was: none of the new detectors reproduced the same results obtained by Weber. And here’s a second puzzle: hadn’t Weber’s critics, who had disproved his observations to rehabilitate relativity, contradict relativity itself by failing to detect gravitational waves? If scientists had followed Popperian falsificationism, they would have had to reject the theory of relativity, until then considered correct, as it was in disagreement with the measurement of the intensity of gravitational waves; but this did not happen.1 This tangled situation re-proposed a stance already formulated by the physicist and historian of science Pierre Duhem and then re-proposed by the philosopher Willard Quine—the so-called Duhem-Quine thesis (Harding, 1975; Quine, 1951). According to this thesis, a scientist Can never subject an isolated hypothesis to experimental test, but only a whole group of hypotheses; when the experiment is in disagreement with his predictions, what he learns is that at least one of the hypotheses constituting this group is unacceptable and ought to be modified; but the experiment does not designate which one should be changed. (Duhem, 1906, p. 55)

 The existence of gravitational waves was confirmed in 2015 and the Noble Prize was won by Kip Thorne, Barry Barish and Rainer Weiss. Weber died in 2000. 1

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Each theoretical model (e.g. Darwin’s theory of evolution or Einstein’s theory of relativity) encapsulates a large number of hypotheses in mutual relationship; no experimental falsification of the model indicates which of the many hypotheses is incorrect. Similarly, in the case of gravitational waves, we can clearly see a problem linked to the non-decisive and non-self-standing character of the empirical test: every experiment, both that of Weber and those of his colleagues who set out to reproduce or disavow his measurements, was based on a very broad series of more or less implicit premises and assumptions. If experiments were always and unequivocally received as confirmations or denials of a hypothesis (stemming from a theory), both Weber’s experiment and those of the other physicists would have called into question the theory of relativity: in the former case, for the incompatibility with the estimate of the age of the universe; in the latter, due to the absence of gravitational waves. Much of the community, instead, preferred to solely question the credibility of Weber’s experiment, discrediting the instrument and thus “saving” relativity. Collins calls this phenomenon “experimenter’s regress”: the repetition of an experiment with a different instrument serves as a test only if we can be sure of the reliability of the second detector, and not vice-versa. According to Collins and Pinch (1993, p. 98), an experiment constitutes a valid test for a theory if it is constructed in such a way as to produce a correct result. But how do we know if the result provided is actually correct? To obtain a correct result, one needs to use a reliable instrument. But again, how can we judge the reliability of an instrument if not from the correctness of the data provided? In fact, the repetition of the results of an experiment does not necessarily guarantee the validity of an experimental hypothesis since an unreliable instrument could simply repeat the error. If we measure the temperature with a broken thermometer, for example, the results might even be stable and reproducible, but this does not make them correct. The circularity of the reasoning seems to be, from a logical point of view, without escape. And yet scientists, sooner or later, manage to break this circle and reach a consensus. This type of conflict can therefore be resolved but not based on a presumed objective scientific logic. On the contrary, the achievement of some kind of transversal consensus within the community (even if almost never unanimous) can only have its roots in the multitude of social forces that come into play in a scientific controversy. Instead of drawing on formal criteria, each assertion is assessed in the light of a series of social criteria: the reputation of the scientists who formulated it, their experience in that precise field, the confidence in the instruments used to obtain evidence, the possibility of getting funds to pursue research in one particular direction rather than another, the potential usefulness of the discovery and so on.

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According to Collins, the experimenter’s regress affects every experiment. However, when a consensus already exists on what outcome to expect, the problem does not arise explicitly. On the contrary, when the subject of the study is new or controversial—and therefore there is no consensus on the nature of the phenomenon being measured, on the kind of results to be expected, or on which criterion to adopt to validate the observations made—then the experimenter’s regress becomes more explicit. It is important to emphasise that this constructivist position does not contrast epistemological criteria (in this case “traditional rational” logic) with social forces (such as reputation, writing style, cultural preconceptions, etc.): by analysing the negotiations that lead to the resolution of scientific disputes, it becomes clear that there is not actual distinction between them. In other words, what the community deems more “logical” is determined by social factors: the reputation of the individuals involved, by the effort that the scientific community has already invested into a theoretical position or into an experiment, by the rhetorical capacity of scientists to sway colleagues and public opinion towards their side and so on.

7.2 Facts, Black Boxes and Ships in Bottles As we have already seen in the first part of this chapter, the foundation on which experiments rest is their alleged replicability. Despite the local problems and the idiosyncrasies that scientists must always and inevitably deal with, experiments— because of their presumed replicability—are considered generalisable, valid everywhere and universal (see Gobo 2021). The experimenter’s regress, as we have already seen, questions this widespread assumption, undermining its very foundations. According to Collins and Pinch, however, the experimenter’s regress does not imply that no knowledge can be drawn from experiments. Quite the opposite! What the authors seek to highlight is that the problem of how knowledge comes about cannot be resolved simply by appealing to the logic of the scientific method. Collins describes knowledge as a ship in a bottle: the observer wonders how such a big artefact could have entered through an opening as tiny as the neck of a bottle, almost making us think that the ship had always been there. It is only by following its construction, step by step, that we are able to understand how it has been introduced and assembled within the bottle, piece by piece. The same is true, according to Collins, for knowledge: by following the process of its construction, we will be able to understand how it acquires that aura of inevitability that is attributed to scientific facts.

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Box 7.1 Facts, Artefacts and Factishes

In his famous On the Modern Cult of the Factish God, Bruno Latour narrates the landing of a group of Portuguese conquerors—covered in symbols of the Virgin Mary—on the coast of Guinea. The conquerors noticed that the local indigenous people idolised an object with shapes that they were unable to understand. Its appearance upset and angered the Portuguese, their stance being that “the object that the indigenous people worshipped was not a feito (in other words, a ‘fact’) but rather it was a fetiço (something like a ‘fact-let’, a ‘small fact’)”. Without seeing the contradiction (the Portuguese themselves actually prayed to the images of the Virgin Mary created by their craftsmen!), the conquistadores attacked the community of indigenous people to “punish” the heresy. Narrating this fact, the French philosopher Charles de Brosses coined a new word, clumsily translating the Portuguese expression: fètiche, or “fetish”. The indigenous people, according to both de Brosses and the Portuguese conquerors, worshipped their artefacts, considering them divinity. The word “fetish” would, over the coming centuries, become very popular thanks to the way it was used not only by anthropologists studying the indigenous population but also by intellectuals such as Karl Marx and Sigmund Freud. A fetish does not so much describe an object but the particular value attributed to it essentially because the very nature of the object is forgotten. Using this anecdote as a source of inspiration and reflection, Latour plays with the semantic ambiguity of the French word “fait” that refers to “what somebody has fabricated” (the “manufactured thing”) and “what nobody has fabricated” (the “autonomous fact)” (p. 18) and coins a new word faitiche, or “factish”. It is thanks to this neologism that Latour rethinks the epistemological matter of scientific facts: the factish makes knowable the weave of relationships between humans and non-humans, nature and culture that underpins every experimental practice. The factish is “the robust certainty that allows practices to pass into action without the practitioner ever believing in the difference between construction and reality, immanence and transcendence” (p. 22). Just as the indigenous people had produced the idols to then worship them as divinity for themselves, similarly scientists laboriously construct natural phenomena that they then consider as existing  independently from their work. Facts and factishes are opposites only in appearance. In reality they are the result of a similar process. The factish helps to reveal the work necessary to make the former objective and the latter subjective—the former linked to knowledge and the latter to the faith, the former to nature and the latter to religion to be able to go beyond these misleading dichotomies so typical of modern life. ◄

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Adopting a similar metaphor, Latour (1987) calls this process the closure of black boxes. The metaphor is borrowed by the world of computing; a black box is a system that, given a certain input, produces a predictable output. The term black box refers to the fact that, to use it, it is not necessary to know how it works and, in fact, its functioning is even precluded to the user. According to Latour, the same is the case for (scientific) facts and (technical) artefacts: their development is achieved through trial and error, discarded possibilities and a good dose of serendipity,2 and yet, after they achieve a certain success, the history of their troubled path becomes irrelevant. At this stage, the system becomes, metaphorically speaking, closed in a box into which one cannot (and, for convenience’s sake, does not want to) look. The black-boxing process is, therefore, the way scientific and technical work is made invisible by its own success. When a machine runs efficiently, when a matter of fact is settled, one need focus only on its inputs and outputs and not on its internal complexity. Thus, paradoxically, the more science and technology succeed, the more opaque and obscure they become. (Latour, 1999, p. 304)

Latour (1987) describes science as a two-faced Janus, the Roman god depicted with two faces, a one young, that of science in fieri or, as Latour calls it, of science “in the making”, and an elderly one, that of “all-made-science”, that of research conducted in the past and then reconstructed (and idealised) afterwards. When science is still in the making, it is uncertain, includes many people struggling with the same problems, a relentless competition, temporary decisions; all-made-science, on the contrary, is certain, detached and non-problematic. When science is in action, its concepts and instruments are continuously problematised, dismantled and reassembled (see Sect. 5.5); instead, when viewed in retrospect, the complex chain of relations and social alliances is hidden. This “concealment” starts with the publication of scientific results. An article must both narrate the operations that have been performed and convince the reader of the robustness of its claims. The work of trial and error that is done to make the technological apparatus work, the long discussions on the nature of the data, all the failed, suspended or abandoned projects, the management of personnel and so on… none of these aspects is reported in the article. Indeed, an inversion occurs at the end of the process of research “through all of the early stages, there are doubts,  The term indicates the luck of having discovered by pure chance and, also, the finding of something not looked for, unexpectedly, while seeking something else. The term, of Persian origin, was translated into English (serendipity) by the English writer Horace Walpole in 1754. 2

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disagreements, and above all work to define a fact. Almost all agency appears to belong to researchers. Once they have decided on it, though, they attribute reality and solidity to the fact. They deny their own agency, making the fact entirely responsible for its own establishment” (Sismondo, 2010, p. 116). All these characteristic elements can be highlighted, in particular, through the study of controversies  (see, for example, Marcheselli 2020). Controversies offer fertile soil to put into play what the strong program called “the symmetry principle” (Sect. 5.2): it is precisely because the truth of a fact or the success of an artefact has not yet been established that truth and success cannot be used as explanatory elements for what scientists do. It is when science is in action, when a consensus has not yet been reached, that the various groups will highlight each other’s weaknesses, strategies, interests and resources. In this way, facts and artefacts lose that aura of inevitability that is attributed to them a posteriori and begin to appear as what they are: the result of an intricate process made up of choices, instrument performances and malfunctionings, rhetoric, strategies, alliances and failures. Similarly, then, the sociological study of controversies while they are still in progress prevents us from yielding to the temptation to consider those who, at the end of the dispute, will be defeated as “unreasonable”. In fact, by doing so, we will see that all the parties involved have some reasons to adopt a particular position. Box 7.2  When Does Death Occur?

Until the second half of the last century, the death of a person was declared when they ceased breathing and their heart had stopped beating for a few minutes. With the invention of mechanical breathing technologies, a new condition, never before imaginable, was created: the heart and lungs could be artificially kept active even when the brain had ceased functioning. This condition of artificial life is first referred to as an “irreversible coma”. From the end of the 1970s, with the advent of surgical techniques of organ transplants, it then became necessary to redefine, also legally, the moment of death to avoid problematic ethical situations. Organs can in fact only be successfully removed from one body and then transplanted when they are still perfectly oxygenated by means of mechanical ventilators. To prevent each transplant from  becoming an ethical dilemma (a situation  that, on the one hand, would put into serious danger the possibility of life of the person receiving the organ and, on the other, would place the responsibility for the decision on the shoulders of the donor’s family members), the expression “irreversible coma” was replaced by the new medical category of “brain death”. This change was included in the legal systems of numerous countries but with very different

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timing, with the paradoxical consequence that it was possible to be considered dead in one country and alive in the neighbouring one. The transition of the traditional definition of death (the state that is reached when the vital functions of the heart and lungs cease) to the new definition of “brain death” was accompanied by heated debates that in some countries went on for at least two decades. Those who opposed the new definition of death claimed that it was not possible to adapt medical knowledge to align it with a practical interest. Many, instead, considered that declaring dead an individual whose heart was still beating—even if only through the use of a mechanical ventilator—was an absolutely counterintuitive action. The need to verify and confirm the state of “brain death” using sophisticated equipment was also bound to reconceptualise the boundary between life and death, making it the domain of specialised technologies. It is important to note that the controversy did not see resuscitators and organ transplant advocates on the one side and ordinary citizens on the other; on the contrary, doctors were present on both sides. This controversy is interesting because, despite both sides proffered convincing and supporting data and arguments, none of the people involved ever changed side during the debate. The same data, the same statistics and the same knowledge of the procedures led the two factions to assume diametrically opposing arguments. How is it then possible to reach a consensus? Logic and rationality could not offer a shared answer to the key scientific question (i.e. “when does death occur?”). The position of those who were in favour of the new category of “brain death”, in the same way as those who were strenuously against it, did not depend on the empirical evidence presented, but on the role supposed to be attributed to science within society. The Scandinavian sociologists Brante and Hallberg (1991) addressed this controversy in the Swedish context: after a lengthy debate, at the end of the 1980s (somewhat delayed with respect to many  other Western countries), a committee of doctors, philosophers, sociologists and so on penned a report which was the basis of a request to the Swedish parliaments to express a vote of conscience, that is, distanced from the official position of their own party. The controversy was therefore not resolved with logic or scientific rationality; instead the presumed adequacy, reputation and legitimacy of the committee who had penned the final report played a determining role that, unlike the previous ones, boasted a multi-disciplinary and governmental composition. However, the authority of their report was not in any case sufficient to dissipate the counterarguments and to reach a shared solution. It was only the vote of the members of the Parliament that ensured that the new definition of “brain death” came into force from 1 January 1989, thus allowing the routinisation of the procedures of organ donation and transplant. ◄

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The objective of the STS is not to challenge science or to control its procedures. The social studies of sciences, on the contrary, set out to critique a simplistic vision of the scientific method and to understand the process of construction and attribution of meaning to knowledge.

7.3 Laboratory Studies and Epistemic Cultures The awareness of the historically situated nature of experiments opens up two important questions facing the emerging field of STS: first, how are scientific facts constructed? How do laboratory activities convey their force and stability? Second, what type of institution is science? How is it organised? How is it produced and reproduced by the activities of its members? To answer these questions without idealisations and simplifications, starting from the 1980s, we witnessed the progressive diffusion of ethnographic studies within laboratories, the so-called Laboratory studies (e.g. Collins, 1991; KnorrCetina, 1981; Latour & Woolgar, 1979; Lynch, 1985; Traweek, 1988). The ethnographic method of “participant observation”, according to the anthropologist Bronislaw Malinowski (1922) who first developed it as a method for social research, is based on the idea that, to be able to understand the life of a community, it is essential to observe it and take part in its daily life for an extended period of time. The aim of this intense involvement is to understand the full spectrum of social facts that make up a certain way of life. Latour and Woolgar (1979, p. 17) write: Since the turn of the century, scores of men and women have penetrated deep forests, lived in hostile climates, and weathered hostility, boredom, and disease in order to father the remnants of so-called primitive societies. By contrast to the frequency of these anthropological excursions, relatively few attempts have been made to penetrate the intimacy of life among tribes which are much nearer at hand. This is perhaps surprising in view of the reception and importance attached to their product in modern civilised societies: we refer, of course, to tribes of scientists and to their production of science.

These new ethnographic studies were (and still are) based on the notion that scientists are organised into social groups with a certain formative process, a language and shared meanings: essentially, a culture. Indeed, once the research activities of multiple disciplines had been investigated, it appeared clear that science is not unitary and monolithic, but scientists from different backgrounds understand concepts such as “experiment”, “precision”, “test”, “evidence” and so on in very different ways.

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The Austrian sociologist Karin Knorr-Cetina formalised this idea through the concept of epistemic cultures, in other words cultural systems for the creation and legitimisation of knowledge. Epistemic cultures are “amalgams of arrangements and mechanisms—bonded through affinity, necessity and historical coincidence— which, in a given field, make up how we know what we know” (Knorr-Cetina, 1999, p. 1). At the very heart of the concept of epistemic culture lies the idea that what counts as scientific knowledge is affirmed through specific strategies for the creation, validation and communication of the results. Each discipline has its own shared methods that are created and recreated in the daily practice of each specific field (Knorr-Cetina & Reichmann, 2015). Like every cultural system, epistemic cultures include a lot of tacit knowledge (see Sect. 2.4). The latter are not sets of information (i.e. a set of formal descriptions or of instructions) but of skills. These skills cannot be passed on verbally; not for lack of will on the part of those who possess them, but because many of them are difficult to verbalise. A bit like what happens the first time you try your hand at cooking: reading a recipe is not enough to produce a successful dish, because there are many skills that a cook must possess and that can be learned only by looking at other more expert chefs and in turn trying and retrying. For example, the precise meaning of expressions like “al dente” or “as needed” are not explicit in any cook book and cannot be formalised or measured: they can only be adequately interpreted with experience. The same happens when a student first attempts experimental activities: mastering of the “appropriate” way of carrying out laboratory activities cannot simply be put into words, but requires a process of inculturation, that is, of socialisation within the community of practitioners. What social studies of science reveal through ethnographies is that the everyday life of scientists is made up of actions, activities and practices that are not entirely different from those of our everyday life (Knorr-Cetina, 1981), and that the meaning of “rationality” cannot be taken for granted but shall be treated as an actual topic of analysis. What happens then inside laboratories? The first thing that newcomers must learn by following more seniors workers is “seeing” (Goodwin, 1994; Sismondo, 2010). Non-experts often do not know how to distinguish the interesting elements from the unimportant surrounding, or the signal from the background noise. The same happens with radiographic images: the non-expert only sees blurred outlines where experts can distinguish organs, tissues, fractures, arthritis and so on. The ability of juggling objects, methodologies and instruments of one’s own discipline, however, does not assume the same characteristics in each area. Quite the opposite: different disciplines present very different forms of knowledge-grounding.

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Complex instruments such as those used by the particle physicists at CERN in Geneva, for example, produce data whose accuracy is defined via statistical methods. Physicists do not ask themselves whether a new particle exists or does not exist but—through a rather counter-intuitive procedure—they wonder what is the probability of obtaining a signal that resembles the trace of a new particle if the particle does not exist. In other words, what intensity must the signal have so that it is extremely improbable for it to be just random noise? The traces of the particles observed are not considered completely real but exist in a chaos of faint but indelible background noise due to the structure of the detector itself and to the analytical processing of the data. For important discoveries such as those of new particles (e.g. the Higgs boson, announced in 2012), physicists have chosen to respect the so-called sigma 5—that is, five points of the unit of measurement of statistical precision (calculated via the standard deviation). Sigma 5 is an arbitrary limit (it could have been more or less stringent) but established by physicists as “sufficient” based on previous experiences of alleged discoveries that were then debunked. When the sigma is less than 5, physicists choose not to immediately rule out the possibility that what appears to be an interesting or significant signal may actually be just an unusual fluctuation in noise. These decisions are not the result of individual choices but are based on long periods during which scientists dedicate themselves to the study of the experiment itself and the apparatus on which it is based; it is only after long processes of negotiation in which groups of physicists and engineers negotiate the necessary compromises (in terms of costs, precision, time, etc.) that an experiment is declared solid and meaningful.  “A detector—writes Knorr Cetina—is a layered deposit of these sales, a balance of trade of various exchanges turned into material form. Trade-offs are presented, reasoned out and collectively endorsed” (p. 113). To highlight the internal discontinuity of science, Knorr Cetina and his collaborators spent many months in other laboratories to explore their specificities. In particular, they compared particle physics to molecular biology, a discipline in which the  processes by which experiments are declared “rational” differ enormously from those discussed above. In biology, the problem is delegated to the individual scientist who is considered responsible for developing efficient strategies to cope with the behaviour of both the natural objects and the instruments with which they conduct their own research. To achieve this, the individual must draw not only on their own previous experience but also on the verbal culture of the laboratory that makes available anecdotes on the successes and failures of others. In biology, in fact, there is not that sort of detachment from the empirical dimension that we see in particle physics: biologists are in constant contact with those

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microorganisms that are both the subject of investigation and work instrument3: they must oversee and feed them on a daily basis, ensure the maintenance of the optimal conditions for their growth and meticulously observe every change. The identification of what constitutes data is therefore the result of an initial interpretative process in which considerations on the functioning of a particular instrument, on the context and the surrounding environment, on the purpose for which a measurement is performed or a device is designed, on the importance of the potential discovery and so on converge. According to Knorr Cetina, “epistemic issues are inextricably intertwined with the organization of epistemic groups […] and rationality must be seen more as a facet of the complex and tensely textured process which constitutes epistemic cultures” (p. 121). Where the previous studies had focused on what philosophers defined the “context of justification” (see Sect. 3.1.5), these studies targeted the process of discovery, the road—full of obstacles, choices, challenges, negotiations, attempts and debates—that leads to the creation of new knowledge. Generalising the ethnographic observations made over the years, Knorr-Cetina (1995) points out that there are three dimensions of nature that in the laboratory must not remain unchanged, but can (and have to) be reorganised: 1. Natural objects must not be taken for what they are in their entirety but can be treated through the traces they leave—in the form of images, sounds, waves, electrical impulses—or by picking out certain components, extracting certain elements (as in the case of the study of DNA through PCR; see Rabinow, 1996). 2. In the second place, natural phenomena must not remain in their own natural environment but can be inserted in more circumscribed, simplified and modifiable artificial environments. In particular, the laboratory changes the scale of phenomena, for example when earthquakes and storm surges are simulated using scale models. 3. Finally, within the laboratory, the temporality of natural phenomena is modified, as they are removed from their own natural cycles (think, for example, of cell cultures that are made to be reproduced in cycles that are compatible with the workers’ shifts). Within laboratories, therefore, natural phenomena are subjected to local conditions related to the social order and the logistical organisation of the work.  These two categories cannot in fact often be distinguished: bacteria, for example, are both the subject of study and instruments to study something specific such as the functioning of DNA or the function of a particular protein. 3

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Furthermore, complex experimental machineries do not always work as scientists would like. Nature continuously attempts to turn back to chaos and rejects the order that scientists seek to impose on it: cell cultures tend to grow in a different way than hoped for; sensors record signals that are difficult to interpret; guinea pigs assume behaviours that cannot be understood by the scientists taking care of them; crystallisations proceed irregularly and so on. These phenomena are par for the course in any laboratory and require enormous dedication by scientists to be (sometimes only temporarily) averted. A “successful” experiment is in fact an experiment that manages to manipulate that naturalness of nature itself, disciplining it artificially. If nature is excluded from laboratories, experimental knowledge is not knowledge of an observer-independent reality, but of a reality meticulously built through experiments (Hacking, 1983; Knorr-Cetina, 1981). According to Knorr-Cetina, it is precisely this malleability of natural objects that allows scientists to place them within the social order of laboratories: “the power of the laboratory (but of course also its restrictions) resides precisely in its exclusion of nature as it is independent of laboratories and in its ‘enculturation’ of natural objects. The laboratory subjects natural conditions to a ‘social overhaul’ and derives epistemic effects from the new situation” (Knorr-Cetina, 1995, p. 146). Exercise: Role Play

Form groups of 4–5 persons. Choose a recent scientific controversy (e.g. vaccines, homoeopathy, electromagnetic pollution, the use of glyphosate in agriculture, biotechnology, animal testing, the legalisation of cannabis, the restrictive measures adopted following the Covid-19 pandemic, etc.). Having chosen the topic, each group tries to identify all the social actors involved in the controversy. Then each member of the group will assume one of the different positions of the controversy, reporting the arguments and the data on which each of them is based. Try to be empathic, seeking to stand in the shoes of the others to understand their reasons and values. When doing so, do not just argue and defend but try to understand the point of view of the others. Before starting the activity, every group shall appoint a moderator: a person who should help the discussion and seek a mediation between the various positions. Then reflect collectively on the experience: how did it go? What did you feel while discussing with the others? Finally, did you change your position? Was the presence of an intermediary useful?

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Further Readings On experiments: • Collins (1991) • Knorr-Cetina (1992) • Shapin and Schaffer (1985) On laboratory studies: • Knorr-Cetina (1999) • Latour and Woolgar (1979) On the ethnography of science: • Knorr-Cetina (1983) • Traweek (1988) Check Your Preparation

1. What does the experimenter’s regress consist of? Why is it important for the studies of scientists? 2. Why is the laboratory a truth-spot? 3. What is an epistemic culture? 4. What does a sociologist of science and technology do when dealing with so-­called Laboratory studies? 5. What is meant by the notion of nature being expelled from the laboratory?

References Brante, T., & Hallberg, M. (1991). Brain or Heart? The Controversy over the Concept of Death. Social Studies of Science, 21(3), 389–413. https://doi.org/10.1177/030631291021003001 Collins, H.  M. (1991). Changing Order: Replication and Induction in Scientific Practice (2nd ed.). Chicago University Press. (1st ed. 1985). Collins, H. M., & Pinch, T. (1993). The Golem. What Everyone Should Know about Science. Cambridge University Press. Duhem, P. M. M. (1906). La théorie physique: son objet et sa structure. Chevalier et Rivière. (transl. The Aim and Structure of Physical Theory. Princeton: Princeton University Press. 2nd. ed., 1991). Gobo, G. (2021), Replicability. Politics and poetics of accountability, validation and legitimation, in Frontiers in Psychology, vol. 11, pp.  1–13. https://doi.org/10.3389/ fpsyg.2020.608451 Goodwin, C. (1994). Professional Vision. American Anthropologist, 96(3), 606–633. https:// doi.org/10.1525/aa.1994.96.3.02a00100

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Hacking, I. (1983). Representing and Intervening: Introductory Topics in the Philosophy of Natural Science. Cambridge University Press. Harding, S.  G. (1975). Can Theories be Refuted? Essays on the Duhem-Quine Thesis. Kluwer Academic Pub. Knorr-Cetina, K. D. (1981). The Manufacture of Knowledge: An Essay on the Constructivist and Contextual Nature of Science. Pergamon Press. Knorr-Cetina, K.  D. (1983). The Ethnographic Study of Scientific Work: Towards a Constructivist Interpretation of Science. In K.  D. Knorr-Cetina & M.  Mulkay (Eds.), Science Observed: Perspectives on the Social Study of Science (pp. 115–140). Sage. Knorr-Cetina, K.  D. (1992). The Couch, the Cathedral and the Laboratory: On the Relationship between Experiment and Laboratory in Science. In A.  Pickering (Ed.), Science as Practice and Culture (pp. 113–138). University of Chicago Press. Knorr-Cetina, K.  D. (1995). Laboratory Studies: The Cultural Approach to the Study of Science. In S.  Jasanoff et  al. (Eds.), Handbook of Science and Technology Studies (Revised ed., pp. 140–166). Sage Publications. Knorr-Cetina, K.  D. (1999). Epistemic Cultures: How the Sciences Make Knowledge. Harvard University Press. Knorr-Cetina, K. D., & Reichmann, W. (2015). Epistemic Cultures. In J. D. Wright (Ed.), International Encyclopedia of the Social & Behavioral Sciences (pp. 873–880). Elsevier. Latour, B. (1987). Science in Action: How to Follow Scientists and Engineers through Society. Harvard University Press. Latour, B. (1999). Politiques de la nature. Comment faire entrer les sciences en démocratie. La Découverte. (transl. Politics of Nature. How to bring the sciences into democracy. Harvard: Harvard University Press, 2004). Latour, B., & Woolgar, S. (1979). Laboratory Life. The Construction of Scientific Facts. Sage. Lynch, M. P. (1985). Art and Artifact in Laboratory Science: A Study of Shop Work and Shop Talk in a Research Laboratory. Routledge and Kegan Paul. Malinowski, B. (1922). Argonauts of the Western Pacific. Routledge and Kegan Paul. Marcheselli, V. (2020). The Shadow Biosphere Hypothesis: Non-knowledge in Emerging Disciplines. Science Technology & Human Values 45(4), pp.  636–658. ­https://doi. org/10.1177/0162243919881207 Quine, W. V. O. (1951). Two Dogmas of Empiricism. The Philosophical Review, 60, 20–43. https://doi.org/10.2307/2266637 Rabinow, P. (1996). Making pcr: A Story of Biotechnology. Chicago University Press. Shapin, S., & Schaffer, S. (1985). Leviathan and the Air-Pump: Hobbes, Boyle, and the Experimental Life. Princeton University Press. Sismondo, S. (2010). An Introduction to Science and Technology Studies (2nd ed.). Wiley and Sons. Traweek, S. (1988). Beamtimes and Lifetimes: The World of High Energy Physicists. Harvard University Press.

8

Scientists, Experts and Public Opinion

We often read articles that begin with: “experts argue that...” or “scholars from the X university have observed that...”. Some groups of scientists have such an outstanding reputation, even beyond the boundaries of the scientific community, that this alone is enough to give credibility to their claims: just think of the authority that we instinctively attribute to a scientist who works at CERN in Geneva, to a financial broker operating on Wall Street (Ho, 2009) or to an astronaut who has been into space. These few words are enough to induce the reader to accord some credibility to those who are designated as “experts”. But who actually is an expert?

8.1 Expertise: A Status Attributed to a Group The studies of science and technology have highlighted how expertise, from a practical perspective, is not simply a resource attributed to a single individual (however “special” he/she may be) but is mainly conferred to a group of which the individual is recognised as a member. Becoming an expert does not simply mean acquiring the necessary knowledge, but also making it socially visible by becoming part of a community that holds authority on the matter in question and whose membership is regulated by some kind of rite of passage: exams, tests, degrees and so on. When, for example, we go to the doctor, we do not know exactly how competent she is. What leads us to consider her as an expert is her degree, usually hanging on the wall, and her licence from the General Medical Council (in the UK).

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2022 G. Gobo, V. Marcheselli, Science, Technology and Society, https://doi.org/10.1007/978-3-031-08306-8_8

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The opposite mechanism is just as valid: the title of expert is revoked when one is excluded from their professional community. Think, for example, of a doctor disqualified from the register: her knowledge remains the same; however, from the moment the order of doctors sanctions her expulsion, she will no longer be consulted as an expert, people will not trust her medical advice, and she will no longer be able to practice the profession. This mechanism of attribution or withdrawal of competence also applies to all the other fields of technoscience: the status of expert does not concern the single individual isolated from the context, but the relationship between them and their reference group. It is precisely the professional groups that provide the means to acquire and maintain competence, through the socialisation of the individual members who, in this way, acquire the ability to act in a compliant manner (according to the parameters of the community itself) and a sort of mastery of a certain epistemic culture.

8.1.1 An Increasingly Blurred Boundary These early formulations on expertise focus on the interactions and institutions through which the status of expert is attributed, denied or revoked in various contexts and disciplines. Today this clear distinction between experts and non-experts is increasingly put into question, especially in contexts where the process of knowledge acquisition involves various social spheres, beyond the small circle of the scientific community. Several examples can be made: climate change, nuclear power, genetically modified organisms (GMO), experiments in the pharmaceutical sector and so on. Who is an expert? How can we test their competence? How can we decide what type of competence is necessary to be able to express an opinion with the credibility attributed to experts? Box 8.1 The Case of AIDS

At the start of the 1990s, during the dramatic debates on experimentation in medicine in the fight against AIDS and HIV, the sociologist Steven Epstein noted how a number of activist movements, mostly consisting of the patients themselves, had managed to transform their marginal position into an active and authoritative contribution. Epstein (1995) focused on how these groups of activists had managed to obtain a certain credibility and become recognised as “lay experts”, creating a breach in the division between experts and non-experts. At that time, the difficulty in managing the illness from a pharmacological viewpoint, its rapid spreading and the lack of responses considered adequate by

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conventional medicine had created a certain distrust of drug testing and clinical trials. On the other hand, though, this critical situation provided fertile ground for activists, who had managed to make their voice heard within the socio-­ medical debate. The historical, cultural and economic context of drug trials was characterised by numerous social actors: doctors and scientists from various academic backgrounds (immunologists, epidemiologists, family doctors, etc.), local, federal and national health authorities, pharmaceutical companies and so on. But where do patients and their relatives stand in all of this? According to Epstein, through a series of strategies—such as, for example, the acquisition of certain particular types of vocabulary which allowed them to discuss medical and legal matters with authority, the creation of a political representation, the taking of a stance in pre-existing methodological debates and the fusion of ethical requests with those of an epistemological nature—these groups of activists created by patients and their families managed to become accredited as lay experts. In this way they succeeded in discussing a number of implicit assumptions about experimentations that all too often marginalise patients in the decision-making process. ◄ In his study, Epstein showed both that science is not an autonomous sphere and that even those who were merely considered patients could, and wanted to, play an active role. This is not an isolated case: feminist groups in breast cancer medical research, environmental groups, farmers’ movements, just to name a few examples. In all these cases, expertise extends well beyond the limits of the scientific community showing other types of knowledge that can be useful, other skills and priorities to be taken into consideration. Attributing expertise solely to scientists prevents social actors from maturing an awareness of the complexity of the real, of the many possible objectives of any socio-technical intervention and of the many possible paths to achieve them. According to Collins and Evans (2002), however, the inclusion of a potentially infinite and indefinite multiplicity of social actors in the decision-making process poses a “problem of legitimacy”: how to establish who can have a say in decisions? In democratic regimes, governments justify and legitimise their decisions based on the opinion of experts, but if the category begins to falter, the foundations of decision-­making authority also could start to erode. We might agree on the fact that it is appropriate to extend the decision-making process beyond the professional elites by including other relevant social actors, but then—Collins and Evans wonder—to what extent this limit should be extended: indefinitely, thus

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risking making the decision-making process inefficient, or is there a way to define a limit that is inclusive but at the same time solid and unassailable? On the one hand, therefore, Collins and Evans wonder how far the concept of expertise can be extended such as to include social groups that are relevant for the decision-making processes concerning science and technology in such a way that does not risk ­stirring their hostility should they feel unduly excluded. On the other hand, the two authors are seeking a way to determine how to define a boundary between experts and non-experts to maintain a democratic participation without however risking a decision-making stalemate. To solve this problem, Evans and Collins propose shifting the focus of STS away from the problem of the construction of knowledge to the problem of the construction of expertise to develop a normative theory of expertise. Collins and Evans (2002, p. 239) complain that “Sociologists have experienced so much success in dissolving dichotomies and classes that they no longer attempt to construct them”. Even if scientists do not have a privileged access to “truth”, Collins and Evans think that their opinion still deserves special consideration. The first theoretical step that Collins and Evans took was to question the expression lay expertise proposed by Epstein, which, according to them, represented a sort of paradox. Its ambivalence entails a hybrid figure of someone who is, simultaneously, an expert and a non-expert. According to the two authors, on the contrary, it would be more functional to identify the various types of expertise that an individual might possess. In particular, they distinguish two fundamental types: contributory, which allows those who possess it to contribute to scientific research in a field, and interactional, or the ability to competently participate in a conversation on a certain topic without however taking part in scientific research. The activist movements followed by Epstein, for example, had accumulated a certain interactional competency that allowed them to formulate appropriate questions and claims even if they could not participate in actual research as doctors, epidemiologists or biologists. Collins and Evans’ proposal was immediately met with a certain number of criticisms. First, they start from the assumption that there is a clear distinction between the various domains of expertise and that contributory competence cannot cross paths, not even occasionally, with the interactional one, and vice-versa. Second, even assuming that this distinction is possible, there are often various degrees of consensus on both technical and moral questions. As such, the situations in which the scientific community reaches a unanimous consensus are an exception, not the rule. The suggestion of Collins and Evans to focus on the decisionmaking process, then, risks obscuring the path that leads a certain problem to being elaborated within a certain theoretical and practical framework (Sismondo, 2010):

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what makes a certain subject problematic or interesting? Within what disciplinary coordinates is it included? What type of political, moral and religious connotation does it assume? These questions are all excluded from the investigation if we only focus on which features are relevant for a social actor to have a say in the decision-­ making process. Sociological studies on scientific and technological controversies show, on the contrary, that the distinction between experts and non-experts, or between scientists and the public, is somehow misleading. No decision, in fact, is solely related to the scientific knowledge of a phenomenon, as many social spheres intersect in the world of technoscience. At the same time, even within the same purported group, opinions and discernment might diverge. Think, for example, of the so-­ called fracking, a technique for the extraction of oil and natural gas. On the one hand, those in favour of fracking boast the support of geologists and engineers who consider this technique not only efficient in the process of extraction (with the consequent reduction in the cost of energy and a potential boost to the economy of the country) but also a step forward in terms of environmental sustainability, as the production of electricity through fracking emits only half the CO2 compared to traditional coal. On the other hand, those opposed to fracking can draw on the support of other experts (in turn geologists, biologists and engineers) who criticise its environmental impact, the enormous amount of water required, the possible link to the generation of earthquakes and groundwater pollution. If those who are in favour of fracking believe that the possible environmental damage is only the result of bad practice (rather than the inevitable consequence of an inherently risky technique) and that therefore the risks can be averted thanks to greater investments in research and the development of new and better protocols of extraction, those who are opposed to the use of this extraction technique argue that excessive confidence in its potential distracts governments and businesses from investing in renewable energy sources and encourages dependence on fossil fuels. The decision on the practicability of fracking, therefore, is not merely technical but concerns what type of vision is to be pursued through the use of these technologies. Then, according to Sheila Jasanoff, Collins and Evans do not consider the context within which expertise is used as a resource in the decision-making process and how, as the cultural context changes, the role of the so-called experts also varies. It is within this framework that Jasanoff formulates the concept of “civic epistemologies” to draw out the cultural sensitivity with which the social actors of various nations approach the opinion of those who are considered experts on a particular field. Each civic epistemology encapsulates various elements such as the style of construction of knowledge, the level of trust enjoyed by institutions and the prevalence of certain argumentative practices over others.

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Jasanoff (2005) takes climate change as an example: if, from the 1990s onwards, the scientific community has reached a fairly high level of consensus in recognising the severity of the situation (Oreskes, 2004), why, wonders the author, is it still so challenging to find an agreement on how to resolve the problem? Why is the position of the scientific community perceived so differently in different countries? To answer these questions, the author examines the civic epistemologies of three countries: the United States, United Kingdom and Germany. In each, according to Jasanoff, the historical and cultural context has led to a particular perception of both the role of science and the possible modes of political action. In the US, for example, the system is based on the explicit confrontation between opposing factions. Public opinion has therefore led to evaluate any information as disclosed in the pursuit of particular interests. Conversely, in the UK, where there is a long tradition of reflection on empirical observation, the opinion of experts is held in high esteem; however, these must possess official qualification allowing their acknowledgement by the entire community. Finally, in Germany, a country whose historical memory is still deeply scarred by the Second World War and by the destruction that the Anglo-Americans had wreaked on German soil, the upheavals—sudden and radical—of climate change are more easily imaginable. According to Jasanoff, these different cultural attitudes play a key role in explaining why, despite the minimal dissent within the scientific community, an agreement on how to act to mitigate climate change has never been reached at an international level. If too often the blame falls on the public, accused not to be sufficiently informed on scientific matters, Jasanoff shows that the creation of consent requires a cultural sensitivity that always relates science and the social, political, economic and historical context within which science is practiced and through which trust and authority are granted. Box 8.2  Science and Power: When the Nobel Prize Speaks the Language of Power

The Italian economists Brancaccio et  al. (2021) retraced the history of the awarding of the Nobel Prize for economics from 1969 (the year it was established) to the present day. According to the authors, economics is a science that is closely connected to politics and to the exercise of power. It follows that theories that are rewarded, disseminated and taught are those that try to explain “scientifically” that the current system of production and distribution of wealth (the status quo) is the best of all possible worlds. From this perspective, the Noble Prize would be nothing but an amplifier of the orthodox thought, within which only some minimal variations—that do not violate the basic postulates— can be admitted. To survive within such a uniform academic system, even radi-

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cal and innovative ideas will be forced—perhaps unconsciously—in the direction of “special” and aberrant cases of the neoclassical economic equilibrium paradigm which remains the undisputed point of reference. Brancaccio, Gallegati and Giammetti claim that, in 50 years, no research that was not de facto reconciled within the neoliberal economic paradigm has been awarded a Nobel Prize. Being captive to the immanent interests of politics and economic power is not the only relevant aspect. For example, in the field of mathematical finance, a minor and hyper-specialised branch of economics, all the defects of the mother discipline are confirmed and amplified. From the 1980s, with the expansion of globalised finance, the financial institutions of developed economies (investment banks, funds, central banks, etc.) invested numerous resources in the scientific development of this subject. However, their goal was not selfless but connected to the growth of profits instead. This flow of investments obviously attracted many brilliant minds from a wide range of backgrounds: physicists, mathematicians and engineers reconverted to finance, taking with them consolidated instruments and solutions in search of problems to be solved. The result was an exponential increase in the complexity of the subject and the development of sophisticated financial instruments which opaquely restructure and transfer financial risks; an impressive corpus of theories from other disciplines that contributed to increasing the instability of the global financial system right on the eve of the great earthquake of 2007–2008. Further Reading Brancaccio et al. (2021) ◄

8.2 The Communication of Science So far, much has been said about the complex relationship between the scientific community and the many social actors it addresses. Since the seventeenth century, when science emerged as the privileged institution in the production of knowledge about the natural world, the activities of a small core of individuals—scientists— had to be communicated to ever wider spheres of society: investors, politicians, legislators and, not least, the general  public. The testimony, dissemination and communication of science, although fashioned according to different needs and modes, have played a constitutive role in scientific practice right from the outset.

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It was only in the 1980s that science communication became subject of analysis, not only in the field of the social studies of science but also in other disciplines such as communication and psychology. Now let’s consider some of the theoretical frameworks within which the communication of science became the subject of analysis and (sometimes) of action by sociologists of science.

8.2.1 Public Understanding of Science and the Information Deficit Model The emergence of the sociological interest in the communication of science is often associated to the critique of the so-called information deficit model, the popular idea that resistance to innovation is due to a lack of understanding of it. The main consequence of this framework is that science communication is mainly aimed at “educating” the public opinion  in order to develop a more favourable attitude towards innovation. This pedagogical and paternalistic approach to communication is still the dominant model in the practical design and implementation of many science dissemination initiatives. In their critique, the Italian sociologists Massimiano  Bucchi and Federico Neresini (2008) identify three key assumptions that lie at the core of the information deficit model. First, the understanding of science is made to coincide with the possession of a certain amount of “correct” notions regarding the scientific method and the contents of science; this knowledge is considered measurable through questions and questionnaires. Second, the information deficit model assumes the existence of a linear connection between the understanding of science and the favourable approach to it. In other words, the distrust of the public is simply attributed to their failure to understand the world of scientific research. According to this perspective, the efficient communication of facts, data and results (by scientists, science journalists and professional communicators) will then undoubtedly facilitate a positive and supportive attitude towards the techno-scientific undertaking (Irwin & Wynne, 1996). Finally, the information deficit model problematises the relationship between science and public only regarding one side of the couple, the public, considered naive and inadequately educated. The only desirable relationship is therefore one-way, based on the transfer of information from scientists (the experts) to the non-expert public. To make up for the lack of knowledge that, according to the information deficit model, would make the public unable to understand and appreciate the achievements of science, organisations and governmental bodies have gone to enormous lengths to improve the efficacy of communication, both in terms of quantity and

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quality, through various initiatives: open days of universities and research institutes, science festivals, museum installations and so on. Since the 1990s, this approach has been criticised on multiple fronts, for example by the English sociologist Brian Wynne (1992), who explored the unfolding of trust and distrust in experts’ advice during the farming crisis in Cumbria (UK) after the Chernobyl nuclear disaster. At first, the British government minimised the risk of contamination, meeting the resistance of farmers who had immediately alerted instead. Government consultants (who were considered “the official experts” in this context) had discredited these protests as “irrational” and the result of a lack of understanding of scientific evaluation. It was only after a long debate that scientists had to revise their assessment. In the meantime, however, their underestimation of the events following the nuclear disaster had already created significant economic damage to the local farming community. The interviews conducted by Wynne revealed that the breeders’ concerns were not a simple lack of understanding. Instead, they evaluated the information provided by the government agencies in the light of their daily experience of the weather, water and soil features of that particular region. The government guidelines concerning risk and how best to proceed were undoubtedly received and understood by the farmers, but also actively ignored. Trust, in fact, is not attributed to the individual pieces of information or indications but to the whole “social package” made up of relationships, interactions and interests within which the various social actors move. In conclusion, the relationship between science and the public is not abstract and one-dimensional, but complex and locally situated. The gap between “experts” and “non-experts” cannot therefore be interpreted as a simple gap or lack of information of the so-called non-experts. On the contrary, as pointed out by Bucchi and Neresini (2004) in the case of mistrust of biotechnologies in the food sector, many sceptics can in fact be found among the most educated and most exposed to scientific communication. Indeed, sometimes it is precisely the most informed people who most zealously oppose the prevailing scientific positions. Box 8.3 Fake News and the Post-Truth Era

In 2016, the expression “post-truth”—up until the previous year considered a rather infrequent neologism—was selected as word of the year by the Oxford Dictionary. This condition, defined as “relating to or denoting circumstances in which objective facts are less influential in shaping public opinion than appeals to emotion and personal belief”, was especially sanctioned by Donald Trump’s political rhetoric and by the adverse reactions of the media.1 In the same years, another word quite similar to “post-truth” hit the headlines: “fake news”.  https://languages.oup.com/word-of-the-year/2016/

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These expressions, now integral part of the media vocabulary, risk fomenting some oversimplifications and lead away from the resolution of the conflicts within which they are invoked. In particular, in the media, the use of the expression “fake news” often reduces debates (including complex and multi-faceted ones) into only two opposing factions, one associated with “truth” and the other with “falsehood”. This mechanism, however, leads all the parties involved to misunderstand the reasons of the others. To better understand the complexity of reality, then, it is increasingly important to go beyond this misleading dichotomy and try to understand the mechanisms of diffusion of a piece of news (whether it is one that we consider true or one that we deem as false) to make sense of the system within which information is assembled and made to circulate. Social media, for example, employ user profiling algorithms that causes people to read repeatedly what interests them, exposing them to the opinions of those with similar values and perspectives with greater frequency. It thus becomes increasingly challenging to stay informed in a truly “impartial” manner. Consequently, what we believe depends on our previous opinions, on the people we spend time with and on the institutions that we choose (or not) to trust. How is it then possible to untangle this complexity? STSers have often felt a deep sense of guilt, as if their criticism of the concept of “truth” may have been one of the causes of the present uncertainty. This volume, however, adopts a diametrically opposite attitude: rather than assuming a singular position that adheres to the oversimplifications with which debates are often presented, STS scholars are well equipped to study the complexity of positions, starting from the system of social values and forces involved in the process of negotiating the truth of a certain statement. Overcoming the uncertainties of the present does not involve the simplification of positions and ideas, but instead requires the understanding of the complexities of the contemporary social fabric. Further Readings • • • •

Collins et al. (2017) Sismondo (2017a, 2017b) Fuller (2018) https://estsjournal.org/index.php/ests/article/view/259 ◄

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8.2.2 From Public Engagement to Citizen Science It is precisely the new awareness of the active role of public opinion that leads local, national and transnational institutions to develop new communication ­strategies and models with the aim of integrating the values, hopes and concerns of the general public within the decision-making processes relating to new technologies. Within the so-called public engagement (Bell, 2008; Grand, 2009; Nishizawa, 2005)—that is the involvement of various social groups in the elaboration of programmes, timeframes, modes and aims of research—are included all those activities that entail a confrontation between scientists and citizens (Horst et al., 2017). These events usually consist of a face-to-face dialogue between scientists and the public with the aim of providing all parties involved the opportunity to ask questions, explore issues from other points of view (Kerr et al., 2007) and reflect on the implications of research and innovation. Unlike the dissemination initiatives designed according to the information deficit model (in which the flow of information is one way), public engagement involves, at least in principle, a more symmetrical relationship between the social actors involved. There are two types of public engagement initiatives: upstream and downstream. Upstream refers to all those forms of participation that take place before the development of innovation; conversely, downstream indicates a subsequent involvement, when the technology in question has already taken shape. In particular, potentially controversial matters—such as the growing popularity of genetically modified organisms, the location of nuclear power plants and of waste storage sites and more generally issues of sustainable development—have created opportunities for citizen participation. However, despite the important step forward facilitated by these initiatives, one of the main criticisms that have arisen is that too often they do not actually aim to involve in the deliberative process as wide a swathe of citizens as possible, but they rather focus on persuading public opinion to prevent future (potential) conflicts on controversial issues (Bucchi & Neresini, 2008). In recent decades, therefore, other forms of interaction that go by the name of citizen science have slowly assumed increasing importance (Horst et  al., 2017). The expression citizen science, in fact, covers a wide range of levels of participation (Haklay, 2013): crowdsourcing, in other words asking citizens for ideas, suggestions and opinions to implement a project or to find a solution to a problem; the intense collaboration between scientists and non-scientists to define problems and to analyse data (e.g. astronomers share thousands of satellite images with amateur astronomers so that the latter can inspect them to try and identify interesting

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phenomena); patient associations; hacker spaces, essentially hybrid spaces, increasingly popular in the US, that combine certain characteristics of workshops and others of laboratories in which ordinary citizens can meet, construct, design and share resources and knowledge; citizen sociolinguistic, namely the request, by language scholars, to collect idioms, slang expressions, dialect and so on. One ­characteristic shared by all these initiatives is that of starting, so to speak, from below, without the organisation or supervision of a formal institution, but driven forward by social groups that actively participate and consider themselves relevant. There are many examples: from the analysis of the data from telescopes that observe the depths of the cosmos in search of planets beyond our Solar System, to the censuses of bird populations and endangered species, to whale sightings. In general, all the projects in which citizens are involved first hand in the knowledge generation process are included in this category. Thanks to the study of these participatory forms of production and dissemination of knowledge, the social studies of sciences have been able to appreciate all the complexity of these interactions. In fact, there are many types of initiatives, driven by a wide variety of objectives, during which information travels following different paths. Beyond the particular model that is used as a theoretical framework to design communication activities and for the interpretation of their results by the stakeholders, it is important for the sociologist to understand what happens, what are the premises and the results, how the public is from time to time defined and for what purpose, what is the frame of meaning within which certain subjects are made the subject of debate, what is the status attributed to scientific evidence in relation to other forms of knowledge and what are the long-term effects on the identity of participants. As noted by Bucchi and Neresini (2008), communication always involves interaction, even when it is not explicit as in the case of a written text or in a frontal lesson: in fact, they are actively received, reconstructed and reinterpreted. Even in these cases, therefore, knowledge is in a certain sense actively co-produced, and none of the social actors involved can be said to be completely “passive”, not even when the communication activities are designed according to this assumption. In reality the interpretation of scientific messages always depends on the context within which these are received and on the professional, personal and civic experiences of those who receive them. The study of British ethnologist Sharon MacDonald (1995) on the London Science Museum audience showed, for example, how a visit to the museum did not always start with a specific interest in science per se but was instead intended as being part of a wider cultural journey, similar to the stopping off point on a tourist itinerary or to an entertainment option within the metropolitan setting. MacDonald also showed how the notions that are imparted

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during the visit of the museum were not simply assimilated by the participants, but were reconfigured and acquired in unexpected ways that, at times, even contradicted the curators’ intent (MacDonald, 1995, p. 20). The social actors involved in the communication of science, at various levels, are therefore manifold: if it was once thought that only a few leading scientists should deal with the communication of science (Goodell, 1975), in recent decades, other professional figures, such as science communicators and journalists, have come to the fore. There is however a whole other set of social actors who are very difficult to identify as being part of the scientific community in the proper sense but which may or may not be included according to the social context in which they are placed: policy makers, research evaluators, teachers, patients and technicians. It would therefore be more correct to abandon the abstract idea of a monolithic science that relates with a homogeneous public to instead embrace the idea of a plurality of scientists and professionals who interact with various audiences, within which expertise and knowledge are heterogeneously distributed. The interaction between the scientific community and other social groups is not only a matter of information but also, and above all, of identity (Callon, 1999; Epstein, 1995). In fact, in the case of patient associations, for example, there are no “relevant groups” until, through dialogue and confrontation, they emerged: just like the disease itself, according to Callon, social actors acquired visibility, relevance and their own identity through interaction. In addition, according to the Austrian sociologists Ulrike Felt and Maximilian Fochler (2010), participants do not build their own identity once and for all. Quite the opposite! They always have room to resist and re-imagine their roles without ever having to adhere to a final and non-negotiable version of their own identity. Therefore, different forms for expert-public can coexist and gradually evolve, so that an issue can see various configurations of this interaction simultaneously present, depending on the conditions and context. This is why rather than wondering which is the best model for effective collaboration between social groups, it is worth asking other questions: under what conditions do different forms of public participation emerge? What are the consequences? And who are the social actors that this interaction involves and at the same time defines? Exercise 1

Take a newspaper and look for all the figures of “experts” who are interviewed, quoted and mentioned. Who is attributed credibility? Try to think which other social groups have expertise in the interaction between same sector or on the same problem: what role is attributed to them? What relationships do the various social groups have?

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Exercise 2 And now, a bit of science! On the website https://eu-­citizen.science/projects, you will be able to find an extensive list of citizen science projects in which you can participate. Choose one and dedicate some time to it. Each of the projects addresses different problems and proposes various solutions. After gaining a little familiarity with the project you have chosen, try to reflect on the following questions: • How have you contributed to the research in the project of your choice? • Who organised the initiative? Which social groups have contributed to creating it and how did they go about setting up the activity? • What sort of involvement is requested from participants? • Is there an exchange of skills between the various social groups involved? • How is communication supported? • What is the image of science that is conveyed by the project you have chosen? Further Readings • Bucchi and Neresini (2008) • Felt and Fochler (2010) • Irwin and Wynne (1996)

Check Your Preparation

1. What is meant by “experts”? How does the sociological view question this definition? 2. What are the critiques to  the  kinds of expertise proposed by Collins and Evans (2002)? 3. What does the information deficit model consist of? Why has it become outmoded? 4. What is meant by public engagement? What is meant by upstream and downstream public engagement? 5. What do citizen science initiatives have in common?

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References Bell, L. (2008). Engaging the Public in Technology Policy: A New Role for Science Museums. Science Communication, 29(3), 386–398. https://doi.org/10.1177/1075547007311971 Brancaccio, E., Gallegati, M., & Giammetti, R. (2021). Neoclassical Influences in Agent-­ Based Literature: A Systematic Review. Journal of Economic Surveys, 36(2), 350–385. https://doi.org/10.1111/joes.12470 Bucchi, M., & Neresini, F. (2004). Why Are People Hostile to Biotechnologies? Science, 5(304), 1749. https://doi.org/10.1126/science.1095861 Bucchi, M., & Neresini, F. (2008). Science and Public Participation. In E. J. Hackett et al. (Eds.), Handbook of Science and Technology Studies (pp. 449–472). MIT Press. Callon, M. (1999). The Role of Lay People in the Production and Dissemination of Scientific Knowledge. Science, Technology and Society, 4(1), 81–94. https://doi. org/10.1177/097172189900400106 Collins, H.  M., & Evans, R. (2002). The Third Wave of Science Studies: Studies of Expertise and Experience. Social Studies of Science, 32(2), 235–296. https://doi. org/10.1177/0306312702032002003 Collins, H. M., Evans, R., & Weinel, M. (2017). STS as Science or Politics? Social Studies of Science, 47(4), 580–586. https://doi.org/10.1177/0306312717710131 Epstein, S. (1995). The Construction of Lay Expertise: aids Activism and the Forging of Credibility in the Reform of Clinical Trials. Science, Technology, & Human Values, 20(4), 408–437. https://doi.org/10.1177/016224399502000402 Felt, U., & Fochler, M. (2010). Machineries for Making Publics: Inscribing and De-­Scribing Publics in Public Engagement. Minerva, 48(3), 219–238. https://doi.org/10.1007/ s11024-­010-­9155-­x Fuller, S. (2018). Post-truth: Knowledge as a power game. Anthem Press. Goodell, R. (1975). The Visible Scientists. Little, Brown. Grand, A. (2009). Cafe Scientifique. In R.  Holliman et  al. (Eds.), Practising Science Communication in the Information Age: Theorising Professional Practices. Oxford University Press. Haklay, M. (2013). Citizen Science and Volunteered Geographic Information: Overview and Typology of Participation. In D. Sui, S. Elwood, & M. Goodchild (Eds.), Crowdsourcing Geographic Knowledge (pp. 105–122). Springer Verlag. Ho, K. (2009). Liquidated: An Ethnography of Wall Street. Duke University Press. Horst, M., Davies, S., & Irwing, A. (2017). Reframing Science Communication. In U. Felt et al. (Eds.), Handbook of Science and Technology Studies (pp. 881–907). The MIT Press. Irwin, A., & Wynne, B. (1996). Misunderstanding Science? The Public Reconstruction of Science and Technology. Cambridge University Press. Jasanoff, S. (2005). Designs on Nature: Science and Democracy in Europe and the United States. Princeton University Press. Kerr, A., Cunningham-Burley, S., & Tutton, R. (2007). Shifting Subject Positions: Experts and Lay People in Public Dialogue. Social Studies of Science, 37, 385–411. https://doi. org/10.1177/0306312706068492 Macdonald, S. (1995). Consuming Science. Public Knowledge and the Dispersed Politics of Reception among Museum Visitors. Media, Culture & Society, 17(1), 13–29. https://doi. org/10.1177/016344395017001002

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Nishizawa, M. (2005). Citizen Deliberations on Science and Technology and Their Social Environments: Case Study on the Japanese Consensus Conference on gm Crops. Science and Public Policy, 32(6), 479–489. https://doi.org/10.3152/147154305781779236 Oreskes, N. (2004). Beyond the Ivory Tower. The Scientific Consensus on Climate Change. Science, 306(5702), 1686. https://doi.org/10.1126/science.1103618 Sismondo, S. (2010). An Introduction to Science and Technology Studies (2nd ed.). Wiley and Sons. Sismondo, S. (2017a). Post-Truth? Social Studies of Science, 47(1), 3–6. https://doi. org/10.1177/0306312717692076 Sismondo, S. (2017b). Casting a Wider Net: A Reply to Collins, Evans and Weinel. Social Studies of Science, 47(4), 587–592. https://doi.org/10.1177/0306312717721410 Wynne, B. (1992). Misunderstood Misunderstanding: Social Identities and Public Uptake of Science. Public Understanding of Science, 1(3), 281–304. https://doi.org/10.1088/0963­6625/1/3/004

9

Science and Technology: Two Sides of the Same Coin

So far, we have almost exclusively talked about science and knowledge. The expression “science and technology studies”, however, reminds us that in this research programme, technology plays an equally fundamental role. Each technological device incorporates a certain amount of scientific knowledge. In turn, scientific research is based on the use of a multitude of technological tools, sometimes very simple, other times extremely complex. Think, for example, of how important particle accelerators are for the development of subatomic physics (Traweek, 1988) or how essential microscopes, pipettes, Petri dishes, centrifuges and so on are to biological research (Knorr-Cetina, 1999). Where does science end and technology begin (and vice versa)? Just as the boundary between science and non-science, the one between science and technology cannot be identified either in objects or in practices but its origins lie in rhetoric, in other words, it belongs to the interpretative dimension. Latour (1987) suggested the expression technoscience to emphasise the hybrid and relational nature of science and technology, and in fact these always exist in systems consisting of interconnected and inseparable elements and cannot be isolated from one another. While not explicitly adopting this term, in the following chapters we will share this sensitivity. Science and technology, however, are different objects of study, at least in part. Where science presents itself as a “universal”, “objective” and “experimental” knowledge (and the task of sociology is to investigate how these characteristics are attributed and sustained), technology is much more explicitly composite, heterogeneous and physically localised (Akrich, 1992). Every technological object, regardless of the purpose for which it was designed, is part of systems of knowledge, persons, products, machinery, funds, markets and so on, that are extremely complex and with blurred boundaries. How are these elements related to each other? © The Author(s), under exclusive license to Springer Nature Switzerland AG 2022 G. Gobo, V. Marcheselli, Science, Technology and Society, https://doi.org/10.1007/978-3-031-08306-8_9

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9.1 The Emergence of Technology Studies The legacy of the Enlightenment guided the reflection on technology up to the first half of the twentieth century. Since that time, the technological apparatus was seen, on the one hand, as the engine of “progress” both on a material and a social level; and on the other hand, it was considered a neutral device, detached from social, economic and political interests. Technology (as well as science) was not considered a social phenomenon since it was thought that only “logical” and “rational” dynamics could determine its direction.1 Just like science before Merton, technology for a long time was not considered a subject of sociological study. It was only in the 1960s and 1970s that a series of radical critiques of technology—its uses and its abuses—began to take shape. It was during those years that distrust and pessimism began to emerge towards technological products and systems which had begun to manifest adverse effects on a large scale. Many are the possible examples: pesticides had shown their toxicity and the subsequent repercussions on natural balances (Carson, 1962; White, 1964); the military and civil use of nuclear energy, against which the first mass environmental movements were organised; the link among alienation, identity and power in relation to the new technologies introduced in production processes (Ellul, 1954, 1977; Smith, 1968). These areas, only apparently distant from each other, had brought about a critical awareness of the close link between science, technology, the exercise of power and social order. It soon became clear that no technological object is neutral; each instrument, artefact or device has, in a more or less obvious way, material and social effects on the systems within which it is integrated. The American sociologist Langdon Winner was one of the first to move in this direction and described the policies inherent in the urban plan devised by Robert Moses, a public officer who designed a series of bridges, roads and tunnels that connected New York City to the nearby Jones Beach. The low height of the bridges designed by Moses meant that buses were unable to pass under them and, consequently, only people with privately owned vehicles (essentially the upper middle class) could access the seaside resort which therefore became extremely exclusive. According to Winner (1980), the infrastructure system and architectural choices had been deliberately contrived to limit access to the beach, thus benefiting the wealthy. Winner’s article, with the eloquent title “Do Artefacts Have Politics?”, paved the way to further analysis on the relationship between technology and society. Do  Obviously interesting exceptions existed, such as for example the Marxist theory or John Bernal’s (1939) social function of science. 1

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artefacts, these studies wondered, incorporate an intrinsic political tendency? Is it social actors that confer these dispositions to them? Can the values and meanings conveyed by a certain technology be modified and altered according to the context? And again, is there a clear distinction between science, technology and society? Exercise: The Design, Technologies and Layout of a Teaching Hall

Anyone who attends university halls is at times struck by the low level of participation (with questions, comments, critiques) of students. Let’s try to understand the reasons behind this with a phenomenological exercise: 1. Try for a moment to disassociate yourself, pretending to be a Martian who is entering a university hall for the first time. 2. Look at your hall and the layout of the furniture and begin a mental experiment, asking yourself: why are the desks positioned as they are? Why do students sit there and not elsewhere? Why does the tutor occupy that area? If the tutor sat where one of the students would normally sit in the middle of the hall, what would happen? 3. Halls are designed and constructed by someone, usually by an architect or by an engineer. Looking at your hall, what didactic model could the architect who designed it have had? What must have been, according to this architect, the structural and environmental requirements of a good didactic? 4. Now take a look at the verbal exchanges during a lesson: does everyone hear what the professor is saying? When a classmate talks, from an acoustic perspective, can everyone hear them? Why does the professor have a microphone? Why don’t the students also have one? 5. Share your reflections. Some of Our Reflections The designer probably has a didactic model in mind in which the professor is the centre (of attention) and the students are peripheral: they need only be correctly positioned to see the professor. In this didactic conception—theatrical and cinematographic—the professor is the starring actor and the students passive spectators. Indeed, today, with the ever more frequent use of multimedia resources, the centre becomes the screen (on which the didactic contents are projected) and also the professor, while speaking, continuously looks at the screen (Schnettler & Knoblauch, 2007). If they were a couple of comedians, we could say that the teacher “acts as a side-kick” to the screen. We have also noticed that when the students in the first row intervene in class discussion, those in the back row start talking in whispers with those seated next

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to them, thus  becoming distracted. A slight but annoying buzz grows; ­psychologists or pedagogues might interpret it as distraction, lack of respect or indifference towards classmates, rudeness and so on. Instead, this (probably) only happens because the students cannot hear what their classmates in the first few rows are saying and therefore become bored. According to the designer, the students’ sole task is to follow what the professor says and diligently take notes, as if they had nothing of importance to communicate and thus have no need for a microphone; all they need is a socket for their laptop. This sort of situation would instead be unimaginable in any Parliament (where even the deputy of the smallest Party has a microphone). Furthermore, the communication between students is greatly impeded by the layout of the desks: those who are in front need to turn their heads and torso to interact with their colleagues and those behind have in front of them a sea of heads. Interaction, in these conditions, becomes extremely unlikely. Do you need some counterevidence? Have you ever attended a lesson in a hall where the table was located in the middle and you were distributed around it in a circular or horseshoe formation? You will surely have noticed how the attendance (interventions, comments, questions, critical observations and even spats between students) is undoubtedly greater in such a layout. Didactic models, power asymmetries and educational ideologies are incorporated in the furniture and in the technologies of the teaching hall.

9.2 From Technological Determinism to the Social Shaping of Technology (SST) A first approach to the study of the relationship between technology and society is constituted by the so-called technological determinism, the theoretical position that affirms the centrality of technology in defining the social, cultural and economic conditions typical of a certain period in history. This theoretical orientation draws from the writings of Karl Marx and Friedrich Engels who, already by the mid-nineteenth century, had theorised a close cause-effect relation between the means of production available in a society and the system of power relationships through which it is ordered. Marx wrote (1847, p. 94), “the windmill gives you society with the feudal lord; the steam mill, society with the industrial capitalist”, somewhat similar to what Pickering stated in Sect. 5.6.

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There are many types of technological determinism (Bimber, 1994; Wyatt, 2008), but they all share two assumptions: first, innovation drives social change in a specific manner that can be accurately described. Second, each form of ­technological determinism deems technology as autonomous and developing based on an internal logic; according to this perspective, technological progress is not only linear but, somehow, inevitable. The role of sociology would thus be to describe these dynamics, without however questioning their content which, according to this approach, cannot be subject to sociological analysis. This position, which is nowadays rather unusual in the academic sphere,2 is often deployed in a wide variety of contexts as an implicit theoretical framework for narratives in favour of innovation (Calvert, 2004). In fact, very few sociologists embrace this type of determinism because its shortcomings cannot be ignored. In the first place, the same piece of technology can give different results in different contexts. Moreover, when we analyse the social changes occurring in relation to the introduction of a technology, it becomes apparent that social change is not only the effect of innovation, but at the same time it generates further innovation: if it is true that within a certain limit, society is modelled by technology, the reverse is also the case. Technology is therefore developed and adopted as the result of a series of economic, political and cultural forces. These early studies, focusing on the impact of technology on society, have often overlooked the complex process of development of a technological instrument and of its adoption. It was only later that this process was highlighted and thus the series of choices, negotiations, disputes and rhetorical strategies that occurred before the stabilisation and normalisation of a piece of technology (whose historical evolution had, up until then, appeared linear) was revealed. The social shaping of technology focuses precisely on the reconstruction of these choices and on the many versions in which an artefact is articulated by different social actors (Mackenzie & Wajcman, 1985, 1999). The expression, thereinafter abbreviated in SST, encompasses many different approaches which, in general, shift the attention away from the technological to emphasise the role of the social within the innovation process. Like technological determinism, the interest is directed towards the impact of technologies on society; however, SST also  A few examples of this exist in the history of technology, for example Lynne White’s paper that connects the invention of the stirrup to the advent of the typical hierarchies of the medieval feudal system. According to White (1962), a simple invention corresponds to an epochal social, political and cultural change. 2

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questions how an artefact embodies values and interests, and how these impart an inertia in its historical path. This journey no longer appears as simple and linear but assumes complex contours, punctuated by choices and conflicts that lead to the affirmation of a particular version of the artefact with respect to other possible alternatives. The prevailing of an option over the others is not merely due to a technical matter but also involves economic, political and social factors. The debate triggered by the SST critique of technological determinism laid the foundations of at least two other theoretical frameworks: the social construction of technology (or SCOT, proposed by the sociologists Trevor Pinch and Wiebe Bijker) and the actor-network theory (ANT, that finds its main proponents in the French philosophers and sociologists Bruno Latour and Michel Callon; see Sect. 5.5). These two theories, while having taken inspiration from the SST, were then developed as independent and, to a certain extent, divergent approaches.3

9.3 The Social Construction of Technology (SCOT) The SCOT approach was proposed by Pinch and Bijker (1984), following in the footsteps of the sociology of scientific knowledge (SSK) (see Sect. 5.2). Their aim was to overturn the cause-effect relationship between functionality and success in technological innovation. Just as in the SSK, it is not the validity of a theory that determines its success but rather it is the success of a theory that makes it “true”; in the same way in SCOT, it is not the efficient operation of an object, its usefulness or its “intrinsic nature” that determines its success, but instead it is the triumph of a particular design out of the many available that makes it “best” and the most “useful” one. To this purpose, Pinch and Bijker chose to focus on the historical, economic and social process that leads to the construction and stabilisation of a successful object. Their analysis is divided into two phases:

 Whether these two approaches are the result of an evolution within the theoretical framework of the SST or an autonomous development is the subject of debate within the same community of technology scholars. This is a further example of the fact that scientists can also study according to an STS perspective: “continuity” and “change” are not in fact diametrically opposed but are rather rhetorical instruments of boundary work that social actors use to fit in or to object to other theoretical frameworks with which they enter into dialogue. 3

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1. Initially, the object of investigation is described from the point of view of the “relevant social groups”, in other words groups of people who collaborate towards a certain goal through a number of routine activities, who share the attribution of certain meanings to artefacts and whose actions and choices are meaningful for the group’s success or failure. According to Pinch and Bijker, each relevant social group provides a different interpretation on how to define the object in question, what functions it can perform, in which contexts it should be introduced and what improvements it can bring to the system. This i­ nterpretive flexibility is essential to highlight how neither the identity of an object nor its functioning are intrinsic properties. 2. Subsequently, the authors reconstruct the historical path that led one of the various interpretations previously described to prevail over the others. At the end of this process, the technological object “stabilises”, a condition similar to the closing of a controversy (see Sect. 7.2) in relation to scientific knowledge (Pinch & Bijker, 1984). An emblematic example of this process is the success of the so-called safety bike, in other words the vehicle most similar to the contemporary bicycle, with wheels of equal diameter covered with tyre and with an inner tube. It imposed itself upon other models in circulation in the late nineteenth century—in particular, it outdid the penny-farthing, also called ordinary bike,4 a velocipede with a large front wheel and a smaller rear wheel. To understand why the safety bike prevailed over other bicycles, Pinch and Bijker started with the description of the relevant social groups that had participated in its development: manufacturers, tyre producers, traders and cyclists. The latter were then divided by the authors into different subgroups that represented the numerous purposes for which the various types of velocipedes were chosen. For the senior age group— who needed an efficient urban vehicle—the penny-farthing was unsafe because it was very difficult to stay balanced given its height and the great speed it could reach. The wide and long skirts, typical of the clothing of the time, made the penny-farthing rather uncomfortable for another important category of users, women. For these reasons, these two social groups tended to prefer the safety bike, despite being intimidated by the violent vibrations it produced, at least until the tyre and the inner tube were invented (which, however, had the inconvenience of breaking very often). Conversely, the youngsters preferred the  The name penny-farthing is a metaphor that came about from the similarity of the two wheels to the most commonly used British coins of the time: the smaller one in fact was called penny and the larger farthing. This model was called ordinary after the invention of the safety bike. 4

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penny-farthing as it reminded them of the style and bearing usually associated with the horse, traditionally the noble means of transport par excellence. Young people also agreed on the low level of safety of the penny-farthing but somehow this characteristic made it even more attractive, as it gave them a way to show off dexterity and courage. As such, the same vehicle (the penny-farthing) was considered “unstable” by some social groups and “macho” by others. This Macho Bicycle was … radically different from the Unsafe Bicycle—it was designed to meet different criteria; it was sold, bought, and used for different purposes; it was evaluated to different standards, it was considered a machine that worked whereas the Unsafe Bicycle was a non-working machine. Deconstructing the Ordinary bicycle into two different artefacts allow us to explain its “working” or “non-working”. There is no universal time and culture-­ independent criterion with which to judge whether the high wheeled bicycle was working or not. (Bijker, 1995, pp. 52-3)

The prevalence of one model over another was therefore by no means inevitable and did not depend on which velocipede was intrinsically “better”: each, in fact, was considered the most functional depending on the use intended to be made of it. It was the achievement of a certain degree of consensus with respect to what was a cycle and what was its most appropriate context of use that determined the prevailing of the safety bicycle.5 In particular, the advertising of the bike as an instrument to perform some functions rather than others, and the resolution of a number of criticalities (such as that of the vibrations that afflicted the safety bike but not the penny-farthing) that made the safety-bike appear less problematic. Following the social construction of the bicycle Pinch and Bijker showed how each artefact can be associated with a plurality of discourses and uses. The success of one of these possible versions is therefore a matter to be resolved at the level of the meanings to be attributed to the bicycle as an instrument and to its use. Of course, in this kind of account the technical side is essential, but it has to be contextualised in a system of interests, values and meanings. Central to this approach is the belief that technological development cannot be explained by the alleged intrinsic properties of objects, but by the social interests that guide the choices related to the use and design of technological artifacts.  The presumed stabilisation of that which today has become the modern bicycle is not in any case a process that is concluded once and for all. Even today there are many types of bicycles: the city bike, the mountain bike, the touring bicycle, the racing one and the folding one (to facilitate its transportation). While they all have equally sized wheels, these bicycles differ hugely in terms of weight, performance, speed and ease of riding. Their greatest difference, however, is that of being used by social actors with varying objectives. 5

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9.4 Actors and Artefacts in the Actor-Network Theory (ANT) The second theoretical framework which took inspiration from the SST is that proposed by Latour and Callon, the Actor  Network  Theory (see Sect. 5.5.1). According to the two French authors, the process of creation of a technical-scientific object goes hand in hand with the establishment of a network of relationships between human and non-human actants. The resulting network, at the same time material and semiotic, shapes the context that promotes the insertion of the artefact within the segments of society involved in its use and the transmission of skills necessary for its production, dissemination and use (Callon, 1987). Within the network of actants, the principle of symmetry is applied not only to humans but it is also extended to non-human actants that therefore occupy positions of equal importance (Volonté, 2017). The observer, writes Michel Callon (1986, p. 200), must abandon all a priori distinctions between natural and social events. He must reject the hypothesis of a definite boundary which separates the two. These divisions are considered to be conflictual, for they are the result of analysis rather than its point of departure. Further, the observer must consider that the repertoire of categories which he uses, the entities which are mobilized, and the relationships between these are all topics for actors’ discussions. Instead of imposing a pre-established grid of analysis upon these, the observer follows the actors in order to identify the manner in which these define and associate the different elements by which they build and explain their world, whether it be social or natural.

The idea of the formation of networks is based on the concept of translation, in other words the process of enrolling an ever increasing number of actants who are persuaded that their interest coincides with the interest of those who are already part of the network (see Sect. 5.5.1). The network, eventually, expands and consolidates into what becomes an actual technical device—the unit of analysis of the actor-network theory—made up of human and non-human actants (researchers, technicians, users, entrepreneurs, but also computers, electrons, algorithms, schools of fish, bacteria, etc.). Once these networks of actants take form, they no longer function as independent elements, but start acting as a whole, constantly increasing the inertia of a certain technology. The success of translation, however, should not be taken for granted; on the contrary, it is a process that can encounter obstacles and might require the redefinition of some of the elements of the network itself, at least until the system eventually becomes routine (Latour, 1993, p. 22). The actants involved in the network thus formed do not have a fixed identity and immutable interests; on the contrary, they assume a specific role based on their own

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position within the actual network. The ANT does not base its analysis on concepts such as “interests” or “values” (typical of methodological individualism) or on pre-­ existing structures such as “class”, “social group” or “type” (typical of methodological holism). These categories, according to Callon and Latour, are not a premise for the formation of a network because they are interpreted and reconstructed within the same network (Latour, 1987, pp. 172–3). Interests and social groups are not immutable, nor are they always consistent within networks which, according to Latour, can contain conflicts and tensions that might require constant reformulations of relationships, and the modifications and construction of new alliances. Conversely, ANT focuses on the bonds that are established between actants and that bind them to each other in a network. It is precisely this mutual relationship that determines and sustains identities and roles. According to Bruno Latour and the French sociologist Madalaine Akrich, the creation of an artefact is accompanied by the configuration of its context of use through the incorporation of scripts, in other words sets of prescriptions that dictate, more or less implicitly, its correct use.6 It is through these scripts that material objects act on and in the world. The keys to a hotel room, for example, can be accompanied by voluminous key rings to induce the guests to drop them at the reception desk when leaving the hotel, as they are too bulky to be carried around. In this way, it is the object itself that, more efficiently than any text or verbal invitation, makes the user perform the actions expected of them. Through scripts, technological objects define the actors and the relationships that bind them, distributing skills and roles, defining the space within which they move and making choices regarding what should be delegated to the machine and what instead should remain an initiative of the human actor (Akrich, 1992, p. 216). However, it is possible that no actor takes on the role conceived by the designers or that groups of users define new and unforeseen roles; when this happens, the technological object remains a mere chimera. Box 9.1  The Repair of Obsolete Objects

In the studies of STS so far described, we have shown how values, interests and choices are imposed on each artefact right from the moment of its design. It is  A similar concept had already been introduced by the US psychologist James Gibson (1979) with the term affordance. According to the author, the physical quality of an object suggests the appropriate actions to manipulate it. Each object possesses its affordances as do surfaces, events and places. However, affordance belongs neither to the object itself nor to its user but is created by the relationship that is established between them. It is, so to speak, a “distributed” property. 6

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also true, however, that users of a product have in turn a series of ways to resist these pre-structured inputs and to modify and adapt these same objects to their advantage (Hyysalo, 2009; Oudshoorn, 2011; Woolgar, 1991). It is therefore necessary to bear in mind how social actors determine the trajectories—unpredictable and non-linear—of technology: when a technological object remains in circulation for a certain amount of time, it enters multiple systems and various contexts of use, establishing numerous and multi-faceted relationships with social actors (Edgerton, 2006). Many of the traditional theoretical frames describe change as a process of innovation in which the new introduces a change in objects and practices. This innovation-centric bias has often averted the analytical gaze of STS from all those practices of maintaining infrastructures and repairing malfunctioning or obsolete devices that instead allow technological objects to remain in use during their life cycle (Russell & Vinsel, 2018; Vinck, 2019). In the early 1900s, for example, the sparse infrastructures of the flourishing automobile industry required that drivers themselves would be able to repair the ordinary faults of their own vehicles. These skills acquired by the individual users and shared through weekly publications resulted in motorists becoming an active part of the innovation cycle, making to their own cars small changes that were often adopted as standard solutions by the car manufacturers themselves (Franz, 2005). Today, we can witness some fairly comparable situations, for example  in collaborative bike workshops, spaces managed by collectives of volunteers who share skills and teach other cyclists how to repair their own bicycles. This model not only promotes a more sustainable urban mobility, but also objects to asymmetries of power in terms of consumption (Carlsson, 2007). The sharing of the skills necessary for repair then also has a social value, creating small urban communities around ecologically sustainable practices. Users are therefore not only passive, docile and easily influenceable consumers; on the contrary, these studies have shown that users develop active adaptation practices (Hyysalo et al., 2016, 5–9), both through repair and DIY and also by guiding new technologies towards unexpected needs. For the STS, maintenance and repair are valuable opportunities of research as it is precisely at these times that everyday life infrastructures become visible. When a breakage occurs, the materiality of the infrastructure, usually invisible in its routine use, is revealed.

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Further Readings Strebel et al. (2018) ◄ Over the years, the ANT has also been adopted in areas in which science and technology do not play a leading role; ANT helps to ground relationships between social actors in the material and practical dimension of their respective activities. ANT however has also received strong criticism, especially from those who consider the process of recruiting allies and expanding the network of actors excessively Machiavellian, and from those who are reluctant to equate humans and non-­ humans (see Amsterdamska, 1990; Collins & Yearly, 1992).

9.5 The Ecological Approach to Technology From the 1990s onwards, technology scholars have gradually expanded their analytical outlook, abandoning the study of individual laboratories, institutions or networks of relationships centred around a specific artefact, in favour of a more diversified system that highlights the complexity, contingency and indeterminacy associated with the process of knowledge production and innovation. Recently, therefore, the so-called ecological approach to knowledge—an expression coined by Charles Rosenberg at the end of the 1970s and taken up by the US sociologist Susan Leigh Star in 1995—has assumed a role of primary importance in the study of the social dimensions of science and technology in relation to the material practices that constitute them. According to this approach, science, technology and society can be studied as an ecosystem within which the various elements exist in a relationship of mutual interdependence (Star, 1995). The components of each ecosystem, in fact, despite being located at different scales and acting at different levels, maintain a relationship of interdependence. To understand a forest ecosystem, for example, it is necessary to consider climate, altitude above sea level, geographical coordinates, the hydrogeological system, the presence of a certain type of vegetation, fauna, flora, of insects, of microorganisms and so on. These elements do not follow rigid cause and effect relationships but shape each other. Similarly, technological apparatuses have systemic properties that can only be understood if one considers the interdependence between local context, social actors, personal problems, public issues, the availability of raw materials and workforce, the role of institutions and so on. Moreover, the term “ecological” has the precise purpose of rejecting dichotomies such as social/natural or social/technological (particularly relevant in the debate between Bruno Latour and Michel Callon on the one hand, and Steven Yearley

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and Harry Collins on the other, regarding the role of human and non-human actors) in favour of more systematic and dialectic units of analysis. If we take ecological to mean treating a situation (an organization or a country or interactions and actions) in its entirety looking for relationships and eschewing either reductionist analyses or those that draw false boundaries between organism and environment, then indeed the human/non-human question is reframed. (Star, 1995, p. 14)

Furthermore, according to the sociologist of science and technology Joan H. Fujimura, the ecological vision—while having certain elements in common with Latour’s idea of network, such as, for example, the importance of relationships—is characterised by a less “militaristic” view, whose actors are not oriented toward specific objective (Akera, 2007; Fujimura, 1995). The ecological approach, on the contrary, requires a “multi-centric mapping” that does not grant primacy to developers, engineers or to those who sell and disseminate a certain artefact, or even to users who put artefacts to use, according to expected or unexpected methods. Each social agent involved assumes a role and an identity that cannot be defined a priori but which is negotiated in an endless process, one that allows changes and multiple identities. This vision is based on two important elements: first, just like ecosystems in nature, socio-technological ones are also open systems with permeable boundaries. Secondly, stability and change7 coexist and balance each other. The ecological approach abandons any finalistic analysis—in other words, unlike SCOT and ANT, the ecological approach is not interested in the final result or in the closure of a process of innovation when one particular technological object prevails over the others. It assumes a more synchronic approach instead, one that focuses on the development process and on the many facets that an artefact assumes in complex landscapes, thus including a wide variety of social actors with many different interests and who act in local and ordinary contexts that at times radically differ from one another.  A problem that is opposite to that of change is one of explaining those systems in which technology has an inertia that is difficult to subvert. In other words, what happens is that a whole social system adapts to a particular technological solution (the so-called lock-in) that then, over time, becomes difficult to change. One example of this is the qwerty keyboard, created for typewriters, with a particular configuration designed to avoid the jamming of the most used keys. Another version (Yasuoka & Motoko, 2011) instead highlights the role of telegraphers who experience difficulty in using a keyboard with the keys placed in alphabetical order. Nowadays, even though typewriters are rarely used, the qwerty keyboard continues to be used (and has now become difficult to replace) despite the obsolescence of the instrument for which it had originally been created (David, 1985). 7

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9.6 Sociotechnical Imaginaries and the Sociology of Expectations By definition, scientific and technological innovation is oriented towards the future: planning research, securing funding and drafting projects are just some of the most obvious aspects of the future direction that scientific research is moving in. In fact, in these practical and mundane activities are embedded specific imaginaries, expectations and visions, which belong to the narrative dimension, and yet play a decisive role in shaping the design, participation and support to scientific and technological activities. These narratives are indeed generative, in other words: they guide activities, provide structure and legitimation, attract interest and foster investment. They give definition to roles, clarify duties, offer some shared shape of what to expect and how to prepare for opportunities and risks. (Borup et al., 2006, pp. 285-6)

But how do the possibilities of the present shape expectations for the future and vice versa? In the so-called sociology of expectations, technological expectations are defined as “real time representations of future technological situations and capabilities, […] the wishful enactment of a desired future” (p.  286). Expectations intersect with other two methods of relating to the future: they are included within visions, or “internally coherent pictures of alternative future worlds […] designed to articulate the shared expectations of a selected group of stakeholder” (Eames et al., 2006, p. 361), and supported by promises, that is the contribution with which it is expected that science and technology will improve social conditions. Due to their highly normative character, expectations are performative: they promote alignment and support (from both a financial and a political perspective) towards shared ambitions. They also provide guidelines for institutions and researchers to define priorities and to reduce uncertainty in the decisionmaking process (see p. 362). Let’s take, for example, the space race: in the 1950s and 1960s, the rapid development of rockets capable of leaving Earth’s atmosphere and orbiting around the planet made people think that, in a not too distant future, space travel would become routine. The more this belief took roots in the common sense, the more funds flowed into the research necessary for its implementation, students became keen to study space engineering and the public embraced space achievements with a sense of social, economic and political victory.

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Box 9.2  When Fantasy and Science Merge

Jules Verne (1828–1905) is considered one of the noble fathers of modern science fiction or, as it was defined at the time, anticipation narrative. Driven by a strong passion for technology, with his stories set in the air, in space, in the subsoil and on the bottom of the sea, he went on to inspire many scientists in future eras. In the novel From the Earth to the Moon (1865), Verne describes a journey aboard a bullet fired from a giant cannon and a moon landing. At the time, this idea was challenged by many scientists but we were, after all, dealing with an adventure novel and science fiction. Somewhat later, Around the Moon (1869) was published; this novel goes beyond the trip and follows the adventures of the heroes on the moon. In Twenty Thousand Leagues Under the Seas (1869–1870), Verne imagines a large electric submarine, the Nautilus. And doesn’t the Nautilus perhaps remind you of Alvin launched in the 1960s? The Nautilus, like Alvin, was exclusively electrically powered. In fact, he also rejected coal as fuel, proposing instead electric batteries to propel the contraption. These batteries have an unknown chemical composition, but they make Verne a precursor of alternative fuels. In the same book he writes about a gun that fires a strong electric shock, very similar to the modern day taser. Studies to create flying machines go as far back as sketches by Leonardo da Vinci, but it was during the late nineteenth century that the helicopter as we know it began to take shape. At the same time, Jules Verne published Robur the Conqueror (1886), a novel in which the main character builds an aircraft out of pressboard (so it had great strength and was light at the same time) that flies via rotors, much like modern helicopters do. Additional rotors at the bow and stern served to propel the invention towards the heavens. Verne took the existing helicopter prototypes and imagined how they would develop. In a short story written in 1889, In the Year 2889, Verne describes an alternative to newspapers: “every morning, instead of being printed as in antiquity, the Earth Herald is ‘spoken’. It is by means of a brisk conversation with a reporter, a political figure or a scientist that the subscribers can learn whatever happens to interest them”. It took much less than the thousand years predicted by Verne for the first radio newspapers (in the 1920s) and then the first news programs (in the 1940s) to become popularised. Jules Verne was far from being a scientist, but his and the progress being made at the time served to introduce many of the inventions that were to come

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and that, over time, have ended up becoming ordinary elements of our every-­ day life. ◄ Expectations therefore are not simply imagined but have a tangible influence on science and technology: it is through them that social actors seek to create a common direction and convince other actors of what the future holds in store for them (Brown et al., 2000, p. 4). The future—imagined, planned, desired or feared—is a very powerful temporal abstraction which is rooted into the present, from both an ideological and a material point of view. The American sociologist Mike Michael (2000, p. 22) writes “the present is the locus (which we can never leave) in which are drawn together substantive representations of particular sorts of ‘sociotechnical’ past and future”. Expectations, in fact, have a social and historical variability: different social actors, according to their disciplinary training, personal experience and their differing scientific, economic, political and institutional stances, support conceptions of the future that may not align with—or even diverge from—each other. Some expectations can be highly influential in some periods and then lose inertia, while others may be relegated to an even more distant future. At times, however, expectations change simply because the present in which these are rooted has changed. Let’s return briefly to the example of space exploration: if, in the 1950s and 1960s, the future of humanity in space seemed tantalisingly close, only a few decades later, from the end of the 1970s onwards, this future was no longer considered likely or even particularly hoped for. The future seen from this perspective no longer seemed the same. Today, however, we are witnessing a new wave of enthusiasm for space exploration and the idea of a future among the stars is again gaining widespread support (Tutton, 2016). Jasanoff formulated the concept of “sociotechnical imaginaries” to characterise those visions of the future that concern science and technology, and only through them can be achieved. These are: collectively held, institutionally stabilized and publicly performed visions of desirable futures, animated by shared understandings of forms of social life and social order attainable through, and supportive of, advances in science and technology. (Jasanoff & Sang-Hyun, 2015)

Unlike the sociology of expectations, sociotechnical imaginaries operate at the level of state and national institutions (the government, foundations, large corporations, NGOs, etc.). Sociotechnical imaginaries do not concern a precise problem or a specific field but provide a larger picture that represents the world that a particular society would like to inhabit in the future. This future can undoubtedly include a

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number of technologies, such as solar-powered vehicles for example, but these will somehow reflect the more general values that drive the imagined society, in this case for example the ideal of an ecologically sustainable way of life. These sociotechnical imaginaries, on the one hand, contribute to justifying investments in certain sectors of science and technology and, on the other, reaffirm the capacity of the state to act for the common good. President Kennedy, for example, in a famous speech at Rice University in Houston (not coincidentally, the same city where the NASA’s space mission control centre was based), announced the economic and political commitment of taking Americans to the moon before the Russian contenders. Kennedy leveraged the belief, quite widespread at the time, that space was the greatest enterprise in the history of humankind, thus justifying his support for an industrial sector without immediate benefits for the country’s economy. Once Neil Armstrong set foot on the moon, US citizens felt a sense of pride and a strong feeling of unity towards their country, commending their government’s ability to act for the common good (despite defeats on other fronts, such as that of the Vietnam war). Sociotechnical imaginaries are therefore both an aim of politics and its fundamental instrument of legitimisation. Exercise on “Invisible” Technologies

In an ethnographic study reported by Alessandro Mongili (2007) on the relationships between gender cultures and domestic technologies, a number of housewives were asked to identify “domestic technologies”. While most of the participants did not include the oven and stove in this category, they did however include the computer. Objects might or might not be labelled as technological, depending on the point of view and the goals of those who are asked to classify them. The most “invisible” technologies (e.g. the clock, the fridge or plastic objects) are actually the most pervasive and meaningful in our everyday life. • Now let’s try and reflect: what are the “invisible” technologies that we constantly use in university life? • How do they structure—and at the same time are structured—by our actions? • What identities and relationships are configured through them? Exercise on Analytical Approaches In small groups, choose a technological object to describe. Commonly used objects such as a bicycle, a smartwatch or an ATM are relevant, but also technological systems that are less mundane, such as the LHC (the particle accelerator of CERN in Geneva), a submarine or the International Space Station, will do.

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Now try to analyse the technology of your choice through the theoretical approaches presented in this chapter. Each of them adopts a different unit of analysis and is driven by different research questions. Here is a guide to the key analytical interests for each of them: • Theoretical framework 1: SCOT 1. Which social groups are (have been) involved in the development and use of the piece of technology? 2. Which are the meanings that each of them attributes to the technology being considered? 3. Which meanings have prevailed? • Theoretical framework 2: ANT 1. Describe the network of actants (human and non-human) established to make it possible to use the chosen technology. 2. Which scripts are linked to the technological object of your choice? 3. What is managed by users and what instead is delegated to the technology itself? • Theoretical framework 3: ecological approach 1. How does the chosen piece of technology intersect with the context? 2. What other technologies are necessary for its use? 3. What relationships are created thanks to the technology chosen in the places where it is used? By the end of this exercise, you will have noticed that the descriptions formulated have a number of important differences. Each theoretical framework highlights certain aspects and ignores others. Discuss within your group and as a class what the strengths and weaknesses of each piece of analysis are formulated in light of the corresponding theoretical framework. Further Readings • • • •

Bijker (1995) Jasanoff and Sang-Hyun (2015) Latour (1992) Star (1995)

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Check Your Preparation

1. What does technological determinism consist of? In what way is it outdated? 2. From a sociological point of view, what does the history of the bicycle tell us? 3. What are the main differences between ANT and SCOT? 4. What is a script? How is this concept discussed? 5. What role do sociotechnical imaginaries play?

References Akera, A. (2007). Constructing a Representation for an Ecology of Knowledge: Methodological Advances in the Integration of Knowledge and Its Various Contexts. Social Studies of Science, 37(3), 413–441. https://doi.org/10.1177/0306312706070742 Akrich, M. (1992). The De-Scription of Technical Objects. In W. E. Bijker & J. Law (Eds.), Shaping Technology, Building Society: Studies in Sociotechnical Change (pp. 205–224). MIT Press. Amsterdamska, O. (1990). Surely You Are Joking, Monsieur Latour! Science, Technology and Human Values, 15(4), 495–504. https://doi.org/10.1177/016224399001500407 Andrew, L., & Russell Lee, Vinsel. (2018). After Innovation Turn to Maintenance. Technology and Culture, 59(1), 1–25. https://doi.org/10.1353/tech.2018.0004 Bernal, J. D. (1939). The Social Function of Science. George Routledge & Sons Ltd. Bijker, W. E. (1995). Of Bicycles, Bakelites and Bulbs: Toward a Theory of Sociotechnical Change. The MIT Press. Bimber, B. (1994). Three Faces of Technological Determinism. In M. R. Smith & L. Marx (Eds.), Does Technology Drive History? (pp. 79–100). The MIT Press. Borup, M., et  al. (2006). The Sociology of Expectations in Science and Technology. Technology Analysis and Strategic Management, 18(3-4), 285–298. https://doi. org/10.1080/09537320600777002 Brown, N., Rappert, B., & Webster, A. (2000). Contested Futures. A Sociology of Prospective Techno-Science. Routledge. Callon, M. (1986). Some Elements of a Sociology of Translation: Domestication of the Scallops and the Fishermen of Saint-Brieuc Bay. In J.  Law (Ed.), Power, Action and Belief: A New Sociology of Knowledge? (pp. 196–223). Routledge. Callon, M. (1987). Society in the Making. The Study of Technology as a Tool for Sociological Analysis. In T.  Pinch, W.  Bijker, & T.  Hughes (Eds.), The Social Construction of Technological Systems (pp. 83–103). MIT Press. Calvert, J. (2004). The Idea of “Basic Research” in Language and Practice. Minerva, 42(3), 251–268. https://doi.org/10.1023/B:MINE.0000038307.58765.b4 Carlsson, C. (2007). “Outlaw” bicycling. Affinities: A Journal of Radical Theory, Culture, and Action, 1(1), 86–106. Carson, R. (1962). Silent Spring. Houghton Mifflin. Collins, H. M., & Yearly, S. (1992). Epistemological Chicken. In A. Pickering (Ed.), Science as Practice and Culture (pp. 301–326). The University of Chicago Press.

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David, P. (1985). Clio and the Economics of Qwerty. American Economic Review, 75(2), 332–337. https://www.jstor.org/stable/i331322 Eames, M., et al. (2006). Negotiating Contested Visions and Space-Specific Expectations of the Hydrogen Economy. Technology Analysis & Strategic Management, 18(3–4), 361– 374. https://doi.org/10.1080/09537320600777127 Edgerton, D. (2006). The Shock of the Old: Technology and Global History since 1900. Profilebooks. Ellul, J. (1954). La technique ou l’enjeu du siècle. Armand Colin. (transl. The technological society. New York: Vintage Books) Ellul, J. (1977). Le système technicien. Calmann-Lévy. (transl. The technological system. New York: Continuum, 1980) Franz, K. (2005). Tinkering: Consumers Reinvent the Early Automobile. Philadelphia: University of Pennsylvania Press. Fujimura, J. (1995). Ecologies of Action: Recombining Genes, Molecularizing Cancer, and Transforming Biology. In Ecologies of Knowledge: Work and Politics in Science and Technology (pp. 302–346). State University of New York Press. Gibson, J. J. (1979). The Ecological Approach to Visual Perception. Houghton Mifflin. Hyysalo, S. (2009). User Innovation and Everyday Practices: Micro-Innovation in Sports Industry Development. R&D Management, 39(3), 247–258. https://doi.org/10.1111/ j.1467-­9310.2009.00558.x Hyysalo, S., Jensen, T. E., & Oudshoorn, N. (eds.). (2016). The New Production of Users: Changing Innovation Collectives and Involvement Strategies. Routledge. Jasanoff, S., & Sang-Hyun, K. (2015). Dreamscapes of Modernity: Sociotechnical Imaginaries and the Fabrication of Power. Oxford University Press. Knorr-Cetina, K.  D. (1999). Epistemic Cultures: How the Sciences Make Knowledge. Harvard University Press. Latour, B. (1987). Science in Action: How to Follow Scientists and Engineers through Society. Harvard University Press. Latour, B. (1992). Where Are the Missing Masses? The Sociology of a Few Mundane Artifacts. In W. E. Bijker & J. Law (Eds.), Shaping Technology/Building Society: Studies in Sociotechnical Change (pp. 225–258). The MIT Press. Latour, B. (1993). The pasteurization of France. Cambridge and London: Harvard University Press. Mackenzie, D.  A., & Wajcman, J. (1985). The Social Shaping of Technology: How the Refrigerator Got Its Hum. Open University Press. Mackenzie, D. A., & Wajcman, J. (1999). The Social Shaping of Technology (2nd ed.). Open University Press. Marx, K. (1847). Misère de la philosophie. Frank. (transl. The Poverty of Philosophy. London: Twentieth Century Press, 1900.) Michael, M. (2000). Futures of the Present: From Performativity to Prehension. In N. Brown, B. Rappert, & A. Webster (Eds.), Contested Futures: A Sociology of Prospective Techno-­ Science (pp. 21–39). Ashgate. Mongili, A. (2007). Tecnologia e società. Carocci Editore. Oudshoorn, N. (2011). Telecare Technologies and the Transformation of Healthcare. Palgrave Macmillan.

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Pinch, T., & Bijker, W. E. (1984). The Social Construction of Facts and Artefacts, or how the Sociology of Science and the Sociology of Technology Might Benefit Each Other. Social Studies of Science, 14(3), 399–441. https://doi.org/10.1177/030631284014003004 Schnettler, B., & Knoblauch, H. (Eds.). (2007). Powerpoint-Präsentationen. Neue Formen der gesellschaftlichen Kommunikation von Wissen. UVK. Smith, M.  A. (1968). Process Technology and Powerlessness. The British Journal of Sociology, 19(1), 76–88. https://doi.org/10.2307/588544 Star, S.  L. (1995). Introduction. In S.  L. Star (Ed.), Ecologies of Knowledge: Work and Politics in Science and Technology (pp. 1–35). State University of New York Press. Strebel, I., Bovet, A., & Sormani, P. (Eds.). (2018). Repair Work Ethnographies: Revisiting Breakdown, Relocating Materiality. Springer. Traweek, S. (1988). Beamtimes and Lifetimes: The World of High Energy Physicists. Harvard University Press. Tutton, R. (2016). Wicked Futures: Meaning, Matter and the Sociology of the Future. The Sociological Review (Special Issue: Futures in Question: Theories, Methods, Practices), 65(3), 478–492. https://doi.org/10.1111/1467-­954X.12443 Vinck, D. (2019). Maintenance and Repair Work. Engineering Studies 11(2), 153–167. https://doi.org/10.1080/19378629.2019.1655566 Volonté, P. (2017). Il contributo dell’Actor-Network Theory alla discussione sull’agency degli oggetti. Politica & Società, 6(1), 31–60. https://doi.org/10.4476/86799 White, L. (1962). Medieval Technology and Social Change. Oxford University Press. White, R. L. (1964). Pesticides. Science, 145(3633), 729–730. https://doi.org/10.1126/science.145.3633.729 Winner, L. (1980). Do Artifacts Have Politics? Daedalus, 109(1), 121–136. https://www. jstor.org/stable/20024652 Woolgar, S. (1991). The Turn to Technology in Social Studies of Science. Science, Technology, & Human Values, 16(1), 20–50. https://doi.org/10.1177/016224399101600102 Wyatt, S. (2008). Technological Determinism Is Dead; Long Live Technological Determinism. In E. Hackett et al. (Eds.), Handbook of Science and Technology Studies (pp. 165–180). MIT Press. Yasuoka, K., & Motoko, Y. (2011). On the Prehistory of Qwerty. Zinbun, 42, 161–174. https://doi.org/10.14989/139379

Science, Technology and Gender

10

The expression “science and gender” encapsulates several different epistemological approaches and problems, which are, nevertheless, strictly interconnected, from both a historical and political point of view. In this chapter, we will be addressing them individually for the purposes of clarity, but it is worth remembering that, like all categorisations, this organisation is the result of a subjective decision. The history of feminist contributions to the study of science and technology has witnessed battles fought simultaneously on many fronts; it is therefore important to emphasise that the simplification, necessary in this context, does not do justice to the social, cultural and material complexity of the relationship between science, technology and gender.

10.1 Women in Science The history of the role of women in science presents two very different aspects. On the one hand, it is easy to think of a number of icons that have made their mark on history: the mathematician, philosopher and astronomer Hypatia (born in Alexandria in Egypt in the fourth century AD); the German abbess Hildegard of Bingen (1098–1179), scholar of medicine, botany and prolific writer; the philosopher Margaret Cavendish; the Italian mathematician Maria Gaetana Agnesi (Mazzotti, 2007); the English mathematician Ada Lovelace; the astronomer Caroline Herschel; or the French naturalised Polish Marie Curie, awarded the Nobel Prize for physics in 1903 and for chemistry in 1911; in the twentieth century the British biochemists Rosalind Franklin and Dorothy Hodgkin, the latter awarded the Nobel Prize for chemistry in 1964. Their personal stories have in © The Author(s), under exclusive license to Springer Nature Switzerland AG 2022 G. Gobo, V. Marcheselli, Science, Technology and Society, https://doi.org/10.1007/978-3-031-08306-8_10

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common perseverance, resourcefulness, a spirit of sacrifice and great talent. But if the stories of these women exert such a strong sense of wonder, it is also because, from many different perspectives, they conceal a reality that is anything but rosy. Until recent times (from just over a century to a few decades ago, depending on the country in question) women were in fact excluded from higher education and scientific professions. In the UK, for example, up until the second half of the nineteenth century, women were not allowed to undertake university studies. It was only in 1869 that the first seven female students were accepted into the University of Edinburgh. However, in the few months they could carry on their own studies, they suffered discrimination, defamation and persecutions. In the end, as if that were not enough, they were officially prevented from completing their studies. In the 150 years that separate us from these violent episodes, things have obviously changed a great deal; however, the inequalities are far from being entirely levelled, especially in certain spheres of scientific activity. Despite the huge variability between countries, the disparity between genders is an almost constant fact in every academic system. If the differences in the early stages of university education are being ironed out, it is during the academic career that the trend is reversed. If the number of women enrolled in scientific departments is now gradually increasing (sometimes even constituting most of the enrolments, as is the case for biology), it is during the subsequent phases that the disparities become striking: in scientific disciplines, the number of young women gradually falls in the transitions from enrolment in university until becoming professor and principal laboratory investigator, thus reaching a very small number of women holding senior positions. Using a famous metaphor, the US journalist and writer Natalie Angier compared this situation to a leaking pipe. However, the academic path is not the linear trajectory that this analogy appears to allude to (Etzkowitz et al., 2000; Lagesen, 2007) and the causes that lead to the decreases in the number of women vary greatly and can be traced back to social forces in action at different cultural levels. Let’s take a look at some of them. To begin with, the collective imaginary on scientific professions has undoubtedly masculine undertones. It is men, more than women, who are encouraged since childhood to develop an interest in scientific and engineering disciplines; far fewer girls, on the contrary, are offered constructive examples of female scientists to be inspired by Easlea (1986) and Orenstein (1994). The iconic models referred to at the beginning of this chapter are also, in a certain sense, disheartening, because they normalise the perception that female success should go hand in hand with a continuous battle against the prejudices of common sense.

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It is this backdrop of distrust in women’s ability to successfully undertake a scientific career that creates a situation whereby, already at a tender age, in those school systems in which it is possible to choose a particular direction, boys are encouraged to enter the scientific and engineering study path much more often than girls. Conversely, boys are discouraged from choosing disciplines considered closer to the “female sphere”, such as, for example, psychology, pedagogy, literature and art. For this reason, already at the start of higher education, it is possible to notice differences in terms of interest and preparation between boys and girls. The gap then becomes even more significant as one approaches the end of university. If the number of young women who achieve a PhD in scientific disciplines is quite similar to that of male colleagues, the latter, according to the statistics, will experience much more success (in terms of performance) in just a few years. What are the reasons for this? Some studies suggest that the committees for the selection of personnel and the evaluation of research are often made up of men who tend, unconsciously, to empathise more with young male researchers in whom they recognise a younger version of themselves (Sismondo, 2010). From women is thus implicitly expected a greater effort to prove their worth compared to that expected from their male colleagues (Wenneras & Wold, 2001). For many women, then, maternity constitutes the true bottleneck: the reduced productivity places them in a position of disadvantage compared to male colleagues. Furthermore, maternity leave is perceived by men as a “privilege”, further worsening the condition of inequity in which female colleagues find themselves. These stereotypes are also reinforced in the communication of science. A study by Barbercheck (2001) has shown how, in advertisements, science is often personified by male figures, especially when the message is associated with words such as “reliability”, “precision” and “speed”; it is only in the cases in which advertisements refer to concepts such as “easy”, “simple” and “natural” that images of women scientists and researchers are more likely to be found. One of the solutions that is often proposed to reduce this asymmetry is that of the so-called pink quotas, an active support for the insertion of more women in scientific institutions, bodies and companies. These policies do not merely aim to increase the number of women in organisations, but above all they seek to create structural and lasting mechanisms and trigger a virtuous circle. This strategy, however, cannot be but a temporary solution to an insidious problem. When this is not understood, the proposal of affirmative actions arouses perplexity in both men, who feel at times unjustly cast aside by a non-meritocratic mechanism, and women, who refuse preferential treatments that go against the principle of equality that the same affirmative actions seek to promote (Gobo, 2016).

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These structural responses aim to remedy a condition that is first and foremost cultural, rooted in the social fabric, in the expectations and habits that concern the way of life in the broadest sense. It is precisely by looking at this context—whose change might be very slow—that more immediate ad hoc solutions might be found. These should be able to bring about improvements in the short term but maintain the flexibility to be progressively adapted to the cultural needs. To this end, a reflection that looks beyond the mere statistical datum and questions the expectations held by men and women in their professional and family spheres is needed. Each field has its own specificities and any generalisation might be misleading. If, for example, we focus on academia and in particular on research evaluation criteria (the parameters that allow an individual to progress in the world of scientific research), we will notice that the research “assessment is primarily a social and political practice, guided by certain ‘theory-driven’, cultural assumptions (whether tacit or explicit) and by particular mental models of what makes a good researcher” (Gobo, 2016, p. 162). In other words, explicit criteria are based on an implicit system of deliberate assumptions of who is a good researcher. For example, frequently evaluation criteria are based on the quantity (rather than on the quality) of the scientific production of an individual. This criterion, with its roots in the ease of measurement and comparison rather than focusing on the appropriateness of the evaluation, places in a position of disadvantage those who have other duties outside of the work sphere, for example care givers (Gobo, 2016). The relationship between care giving and scientific output is especially meaningful because it is often one of the bottlenecks that places women at a disadvantage in the academic career. According to the report Status of Women in Sociology 2004: women may face serious disadvantages. Careers often are built … around a model of a worker who has no competing responsibilities to work and is able to devote full attention to (usually his) professional life. Persons who do not conform to this pattern of the unencumbered worker will be disadvantaged in achieving success within the profession.

By trying to understand the cultural models that underpin these evaluation criteria and the silent assumptions hidden beneath the surface, it will be possible to gradually improve the work conditions and adopt strategies that consider national contexts and their gradual changes. The situation is obviously very complex and every proposal has strengths and weaknesses. However, we like to point out that many of the causes that make academic or research difficult for a woman do not concern only the scientific sphere but also are part of a wider cultural heritage. A trend reversal must necessarily take this into account.

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10.2 The Construction of Gender and Critical Empiricism Feminist social studies of science and of technology, however, do not just stop at the level of the organisation of science as an institution: they also went on to investigate the very content of scientific knowledge, showing how it reflected the inequalities of social organisation. Within the multi-faceted feminist movement, those with a background in natural sciences (especially in biology) began to make their critical voices heard. Theories on sexual differences, reproduction, anatomy and so on were revisited from a feminist perspective which underlined the very strong political component of the contents themselves. These studies therefore had huge importance beyond the realm of gender studies as they were among the first to show the relationship between scientific knowledge, research practices and the cultural and political organisation of society. According to the American biologist, feminist and science sociologist Evelyn Fox Keller (1995, p. 28): the historically pervasive association between masculine and objective, more specifically between masculine and scientific, is a topic that academic critics resist taking seriously.[…]Unexamined myths have a subterranean potency; they affect our thinking in ways we are not aware of, and to the extent that we lack awareness, our capacity to resist their influence is undermined.

To counter biological determinism, the set of ideas that argues that social and behavioural differences have organic or biological causes, feminist theory draws from a notion that had originally been formulated by Simone de Beauvoir (1908– 1986) according to whom “one is not born, but rather becomes, a woman”. In other words, the characteristic traits normally associated with men and women are not “natural” but “cultural”. An initial strategy to distinguish the “cultural” from the “natural” was to differentiate the concept of sex from that of gender: where the former denotes being male or female according to biological characteristics, the latter refers to those cultural attributes that, from time to time, are associated with man or woman. A key element of this distinction is that the two pairs are not equivalent, in the sense that the female or male sexual characteristics do not correspond to being a man or a woman. The aim of this distinction was to take the first steps towards the deconstruction of conventions hitherto considered natural distinctions. At the end of the nineteenth century, for example, Patrick Geddes and Arthur Thompson, two British naturalists, attributed the different predisposition of men and women towards politics to the hypothetical differences found in their metabolic systems: where women showed passive and disinterested behaviour due to their presumed tendency to

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c­onserve energy, men were instead inclined to dissipate any energy in excess, therefore showing a more active approach towards life and a more passionate political attitude. This theory not only attempted to understand the differences and to explain them through alleged biological reasons but resulted in justifying and reinforcing the absence of women from the political sphere, discouraging their involvement to preserve their health. Many case studies proposed by feminist scholars were drawn from theories— historical and contemporary—on reproduction and anatomy (see Box 10.1). However, if it is easy to be surprised by the implicit assumptions of outdated paradigms, it is very difficult to perceive the gender inequalities inscribed in contemporary scientific theories. An example of this is the description of sperm as an active agent of fertilisation and the female oocyte as a passive receiver: thanks to the push provided by the feminist movement, recent research has shown that the egg cell also possesses an active character; as such, the definition of fertilisation has been reformulated as that process in which the egg cell and sperm meet and mutually collaborate (Gherardi & Perrotta, 2011; Martin, 1991). Box 10.1  Why Are Mammals Called... Mammals?

In 1758, in the tenth edition of the Sistema Naturae, the Swedish botanist Linneo introduced the term mammalia (that we could translate with the expression “those with breasts”). The term was intended to refer to the members of that class of vertebrates who until then, following Aristotle, were called quadrupeds. After Linneo, however, they would always be called “mammals”. In performing this linguistic transformation, the famous botanist considered only one of the many properties common to mammals and, what is more, only for the females of that species. The historian of biology Londa Schiebinger (1993) argues that linguistic choice was not the only one possible. Linneo, in fact, had other alternatives or equivalent definitions, always relating to the properties of mammals, such as pilosa (“those with hair”), aurecaviga (“those with hollow ears”), lactentia or sugentia (“those suckling” or “those sucking”) and vivipora (“those who raise the young”), which, however, he did not choose. So why then did Linneo prefer the term “mammal”? In beginning to define a response, the scholar notes that mammalia sounds good from a phonetic perspective because of its easy assonance with respect to the terms animalia and mamma, the latter one of the first words present in a child’s vocabulary. Furthermore “Linnaeus’s fixation on the female mammae” (see p. 404) became part of a cultural process of eroticisation of the female breast which, in those years, reached its pinnacle, also with very visible results in the history of clothing. In addition, Linneo was also politically

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locked in a socio-cultural battle against the habit of letting nurses breastfeed their children, which was becoming popular among women of all social classes: in 1780 in Paris and Lyon, for example, 90% of new-borns went to wet nurses (see p. 404). In fact, to stem this practice that was at the time frowned upon, in 1793 France (and immediately afterwards in Prussia), a law was brought out, the aim of which was to promote maternal breast-feeding. Linneo considered nurses’ breast-feeding a social catastrophe while, according to him, mothers’ breast-feeding was harmonious with the natural law, a benign practice both for the new-born and for the mother. This battle also barely concealed a more general aversion to female emancipation, in an attempt to return the woman to the traditional domestic role. Schiebinger also observed the different treatment that Linneo reserved for the female sex and for the male sex, given that he introduced the expression Homo sapiens to identify the human species. This step is particularly interesting because if on the one hand it unites our species with the  other mammalians through a distinctive attribute of the woman (the breasts), on the other it uses another attribute (prejudicially, especially at the time of Linneo) of men (reason) to distinguish the human from the animal species. ◄ A fundamental question remains: what is the relationship between (1) the change of metaphors used to describe the female and the male role in reproduction; (2) the development of new techniques and new instruments for the representation of these processes; (3) a greater awareness towards sexual equality? According to Fox Keller, the study of examples, such as that just described, allows us to reconstruct the influences and the interactions between cultural conventions, metaphors and scientific and technological development. The author advocates an approach that takes the name of critical empiricism, according to which the pursuit of feminist ideals can be integrated with the scientific enterprise and improve it from within. Greater awareness of the silent assumptions that underpin theories contributes to making science itself more objective and rigorous.

10.3 The Standpoint Theory and Situated Knowledge This optimism was not shared by those feminist scholars who embraced the so-­ called standpoint theory, an expression coined by the American feminist philosopher Sandra Harding (1986, 1992, 2004) to describe the theoretical perspective according to which knowledge derives from one’s own social positioning.

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This approach is based on two Marxist assumptions. The first argues that those who come from an oppressed class have a privileged access to knowledge which would not be available to the members of the privileged classes. The second states that in Western societies, characterised by the stratifications of gender, class, ethnic origin and so on, the social position that an individual occupies in the community determines what they may know. Starting from these two assumptions, feminist writers began to examine how the inequalities between men and women had influenced the production of knowledge. According to Harding, science, being an (almost) exclusive domain of men—having ignored and contributed to the marginalisation not only of women but of other oppressed social groups too—cannot be said to be objective and cannot boast an impartial and objective access to the natural reality. Unlike feminist critical empiricism (the aim of which is to make science more rigorous), standpoint theory argues that some perspectives (such as those of people on the fringes) are more lucid, clearer and disenchanted because they are more aware of the conditions of their own oppression. Consequently, it is precisely approaches such as the feminist one that, better than others, can define new research questions and scientific priorities, and produce self-critical and coherent knowledge. In response to Harding’s position, in 1988, the celebrated American philosopher Donna Haraway published an essay entitled Situated Knowledges: The Science Question in Feminism and the Privilege of Partial Perspective. She argued that no knowledge is privileged or innocent, not even that of the oppressed. Each perspective is situated in local, cultural logics and within power relations. It is thus necessary to abandon forever the ideal of objectivity and instead aspire to enhancing the specificity of each perspective and their mutual integration. Haraway (1988) uses the metaphor of “vision” to illustrate what she means by “situated knowledge” and how this differs from the previous epistemological concepts. The author compares objectivity to what she calls God Trick, a kind of vision based on the illusion of eliminating the knowing body, adopting a vision from “nowhere”, that is disinterested and impartial. However, this type of gaze is impossible to assume: each time we observe something, we inevitably see it from a certain perspective, determined by our position. Vision is always and unavoidably situated, embodied, limited and never innocent. In a nutshell: according to Haraway, this awareness is the closest one can get to objectivity. It is therefore necessary to abandon the ideal of a transcendental and divine objectivity and embrace the many possible partial, multiple, highly specific, active and never complete ­perspectives. Haraway’s philosophy is based on the need to overcome dualisms because, starting from Descartes, Western culture has always been underpinned by a binary

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structure, revolving around oppositional dichotomies: body/mind, man/woman, natural/artificial. These pairs are not symmetrical but are based on the superiority of one of two elements which exercises power over the other. These asymmetrical dualisms have historically been functional in subjugating not only women but a multitude of social classes and subordinate categories: nature was dominated by culture, working classes by capitalist ones, animals by man. Box 10.2  Queer Theory

So far, we have addressed the social construction of gender inequalities following a binary distinction. This is also a fictitious choice: not only is gender today considered a fluid category but the determination of the sex of an individual is also a much more sociologically complex matter than a simple binary category. Used with a derogatory meaning towards homosexuals in the nineteenth century, the term queer literally means “strange”, “bizarre” and comes from the German quer that means “askew” (its metaphorical use in fact counters “straight”, a normative term used as a synonym of “heterosexuality”). The term entered the academic reflection in the 1990s when at the University of California in Santa Cruz a conference entitled Queer theory. Gay and lesbian sexualities was organised. The intention was, on the one hand, to present a refusal of heteronormativity (the tendency to consider heterosexuality as a term of comparison for every other orientation); on the other, the organisers set out to go beyond the monolithic representation of homosexuality to instead highlight its intrinsic heterogeneity, the variety of choices, of expressive forms and of symbolic-­ material conditions of existence. Queer studies are, in a certain sense, a re-elaboration of the feminist critique of the idea that male and female are only natural facts or universal identity categories. Each identity category is, instead, the historical result of a particular social and cultural order. Discussing heteronormativity, queer studies aspire to inclusivity and the valuing of differences. From an STS perspective, the aim is to investigate all those subjects until recently obscured by historical social narratives, especially in relation to the production of scientific knowledge and to the technological dimension. Further Readings Butler (1990) De Lauretis (1991) Turner (2000) ◄

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To move beyond these dual logics, Haraway (1985, 1991) proposes the science fiction figure of the cyborg, a hybrid, at the same time human and machine, situated beyond gender categories, suspended between fantasy and reality. The cyborg is meant as a metaphor of the human condition: we are all, to a certain extent, hybrids. Science and technology are already an integral part of our bodies (see Sect. 5.5.2). The opposition between natural and artificial, or biological and cultural, therefore loses meaning as they are no longer clearly distinguishable. Not only this but the other fundamental dichotomies of Western thought also wane: man/woman, machine/human, object/subject. The cyborg manifesto, in which Haraway grounds her philosophy about partiality and specificity, goes against the positions of traditional feminism as she claims that there is nothing “natural” that binds all women together in one category. Every category with which an individual identifies is in itself highly complex, constructed within discourses and practices of the body: each individual is many things together and at the same time can never be defined once and for all. Identities are multiple, continuously being constructed, always partial and yet unique in their specificity. The cyborg definitively moves away from essentialist positions.

10.4 Gender and Technology The word technology has often a decisively masculine connotation. Tractors, mechanical equipment of any kind, IT devices, cars and so on are linked to an imaginary which was created at the end of the nineteenth century together with the consolidation of the professional figure of the engineer, dominated in the US by elite middle-class white men. The US historian Ruth Oldenziel, in Making Technology Masculine, reconstructs the process during which instruments and practices for weaving, spinning and embroidery—formerly considered on a par with all other technological devices—slowly began to be debased. It is in the context of “applied engineering” that the concept of technology is used with reference to a civil and military industry in which production, management and consumption are dominated, almost exclusively, by men. It is precisely to counter this stereotype of the woman as technically incompetent or detached from the world of technology that a series of studies from the 1980s onwards focused on domestic technologies. A paradigmatic example is that of the microwave oven: technological descendent of the radar, the first civilian use of this technology was that of an instrument to heat precooked foods, intended primarily for single men. As such, the microwave was included in the category of “brown” home appliances (i.e. products for entertainment and free time).

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Configured as such, the microwave did not gain a foothold and was therefore re-proposed in other guises, those of white household appliances, essentially becoming one of those products proposed for housewives to support the management of household chores (this category also includes refrigerators, freezers, washing machines, etc.). But this was not the only change: whole families were involved in the rebranding of the microwaves to understand the practices and expectations within which this new appliance was inserted. Besides the defrosting and rapid cooking of certain types of food (to adapt to the new working habits emerging in that period), a number of functions were also added for the cooking of more traditional foods such as, for example, the traditional British jacket potato. In this emblematic example, gender is not solely materialised at the time of planning (which, in fact, at first diverged hugely from the trajectory that the microwave oven would then follow), but it is articulated and re-articulated into the various phases of its development and promotion. During the same years—thanks to the appearance of “disruptive technologies”, in other words technologies that disrupt traditional habits and legacies, and the growing popularity of feminist perspectives in the field of scientists—studies on gender and technology moved further away from determinist positions and drawing on contributions such as that of Donna Haraway and embraced a more marked optimism towards the emancipative possibilities offered by innovation. The spheres in which the so-called cyberfeminism (a theoretical position whose reference to the cyborgs theorised by Haraway becomes explicit) sees possibilities of redemption are many: for example the biomedical technologies for fertility that not only redefine the reproductive process in socio-technological terms, but also fragment them into various manipulable and upgradeable phases, removed from the physicality of the body (such as, for example, in the case of in vitro fertilisation). Another example is prosthetic technologies (the fabrication and custom fitting of artificial limbs) which gives shape to hybrid individualities, capable of subverting pre-existing situations, making them fluid, giving back to technoscience a performative capacity to create new meanings, new identities and redefine normality. In particular, it is information technologies that lie at the heart of the hopes of redemption. The web, in fact, is based on horizontal networks rather than on vertical hierarchies and therefore appears more democratic and emancipatory. And not only this, the virtuality that characterises the web is perceived as liberating with respect to the constraints of the physicality of the body. Over the following decades, however, this optimism often proved illusory. Today, for example, the prevalence of an image-based culture, especially on social media that occupy an increasingly central position in communication, makes the

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web a very powerful channel for the dissemination of sexism and gender stereotypes. The US sociologist Ruth Schwartz Cowan, in her famous work More Work for Mother, shows how domestic technologies, spread with the promise of alleviating the workload of housewives, turned out to be instruments of oppression instead, as they redefined and increased the expectations heaped on those who take care of the house. Even in the case of house management, the trajectory of domestic technologies intersects with that of IT especially since remote and agile working have burst into the daily life of many families. The boundary between professional and private life has blurred, perhaps even disappeared with a consequent redistribution of the work, to the detriment of the categories traditionally more oppressed by social and cultural expectations (Wajcman, 2018). Over the last half a century, feminist studies on technology have contributed to the theorising of the relationship between gender and technology in a relationship of dynamic mutual modelling (Faulkner, 2001). Thanks to the contribution of scholars such as Judith Butler, gender is redefined in processual terms, in other words as continuously reproduced in social interaction. Technology and gender are not only socially constructed but are also interconnected and mutually modelled, the result of complex and iteratively transformative processes. Exercise

The feminist reflection has developed, from its very beginnings, within circles that not only include intellectuals of the academic world but also a wide array of artists and thinkers of all kinds. These environments have been fertile ground for the development of a series of experimentations, such as, for example, feminist science fiction, which constitutes an excellent exercise of scientific thought as it creates contexts and narrations that entwine with scientific imaginaries and futuristic technologies. Science fiction writers create the opportunity to question the very social norms that we all normally take for granted, altering the perspective of the reader and thus creating paradoxical and provocative situations. If your science fiction imagery is a universe populated by characters and situations with a strong masculine connotation, we suggest here a number of titles that will surely make you change your mind. Form groups. Each group will agree on the reading of a title from those proposed below (or search among the many other novels or stories of feminist science fiction: indulge yourself!). Then share the reflections prompted by the reading, focussing in particular on the way in which science, technology and society intersect in these imaginary universes.

References

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Joanna Russ, Female Man, 1975 Ursula Le Guin, The Left Hand of Darkness, 1969 id., The Matter of Seggri, in The Birthday of the World and Other Stories, 2002, Margaret Hatwood, The Handmaid’s Tale, 1985 Marge Piercy, Woman on the Edge of Time, 1976

Check Your Preparation

1. What is meant by the metaphor of the leaking pipe? Why is this metaphor considered simplistic? List some of the causes that result in a decrease in presence of women within the scientific community. 2. What is meant by critical empiricism? 3. What is standpoint theory? What political-philosophical movement inspired Sandra Harding? In what way? 4. What is a cyborg? How is this hybrid figure inserted in the context of feminist and STS reflection? Further Reading Fox Keller (1995) Haraway (1991) Harding (1986) Harding (1992) Ormrod (1994) Ortner (1972) Oudshoorn (1990)

References Barbercheck, M. (2001). Mixed Messages: Men and Women in Advertisements in Science. In M. Wyer et al. (Eds.), Women, Science, and Technology: A Reader in Feminist Science Studies (pp. 117–131). Routledge. Butler, J. (1990). Gender Trouble. Feminism and the Subversion of the Identity. Routledge. De Lauretis, T. (1991). Queer Theory. Gay and Lesbian Sexualities. Indiana University Press. Easlea, B. (1986). The Masculine Image of Science with Special Reference to Physics: How much Does Gender Really Matter? In J.  Harding (Ed.), Perspectives on Gender and Science (pp. 132–159). The Falmer Press.

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Etzkowitz, H., Kemelgor, C., & Uzzi, B. (2000). Athena Unbound: The Advancement of Women in Science and Technology. Cambridge University Press. Faulkner, W. (2001). The Technology Question in Feminism. Women’s Studies International Forum, 24(1), 79–95. https://doi.org/S027753950000166710.1016/ S0277-­5395(00)00166-7 Fox Keller, E. (1995). Gender and Science: Origin, History and Politics. Osiris, 10, 26–38. https://doi.org/10.1086/368741 Gherardi, S., & Perrotta, M. (2011). Egg Dates Sperm: A Tale of a Practice Change and Its Stabilization. Organization, 18(5), 595–614. https://doi.org/10.1177/1350508410393057 Gobo, G. (2016). The Care Factor: A Proposal for Improving Equality in Scientific Careers. In M.  Bait, M.  Brambilla, & V.  Crestani (Eds.), Utopian Discourses across Cultures. Scenarios in Effective Communication to Citizens and Corporations (pp. 157–183). Peter Lang. Haraway, D. J. (1985). Manifesto for Cyborgs: Science, Technology, and Socialist Feminism in the 1980s. Socialist Review, 80, 65–108. https://doi.org/10.1080/08164649.1987.996 1538 Haraway, D.  J. (1988). Situated Knowledges: The Science Question in Feminism and the Privilege of Partial Perspectives. Feminist Studies, 14, 575–599. https://doi. org/10.2307/3178066 Haraway, D. J. (1991). Simians, Cyborgs and Women. The Reinvention of Nature. Routledge, Free Association Books. Harding, S. (1986). The Science Question in Feminism. Cornell University Press. Harding, S. (1992). Rethinking Standpoint Epistemology. What Is “Strong Objectivity”? The Centennial Review, 36(3), 437–470. https://www.jstor.org/stable/23739232 Harding, S. (2004). The Feminist Standpoint Theory Reader: Intellectual and Political Controversies. Routledge. Lagesen, V. A. (2007). The Strength of Numbers: Strategies to Include Women into Computer Science. Social Studies of Science, 37, 67–92. https://doi.org/10.1177/0306312706063788 Martin, E. (1991). The Egg and the Sperm: How Science Has Constructed a Romance Based on Stereotypical Male-Female Roles. Signs, 16, 485–501. https://doi.org/10.1086/494680 Mazzotti, M. (2007). The World of Maria Gaetana Agnesi, Mathematician of God. The John Hopkins University Press. Orenstein, P. (1994). School Girls. Doubleday. Ormrod, S. (1994). “Let’s Nuke the Dinner”: Discursive Practices of Gender in the Creation of a New Cooking Process. In C. Cockburn & R. First-Dilić (Eds.), Bringing Technology Home: Gender and Technology in a Changing Europe (pp.  42–58). Open University Press. Ortner, S. B. (1972). Is Female to Male as Nature Is to Culture? Feminist Studies, 1(2), 5–31. https://doi.org/10.2307/3177638 Oudshoorn, N. (1990). Endocrinologists and the Conceptualization of Sex, 1920–1940. Journal of the History of Biology, 23(2), 63–86. https://doi.org/10.1007/BF00141469 Schiebinger, L. (1993). Why Mammals Are Called Mammals: Gender Politics in the Eighteenth-Century Natural History. The American Historical Review, 98(2), 382–411. https://doi.org/10.2307/2166840

References

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Sismondo, S. (2010). An Introduction to Science and Technology Studies (2nd ed.). Wiley and Sons. Turner, W. B. (2000). A genealogy of queer theory. Temple University Press. Wajcman, J. (2018). Digital Technology Work Extension and the Acceleration Society. German Journal of Human Resource Management: Zeitschrift für Personalforschung, 32(3-­4), 168–176. https://doi.org/10.1177/2397002218775930 Wenneras, C., & Wold, A. (2001). Nepotism and Sexism in Peer-Review. In M. Lederman & I. Bartsch (Eds.), The Gender and Science Reader (pp. 42–48). Routledge.

Part III Contemporary Fields of Inquiry

Environment

11

Human-induced climate change is today a major concern for researchers, politicians, farmers and ordinary citizens; its consequences increasingly appear on the front pages of newspapers (unlike many other pieces of perhaps noteworthy scientific news) and environmental movements are reaching an ever wider and more diversified public and pool of activists. The Fridays for the Future, the global movement organised in the wake of the school strikes started by Greta Thunberg in Sweden, has involved not only young people but also people of all ages and from all over the world. The intensification of the consequences of climate change— such as hurricanes, floods and drought—and an increasingly shared and widespread system for the monitoring of ecosystem dynamics have placed the environment at the centre of public and political life. Unfortunately, the problems related to climate change are presented in a simplistic way, while in fact the issue is much more complex. For example, debates are multiplying on what exactly climate change consists of, what measures must be adopted and, above all, how quickly it is necessary to act. In this regard, we are witnessing an interesting (and alarming) phenomenon: on the one hand, reassuring and non-alarmist positions are increasingly marginalised among both climatologists and geologists and in the public debate; on the other hand, they are often ridden by governments with the intent of adopting minimalist environmental policies. Furthermore, the problem is not only of a scientific or technological nature, but inevitably involves many spheres of contemporary life: current and future lifestyles, economy, politics, local traditions and industrial innovation on a global scale. In this scenario, social sciences and humanities can make a significant contribution, starting from the following questions: why, if the process of climate change © The Author(s), under exclusive license to Springer Nature Switzerland AG 2022 G. Gobo, V. Marcheselli, Science, Technology and Society, https://doi.org/10.1007/978-3-031-08306-8_11

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began a long time ago, is it only now that we are realising its severity? Is there a link between contemporary society and the “discovery” of climate change? Why, despite the almost total agreement on the urgency to act, do environmental policies remain so contentious? What exactly does the expression “climate change” refer to? For some, it is synonymous with the urgency to recycle and embrace a more sustainable lifestyle; for others, it conjures up images of catastrophes, hurricanes and drought; it can even evoke fears of whole habitats disappearing, mass extinctions and the degradation of biodiversity in remote locations of the planet, or the extinction of bees, birds, bats and other animals which, up until a few years ago, were part of our everyday life. Everyone agrees on the fact that these problems are due to humans’ abuse of the environment; however, the link between them is often overlooked. How then do knowledge, socio-technical imaginaries, ideologies, economic systems, innovations and policies meet on this plural and multifaceted terrain? These questions and many more besides can only be answered if we study the way in which knowledge is shared, legitimised, accepted or rejected, not only within the scientific community but also beyond its (always flexible) boundaries. For this reason, this chapter is not only dedicated to climate change, but it addresses many forms of knowledge rooted in the interaction between humans and the environment, of which undoubtedly climate change represents a particularly significant example.

11.1 The Cultural Construction of Nature Try to visualise “nature”; what springs to mind? A crystal-clear blue sea, a beach covered in fine white sand, luxuriant palm trees? The sound of the wind, the chirping of birds? These picture postcards of a seemingly untouched nature stem from a profoundly cultural imaginary. They are ideal images made popular through tourist industry advertising, by adventure stories (such as Robinson Crusoe, for example) and by the cinema. They are familiar to all of us, even to those who have never left their urban landscape, as they represent topoi, that is not only physical places but also commonplaces, narrative patterns pervasive in the Western world (Heise, 2008; Yearly, 2005). At the same time, depending on the activity we are undertaking and the experiences that we have matured, each of us will recognise completely different scenarios in the same landscape. Just think, for example, of what a farmer, a builder and a hunter see when looking at the open countryside. In each scenery, therefore, we reflect, first and foremost, our cultural identity (Greider & Garkovich, 1994).

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And pristine nature, is that too a cultural product? Yes, according to the American science historian William Cronon (1996): on this matter, read Box 11.1. Box 11.1  The Cultural Nature of the “Wild Lands”

Up until just over two centuries ago, “wild” nature was considered either a wasted resource for the community because agricultural production was not ­being exploited or a risk for the individual, as there was no control over potential dangers. Occupying a land, therefore, was, in a certain sense, the same as rescuing it from a state of chaos and giving it an order. One century later, however, what previously had been perceived as endless expanses of land with no intrinsic value became a treasure to be preserved. What had changed? According to William Cronon, it was two cultural constructs that contributed, in their own particular ways, to this reversal of perspective: On the one side, the idea of the “sublime” introduced by European romanticism, which is the sentiment of confusion and terror and, at the same time, of presence of the divine, stirred by majestic places, such as the tops of mountains, abysses, the skies filled with menacing clouds and so on. It was with the advent of tourism, in the second half of the nineteenth century, that the sublime was tamed, essentially by those who sought it out and who celebrated its non-human beauty. What had previously been a terrifying experience of the divine evolved into a literary metaphor of the “mountain as cathedral”*. The second concept, according to Cronon, is instead that of the “frontier”: if on the one hand it represents the vigour and the independence that cemented the national characteristic of the US, on the other, the frontier exists in only a temporary horizon. In fact, having reached the Pacific Ocean, the expansion towards the West ended and nothing more remained of the US frontier apart from the myth of “origins”, a place in which to temporarily escape, to withdraw from urban life and to return to a more “authentic” existence. The notion of a pristine nature is the merging, according to Cronon, of these two ideals. With this example he sought to highlight two problems: the first is that the image of pristine nature, virgin and wild, is not a “natural” idea but a perception of a profoundly cultural environment. Furthermore, it seeks to present the conviction that the (presumed) pristine nature might represent an ideal to be aspired to as the antithesis of ecological degradation. If in fact we image that nature, while being preserved, should have nothing to do with humans, then, according to Cronon, we condemn ourselves to a bleak future. According to this logic, it is only by seeking to imagine an ecological model in which human beings are an integral part of nature that we can conceive of the roads we can take towards a more sustainable future.

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* John Muir, the naturalist who first contributed to the construction of the US natural parks, used this metaphor several times in his writings. “Yonder, to the eastward of our camp grove, stands one of Nature’s cathedrals, hewn from the living rock, almost conventional in form, about two thousand feet high, nobly adorned with spires and pinnacles, thrilling under floods of sunshine as if alive like a grovetemple, and well named ‘Cathedral Peak’”. (Muir, 1911. pp. 196–7) ◄ If it is not difficult for us to accept that the relationship between nature and society is historically determined, are we willing to maintain the same stance even when science comes into play? Or can science, unlike all the other worldviews, provide an “objective” and “neutral” representation of what exists beyond us? As we have seen in the previous chapters, science and technology construct their own object of study. They do so in laboratories where they impose on natural phenomena timing and methods that would not exist elsewhere (see Sect. 7.3), through cultural categories and typologies imposing on the world an order that is not inscribed in the objects themselves (see Sect. 2.4); through social institutions, such as gender, that act in a performative manner, creating and recreating the very status they define (Chap. 10); through authority and research for the consent that transform an assertion into a scientific fact (see Sect. 5.5); finally, through the co-­construction of science and social order (Jasanoff, 2005), because many of the existing policies are sustained by scientific data that construct the rules of the world as it should be. Even science, therefore, constructs representations of nature and of the physical environment from a perspective that is historically, culturally and socially situated to “reflect and configure being in the world” (Soja, 1989, p. 25).

11.2 Climate Change In debates on the environment, science and technology play a dual role: on the one hand, they are, in a certain sense, the cause of environmental upheaval; on the other, they offer privileged interpretations to understand and remedy such radical changes. If it is true that our planet has always alternated periods of glaciation and significant increases in temperature, these however have taken place over a period of time of tens of thousands, if not millions, of years. On the contrary, today climate change is unfolding, according to scientists, at an unprecedented speed as a result of anthropogenic activities. Science and technology, which constitute the beating heart of contemporary society, are therefore seen simultaneously as both cause and necessary instruments to solve the many problems that we face today.

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In a sense, this ambivalence has somehow inhibited sociologists of science from entering into this debate (Yearly, 2005). Indeed, if on the one hand their contribution, in the context of the very explicit way in which human-induced climate change blurs the boundary between society and nature, is now more than ever essential, on the other, it places them in the awkward position of those who, ­questioning scientific “progress” and underlining the social nature of knowledge, can be accused of undermining any possibility of redemption (e.g. Crist, 2004). If they claim that environmental problems, like the environment itself, are socially constructed, are they not perhaps running the risk of weakening the political and ethical position of those who are forcefully demanding greater attention to the planet? According to the environmental sociologist Elizabeth Bird (1987, p. 260), Not at all, because we recognize environmental problems through a variety of health, survival, moral, empathetic, aesthetic, political, economic and cultural interests. Those interests, grounded in individual, collective, historical, cross-cultural, and visionary experience, are socially constructed (negotiated through time) and socially interpreted (through received metaphors, stories and ethics). But that does not diminish their role as a legitimate ground for political claims. On the contrary, their very historicity gives them enormous normative weight. (Bird, 1987:260)

Indeed, the complex and multifaceted issue of climate change offers a privileged ground to explore the continuity between science, technology, culture, politics, economy and society. Let’s take, for example, the definition of “climate change” of the UNFCCC (United Nations Framework Convention on Climate Change)—a non-binding international treatise also known as the Rio Agreement—that considers it as a change “that is attributed directly or indirectly to human activity that alters the composition of the global atmosphere and that is in addition to natural climate variability observed over comparable time periods”.1 This definition, conceived in the early 1990s, has its roots in the 1960s and 1970s when, thanks to substantial state funding, the so-called Earth System Science emerged. This discipline, for the first time, studied our planet as a single system, composed of highly interconnected mechanisms (Uhrqvist & Lövbrand, 2014). This approach emerged in conjunction with space exploration (Moore Daly & Frodeman, 2008), both for the so-called overview effect, that is, the possibility of observing the Earth from a distance and in its entirety (White, 1987), and because of the parallel development of instruments (such as satellites and computers) that provided the computing power necessary for the development of large-scale mathematical models. These instruments began to make a new approach to climate possible, but it was only in  https://unfccc.int/files/press/backgrounders/application/pdf/press_factsh_science.pdf

1

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the 1970s, in the wake of works such as Silent Spring (1962) by the American ­biologist Rachel Carson and Gaia (1979) by the British chemist James Lovelock,2 that the first environmental movements began to take shape. More than 50 years later, however, not only has the problem of climate change not been solved, but its effects have become ever more dramatic. Climate change has grown into an extremely complex problem, from both scientific and political points of view: how can we perceive and conceive of climate change? What spatial and time scale should we adopt to properly apprehend it? What other phenomena does it intersect? How can we provide exhaustive representations that convey a message that can be understood and shared by the general public? And how can we reconcile local and global representations when these seem to be in conflict? Predictions on future climate developments are technically very difficult and characterised by a high degree of uncertainty. For a long time, activists and climate advocates hoped that improved scientific evidence would persuade governments (even the more reluctant ones) to adopt measures for environmental sustainability. Scientists and politicians believed that climate change could be better understood and managed by identifying a series of measurable natural and social forces that could be aggregated in large-scale models in such a way as to be able to make predictions for the future and to use them as inputs to ratify adequate and efficient strategies (Jasanoff & Wynne, 1998). This belief was based on two misleading assumptions. The first is that environmental policies can be directly extrapolated from scientific knowledge; in fact, even a unanimous agreement on the nature of climate change would not imply an equally unanimous agreement on the environmental policies to be adopted to counteract its effects. Any intervention will (inevitably) present advantages for some actors and disadvantages for others, who will therefore seek to propose alternative, perhaps less drastic and ultimately less efficient, solutions. Furthermore, the consequences of climate change are often indirect, in the sense that the most disastrous effects in fact occur in those regions of the world that least contribute to global pollution (ibid.): the large-scale deforestation of the Amazon rainforest, for example, is having an impact on the temperatures and rainfall in the Tibetan region (Snyder et al., 2003,  in Steffen, 2011). The second fallacious assumption concerns scientific evidence itself: sometimes, the demand for more or better evidence by policy makers has been interpreted by environmentalists as an attempt to delay or avoid action  James Lovelock formulated the theory of Gaia while he worked for NASA designing experiments and observations to determine if forms of life might exist on Mars (or on other planets of the Solar System). It was precisely this problem that induced Lovelock to reflect on the relationship between environment and forms of life. 2

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(Yearly, 2005).3 The problem therefore regards the very definition of scientific evidence and the rhetorical use that social actors make of it. In 2009, the publication by a hacker of an exchange of emails between scientists regarding climate data raised suspicions  about the entire community of climate scientists. The email exchange showed—in an unprecedented way—the social background and the demanding work that scientists perform to “construct” data, to condense the huge number of measurements collected into usable information to formulate models, theories, and experiments. The Spanish sociologist of science Meritxell Ramírez-i-Ollé, following this episode known as “climategate”, tracked for an entire year the work of a group of Scottish dendroclimatologists in their efforts to reconstruct prehistoric climate. According to Ramírez-i-Ollé (2019, pp. xii–xiii), rather than providing more context […] by explaining that scientific facts are a product of human labour and negotiation […] some scientists criticised the very social processes and influences that constitute the practical reliability of all sciences. […] By upholding a conventional and very false image of the procedures of science, scientists might have inadvertently given weaponry to the critics of climate science who—because of bad faith or genuine ignorance—uphold scientific standards that no science will ever reach. If climate scientists continue romanticising their work (or allow others to do so), they will likely generate further public distrust and cynicism. After all, we should not be surprised that educated and well-informed people look for alternative explanations and experts when things do not turn out to be quite as they were always told.

In her epistemography,4 Ramírez-i-ollé describes the work of the dendroclimatologists who reconstruct the evolution of prehistoric climate using vegetation coring. Their work includes two notions that are difficult to identify and define, from both an empirical and a conceptual point of view: “climate” and “change”. Climate is an abstraction of the weather which we all experience. But, according to the philosopher Dale Jamieson, it is precisely because individual experiences are highly variable, even in the short or medium term that it is extremely difficult to reach a common understanding and consensus on climate change. Indeed, ­almost every aspect related to climate change is contested on one or more fronts: whether  At times, quite the opposite happens: in the context of the introduction of 5G (the fifthgeneration technological standard for cell phone networks), of OGM and so on, it is conversely environmentalists who are demanding more data. As such, the so-called principle of precaution (i.e. a policy of proceeding cautiously regarding political and economic decisions on the management of scientifically controversial matters) is being exploited on both fronts. 4  A word coined from the fusion of “epistemology” and “ethnography”. 3

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it is real, whether it is anthropogenic, whether it actually constitutes a problem, if there is a solution and, if so, what counts as a satisfactory one (Jamieson, 2011). What is even more difficult is acting in a way that involves a joint effort. This is partly because, in the case of the environmental emergency, experience and action seem to exist at multiple levels: if, in fact, there is a huge local and regional variability in the way the climate is experienced, the measures of the emission reductions are instead negotiated and adopted globally. The need for a collective response creates another fundamental challenge for negotiators: climate change is indeed profoundly unfair (Gardiner, 2004). The richest nations have used much of the atmosphere’s capacity to absorb waste from industrial metabolism, leaving little leeway to developing countries, too little to take their own population out of poverty. Therefore, not only are the responsibilities not equally distributed but the consequent moral and ethic dilemma (Baer, 2006) is made even more pressing by the fact that the effects of climate change have so far been milder in richer and industrialised countries. In part, this is due to a geographic issue: at higher latitudes, where most wealthy countries are located, the effects of climate change are less severe while countries in tropical and subtropical zones are often victims of phenomena such as floods and drought, opposite but equally destructive events. But that is not all. The greater economic availability of industrialised countries translates into a higher structural capacity to adapt to an increasingly changing climate (Steffen, 2011). If at the start the role of social sciences seemed simply that of contributing to the scientific agenda, highlighting which areas of climate change would have an impact on the quality of life, in reality sociologists have demonstrated to be equipped to dig into the complexity of climate change, exploring how problems are articulated in the research process, the production and validation of scientific knowledge and its role in political decisions. In addition, sociological research has shed light on the origins of controversies and uncertainties in public policy making (Jasanoff & Wynne, 1998). According to the Australian sociologist Will Steffen (2011, p. 31), There is no doubt scientifically that the emission of greenhouse gases, predominantly carbon dioxide, from the combustion of fossil fuels lies at the heart of the climate change problem. […] However, there is a significant—and growing—body of scholarship that focuses on global change rather than only on climate change, and views climate change as a symptom of a much deeper problem that centers on the fundamental relationship of humanity with the rest of nature.

As suggested by Steffen, climate change can be included within a wider process that not only involves climate and greenhouse gas emissions but also their socio-­

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economic roots, for example, the contemporary modes of consumption that—far from being simply linked to survival—have become an autonomous activity that feeds into a chain of consequences that embrace and constrict the entire planet (Yearly, 2005).

11.3 Anthropocene In 2000, the Dutch Nobel laureate and atmospheric chemist Paul Josef Crutzen and the US biologist Eugene Filmore Stoermer suggested that the impact of human activities on the environment is today so disruptive that it is causing geological changes of epochal magnitude. According to the two authors, the Holocene, the most recent of the geological eras, is now giving way to a new period in the history of the Earth, the Anthropocene or the “era of human beings”. According to biological and environmental studies, human activities have become a geological force capable of changing global balances in an ever more significant way. According to Crutzen and Stoermer, the beginning of the Anthropocene coincides with the beginning of the industrial revolution in Europe, around the end of the eighteenth century, when the invention of the steam engine radically changed not only the processes of industrial production but also lifestyles and styles of consumption. Carbon dioxide (CO2), methane (CH4) and other particulates released into the atmosphere began to deposit on rocky formations and form new layers that will remain as geological evidence of modern-day industrial history and of the effects of atmospheric pollution, even in millions of years. The concept of “Anthropocene” is therefore based on the intellectual effort to project into the future the effects of anthropogenic activities on geological processes: social transition is disclosed by the geological datum. According to the British geographer Jamie Lorimer (2017, p. 8), Surely the most striking feature of the Anthropocene is that it is the first geological epoch in which a defining geological force is actively conscious of its geological role. The Anthropocene therefore really commences when humans become aware of their global role in shaping the earth and, consequently, when this awareness shapes their relationship with the natural environment. This is thus not just a new geological epoch; it also potentially changes the very nature of the geological by clearly marking it as a domain that includes intentionality and meaning. Conversely, it also marks a transformative moment in the history of humanity as an agent, comparable perhaps to the development of technology and agriculture.

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To respond to the proposal of naming the current era “Anthropocene”, the International Commission for Stratigraphy set up a working group (the Anthropocene Working Group), with the task of sounding out the opinions of the scientific community, formalising a definition of Anthropocene and responding to the numerous questions that a possible adaptation of the geological time scale might raise: for example, where to place the beginning of the Anthropocene? What are the social, ethical and regulatory consequences of such a decision? In fact, Crutzen and Stoermer’s suggestion that the industrial revolution triggered these geological changes on a planetary scale was not the only one been laid on the table; alternative proposals have been put forward by those who consider the industrial revolution too centred on European history5; it was proposed, for example, to postpone the beginning of the Anthropocene to the Second World War, when industrialisation and “globalisation” (another controversial term with flexible boundaries) underwent a rapid acceleration. Other scholars, in turn, wanted to highlight that, even before the spread of agriculture, economies based on hunting and gathering may have already triggered environmental transformations, for example, with the systematic use of controlled fires as a hunting strategy (Stephens et  al., 2019). According to this perspective, identifying the beginning of the Anthropocene with a specific event in the history of humankind would entail a division of the relationship between environment and humanity into two clearly distinct eras, with the consequent misleading classification of all the episodes prior to the Anthropocene as “innocent”. On the one side, this controversy has highlighted how the reference to an almost mythical past, during which humans lived in harmony with their environment, is nothing more but a distortion that prevents the formulation of reliable climate models and the understanding of the complex relationship between human being and the  environment. On the other side, however, expanding the definition of Anthropocene, to a point where it coincides with the beginning of humanity, does nothing but empty the concept and minimise the responsibility of contemporary economies that make the exploitation of natural resources their founding pillar. This would inhibit any effort to achieve a more sustainable economy, what is sometimes referred to as a “good Anthropocene” (PECS, 2015).

 Some criticisms of the term stem from the consideration that the impact on the climate of the activities of Western countries is much greater than those of the southern areas of the world; in this way, the concept of the Anthropocene would end up depoliticising the responsibilities of the Western world. Other terms were therefore coined, such as “capitalocene” (Haraway, 2015; Moore, 2016, 2017, 2018), which therefore highlighted this aspect. 5

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The term “Anthropocene”, while still far from being defined with precision and legitimated within the geology community, has taken a foothold in a multitude of contexts, thus promoting an interdisciplinary dialogue and providing a vocabulary to articulate the growing concern for the condition of the planet. Jamie Lorimer (2017) identifies other areas, besides those relating to geology and geopolitics, in which the concept of Anthropocene has taken root: the term has in fact centred the contemporary intellectual Zeitgeist (“the spirit of time”), creating a captivating but at the same time flexible frame to explore interesting aspects and fears about the future of the planet. Characterised by a vast time scale and by a connotation with dramatic tones, the term “Anthropocene” is constructed on the basis of other more specific concepts such as biodiversity, climate change and sustainability, but at the same time allows a much more heterogeneous and speculative involvement. The term has proved particularly fruitful in art—where it has provided, and still provides, opportunities for fertile blends between science, technology, environmentalism, forms of indigenous art, imagination and creativity—and in the so-called environmental humanities, a highly interdisciplinary academic field that seeks to explore the role of human sciences in this era of environmental crisis. The Anthropocene also served as an ideological call to undertake a critical discussion on the causes and consequences of anthropic action on the climate. The concept has also catalysed a generation of new ontologies for environmentalism, with a spectrum that cuts across the natural and social sciences, fuelling new modes of perceiving our presence in the world and that of the creatures that, together with us, populate it. In this sense, it does not matter what the commission for stratigraphy will decide on the institutionalisation of the Anthropocene as a geological era because the term has already become, to paraphrase Hannah Arendt, the new “human condition” (Pálsson et al., 2013). These spheres of thought and action are not isolated, but intersect each other, making possible a bridge between these contexts and the epistemology that together shape contemporary political ecology. The heart of multidisciplinary reflection on the Anthropocene lies precisely in the epistemological, aesthetic and disciplinary pluralism, which makes new forms of environmentalism possible. Exercise

Climate change lies today at the centre of public debate. STS can contribute to this debate by posing questions that help to focus on the complexity of the environmental problem, which cannot be relegated to merely scientific issues but must also include history, cultures, politics, economics and ethics. These ­questions concern the way in which knowledge is shared, legitimised, accepted or rejected, not only within the scientific community but also beyond its imme-

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diate (and in any case always changing) boundaries. Our perception of nature (see Box 11.1), both that as a place uncontaminated by human presence (the wilderness) and its opposite, is deeply cultural because it refers to socially shared previous experiences. Look through various types of magazines and newspapers for three to four images of natural places. Try to observe how nature is represented in each of the images and, in turn, which values and interests the image conveys. In addition, which elements are visually represented? Which social actors are behind the production of that image? How do the images differ from each other? And instead, which common elements do they share?

Check Your Preparation

1. Why is climate change such a complex problem and impossible to address only from a scientific perspective? 2. What is meant by the term “Anthropocene”? Further Readings • Merchant (1980) • Yearly (2005)

References Baer, P. (2006). Adaptation to Climate Change: Who Pays Whom. In W.  N. Adger et  al. (Eds.), Fairness in Adaptation to Climate Change (pp. 131–153). The MIT Press. Bird, E.  A. R. (1987). The Social Construction of Nature: Theoretical Approaches to the History of Environmental Problems. Environmental Review, 11(4), 255–264. https://doi. org/10.2307/3984134 Crist, E. (2004). Against the Social Construction of Nature and Wilderness. Environmental Ethics, 26(1), 5–24. https://doi.org/10.5840/enviroethics200426138 Cronon, W. (1996). The Trouble with Wilderness: Or, Getting back to the Wrong. Environmental History, 1(1), 7–28. https://doi.org/10.2307/3985059 Gardiner, S. M. (2004). Ethics and Global Climate Change. Ethics, 114(3), 555–600. https:// doi.org/10.1093/oso/9780195399622.001.0001 Greider, T., & Garkovich, L. (1994). Landscapes: The Social Construction of Nature and the Environment. Rural Sociology, 59(1), 1–24. https://doi.org/10.1111/j.1549-­0831.1994. tb00519.x Haraway, D. J. (2015). Anthropocene, Capitalocene, Plantationocene, Chthulucene: Making Kin. Environmental Humanities, 6, 159–165. https://doi.org/10.1215/22011919-­3615934 Heise, U. K. (2008). Sense of Place and Sense of Planet. Oxford University Press.

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Jamieson, D.  W. (2011). Nature of the Problem. In J.  S. Dryzek, R.  B. Norgaard, & D. Schlosberg (Eds.), The Oxford Handbook of Climate Change and Society (pp. 38–54). Oxford University Press. Jasanoff, S. (2005). Designs on Nature: Science and Democracy in Europe and the United States. Princeton University Press. Jasanoff, S., & Wynne, B. (1998). Science and Decisionmaking. In S. Rayner & E. L. Malone (Eds.), Human Choice and Climate Change (pp. 1–87). Battelle Press. Lorimer, J. (2017). The Anthropo-Scene: A Guide for the Perplexed. Social Studies of Science, 47(1), 117–142. https://doi.org/10.1177/0306312716671039 Merchant, C. (1980). The Death of Nature: Women, Ecology and the Scientific Revolution. The Wildwood House. Moore, J.  W. (2016). Anthropocene or Capitalocene? Nature, History, and the Crisis of Capitalism. PM Press. Moore, J. W. (2017). The Capitalocene, Part I: On the Nature and Origins of Our Ecological Crisis. Journal of Peasant Studies, 44(3), 594–630. https://doi.org/10.1080/03066150.2 016.1235036 Moore, J.  W. (2018). The Capitalocene Part II: Accumulation by Appropriation and the Centrality of Unpaid Work/Energy. Journal of Peasant Studies, 45(2), 237–279. https:// doi.org/10.1080/03066150.2016.1272587 Moore Daly, E., & Frodeman, R. (2008). Separated at Birth, Signs of Rapprochement: Environmental Ethics and Space Exploration. Ethics and the Environment, 13(1), 135– 151. https://doi.org/10.2979/ete.2008.13.1.135 Muir, J. (1911). My First Summer in the Sierra. Houghton Mifflin. Pálsson, G., Szerszynski, B., & Sörlin, S. (2013). Reconceptualizing the “Anthropos” in the Anthropocene: Integrating the Social Sciences and Humanities in Global Environmental Change Research. Environmental Science & Policy, 28, 3–13. https://doi.org/10.1016/j. envsci.2012.11.004 PECS (Programme on Ecosystem Change and Society). (2015). Seeds of a Good Anthropocene. https://goodanthropocenes.net/. Ramírez-I-Ollé, M. (2019). Into the Woods. Manchester University Press. Soja, E. W. (1989). Postmodern Geographies: The Reassertion of Space in Critical Social Theory. Verso. Steffen, W. (2011). A Truly Complex and Diabolical Policy Problem. In J. S. Dryzen, R. B. Norgaard, & S.  David (Eds.), The Oxford Handbook of Climate Change and Society (pp. 21–37). Oxford University Press. Stephens, L., et al. (2019). Archaeological Assessment Reveals Earth’s Early Transformation through Land Use. Science, 365(6456), 897–902. https://doi.org/10.1126/science. aax1192 Uhrqvist, O., & Lövbrand, E. (2014). Rendering Global Change Problematic: The Constitutive Effects of Earth System Research in the IGBP and the IHDP. Environmental Politics, 23(2), 339–356. https://doi.org/10.1080/09644016.2013.835964 White, F. (1987). The Overview Effect. Space Exploration and Human Evolution. Houghton-­ Mifflin. Yearly, S. (2005). The Sociology of Environment and Nature. In E. C. Calhoun, C. Rojek, & B. Turner (Eds.), The Sage Handbook of Sociology (pp. 314–326). Sage Publications.

Digital Societies

12

How many times have we heard expressions such as “information society”, “digital revolution” or “global networking”? These expressions, used to describe the post-­ industrial condition made possible by the invention and circulations of computers and telecommunications, are now familiar while remaining generic and, in a certain sense, ambiguous expressions. Just as in the case of the Anthropocene, these phrases encapsulate a fundamental tension: if, on the one hand, they seek to emphasise how the current condition is (both quantitatively and qualitatively) unprecedented, on the other they indicate a fundamental continuity with other social and cultural processes, in this case, for example, other forms of communication and mobility. The term “digital” (from the English digit, literally “finger” which in turn comes from the Latin digitus, or “finger”, the first tool used to count) refers to all those information packages that are translated into numbers (i.e. into 0 and 1, the binary code) to be transmitted or manipulated (Artmann, 2010). Digital systems differ from those of the analogue type, in which the signal is not transformed into symbols but is reproduced through its analogies (e.g. the passing of time is represented by the changes in the angle of the clock hand; temperature is represented by the height of the mercury in the thermometer graduated column). The first mechanical calculator we have evidence of, the Antikythera mechanism, dates back to the first century BC and was retrieved from a wreck of a Roman ship that had sunk off the coast of the Greek island of the same name (Swedin & Ferro, 2005). The remains of the instrument, encrusted and rusty, remained shrouded in mystery until the physicist and science historian Derek de Solla Price (1974) deciphered its functioning: the gears formed part of a calculator capable to determine the solar and lunar calendar, the positions of the planets and the dates of the Olympics. We would then need to wait until the early modern age to find © The Author(s), under exclusive license to Springer Nature Switzerland AG 2022 G. Gobo, V. Marcheselli, Science, Technology and Society, https://doi.org/10.1007/978-3-031-08306-8_12

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computation devices that were anything like that machine. The first modern mechanical calculators were again dedicated to astronomical measurements. These first devices could perform rather simple operations such as addition and subtraction and always remained dependent on manual activity (see Box 12.1). It was in the nineteenth century that the British mathematician Charles Babbage (1791– 1871) began to design an analytical engine, taking forward Leibniz’s intuition (1646–1716) of using a binary code. Thanks to the collaboration with the English mathematician Ada Lovelace (1815–1852), the idea of “programming” was introduced. They made use of perforated cards, already employed in mechanical spinning machines, to impart a series of instructions. By placing a string of simple calculations in orderly succession, the machine was able to eventually perform extremely complex operations (Artmann, 2010). In the 1970s, a series of declassified military documents revealed that the first programmable electronic calculator, called Colossus, had been designed during the Second World War in the UK to decrypt the code used by the Nazis for their secret communications. After the war, however, Colossus was destroyed, together with many of the documents that described its functioning. For the first digital computers, we would then need to wait until the second post-war period when the US government funded the first prototypes for military use. Nowadays, the presence of computers is widespread. According to the German philosopher of science Stefan Artmann, two fundamental elements contributed to this popularity: on the one hand, the miniaturisation of the components allowed the transition from the first machines, as large as entire rooms, to personal computers of very reduced sizes and weights; on the other hand, the implementation of graphic interfaces and the design of increasingly intuitive tools promoted its diffusion in every context, including the domestic environment. Box 12.1  Human Calculators

Nowadays, the term “computer” is sometimes used to indicate the antithesis of human: when we want to state, for example, that someone lacks empathy, creativity and sociality, characteristics that we consider typically human, we can refer to them, jokingly, as a “computer”. Up until the second half of the last century, however, the word “computer” had a completely different meaning: it did  not in fact refer to calculators that would then go on to be developed as modern personal computers, but actual flesh and blood persons that, by profession, performed calculations. The English term “computer” dates back to the start of the 1600s when it was sometimes used as a synonym for “mathematician”, that is the scholar that dealt with calculations, mostly aimed at determining the positions of the planets to

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compile horoscopes. Scientists of the past, for example Kepler, were temporarily employed as calculators on the ladder to obtaining more prestigious positions. Over the coming centuries, teams of calculators were involved in a wide variety of fields, from meteorology to navigation. During the Second World War, to make up for the lack of a male workforce, otherwise engaged at the front, the profession of calculator was typically performed by women. Teams of calculators were, for example, used in the Manhattan project and in many other sectors linked to the war effort (Grier, 2005). After the war, the work of computation, considered at the time an activity that did not require qualifications, remained a female domain. The story of three Afro-American women—Katherine Johnson, Dorothy Vaughan and Mary Jackson—employed by NASA during the space race is notably famous. Their story, narrated by US writer Margot Lee Shetterly and represented in the film of the same name, entwines scientific and technological matters, such as the development of knowledge linked to aeronautics and the transition of human computation to the mechanical type, set against a backdrop of social issues such as racial prejudice and female discrimination (Shetterly, 2016). ◄ From a sociological perspective, perhaps the most significant tendency is that of an increasingly widespread presence of computers in every field of human activity: home, work, health, science and so on, mainly due to the development of the World Wide Web that connects all devices to a global network. Computers, integrated in practices and in the social-material context, shape “technologically dense environments” (Bruni et  al., 2013), thereby creating new sociotechnical systems.

12.1 Algorithms In computer science, an algorithm is a sequence typically used to solve a problem or to perform an action via a finite set of instructions expressed in a formal language. The term “algorithm” comes from the name of the Arabic mathematician Al-Khwarizmi and originally referred to each procedure composed of simple elements that, once executed in succession, allowed the processing of a more complex task. Unlike traditional statistical methods that use the data collected to test previously formulated models (deductive method), algorithms allow the identification of relationships that we did not even know we were looking for (Kitchin, 2014). An algorithm, while being an abstraction, has very practical consequences: for example, the advertisements that we are presented with as we browse the internet

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are the result of our previous “profiling” as users, performed by algorithms; airport security is reinforced through the use of closed-circuit televisions allowing both facial recognition and anomalous behaviour detection by means of sophisticated algorithms; weather forecasts are also made through algorithms, as it is the programming of traffic lights in a city. Google search engine is probably the most famous algorithm in the world. It allows the search for very specific content in the immense ocean of the web. But there are also algorithms that decide who can be granted a mortgage or how likely is a certain disease to spread. Algorithms, therefore, have a strong social and economic power. Our very experience of reality is often mediated by algorithms that select the information we receive, the way in which we can access it and the meanings we attribute to it. Even electoral campaigns are today designed to adapt to the different users’ sensibilities: thanks to user profiling algorithms, the political content can be customised to fit the lifestyle and interests of different kinds of audiences. Although they are faster and more efficient in processing large amounts of data, algorithms do not work very differently from humans in making decisions: they interpret the information they possess based on already known models. For this reason, from a sociological and anthropological point of view, algorithms reflect, more or less unconsciously, their programmers’ choices, models, worldviews and ideologies, which then become part of the very code of the algorithm and thus, somehow, act back on society. In other words, the design of algorithms cannot but embody the purpose for which they were formulated and the interests of the various social actors involved in their development, thus producing recursive processes (Parisi, 2013). There are algorithms, for example, to identify the areas and the times of the day in which crimes are more likely to occur. The use of these algorithms might increase the presence of police in areas that are already highly ghettoised, thus reinforcing the sense of persecution suffered by certain minorities who, as a side effect, will tend to further isolate themselves and commit crimes (Benbouzid, 2019). Things have come full circle. As pointed out by the Italian historian and sociologist Massimo Mazzotti, this key role of algorithms in creating the conditions for our dealing with both natural and social reality starkly contrasts with their relative invisibility (2015, 465). Algorithms and their way of operating are not always understandable or even only open to analysis (especially in the case of proprietary algorithms). While frequently called “secrecy” or “confidentiality”, sociologists have preferred to refer to this characteristic as “opacity” (Burrell, 2016). Algorithms are in fact a perfect example of black box (see Sect. 7.2). According to Mazzotti, opacity refers to the fact that whoever receives the output rarely has a concrete sense of how that classification

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was produced and, at times, does not even know what might be the nature of the original database (2015, 471). Opacity depends on various factors. First, there is the voluntary choice of hiding certain information; this management aspect often does not depend on the technicians who design the algorithm but on the upper echelons of the producer company, so that the term “algorithm” does not simply denote a string of code but an entire socio-technological system. Second, even where an explicit choice is not made, it is the same complexity of the software (which can be modular and designed by different groups of computer scientists) that makes it difficult for the non-expert to access the functioning of the algorithm. Finally then, there is a factor that does not depend on human choices: it is in fact the same process of machine learning that, proceeding according to criteria that cannot always be deduced, places algorithms out of the reach of any human being, even of the most accomplished computer scientist. The opacity of algorithms creates the paradoxical situation in which some technical choices have an enormous impact on the community, yet neither the public nor the regulator has the necessary skills to evaluate their working (Mazzotti, 2015). On top of that, the power of algorithms today also lies in how they are imagined and how these ideas circulate in social worlds. It is the very notion of algorithm and its opacity—associated with ideals of objectivity, logic and rationality—that confer to it a certain power. Being considered producers of “truth” confers authority not only on a scientific but also on a social level. In accordance with what was theorised by the French philosopher Michel Foucault, it is precisely through the production of what is “true” and “normal” that power operates. And the more the authority of one of these truth production mechanisms, the more it will be politically strong. According to the British sociologist David Beer (2017, p. 8), algorithms have the capacity to produce truths in two specific ways. First, through the material interventions that algorithms make. These are […] ways in which algorithms produce outcomes that become or reflect wider notions of truth. Power then is operationalised through the algorithm, in that the algorithmic output cements, maintains or produces certain truths. From this perspective, algorithms might be understood to create truths around things like riskiness, taste, choice, lifestyle, health and so on. The search for truth becomes then conflated with the perfect algorithmic design—which is to say the search for an algorithm that is seen to make the perfect material intervention.

The search for a perfect mechanism encompasses the belief that there is an absolute truth that can be discovered, given a sufficient number of pieces of information and

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that it is then possible to act accordingly. Algorithms then become part of a narrative on science, on the production of “truth”. Today algorithms are an important, almost iconic, cultural presence—not only because of what they do but for what they represent and for all the values that are projected in them: neutrality, objectivity, efficiency and reliability. For this reason, Beer suggests, science studies should explore the meanings attributed to the notion of algorithm in the contexts in which it is articulated. Only in this way its significance as a rhetorical means to influence, convince and guide can be understood. It is precisely these values that make the algorithm so powerful in pre-forming decisions and influencing behaviour. “The algorithm’s power”, concludes Beer, “may then not just be in the code, but in that way that it becomes part of a discursive understanding of desirability and efficiency” (Beer, 2017, p. 9). In this way, algorithms are modelled and at the same time model the complex social and technological system of which they are part.

12.2 Digital Sociology and Its Methodological Challenges Every time we make a phone call, use a search engine, consult social media or make a purchase by credit card, we leave behind a variety of information that is recorded and stored by service providers and sometimes sold to third party companies. These huge data sets, called “big data”, can be aggregated and analysed for several purposes, commercial and otherwise, such as, for example, advertising and political campaigns. A famous example is that of the consultancy company Cambridge Analytica that, in 2018, was accused of having used data collected by Facebook to produce a pro-Donald Trump election campaign. The operation was managed through contents diffused by fake accounts, advertisements and the continuous monitoring of users’ reactions to tailor subsequent messages, almost in real time. Big data can be divided into three categories, according to their origin (Lazer & Radford, 2017). These can in fact be extracted: 1. From digital life, essentially from social behaviours mediated by digital technologies, such as a tweet, the reaction to a Facebook post, the sharing of a link to a news story, tags, messaging and exchanges with other users and so on. The recorded information is then associated not only to the content of the communication act but also to the reactions of the other users that view, share or react to it in some way.

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2. From digital traces, for example telephone records, which report when a call begins, when it ends, the telephone cells to which the users have connected; but also credit card payments, the time one spends on a website, a blog post or an advertisement; the record of geographic location and so on. 3. From the digitalisation of life, namely the passage into digital format of materials (information or artefacts) that were originally in analogue format. ­Digitalised ancient texts belong to this category. Once acquired in the form of files, these texts not only are made available as very high-definition images but can also be inspected through informatic systems thanks to recognition software that transforms them into text. The disciplines that deal with the creation, management and study of the latter type of data are called Digital Humanities. The volume of data collected using these methods is far superior to that of the sets of data processed using more traditional statistical methods (such as surveys and polls). There is no actual threshold to distinguish big data from a set of traditional data; however, a frequently used definition suggests that big data are those sets that cannot be processed by common computer programs as they are not able to manage the sheer quantity of data involved. Big data thus require the development of new computer analysis tools. For social sciences, these new forms of collection, processing and exploitation of data constitute a new research object that, as we have seen, contributes to the development of new social facts. Big data and algorithms offer new research opportunities and confront the social sciences with the emergence of a new approach to knowledge production, or of another “paradigm”, to use a Kuhnian term. Some social media (such as Twitter) have become a sort of model system thanks to the ease with which they provide access to data for research purposes. The use of these sets of big data as model systems makes the studies carried out by different research groups comparable (Tufekci, 2014). Unlike traditional statistical models that mostly operate deductively (i.e. starting from the formulation of a hypothesis to be tested through the data), the algorithms that manipulate these sets of big data tend to operate inductively, in other words they seek to extrapolate trends and patterns from the data itself (Kitchin, 2014). The aim, in this case, is not to understand the world, but to describe it and predict future trends following the myth of the objectivity of data. This new empiricism—very popular in business research, where big data are used to identify new products, markets and opportunities—is particularly dangerous for the social sciences, which risk falling back into neopositivist and determinist paradigms. As the British geographer Rob Kitchin (2014) has pointed out, these are based on false premises. Even if big data give us the illusion of being all-encompassing, in fact

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they are a representation of a reality that stems from a particular sample of users. Despite being enormous, a dataset is in any case the result of the use that a certain type of users makes of platforms, according to ever-changing modes and regulations. Each individual, for example, is part of a variety of networks of friendships and relations with whom they maintain contacts via various instruments and social media: we could, for example, use Facebook to interact with old friends, Twitter for colleagues and Instagram to share images with people from all over the world. The analysis of a set of data received from only one of these social media inevitably leads to an undoubtedly very detailed, but at the same time also very partial, representation of the individual behaviour. Even these data, therefore, are based on samples that do not fully reflect society and  the relationships that constitute it (Crawford, 2013; Kitchin, 2014; Leonelli, 2012). Data are not simply collected but generated according to precise choices made by engineers, computer scientists, specialists in digital security and by all those who contribute to the creation of a dataset. Numeric strings and the automation of processes do not replace the human component that designed them but incorporate it and at the same time conceal it. Finally, data are not always generated by just one individual: some people, for example, have many accounts, email addresses and so on, each dedicated to a specific activity (e.g. one might have an email address for work, one for the private exchanges and another used for online purchases); other accounts, on the other hand, might not be managed by individuals, but rather by groups of people such as associations, clubs and consortia and might therefore provide widely divergent pieces of information; a vast number of addresses are then fraudulent, in the sense that they are not used by physical persons but by calculators for precise commercial and non-commercial purposes. These technical limits, absolutely inevitable and common to every method, are particularly insidious in this context as the illusion of operating with sets of complete and objective data could lead researchers to overlook and underestimate the importance of correct methodological reflection. Instead, it is worth bearing in mind that all data, even the largest and apparently more extensive data sets, provide a vision of the world from a certain perspective. We must therefore not give in to the so-called big data hubris (Lazer et al., 2014), in other words the belief that the large volume of data could solve every problem. Of course, the accumulation of big data could improve the understanding of contemporary individual and social life and therefore represents an important opportunity to highlight behaviours and dynamics that otherwise are not easily accessible. However, to avoid falling back into reductionist and positivistic analyses, it is necessary to critically look at the opportunities and challenges that big data present.

12.3  Artificial Intelligence

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12.3 Artificial Intelligence The desire to create artefacts that somehow replicate the human being goes back a long way in history: automata, simulacra and robots have populated the philosophical, literary and technological imagery, reproducing various aspects of human action (McCorduck, 1988, 2004). Among all mechanically emulated activities, those linked to intellect have held a particular role. With Cartesian philosophy, in fact, thought (res cogitans) was identified as the founding characteristic of human beings and disconnected from the material and physical dimension of the individual (res extensa). Over the next three centuries, Western thought converged on the mind-body problem, an asymmetrical dichotomy in which the intellectual dimension was seen as being superior to the bodily one. Despite this, the thought remained elusive and beyond reach. The branch of studies called “artificial intelligence” (often abbreviated to AI), a term coined in 1955 by the American computer scientist John McCarthy, builds on this tradition, but at the same time marks a turning point. This expression was used to describe devices that replicate cognitive functions that are usually associated with the human mind, such as “learning” or “solving problems” (Russell & Norvig, 2009). According to McCarthy et al. (1955, p. 2), this study is to proceed based on the conjecture that every aspect of learning or any other feature of intelligence can in principle be so precisely described that a machine can be made to simulate it. There are three fundamental assumptions on which, from its outset, artificial intelligence has been based: Intelligence • can be described and explained in detail; • can occur outside the human brain; • can be studied through a computer that thus becomes the best instrument to explore its predispositions (McCarthy, 1988). This last assumption has been taken so seriously that the computer became a metaphor for human reasoning, the mind became associated with a computer program and its functions described in mechanical and computational terms. The result was a correspondence of structure and functioning between the human mind and a computer. The first problem is what is intelligence: rational thought, the cogito, the capacity to create associations, to process symbols, creativity or imagination? According to some cognitive scientists, answering this question is not the starting point of

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studies on artificial intelligence but the finishing line. In other words, the construction of a “thinking machine” from its elementary components would allow us to grasp the very essence of thought. The empirical process of construction of a machine equipped with artificial intelligence, proceeding by trial and error, offers the opportunity to formulate and test the hypothesis on what is intelligence. “The computer”, according to this perspective, “has made explicit the fundamental division between the two components of intelligent behaviour, hardware and software, finally demystifying the mind-body conundrum. The computer not only provides an instance of symbolic functioning arising out of matter; it also reveals how this can happen” (ibid., p. 71). A little like what happens in synthetic biology, which aims to understand what life is through the creation of new “living” cells (Sect. 11.3): also in this context, creating intelligence in the laboratory becomes synonymous with defining and fully understanding it. Up until the 1990s, most computer scientists and cognitive scientists believed that the success of artificial intelligence would bring evidence in favour of those reductionist philosophies that believe that human behaviour could be reduced to formal, describable and programmable sequences.1 However, the English anthropologist Lucy Suchman, in an ethnomethodological study that has become paradigmatic, showed how people do not act by thinking logically or following a clearly defined plan. It is only in hindsight (once the action is completed) that the actors attribute a rational logic to their own actions  (Suchman, 1987). Furthermore, no-one thinks or learns in isolation; on the contrary, elements that were previously learnt from language, from the family context, from the people we have spent time with and so on are needed (Mccarthy, 1988). According to the US anthropologist Edwin Hutchins, the metaphor of the computer has distanced cognitive sciences from understanding human reasonings, because it has isolated thought from the body of the thinking individual and from the context within which she moves (Hutchins, 1995). Finally, the Wittgensteinian philosophical argument, of which the philosopher Hubert Dreyfus (1972) was the main advocate within the AI context, sustains that no program can replace human practice as the rules cannot contain rules for their own application (Collins, 1995). The sociological and anthropological study of artificial intelligence can contribute to overcoming this simplification and relocate thought and cognition in their incorporated social and cultural context.

 The mental experiment called “the Chinese room” is very well known, conceived by the US philosopher John Searle (1980) with the aim of answering the question of whether machines can think. 1

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In an article entitled “Why Not a Sociology of Machines?” the British sociologist Steve Woolgar (1985) identifies four main sociological approaches to artificial intelligence. First, he suggests a sociological study centred around the figure of researchers (computer scientists, cognitive scientists, engineers, etc.) who work on artificial intelligence (e.g. Forsythe, 1993): how are they organised? How do they do their jobs? How do they interface with other IT disciplines, with the market and with the public opinion? Are there any inequalities? Are there any social classes that are less represented than others? This approach can then be followed by a second and a third type of sociological investigation that shift the focus from researchers to machines: the social construction of intelligent machines in which artificial intelligence systems are seen as artefacts that incorporate the assumptions, values and objectives of the community that produced them; then there is the sociology of intelligent machines in which the interaction between machine (and between humans and machine) becomes the beating heart of sociological study (e.g. Alač et al., 2011). Finally, Woolgar suggests the study of how the distinction between humans and artificial machines is maintained; what distinguishes them? What instead do they have in common? The response to these questions varies depending on the contexts, on the technological instruments being examined, on the applications that these have within the social world and on the narrations that accompany them on their path. Another interesting sociological approach is that which considers the controversies that, during its history, have characterised artificial intelligence. There is in fact a fundamental tension in the way in which these technologies are narrated. On the one side, the expectations towards them are sustained by a rhetoric that hinges on the “progress” and on the idea that artificial intelligence is the new frontier of technological innovation; on the other, however, this “technological myth” (Mosco, 2004) has experienced several setbacks and has been repeatedly considered a failure (Magaudda & Balbi, 2018). According to the Italian sociologists Ballatore and Natale, popularity and discredit do not alternate in stages but instead coexist throughout the historical path of this discipline. The presumed technological failure, linked to the idea of a never fully completed project, should be understood as a cultural construction or as a rhetorical strategy rather than an objective event (Gooday, 1998) and represents a symbolic resource that should be considered an integral part of its development. The very expression “artificial intelligence”, according to Woolgar (1985), encapsulates an idea that is so paradoxical (almost oxymoronic) from both a practical and a conceptual point of view that cannot but stir debate. This is particularly

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evident in what is called the “AI effect” or (jokingly) “Tesler theorem”,2 according to which artificial intelligence is anything that has not been done yet (McCorduck, 2004). In other words, what machines are already able to accomplish (routine technology) loses, in a certain sense, the special character that is attributed to i­ ntelligence. Today, AI systems find many applications: voice assistants, autonomous vehicles (self-driving cars), robots for the automation of logistics systems, bank loan granting assessment tools, social control via app and even digital weapons, to name just a few examples. These devices, while possessing extremely sophisticated problem-solving capabilities, are not generally considered truly intelligent. Even though machines are becoming increasingly capable, the promise of defining intelligence through the creation of thinking machines still seems to belong to the future. Each new application therefore reinforces the so-called AI effect and reignites the same question: “what is intelligence?” To find a reference point in the present and in the future of these technologies, the distinction proposed by Searle (1980) between strong AI (whose aim is the creation of a general intelligence, in all respects similar to human intelligence) and a weak AI (that imitates human behaviours only in a limited number of contexts) may be useful. These abovementioned tools that we use today could therefore fall into this second category. Strong artificial intelligence, however, continues to populate a technological imaginary in which promises and fears go hand in hand. In fact, AI is often the subject of a warning, especially by scientists from other disciplines, such as the British astrophysicist Stephen Hawking (1942–2018), who in 2017 declared to the press that: Success in creating effective AI, could be the biggest event in the history of our civilization. Or the worst. We just don’t know. So we cannot know if we will be infinitely helped by AI, or ignored by it and side-lined, or conceivably destroyed by it. […] Unless we learn how to prepare for, and avoid, the potential risks, AI could be the worst event in the history of our civilization.

Regulation however requires that possible ethical and practical dilemmas are contemplated, to be gradually addressed as innovation progresses. In this exercise of anticipation—for which it is not enough to imagine the technologies of the future but it is also necessary to insert them in the social, economic, political and cultural context in which they will be established—science fiction still plays an important role. Just think of the famous 2001: Space Odyssey by the British writer Arthur Clarke (1968—from which the film of the same name by Stanley Kubrick) or of  The US computer scientists Lawrence Tesler, specialised in human-machine interaction, is also remembered for having invented the “cut”, “copy” and “paste” commands. 2

References

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The Three Laws of Robotics, invented in the early 1940s by Isaac Asimov, or of the famous novel Do Androids Dream of Electric Sheep? by the American Philip K. Dick (1968), which inspired the film Blade Runner (1982). The technological myth that develops thanks to the literature and to its dissemination among scientists and the public cannot be reduced to naive beliefs but instead constitutes a complex and pervasive imaginary that on the one hand stimulates reflection and on the other can act as a drive for innovation. Exercise

Ask one of your relatives, possibly of an age group other than yours, to show you their wall of a familiar social network, for example, Facebook, Instagram or Twitter, and then compare it with your own. What do you see that is similar? What is different? Do your profiles show outlooks on the world that are similar or are they in some way different? Check Your Preparation

What is an algorithm? Why do algorithms play such a crucial role in our lives? What is meant by the term “big data hubris”? How are big data generated? What principles is the idea of artificial intelligence based on? What are the limits of artificial intelligence? Further Readings • • • • •

Kitchin (2014); Dreyfus (1972); Forsythe (2001); McCorduck (2004) Suchman (1987).

References Alač, M., Movellan, J., & Tanaka, F. (2011). When a Robot Is Social: Spatial Arrangements and Multimodal Semiotic Engagement in the Practice of Social Robotics. Social Studies of Science, 41(6), 893–926. https://doi.org/10.1177/0306312711420565 Artmann, S. (2010). Computers and Anthropology. In H.  J. Birx (Ed.), 21st Century Anthropology: A Reference Handbook (pp. 915–924). Sage publications.

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Beer, D. (2017). The Social Power of Algorithms. Information Communication and Society, 20(1), 1–13. https://doi.org/10.1080/1369118X.2016.1216147 Benbouzid, B. (2019). Values and Consequences in Predictive Machine Evaluation. A Sociology of Predictive Policing. Science and Technology Studies, 34(2), 119–136. https://doi.org/10.23987/sts.66156 Bruni, A., Pinch, T., & Schubert, C. (2013). Technologically Dense Environments: What for? What Next? Tecnoscienza, 4(2), 51–72. http://www.tecnoscienza.net/index.php/tsj/ issue/view/28 Burrell, J. (2016). How the Machine ‘Thinks’: Understanding Opacity in Machine Learning Algorithms. Big Data & Society, 3(1). https://doi.org/10.1177/2053951715622512 Collins, H.  M. (1995). Science Studies and Machine Intelligence. In S.  Jasanoff et  al. (Eds.), Handbook of Science and Technology Studies (Revised ed., pp. 286–301). Sage Publications. Crawford, K. (2013). The Hidden Biases of Big Data. Harvard Business Review.http://blogs. hbr.org/cs/2013/04/the_hidden_biases_in_big_data.html De Solla Price, D. (1974). Gears from the Greeks. The Antikythera Mechanism: A Calendar Computer from ca. 80 B. C. Transactions of the American Philosophical Society, 64(7), 1–70. https://doi.org/10.2307/1006146 Dreyfus, H.  L. (1972). What Computers Can’t Do: The Limits of Artificial Intelligence. Harper & Row. Forsythe, D. (1993). The Construction of Work in Artificial Intelligence. Science, Technology, & Human Values, 18(4), 460–479. https://doi.org/10.1177/016224399301800404 Forsythe, D. (2001). Studying Those Who Study Us: An Anthropologist in the World of Artificial Intelligence. Stanford University Press. Gooday, G. (1998). Re‐writing the ‘Book of Blots’: Critical Reflections on Histories of Technological ‘Failure’. History and Technology, 14(4), 265–291. https://doi. org/10.1080/07341519808581934 Grier, D. A. (2005). When Computers Were Humans. Princeton University Press. Hutchins, E. (1995). Cognition in the Wild. The MIT Press. Kitchin, R. (2014). Big Data, New Epistemologies and Paradigm Shifts. Big Data and Society, 1(1), 1–12. https://doi.org/10.1177/2053951714528481 Lazer, D., & Radford, J. (2017). Data Ex Machina: Introduction to Big Data. Annual Review of Sociology, 43, 19–39. https://doi.org/10.1146/annurev-­soc-­060116-­053457 Lazer, D., et al. (2014). The Parable of Google Flu: Traps in Big Data Analysis. Science, 343(6176), 1203–1205. https://doi.org/10.1126/science.1248506 Leonelli, S. (2012). Introduction. Making Sense of Data Driven Research in the Biological and Biomedical Sciences. Studies in the History and Philosophy of Biological and Biomedical Sciences, 40(1), 1–3. https://doi.org/10.1016/j.shpsc.2011.10.001 Magaudda, P., & Balbi, G. (2018). Fallimenti digitali. Un’archeologia dei “nuovi” media. Unicopli. Mazzotti, M. (2015). Per una sociologia degli algoritmi. Rassegna italiana di sociologia, 56(3-4), 465–478. https://doi.org/10.1423/81801 Mccarthy, J. (1988). Artificial Intelligence: An Aperçu. Daedalus, 117(1), 65–83. https:// www.jstor.org/stable/i20025133 Mccarthy, J. (2004). Machines Who Think: A Personal Inquiry into the History and Prospects of Artificial Intelligence. CRC Press.

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Mccarthy, J. et  al. (1955, August 31). A Proposal for the Dartmouth Summer Research Project on Artificial Intelligence. http://jmc.stanford.edu/articles/dartmouth/dartmouth. pdf. McCorduck, P. (2004). Machines Who Think: A Personal Inquiry into the History and Prospects of Artificial Intelligence. AK Peters Ltd. Mosco, V. (2004). The Digital Sublime: Myth, Power and Cyberspace. The MIT Press. Parisi, L. (2013). Contagious Architecture. Computation, Aesthetics, and Space. The MIT Press. Russell, S.  J., & Norvig, P. (2009). Artificial Intelligence: A Modern Approach (3rd ed.). Prentice Hall. Searle, J.  R. (1980). Minds, Brains, and Program. Behavioural and Brain Science, 3(3), 417–457. https://doi.org/10.1017/S0140525X00005756 Shetterly, M. L. (2016). Hidden Figures. William Morrow and Company, New. Suchman, L.  A. (1987). Plans and Situated Actions: The Problem of Human-Machine Communication. Cambridge University Press. Swedin, E.  G., & Ferro, D.  L. (2005). Computers: The Life Story of a Technology. John Hopkins University Press. Tufekci, Z. (2014). Big Questions for Social Media Big Data: Representativeness, Validity and Other Methodological Pitfalls. In ICWSM’14: Proceedings of the 8th International AAAI Conference on Weblogs and Social Media. http://www.aaai.org/ocs/index.php/ ICWSM/ICWSM14/paper/view/8062. Woolgar, S. (1985). Why not a Sociology of Machines? The Case of Sociology and Artificial Intelligence. Sociology, 19(4), 557–572. https://doi.org/10.1177/0038038585019004005

Medicine and Biotechnologies

13

Numerous disciplinary fronts intersect within the social studies of medicine and health. Following the early constructivist studies on science and in the footsteps of the Foucauldian tradition, an increasing number of sociologists, historians and anthropologists have looked into medicine, questioning the nature (up until then undisputed) of scientific knowledge in medical practice. How do structures of power act on medical practice? How is illness constructed within doctor-patient interactions? What does being ill or healthy actually mean? How is the medical condition pieced together within hospitals for therapeutic purposes? What form does the healing process take or—if complete recovery is not achievable—what is it like to live with a chronic illness? The answers to these questions are developed through clinics, laboratories, diagnostic tools, therapeutic options, protocols, waiting lists and hospital administrations. It is at the intersection of these practices that the human body and the lived experience of health and illness are continually constructed and redefined. The term “medicine” usually refers to Western medicine, also called “biomedicine”, in other words a system of knowledge and practices that interpret health and illness as a pure biological fact. The activities related to biomedicine are presented, both in theory and in practice, according to a reductionist model, one which essentially reduces the complexity of the social, psychological and cultural experience of the illness to a biological matter (Pizza, 2005, p. 157; Gobo 2019b; Gobo & Campo 2021). Thanks also to the valuable comparative work undertaken by medical anthropology, it has been demonstrated that biomedicine is just one of the many ways of conceptualising and managing illness within a wider plurality of forms of medicine. Other systems of medicine, such as traditional Chinese medicine (especially acupuncture), are not only extremely widespread but at times inte© The Author(s), under exclusive license to Springer Nature Switzerland AG 2022 G. Gobo, V. Marcheselli, Science, Technology and Society, https://doi.org/10.1007/978-3-031-08306-8_13

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grate and support biomedical practices within the national health system itself. In turn, Western medicine is not homogeneous and monolithic but includes a variety of divergent and sometimes conflicting events, actions, arguments and procedures (Pizza, 2005; Gobo 2019a; Gobo & Sena 2022). In The Body Multiple, for example, the Dutch philosopher and sociologist Annemarie Mol describes the different ways in which the body affected by atherosclerosis is enacted, depending on the tools, contexts and purposes of doctors and patients. In fact, according to the situation, atherosclerosis can be seen as a functional pathology that prevents patients from walking, the hardening of an arterial vessel observed under the microscope, a representation that allows the surgeon to operate on the patient. “In the hospital”, writes Mol (2002, p. 84), the organism hangs together thanks to the paperwork that travels from one department to the other; the correlation studies that correlate the outcomes of different diagnostic tests; the formulae and pictures that translate numbers and other data back and forth; the meetings where different specialisms come to agree on the diagnosis and treatment of individual patients. The organism in hospital Z (and other places like it) has gaps and tensions inside it. It hangs together, but not quite as a whole. It is more than one and less than many.

According to Mol, medical practice is not homogeneous or necessarily consistent. However, a number of translation techniques that create a common ground for practices and make the different ways in which illness unfolds compatible (at least in part) are implemented and made real within the material coordinates of medical practice (Mol, 2002). It is precisely because medicine contributes to the construction of our ways of perceiving and experiencing the body that its scope does not end within the clinic or doctor’s office but involves (and constitutes) numerous social worlds that intersect and define each other within the biomedical field: those of doctors, patients, their families, nurses, administrators of health systems, volunteers, paramedical associations, researchers, politicians, etc. Health and illness, fundamental categories of medical practice, also vary over time and in different contexts. The Canadian anthropologist Allan Young, for example, describes the historical trajectory of post-traumatic stress disorder (PTSD), a set of disorders resulting from a traumatic event, such as an earthquake or a war. Young (1995) retraces the historical guidelines (from the study of traumas linked to physical events such as proximity to an explosion to the theories of the Viennese psychoanalyst Sigmund Freud on the role of the unconscious in preserving traumatic events), showing that it was only as a result of the social and political pressures exerted by the lobbying of Vietnam veterans seeking recognition for their

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suffering that inclusion of PTSD in the diagnostic and statistical manual of mental disorders was conceded. Using an ethnographic study, he then examined the condition of PTSD as a product of the practices, technologies and narratives with which it is diagnosed, studied and treated. It is not only the particular historical conditions that reveal/create a new diagnosis, but in turn the diagnosis is made real (in the lived experience of the veterans) by the organisation of a new social institution such as the hospital ward within which Young himself had carried out his ethnography. The definition of the disease and the prevalence of characterising symptoms, Young explains, vary over time as does the experience of those affected and the relationships that bind them to loved ones and to other social actors in the biomedical field. Today PTSD is not only related to war scenarios but also to a whole series of other types of trauma such as natural disasters or calamitous events. The diagnosis of post-traumatic stress syndrome, like any other disease, syndrome or condition, is not “invented” or made-up; it is real, but it is not timeless. The lived experience of health and disease is constructed through an intricate mesh of practices of the body, knowledge and visions of the world, technologies and healing practices. Studying medicine as a cultural system does not only mean describing practices and knowledge but also, as the Italian anthropologist Giovanni Pizza (2005, p. 129) writes, showing how medical discourse goes far beyond the specific field of illness: biological reductionism (…) is a cultural and theoretical, but also political perspective which goes beyond biological aspects and—perhaps more implicitly, and therefore more pervasively—, provides us with ways of thinking about ourselves, our body, our self, our idea of person, intersubjective relationships, the categories of feminine and masculine, of the individual and of society.

Box 13.1  Synergies Between Medicine and Art

It is not easy to establish when a number of illnesses made their first appearance. In this context, novels provided us with important information on plague, cholera, smallpox and so on that occurred over the course of the centuries. Painting is another inexhaustible source. The signs of illness can be found in the characters portrayed in these paintings: Mondor’s syndrome in Rembrandt’s Betsabea (1654); hexadactylism in Leonardo’s Vitruvian Man (1490) and in Raphael’s Madonna di Casa Santi (1498) and Sistine Madonna (1513–14); type I neurofibromatosis in Mantegna’s La Camera degli Sposi (1465–1474); hypertrichosis in Petrus Gonsalvus by an anonymous German painter (about 1580); breast cancer in Michelangelo’s The Night sculpture (1534); and so on for many

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other illnesses such as tuberculosis, herpes zoster, skin depigmentation, rinofima, arthritis, and others. An exemplary case is Caravaggio’s Bacchino malato (1593), afflicted by Addison’s disease, from the name of the British doctor who first described it. But only in 1855, no less than 250 years later!

Bacchino malato (1593) by Caravaggio

As the Italian vascular surgeon Paolo Zamboni wrote, in the pages of the Journal of Thrombosis and Haemostasis (28 April 2020), the model is pale, with dark reflections in some areas of the skin, he perhaps also has abdominal pains, perhaps making him assume a forward leaning position, he is feeding on grapes as if needing sugar due to a possible hypoglycaemia. In addition, the inner corner of the eye, with its insufficient blood supply, is indicative of anaemia. The dark thumb and the blackish and opaque nail (instead of both of them being

13.1  Medicalisation, Normalisation and Biopolitics

253

pinkish) reveal an acanthosis nigricans (a condition in which the skin is hyperpigmented, thickened, velvety and of a darker colour with respect to the surrounding areas). ◄

13.1 Medicalisation, Normalisation and Biopolitics Biomedical practices do not simply pertain to illness but also encompass health and the body. If, in the Western reductionist and positivist paradigm, health corresponds to the possibility of the individual to maintain “their role […] according to the degree of efficiency required” (Ongaro Basaglia, 1982, p.  365), then biomedicine defines a “norm”, an ideal, which stigmatises all those conditions that deviate from it. Science and technology fit into this equation as they become part of the definition of what counts as “normal” or “pathological”. In recent decades, for example, STS scholars have investigated how knowledge and technology are redefining the experience of ageing. The improvement of general living conditions in many countries of the world, together with the increasing success of medicine in the treatment of pathologies, has led to a significant increase in life expectancy. While this is definitely a success, some of its consequences present challenges from an economic point of view, such as the subsequent increase in health care expenditure and the sustainability of the pension system (Johnson, 2005). Science and technology are therefore often invoked as resources to mitigate these effects and to reconcile the attempts to improve the living conditions of the elderly and, at the same time, alleviate the social consequences of an ageing population. Contrary to what is often thought, however, ageing is not a purely biological and ahistorical process. Several studies on Eastern societies, such as that of the Canadian anthropologist Margaret Lock (1993) about menopause in Japan, have shown significant differences in the ageing processes in Western societies: what features are considered characteristic of ageing and what aspects are deemed desirable are different in different cultural and social contexts. Technology and science help to create and recreate the narratives within which life, body, health and illness are inscribed. In the Netherlands, for example, a robot was designed to provide practical and emotional support to the elderly. The product, conceived by its designers as a device offering greater independence, was in fact deemed stigmatising by its users: the help provided was associated with the idea that they were particularly needy, fragile and isolated individuals. Instead of offering a chance for self-­ sufficiency, it ended up reinforcing a prejudice prevailing not only among young

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people but also among those approaching old age. It was therefore the elderly themselves, in many cases, who declined the use of a technology developed precisely with the aim of improving their quality of life (Neven, 2010, 2011). By critically investigating the relationship between users and designers of technologies intended for the elderly, we discover what often turns out to be a paternalistic approach. This is particularly problematic for two reasons: first, because it does not involve the users in the design of technologies intended specifically for them (Compagna & Kohlbacher, 2015; Neven, 2010; Wu et al., 2011); second, because of the mental and social models that are embedded in these technologies that assume a passive user with limited agency (Neven, 2010, 2015; Oudshoorn & Pinch, 2008). Through technologies, in fact, a double naturalisation occurs (Neven, 2011): user representations and technological design produce and reproduce new identities which then become “normal” and “natural”. When technologies are thought of as neutral, no reflection is dedicated to how they might act on identity and experience, for example, by limiting or expanding the capacity for action of those for whom they are intended or by modifying the conception of what counts as normal and “desirable”, among both the users themselves and those around them (Neven, 2010; Peine et al., 2015). However, it is not only technology that contributes to this normalisation process: biomedicine—by setting norms, standards, threshold values and lists of symptoms of illnesses and dysfunctions—establishes what is normal and what is pathological, thus substantiating a set of power relations. The attempt to manage socially and economically an ageing population is only one of the many areas in which we are witnessing the politicisation of medicine and the medicalisation of politics. The term “political”, in this context, does not necessarily refer to politics as a formal activity conducted within Parliament, at party headquarters, at rallies or at the polls; the word “political”, in fact, refers to all those relationships of power and subjugation that pervade our societies and which are often not documented, but become engrained in our everyday lives. Essentially, the events of life, and life itself, become part of a system of socially organised forces of power that is wielded in institutions such as the family, the school and the hospital. Foucault (1976) coined the term “biopolitics” to indicate the entry of the power into the biological life of people, with the aim of disciplining (also through medical sciences) their physical bodies. The word “biopolitics” is the result of the combination of the prefix bios, “life”, and “politics”. Several interpretations of this binomial have attempted to attribute primacy to one or the other of the two domains, to life or politics, to nature or society. The key feature of this term, nevertheless, is that of placing the two antipodes of the binomial in a constant reciprocal relationship and of situat-

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ing this relationship historically (Lemke, 2011). Life, therefore, does not represent a stable and normative point of reference, but can be modelled and controlled within biopolitical relationships. According to Foucault, biopolitics developed together with a number of modern techniques and knowledges, such as statistics, epidemiology, biology and demography. Within these disciplines, life is no longer identified with the single human being but becomes an abstraction, aggregable and measurable in terms of population. Foucault analyses the historical process during which, precisely through these new knowledges, life emerges at the centre of political strategies and—in turn—structures political action and determines its objectives. In The History of Sexuality, Foucault traces the shift from a form of sovereign government—which imposed its authority through oppression—to biopower, a new form of exercising power that passes through the government of life itself. Biopower, according to Foucault, is mainly divided into two forms: the disciplining of the individual body (to increase its productivity and, at the same time, to weaken its forces to ensure its political subjugation) and population control, understood as an independent biological entity characterised by specific processes such as births, mortality rate, life expectancy, health status and so on. The result of these two levels of exercising power is to establish a bodily stance that reveals normative expectations. Sexuality, according to Foucault, is a key area in which biopower is exercised (although it is not the only one): power, in fact, is not reduced to negative obligations but rather works through education and the continuous management of what it is “normal”, “desirable” and “possible”. The individual, therefore, does not undergo an imposed power, with force from the outside, but internalises rules through the discipline put in place by institutions such as schools and clinics. In this sense, medical knowledge and the work of continuous redefinition, in which it operates between normal and pathological, are a constitutive part of the exercise of power itself.

13.2 The Human Genome Project “We used to think that our fate was in our stars; now we know, in large part, that our fate is in our genes” (cit. in Conrad & Gabe, 1999). With these words James Watson, one of the discoverers of the double helix structure of DNA, summarised the spirit of the Human Genome Project (HGP) and the new era of genomics. The gene is a portion of DNA that contains the information necessary for the production of proteins which in turn have specific functions in the development and functionality of living organisms. The genome is the set of all the genes of an individual

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and, according to a well-known metaphor, contains the “instruction manual” of the entire organism (Nelkin, 2001). The goal of the project—launched in 1990 and completed in 2003—was to identify and map the entire human genome. The extensive consortium supported by public funding that made the HGP possible involved a number of research laboratories in the United States, Canada, Europe, Japan and China and is still considered to be the largest collaboration ever undertaken in the world of biology. The conclusion of the venture, two years earlier than expected, hit the headlines for the head-­ to-­head that saw the HGP consortium compete with Celera Genomics, a private company founded by the American entrepreneur and philanthropist Craig Venter (Shreeve, 2004). The competition—which symbolised the rivalry of two different approaches to research, the public and the private one—ended in a draw when the representatives of the two factions, along with Bill Clinton, then president of the United States, and Tony Blair, British prime minister, announced that the results of the two teams would be published simultaneously. The ferment within the scientific community was matched by the enthusiasm, fanned by the media, among the general public. The mapping of the entire DNA, already recognised as a cultural icon in American society (Nelkin & Lindee, 1995), lent itself to a number of metaphors and analogies: the deciphering of the book of life, the search for the holy grail of biology or the distillation of the very essence of human life. All these narratives shared an underlying premise: the idea that human problems were fundamentally traceable to genetic traits. Throughout the decade leading up to the conclusion of the Human Genome Project, the front pages of newspapers extolled the discovery of genes associated with the widest variety of diseases, inclinations, behaviours and human characteristics: from Alzheimer’s to shyness, from thinness to happiness. This “genetisation” of human problems (Lippman, 1992) sometimes resulted in a kind of genetic fatalism or the idea that there is a deterministic relationship between an individual’s genetic make-up and his or her physical and behavioural traits, which turn out to be, therefore, immutable. Although many of these purported “discoveries” were not later confirmed, the protracted media hype had created a new paradigm within which life, illness, disability, human abilities (and its failures), family relationships, social problems and quality of life were re-thought (Conrad & Gabe, 1999). Box 13.2  The Case of HeLa

HeLa is the name of the first and most important in vitro cell line, cultured since 1951. This cell line is considered “immortal” because it multiplies at an extraordinary speed (the number of cells doubles every 24 hours) and without the limits imposed by cellular ageing. Scientists calculated that if all the in vitro cul-

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tured HeLa cells could be stacked one on top of another, the result would be a skyscraper as tall as about 100 Empire State Buildings. Thanks to HeLa cells, the polio vaccine was discovered in 1953 and the effects of radiations and toxic substances were tested; this cell line has also been used in AIDS research and in gene mapping, as a standard for all cancer research and for countless other ­studies. It is estimated that more than 60,000 scientific articles have been written based on research carried out with this cell line. But where did these cells come from? “HeLa” are the first letters of Henrietta Lacks, a young African-American woman from Baltimore, from whom a sample of cancer cells was taken for diagnostic purposes. Henrietta Lacks was not informed of either the sampling or the attempt to cultivate the cells in vitro and died eight months later not knowing that a new branch of life sciences would be created because of the use of her cells. When researchers at John Hopkins University Hospital (the only public hospital in the city that admitted African-­ American citizens at the time) realised that their attempts to establish an “immortal” cell line had finally been successful, they began to distribute free samples of Henrietta Lacks’ cells, renamed “HeLa”, to any laboratories that requested them. Even after the young woman’s death, her cells were propagated in laboratories throughout the world. The origin of HeLa cells was soon forgotten and these cells—despite being present in virtually all biology laboratories around the world—remained completely anonymous until the late 1970s. Even the Lacks family remained unaware of this for more than two decades, continuing to live in poverty even though Henrietta’s cells had become the basis for the search for cures for dozens of diseases and had actually created a market worth millions of dollars. This case presents us with a paradox in terms of body, identity and spatio-­ temporal scale: although Henrietta Lacks’ illness led to her untimely death, part of her body survived, becoming a common good whose presence spread in space (HeLa cells can be found all around the globe) and in time. But this story also offers an opportunity to rethink many ethical issues. First, the problem of access to medical care, which in the United States is an extremely pressing problem: while Henrietta Lacks’ cells were becoming essential for medicine, ironically her children were unable to afford long-term health insurance that would ensure access to the same treatments that the HeLa cell line had made possible. Then there is the issue of consent: Henrietta Lacks had not been informed of her cell harvest and what would become of it and some scholars believe that, although at that time the ethical rules on consent were not as stringent as they are today, a white male would have been treated quite differently. 

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Further Readings • Landecker (2007); • Foucault (1976); • Skloot (2010). ◄ In fact, the mapping of the genome failed to deliver on many of its promises. The functioning of genes is more complex than expected and the relationships between genetic make-up and individual traits resist any generalisation. On the other hand, the importance of environmental causes was recognised not only in relation to behavioural traits such as shyness or a predisposition to languages but also for many pathological conditions, such as cancer or heart disease, which geneticists had hoped to unequivocally attribute to a genetic cause. On the contrary, genetics can—at the most—identify trends and propensities, expressed in statistical terms. Furthermore, there are still portions of DNA whose function is not fully understood and which even today, almost two decades after the first complete mapping of the genome, are still being explored. The Human Genome Project has another important record: 5% of the entire budget was used for the study of ethical, legal and social impact (whose acronym is ELSI). The task force of sociologists, philosophers, historians and experts in communication, economics and law had the aim of anticipating possible problems and engaging the public in their resolution. The attempt was prompted by the so-­ called Collingridge dilemma,1 according to which as long as a technology is still in its early stages of development, it is too early to predict its problems; when the critical issues are perceived, it is too late and the technology is already too widespread. The Human Genome Project had in fact raised problems that required consideration because they had not been addressed in any of the regulations in force: how could the new technologies be brought into line with existing healthcare systems? How would the acquisition of new genetic information change the view of humanity and individuality, of health and disease on a philosophical, theological and ethical level? How is this information processed within socio-economic systems? What would be the best way to publish, share and exploit this type of information for an economic return? Who does it belong to? (see Box 11.3). For what purposes can it be disclosed (Hedgecoe & Martin, 2008)? These questions did not find simple and definitive answers, but the model proposed by  David Collingridge is a physician, known for his The Social Control of Technology, St. Martin’s Press, New York 1980. 1

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the ELSI task force offered the possibility of developing a greater awareness of these problems, of recognising the impossibility of finding stable solutions and of the consequent need to continually rethink them in the light of the new situations that will arise in future. Following the Human Genome Project and the rapid development of DNA coding technologies, the terminology derived from biology and genetics has been absorbed into the common vocabulary. According to the American anthropologist Paul Rabinow (1996), this has led to the appearance of new identities and new forms of sociality: people are identifying, with increasing frequency, with characteristic traits of their genetic make-up, especially regarding risk, predisposition to diseases or their ancestral roots. Rabinow jokingly coined the term biosociality, as opposed to sociobiology (a current of sociology that came about in the first half of the 1970s, which proposed the systematic study of the biological basis of every form of social behaviour) and which indicates the progressive remodelling of nature starting from culture understood as practice. Contemporary family ties are an example of biosociality as the techniques of reading the genetic code provide new biological data around which to form ties and new identities, to organise new aggregations as well as political and social communities (Gibbon & Novas, 2008; Pálsson, 2009). In addition to these new forms of sociality, other forms of discrimination that were thought to be outdated have gradually and inexorably re-emerged, such as the concept of race, which has found a new form of naturalisation in genetics. Today DNA decoding services such as 23 and me, a paid service which, using a saliva sample sent to the laboratory by post, provides the client with all the genetic information requested (together with a short manual on how to interpret it), are spreading. These kits, which are extremely cheap and fast, provide information such as the predisposition to diseases and the presumed origin of an individual in ethnic and statistical terms. We are thus witnessing an involuntary yet profound reintroduction of the concept of race. The “biology” of race, write anthropologists Kirksey and Helmreich (2010, p. 550), “migrated from population genetics to genomes, both reinforcing and overturning earlier understandings of human taxonomy”.

13.3 Biotechnology and Synthetic Biology If the Human Genome Project marked a huge step forward in the techniques of DNA reading, numerous techniques to rewrite the genetic code have also been perfected in recent decades. The recombinant DNA technique, for example, allows

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the combination of genes from different organisms with the aim of modifying some of the characteristics of the individual which will compose the genetic make-up. This is the case, for example, of Alba, a fluorescent rabbit obtained (at the request of the artist Eduardo Kac) through gene editing which involved the inclusion in its genetic make-up of a sequence “borrowed” from a species of jellyfish. One of the most commonly used gene editing techniques today is called crispr-Cas9, a “molecular scissor” that allows the cutting and re-insertion of parts of DNA into selected sites. Today this crispr-Cas9 provides a genetic modification tool whose use is much more precise and cheaper than pre-existing technologies. Thanks to these techniques, an attempt has been made to modify the functionality of a number of living organisms, especially microorganisms. The first molecule produced by a microorganism with recombinant DNA was insulin, essential for the treatment of diabetes. To date, the applications of biotechnology are many: from medicine to agronomy, from the textile industry to the food industry, and to the production of biofuels. But are biotechnologies a true revolution? Undoubtedly the extent of the changes that can be made to an organism is unprecedented, but the selection of characteristics to make plants and animals more suitable for domestication is a process that dates back to the dawn of agriculture. There is therefore a certain continuity between the more traditional activities of agriculture and farming and modern biotechnologies (Franklin, 2006). The common thread that links both is the desire to “domesticate” nature, to “tame” it to the needs of human beings. The approach that deviates most of all from this millennial process is synthetic biology, often referred to as the engineering approach to biology (Breithaupt, 2006; Calvert, 2010). Synthetic biology does not seek to make changes to what nature has made available but aspires to the creation (in whole or in part) of artificial living systems. This objective is divided into three possibilities: 1. the creation of interchangeable biological parts, called BioBricks, or “biological bricks”, an explicit reference to the famous Lego bricks (Endy, 2005); 2. acting at the whole genome level, by both synthesising viral genomes de novo and manipulating the existing ones to eliminate the “exceeding” parts to produce the minimum genome for life (Glass et al., 2006); 3. the creation (the most ambitious goal) of “proto-cells” starting from the single fundamental components, such as lipids and amino acids, but synthesising versions not originally present in nature. Synthetic biology is gaining increasing importance both academically and industrially as it draws on the promise of replicating engineering success in improving the efficiency, reliability and predictability of biological components

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(Calvert, 2010). Like engineering, synthetic biology seeks to develop interchangeable, functionally discrete and modularly combinable components. However, the engineering approach to biology does not stop there: in addition to the attempt to reduce genetic information to the bare essentials, the goal of synthetic biology is to design biological parts that are different from those found in nature, for example, by using new amino acids or developing new nucleic acids to “write” the DNA. According to synthetic biologists, these artificial systems that offer an alternative to those that can be found in nature would, on the one hand, guarantee the safety of what is created as, being dependent on nutrients not found in nature, synthetic cells would quickly die in isolation and, on the other, offer the possibility of patenting artificially created cells as actual “inventions”. But is it really possible to remove complexity from living systems? According to the French philosopher Sven Dupré (2009), living beings are the result of billions of years of trial and error, the residues of which are still stored in our genetic make-up. Eliminating complexity and contingency could therefore have as an undesirable consequence the loss of the emergent properties that define living systems. According to other philosophers and biologists, however, this position comes close to vitalism, or the idea that there is something special and irreducible in living beings and which, by definition, is impossible to recreate using scientific methods. In the same way the  American biochemists Harold Urey and Stanley Miller, in 1952, reproduced a complex molecule starting from a sort of “primordial soup”, synthetic biologists also hope to be able to recreate living systems starting from their components. In 2007, an interdisciplinary conference entitled “What’s Left of Life?” was organised at the University of Berkeley. It invited participants to reconsider Foucault’s biopolitics in the light of the limits, possibilities and reconfigurations but also of the new sites of knowledge production and technological intervention offered by biotechnology (Helmreich, 2011). Analysed from the perspectives of anthropology, STS and philosophy, the very concept of life appears to be in transformation (if not, indeed, in the process of dissolution) given the possibility of cloning technologies, the exploration of biodiversity, biosecurity, digital simulation and bioinformatic representation. According to Helmreich (ibid., p. 674), these changes unsettle the nature so often imagined to ground culture. Life moves out of the domain of the given into the contingent, into quotation marks, appearing not as a thing-in-itself but as something in the making in discourse and practice. “Life” becomes a trace of the scientific and cultural practices that have asked after it, a shadow of the biological and social theories meant to capture it.

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Attempts to modify or engineer microorganisms, plants and animals drive us not only to analyse the relationship between natural and cultural, but also to reconsider the very idea of natural. According to Fox Keller (2008), in fact, the definition of “natural” is relative and depends on what is opposed to it: natural can be the opposite of artificial, social and imaginary. Once again, natural and cultural, social and biological are not fixed and stable entities but are negotiated and renegotiated within the practices that define them. Exercise

Check Your Preparation How is it that the obsolete concept of “race” has re-emerged within the frameworks of new biotechnologies? How do medical knowledge and technologies redefine ageing? What does “biopolitics” mean? Why is it a significant concept in the twentieth and twenty-first centuries? Further Readings • Constructivist Perspectives on Medical Work: Medical Practices and Science and Technology Studies, Special Issue di “Science, Technology, & Human Values”, 20, 4, pp. 408–437. • Balmer et al. (2016). • Calvert (2010). • Lemke (2011).

References Balmer, A., Bulpin, K., & Molyneux-Hodgson, S. (2016). Synthetic Biology: A Sociology of Changing Practices. Springer. Breithaupt, H. (2006). The Engineer’s Approach to Biology. EMBO Reports, 7(1), 21–24. https://doi.org/10.1038/sj.embor.7400607 Calvert, J. (2010). Synthetic Biology: Constructing Nature? Sociological Review, 58(1), 95–112. Compagna, D., & Kohlbacher, F. (2015). The Limits of Participatory Technology Development: The Case of Service Robots in Care Facilities for Older People. Technological Forecasting and Social Change, 93, 19–31. https://doi.org/10.1016/j.techfore.2014.07.012 Conrad, P., & Gabe, J. (1999). Introduction: Sociological Perspectives on the New Genetics: An Overview. Sociology of Health and Illness, 21(5), 505–516. https://doi. org/10.1111/1467-­9566.00170

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Dupré, J. (2009). It Is not Possible to Reduce Biological Explanations to Explanations in Chemistry and/or Physics. In F.  J. Ayala & R.  Arp (Eds.), Contemporary Debates in Philosophy of Biology. Wiley. Endy, D. (2005). Foundations for Engineering Biology. Nature, 438, 449–453. https://doi. org/10.1038/nature04342 Foucault, M. (1976). La volonté de savoir. Gallimard. (transl. The Will to Knowledge, Volume 1 of The History of Sexuality. London: Allen Lane, 1978) Fox Keller, E. (2008). Lecture: Nature and the Natural. BioSocieties, 3, 117–124. https://doi. org/10.1017/S1745855208006054 Franklin, S. (2006). The Cyborg Embryo: Our Path to Transbiology. Theory, Culture and Society, 23, 167–187. https://doi.org/10.1177/0263276406069230 Gibbon, S., & Novas, C. (Eds.). (2008). Biosocialities, Genetics and the Social Sciences. Making Biologies and Identities (pp. 1–19). Routledge. Glass, J. I., et al. (2006). Essential Genes of a Minimal Bacterium. Proceedings of the National Academy of Sciences, 103(2), 425–430. https://doi.org/10.1073/pnas.0510013103 Gobo, G. (2019a). The Intricate Relation between Science, Economy and Politics: The MMR Vaccine Case. In B. Schnettler et al. (Eds.), Kleines Al(e)phabet des Kommunikativen Konstruktivismus (pp. 393–400). Springer VS. Gobo, G. (2019b). Vaccini e vaccinazioni. Una questione solo medica? Rassegna italiana di sociologia, 60(3), 627–636. https://doi.org/10.1423/95513 Gobo, G. & Campo, E. (2021), Covid-19  in Italy: should sociology matter? European Sociologist, 46(2), https://www.europeansociologist.org/issue-46-pandemic-impossibilities-vol-­2/covid-19-italy-should-sociology-matter Gobo, G. & Sena, B. (2022). Questioning and disputing vaccination policies. Scientists and experts in the Italian public debate, in Bulletin of Science, Technology & Society, 42(1-­ 2), pp, 25–38, https://doi.org/10.1177/02704676221080928 Hedgecoe, A., & Martin, P. A. (2008). Genomics, STS, and the Making of Sociotechnical Futures. In E. Hackett et al. (Eds.), The Handbook of Science and Technology Studies (pp. 817–839). MIT Press. Helmreich, S. (2011). What Was Life? Answers from Three Limit Biologies. Critical Inquiry, 37(4), 671–696. https://doi.org/10.1086/660987 Johnson, M. E. (2005). The Cambridge Handbook of Age and Ageing. Cambridge University Press. Kirksey, E. S., & Helmreich, S. (2010). The Emergence of Multispecies Ethnography. Cultural Anthropology, 25(4), 545–576. https://doi.org/10.1111/j.1548-­1360.2010.01069.x Landecker, H. (2007). Culturing Life: How Cells Became Technologies. Harvard University Press. Lemke, T. (2011). Biopolitics. An Advanced Introduction. New York University Press. Lippman, A. (1992). Led (Astray) by Genetic Maps: The Cartography of the Human Genome and Health Care. Social Science and Medicine, 35, 1469–1476. https://doi. org/10.1016/0277-­9536(92)90049-­v Lock, M. (1993). Encounters with Aging: Mythologies of Menopause in Japan and North America. University of California Press. Mol, A. (2002). The Body Multiple: Ontology in Medical Practice. Duke University Press. Nelkin, D. (2001). Molecular Metaphors: The Gene in Popular Discourse. Nature Reviews Genetics, 2, 555–559. https://doi.org/10.1038/35080583

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Nelkin, D., & Lindee, S. M. (1995). The DNA Mystique: The Gene as a Cultural Icon. W. H. Freeman. Neven, L. (2010). “But Obviously not for Me”: Robots, Laboratories and the Defiant Identity of Elder Test Users. Sociology of Health and Illness, 32, 335–347. https://doi. org/10.1111/j.1467-­9566.2009.01218.x Neven, L. (2011). Representations of the Old and Aging in the Design of the New and Emerging: Assessing the Design of Ambient Intelligence Technologies for Older People. University of Twente. Neven, L. (2015). By Any Means? Questioning the Link between Gerontechnological Innovation and Older People’s Wish to Live at Home. Technological Forecasting and Social Change, 93, 32–43. https://doi.org/10.1016/j.techfore.2014.04.016 Ongaro Basaglia, F. (1982). Salute/malattia. Le parole della medicina. Einaudi. Oudshoorn, N., & Pinch, T.  J. (2008). User-Technology Relationships: Some Recent Developments. In E. J. Hackett et al. (Eds.), The Handbook of Science and Technology Studies (pp. 541–565). MIT Press. Pálsson, G. (2009). Biosocial Relations of Production. Comparative Studies in Society and History, 51(2), 288–313. https://doi.org/10.1017/S0010417509000139 Peine, A., et  al. (2015). Science, Technology and the “Grand Challenge” of Ageing − Understanding the Socio-Material Constitution of Later Life. Technological Forecasting and Social Change, 93, 1–9. https://doi.org/10.1016/j.techfore.2014.11.010 Pizza, G. (2005). Antropologia medica. Saperi, pratiche e politiche del corpo, . Rabinow, P. (1996). Making PCR: A Story of Biotechnology. Chicago University Press. Shreeve, J. (2004). The Genome War: How Craig Venter Tried to Capture the Code of Life and Save the World. Ballantine Books. Skloot, R. (2010). The Immortal Life of Henrietta Lacks. McMillan. Wu, Y.-H., et  al. (2011, March). Robotic Agents for Supporting Community-Dwelling Elderly People with Memory Complaints: Perceived. Needs and Preferences. Health Informatics Journal, 17(1), 33–40. https://doi.org/10.1177/1460458210380517 Young, A. (1995). The Harmony of Illusions: Inventing Post-Traumatic Stress Disorder. Princeton University Press.

Five Challenges for the Future

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In the previous chapters we examined the fundamental theories, the most relevant issues and some of the most representative case studies in the sociology of science and technology. We can now envision, based on the direction that the STS are taking, what might be the main research areas and trends for the future, in both substantive (concrete themes) and methodological terms, to acquire the theoretical instruments needed to analyse science as an intrinsically social enterprise.

14.1 Multispecies Ethnography The so-called multispecies ethnography emerges from the desire to re-image the relationship between humans and other living beings, whose existence intersects with (and is also threatened by) our own. Studies on the relationship between human beings and animals have a long tradition in anthropology (e.g. Leach, 1964; Morgan, 1868). In many of these canonical works, animals have been the object of interest as a symbolic instrument or subject of classification, but have always been marginalised, merely becoming part of the background against which social life was set. At the end of the twentieth century, the intertwining of research interests that had evolved in different disciplines gave new impetus to the critique of the nature/culture dualism. If, on the one hand, evolutionary philosophers and anthropologists1  In the US, anthropology is traditionally divided into four branches which often coexist within departments: cultural, biological (also called physical or evolutionary anthropology), linguistic and archaeological. 1

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had started to rethink the, by then, obsolete concepts of race and species in the light of new biotechnologies (see Chap. 13) (Koenig et al., 2008), on the other, feminist movements had shown how biological and naturalistic knowledges had affected the construction of identity and the power relations between individuals. These contributions breathe new life into the exploration of human nature (anthropos) and, simultaneously, placed other living beings at the centre of social research (a conceptual shift that has been named animal turn). If the boundary between nature and culture began to appear more flexible than ever, everything that up until then had been relegated to the natural world and excluded from the cultural investigation found a new space at the centre of anthropological inquiry. An ever-increasing number of anthropologists have therefore begun to investigate the lives of animals, plants, fungi and microorganisms in laboratories, agricultural production, dynamic ecosystems, food transformation processes and domestic settings (Fischer, 2009, pp. 141–53). This line of research—heterogeneous and populated by a multitude of different creative agents (Hardt & Negri, 2004, p. 92)—has become popular, thanks especially to the Multispecies Saloon (Kirksey & Helmreich, 2010), an exhibition periodically organised during the annual conference of the American Anthropological Association. It is here that anthropologists, scientists and artists put their works into dialogue and, through art, have formalised a programme for an anthropology “that is not just confined to the human but is concerned with the effects of our entanglements with other kinds of living selves” (Kohn, 2007, p. 4). Donna Haraway (2008) collected these emerging sensitivities, criticising what she called the “foolishness of human exceptionalism”, in other words the belief that human beings are at the centre of the world, in a dominant position with respect to other living beings. The US anthropologist has therefore called for new studies that can offer a novel biographical and political history to creatures too often relegated to the margins of anthropological investigation. Through the observation of everyday experience and technoscience, the lives of animals have been reconceptualised as active subjects2 in relations with human beings and not as mere objects for analysis of their physical and symbolic functions. This new conceptualisation offers a revision of the definitions of “culture”, “nature” and “species” but also of “friendship”, “kinship” and “belonging”. These categories are rethought in terms of relations of reciprocity, interaction and co-production of ecological niches (Kirksey & Helmreich, 2010).  See also Latour (Sect. 5.5.1) who on the one hand already considers animals as imbued with agency, but on the other calls them non-humans, an expression criticised by Susan Leigh Star because it implies a reduction, a lack of something. 2

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Aside from inducing a rethinking of traditional categories, this field of studies offers a methodological challenge, taking to the extremes the so-called “problem of representation” (Appadurai, 1988): how best to represent the world through the eyes and words of those with whom the ethnographer interfaces? How can we do justice to differences and otherness, translating them into anthropological language? Multispecies ethnography is therefore guided by a continuous reflection on how to position oneself in relation to the species encountered: what kind of relations are possible? How to tell the story of a member of another species? What are the potentials and the limits to be aware of? How do relations between species shape the field? How can humans, animals, plants, fungi and microorganisms thrive in the reciprocal relation? And how, on the other hand, do they hinder or threaten each other? What are the conditions for coexistence, with both human beings and the other living beings with whom they mutually create the surrounding environment? By asking these questions, anthropologists discover a myriad of possibilities and modalities, constantly in progress, into which relations between the species are articulated: protection, comfort, rescue, threat and destruction but also resilience and adaptability. It is in this prospective multiplicity that multispecies ethnography also dialogues with other similar theoretical frameworks such as that of the Anthropocene. Faced with apocalyptic stories of environmental destruction, the lives of other living beings provide examples of biocultural hope such as the love between insects (Raffles, 2010), the collaboration between species that make survival and the proliferation of rare fungi possible among the ruins of capitalism and the fragility of ecosystems (Tsing, 2015), microorganisms involved in the fermentation of wine and beer, in the production of cheeses (Paxson, 2008) and in the leavening of bread. According to multispecies ethnography, other creatures teach alternative ways of being the world, to decentre the anthropos and image what Haraway (2016) called “Chthulucene”,3 an era made up of new networks of relationships, adaptability, acceptance, compromises and cohabitations that provide local solutions, contingent and never complete, of cohabitation and prosperity even in this era of ecological disasters.

 According to Donna Haraway, Chthulucene is an alternative name for the era we are currently living in. It takes its name from the Californian spider Pimoa Cthulu. Haraway claims that Anthropocene is a definition that, in itself, is closed and incapable of being accountable for the heterogeneous complexity of the world. 3

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Further Readings • Haraway (2013) • Kirksey and Helmreich (2010) • Tsing (2015)

14.2 Agriculture In a famous essay on agriculture and technology, the US environmental historian Ann Vileisis wonders, provocatively, if tomatoes are natural or if they are, so to speak, technologies shaped by human beings (Vileisis, 2011, cit. in Berry, 2018). On the Peruvian plateaus, hundreds of species of tomato have spontaneously grown for millennia, but the first written evidence of their cultivation dates back only to the early decades of the sixteenth century, thanks to a missionary friar’s description of the xitomatl, a term subsequently translated into tomato. From that moment on, the tomato has undergone a long series of mutations linked4 to the social and economic context in which it had just entered: in the first instance, a few tomato seeds were transported to the Old Continent where, due to the lack of insects that would play the role of pollinators of its flowers, only the self-fertile species proved capable of producing fruit (at least in large quantities) and therefore being replanted the following year. Over the five centuries that separate us from the first written trace of the existence of the tomato, its physical and organoleptic characteristics have been selected based on the needs of harvesting and transportation requirements imposed by the market. Over time, types with greater resistance to parasites, that could be cultivated at various latitudes, and compatible with fertilisers and herbicides, were preferred. Today, tomatoes are genetically modified, artificially ripened, cultivated in greenhouses, mechanically watered, catalogued into standardised varieties and controlled according to national and transnational rules. The hundreds of types of tomato of the Andean plateaus are now, at most, very distant relatives of both the tomatoes that we harvest in the garden and those produced and distributed by the industrial agri-food system (Vileisis, 2011).

 Mutations are certainly not caused by social conditions but by the action of human beings: a peasant, for example, will replant in their vegetable patch the seeds of tomatoes that are larger and tastier while they will discard the seeds of plants whose fruit had less palatable characteristics. 4

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Vileisis’ question is clearly provocative but the long and intricate historic trajectory of an apparently simple food like the tomato helps us to appreciate the complexity of agriculture, a human activity in which nature, knowledge, landscape, instruments, innovation and social organisation have often been articulated into a very close reciprocal relation. In particular, with the advent of industrial agriculture in the second post-war period, science and technology played a fundamental role in giving direction to the productivist paradigm that was gaining ground in three ways: 1. with the transformation of agricultural activities into industrial organisations, integrated into increasingly articulated value chains; 2. with the emergence of research institutions that played a role of primary importance in the agri-food industry, thanks to the production of a whole range of substances (fertilisers, pesticides, herbicides) on which agriculture became increasingly dependent (Iles et al., 2016); and 3. finally, with the establishment of a narrative that presents this mode of production and consumption of food as the only one possible in the context of a continuously expanding global population.5 STS studies in the field of agriculture seek to reveal the policies and relations of power within which agriculture, food, physical infrastructures, tradition, practices, values, institutions and knowledge are co-produced (ibid.). These value chains bring people, organisms and technologies together in such stable ways that they often appear necessary, almost unchangeable. However, the growing awareness of the negative effects of this system—for example, the exploitation of people and animals, the adoption of unhealthy food systems (in terms of quantity and quality), the increase of economic pressure on small farm producers, the disappearance of many species of plant and animals (biodiversity), and so on—have triggered a turnaround. Today, in fact, a significant percentage of fruit and vegetables production has been converted into alternative agricultural forms (organic and biodynamic) whose large-scale success would be impossible to imagine until a few decades ago.

 In practice, in any case, this narrative clashes with a reality in which the food surplus of Western countries is in stark contrast to the deficit of food in other poorer and more densely populated areas of the world and in which, often, food itself is actually produced. 5

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According to the principles of organic farming,6 the life of the microorganisms present in the ground and the transformation of organic substances they operate are the basis of the fertility of the soil itself; practices such as composting and crop rotation are key to encourage a healthy proliferation of diverse communities of microorganisms in the soil. If at the end of the 1980s these positions were marginal and ridiculed by most scientists, today they enjoy a certain consensus even within the scientific community. In the last decade, thanks also to a very efficient marketing and the organisation of a consortium for the certification of organic products, organic cultivation has conquered a considerable share of the market (Ingram, 2007). Biodynamic farming (emerged in the 1920s from the theories of the Austrian philosopher Rudolf Steiner) is instead based on principles that link science and spirituality. In this context, spirituality is not understood in a religious sense, but conceived as a framework within which earth and humans are integral part of the same cosmos, sensitive to its rules and to its influences (Abouleish, 2005). According to this approach to agriculture, therefore, in every aspect of nature, even the most material one, there are spiritual components. A common feature of these nascent movements is the reflection on soil fertility: since the 1920s, in fact, it was recognised that the use of synthetic products impoverishes and destroys the complex system of microorganisms that populate the soil, leaving it “dead” and sterile. If conventional techniques involve the administration of synthetic nutrients necessary for crop growth and pesticides to deter harmful organisms, on the contrary, organic and biodynamic farmers are proposing a less reductionist conception of the relationship between plants and the soil (Ingram, 2007). From the point of view of the creation and management of knowledge, industrial agriculture makes a fairly clear distinction between technicians and farmers, conferring to the former the status of experts and relegating the latter to simple executors and passive recipients of information (Warner, 2007, 2008). The recourse to alternative forms of agriculture instead relies on local and traditional knowledge and poses questions such as: who are the experts? How is knowledge produced and validated in this sector, which is so complex and, at the same time, concrete, pragmatic and far from the aseptic precision and technicalities of laboratories? How do different forms of knowledge interface, compete or— literally—find common ground?

 Partly inspired by traditional agricultural practices of countries such as India, where the British botanist Sir Albert Howard (1873–1947), considered the founding father of organic farming in the Anglo-Saxon world, worked for years. 6

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Furthermore, highlights Warner (2007, 2008), the legitimacy of organic farming derives from the fact that it does not counter science but, on the contrary, dialogues with it, adopting its language and experimental practices (of whom, nevertheless, reorganises the priorities). These production systems participate in an intense boundary work, redefining what is science and who takes part in it. This not only applies to organic farming of Western countries but also to all those synergies between agricultural activities and indigenous knowledge (Brice, 2014a; Delgado, 2008). The importance attributed to organisms that participate in metabolic processes that are able to improve the quality of agricultural work has gone hand in hand with a reformulation (in sociological analysis) of the relationship between species—plants, microorganisms, fungi and humans. Much importance is today attributed, for example, to synergies that are created in the production of fermented foods such as cheeses (Brice, 2014b; Paxson, 2008), wines (Brice, 2014b) or leavened products. There is also a fertile mixture of anthropology and STS in the exploration of principles linked to the care of the earth (or of the terroir, Szymanski, 2018), no longer conceived as a defenceless substrate but as a complex system of minerals, substances, metabolic processes and seasonal cycles. Sebastian Abrahamsson and Filippo Bertoni (2014), two anthropologists of science, have experienced what they call “the politics of composting” and wondered how humans, earthworms and other microorganisms cohabit and coordinate their own activities in the mutual (but not symmetrical), continuous and dynamic effort to feed each other: humans providing their own food scraps to earthworms, the latter converting it into fertiliser for the earth. For many anthropologists and sociologists of science, paying attention to soil means looking at all those relations of power and of mutual dependence, too often overlooked or underestimated, through which agricultural practices take shape (Krzywoszynska & Marchesi, 2019). Further Readings • • • •

Berry (2018); Delgado (2008); Iles et al. (2016); Touzard et al. (2015).

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14.3 Science and the Senses “I will now shut my eyes, stop my ears, and withdraw all my senses”—it is with these words that Descartes opens the third metaphysical meditation, one of the sections that compose his famous Discourse on Method. Like in Buddhism and Hinduism, as well as for the founder of Taoism Lao Tzu, and for Socrates and Plato,7 Descartes claimed that the senses are deceptive and it is always necessary to question the knowledge that derives from them. According to Descartes, only the presence of doubt itself provides proof of the existence of thought, the only true certainty. The philosopher considered the mind and the body (which he referred to as res cogitans and res extensa) as ontologically different substances, irreducible to each other. The so-called Cartesian dualism—the distinction between mind and body,  between reason and senses—would influence Western thinking for many centuries to come. Even beyond the philosophical sphere, sensoriality and sensory experience were, until a few decades ago, the exclusive domain of neurosciences and of psychology, mostly focusing on the neurological dimension of cognition. A relevant theme, within this theoretical framework, concerns the precision of perception: what is the degree of correspondence between things “as they really are” and how we perceive them? It was only with the advent of phenomenology (in particular Merleau-Ponty, 1945) and of the concept of “embodiment” that the separation between mind and body began to be questioned and the dispute about precision was overcome. The body, no longer conceived only as a more or less reliable source of knowledge, but as an actual “intersubjective ground of experience” (Csordas, 1999, p. 143), underwent a radical rethinking, becoming an object of study by historians, sociologists, anthropologists, geographers and so on. The English anthropologist David Howes sustains that the sensory turn, in other words the conceptual turn that brought the senses to the centre of the anthropological investigation, is based on the premise that the sensorial apparatus is a social construction. As such, it requires an approach that keeps together on the one side the immediacy of the experience and on the other the culture in which we are, always and inevitably, immersed (Howes, 2004). In light of these theoretical developments, it will come as no surprise that in recent years an increasingly large number of studies have been conducted on the inherently embodied dimension of the activities of scientists, engineers, doctors, patients, designers and users: what type of sensory experience is deployed in knowledge production practices? And in turn, what are the possibilities, the chal-

 Platone - Fedone, 79 C et seq. and 99 E 1 et seq.

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lenges and the weaknesses offered by the new technologies and knowledges that leverage sensory experience? And in what way are the construction of scientific objectivity and sensoriality linked in the research practices? In the study of sensoriality as a social phenomenon, it is possible to identify three main methodological traditions: 1. ethnomethodology, focused on the study of action and interaction (e.g. Goodwin, 1994, 1995, 1996, 1997); 2. social semiotics, dedicated to the study of multi-modal communication (e.g. Kress & Van Leeuwen, 2001); 3. ethnography of the senses, centred around the experience of the perception instead (e.g. Pink, 2009). These three traditions—while at times differing significantly in defining their central themes of investigation, the role of the context and the relation between the researcher and the participants—emerged from a theoretical ground that allows productive overlaps. According to the British sociologist Bella Dicks, the first two approaches conceive the domains of non-verbal meaning (i.e. everything concerning experience of the world that is not articulated into words) essentially as a resource, while ethnography of the senses describes them as perception, that is, as originating from subjective experience of being in the world. In other words, where the first two deal with observation, listening and touch, that is actions that can be analysed through data such as audio and video recordings, ethnography of the senses examines the subjective experience of seeing, hearing and feeling (Dicks, 2014). The sense that has most attracted scholars is undoubtedly sight: watching, observing and seeing (but also representing through visual aids) have often been described as social and cultural activities developed from pre-existing professional frameworks (Coopmans et  al., 2014). The US anthropologist Charles Goodwin (1994) used the expression “professional vision” to indicate that the way we perceive the world is deeply rooted in the characteristic of a particular discipline or profession. Studying the interactions during an archaeological excavation, he observed a student negotiate with her tutor the relevant elements of the terrain and then together code colours and textures by comparing them against standardised tables. This professional activity does not merely record reality, but it also creates the object itself (as theorised by Foucault, 1971), which becomes theory, artefact, knowledge and skill. According to Goodwin, each professional group—not only archaeologists but also astronomers, psychologists, economists and so on—uses

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particular discursive practices that allow the modelling of events in such a way as to be able to boil them down to their spectrum of competences to deal with them. As such, the sensory experience is historically structured, negotiated by various artefacts and organised by social actors through discursive and gestural practices. Cognitive processes are therefore not individual and internal processes, but are social, visible and audible and organised in an interactional and intersubjective manner (Alač, 2009; Mondada, 2018; Shaping, 2016). Other senses, such as taste, touch and smell, have only recently begun to receive greater attention from the sociological and anthropological perspective, especially in the scientific and technological context. In conclusion, the sensory turn in STS has highlighted, on the one hand, the central role played by the body in the production of knowledge and, on the other, the cultural origins of sensory experience. This line of inquiry is however only at the beginning: STS, anthropology, history, ethnomethodology, philosophy and semiotics still have much to say about the multisensory aspects of science and technology, to restore body and sensoriality back at the centre of scientific practices through which the world is socially and materially organised. Further Readings • • • • •

Alač (2020a); Alač (2020b); Clark (1997); Latour (2004); Shapin (2012, 2016).

14.4 Risks, Disasters and Resilience The word “disaster” comes from the union of the Latin term astro, or “star”, and the prefix dis- which means “contrary” to; it therefore indicates an adverse fate. Chronicles and myths of natural disasters have been handed down to us since ancient times—from the biblical flood to the disappearance of the city of Atlantis; from the eruption of Vesuvius that destroyed the city of Pompeii to the epidemics that decimated the Mesoamerican populations following the arrival of European settlers. But what, in fact, is a disaster? The range of events that fall within this category is wide and diverse; it can include volcanic eruptions, epidemics, earthquakes and floods but also nuclear disasters,

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fires and acts of terrorism. Each of these circumstances has varying time frames, scope and possibilities of systematic action. Sociological studies of catastrophes and emergencies have demonstrated that it is not the nature of the calamitous event that determines the entity of a disaster but the capacity of reaction of a given society (Fortune et al., 2016). In other words, it is not a physical agent (whether it is an atmospheric condition, a geological force or a pathogen) that determines the risk but the vulnerability of a community to the phenomenon in question. Enrico Quarantelli (1993), one of the founding fathers of the sociology of disasters, defines “disaster” as a social event observable in space and time, in which certain social entities undergo upheavals of their ordinary activities as a consequence of the threat, real or presumed, produced by the relatively sudden appearance of natural or technological dangerous agents which cannot be fully or directly controlled through existing social knowledge. Risk exposure—the extent to which a community or an individual perceive risk and is ready to react to it effectively—will ultimately have a significant impact on the extent of the damage caused by the disaster. The Italian anthropologist Antonello Ciccozzi, for example, argues that complex forces come into play within the perception of risk: the relationship of trust or distrust that a community ­maintains towards its authorities, the reliability attributed to experts’ statements, the observation and assessment of other people’s behaviour, the knowledge and beliefs disseminated among a community, the role of the media and so on (Ciccozzi & Clemente, 2013). The erroneous perception of the risk presented by a certain situation (or even its lack of perception, what Ciccozzi refers to as “disastrous reassurance”, caused by an explicit underestimation of the risk by institutions) can have dramatic effects on a community. In particular, STS have dealt with the knowledge that come to light and is deployed in these situations to analyse, predict, rationalise and mitigate emergencies and disasters. Just like scientific controversies (addressed in Sects. 2.1 and 7.2), disasters are a prolific research topic as they allow us to make explicit a number of implicit assumptions and cast light on networks of social and material relations that would otherwise remain hidden in their routine working (Sims, 2007). Another topic of great interest at the interface between STS and the sociology of risk is the decision-making process in dangerous situations. How do people take decisions on safety in nuclear plants or about food preservatives, pesticides and seismic risk, for example? How is technical knowledge constructed in this field? What type of information must be provided to guarantee a rapid and efficient reaction in the case of danger? And how is the uncertainty that characterises risk assessment represented and managed? All these types of knowledges and systems of signification contribute

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to providing an agenda of actions to be (or not to be) undertaken and a social apparatus on which the responsibility for such events is distributed. At the end of the 1980s, shortly after the Chernobyl disaster, the German sociologist Ulrik Beck published a work entitled Risk Society (1986), in which he sustained that the technological and industrial development had produced new perils; in addition to individual risks, collective ones have emerged: nuclear incidents; diseases related to work, environmental conditions and lifestyles; disasters caused by climate change and so on. In the contemporary world, states Beck, the same activities through which wealth is produced—that is, technology and industry— create greater dangers that afflict communities and to which they must continually adapt. These forms of risk, while not recognising social, spatial or temporal limits—as they can affect various segments of societies, are a global threat and also extend to future generations—are not evenly distributed. Economic resources and knowledge provide tools to reduce risk, to respond more quickly to situations of emergency and to mitigate the impact of a catastrophe on a community. To face this situation of unparalleled risk, contemporary society must become reflective and develop a degree of awareness to dynamically change the course of those actions. Science and technology therefore play a central role in Beck’s society, as they are both the cause and the possible (but always partial) solution to risk. Another central theme in risk sociology is that of resilience. Partly borrowed by psychology that defines it as the ability of an individual to react and flexibly adapt to traumatic situations, social sciences transfer resilience from individuals to communities (Fortune et al., 2016). Adaptation to change undertaken by a community might mean that even the most dramatic situations of danger can have, at least in part, possible positive outcomes (such as learning, awareness and the need to change the state of things). The concept of resilience restores agency to the ordinary citizens who are instead traditionally considered passive victims of the events they experience, especially in light of the upheavals due to climate change. Further Readings • Beck (1986); • Fortune et al. (2016).

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14.5 The Personalisation of Medicine: From Pharmacogenomics to Self-Tracking Tools Personalised medicine has been proposed, with great enthusiasm, as the overcoming of the paradigm of universal medicine, defined as the approach to health that aims at the formulation of standardised diagnoses and treatments.8 The promise of personalised medicine is to pay greater attention to the specificities of the individual patient, thanks to the development of new technologies, products and services (Corrigan, 2011; Hedgecoe, 2004). According to the British sociologist of science Richard Tutton (2012), the narrative of the personalisation of medicine has its roots in the tension between the variability of the individual and universality of medical knowledge. This tension dates back to the nineteenth century when the model of “bedside medicine”, focused on the specificity of the patient and based on the clinical skill of the physician, was absorbed by “laboratory medicine”, which, instead, sets aside the patient to focus solely on the disease (Jewson, 1976, cited in Tutton, 2012). The expression “personalised medicine” can be used to indicate the various decision-making processes and approaches to health that are based on the identification of the individual predispositions identified through the history of the patient, on the tailoring of therapeutic options and on the daily monitoring of well-being (even in the absence of disease). Personalised medicine has undergone an enormous development with the advent of the so-called pharmacogenomics, the branch of genetic research that aims to calibrate the therapeutic process of each patient thanks to the identification in their genetic make-up of specific markers that allow to determine how they will react to a certain drug. Starting from the early 2000s, pharmacogenomics has gained a foothold mainly in oncology, due to the wide diffusion of associated diseases and the huge variety of therapeutic options. In this field, custom medicine reshapes the traditional boundaries between spaces of care and spaces of scientific innovation, making laboratories and hospital wards hybrid places in which bodies, technology, disease and health redefine each other (Crabu, 2017).

 The critique of the standardisation of medicine (Montgomery, 2017; Timmermans & Epstein, 2010) and of the tacit assumptions of biomedicine on the existence of a universal body (proposed by a globalised clinical experimentation methodology) towards “local biologies” (Lock, 1993; Lock & Nguyen, 2010) are becoming increasingly popular (see Merz, 2020). For example, Towghi (2013) has documented how the testing of vaccines against human papillomavirus (HPV) has widely ignored scientific evidence on the existence of various genotypes of HPV and the demography of the incidence and of the prevalence of cervical cancer in the Indian population. 8

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If pharmacogenomics is focused on the diagnosis and treatment of specific pathologies, there are also tools whose aim is to make the maintaining of health and psycho-physical well-being more personalised and participated through a process of daily medicalisation. In the last ten years, self-tracking devices—from smartwatches to all those applications that allow the monitoring of daily routinary actions via smartphone—have stirred a new wave of enthusiasm towards the personalisation of health. With these tools, each user can record and store data on their heart rate, on the physical activity performed, on the quality of their sleep, on their diet and on other physical-metabolic activities considered significant. The adoption of this digital apparatus allows the creation of numerical and statistical data that are normalised (i.e. in compliance with established standards) and normalising (in turn establishing which is the standard to comply with). This daily routine of monitoring the body seeks to involve individuals in the management of their health and in the collection of data that allow, in case of illness, a more efficient clinical decision-­ making process. An example of this is Verily—a company that belongs to the same group as Google and that, like the web giant, hoards the enormous amount of information collected from users. On their website, Verily’s executives state the company’s mission as being that of combining the clinical experience of its consultants with technological innovation and algorithm development to “empower patients to take ownership of their health and help physicians and caregivers deliver more personalized and evidence-based care” (from https://verily.com/). This rapidly expanding industry sector includes programmes ranging from the monitoring of newborns to the tracking of the daily routines of those with Parkinson’s disease. According to the philosopher and sociologist of technology Tamar Sharon (2017), the debate on the use of these technological aids has become defined along three lines. 1. Emancipation vs. surveillance and discipline. Advertisements present self-­ tracking devices as tools enabling the individual to take charge of their health, to take control of the most “uncontrolled” elements of their lifestyle and, as such, to establish a more equal footing with their doctor. This sort of democratisation of medicine proposes to leave behind a paternalistic and one-sided model of health-care to move towards a joint, more equal and participatory relationship. However, this approach, according to some critics, is simply hiding an attempt to encourage users to align with pre-established medical regimes, which in this way would not be negotiable in a two-way relationship but would enormously extend their authority instead. The medicalisation of everyday life would not only concern those who, in the presence of a pathology or a chronic condition, require treatments and cures but, by virtue of the principle of preven-

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tion, would also expose healthy individuals to intense control. According to US sociologist Debora Lupton (2012), the voluntariness and enthusiasm with which these technologies are adopted make this type of surveillance difficult to classify according to more traditional theoretical frameworks in which the supervised becomes a passive subject under the normalising gaze of the system. 2. Improvement of health vs. disintegration of state and collective responsibility for health. The promotion of self-tracking technologies often leverages on the fact that personalised health care is not only actually more effective but also more financially sustainable in the long run. This notion often goes hand in hand with the neoliberal trend of many Western countries to urge the individual citizen to take charge of their state of health to ease the burden on the health system. From this perspective, it is difficult to separate the individual and the community: the management of individual health is a means for the community-­ wide administration of the entire health system. This narrative, focused on the individual’s empowerment, has another consequence too: if being healthy is linked to choices that each of us can make, then being subject to chronic pathologies and conditions implicitly becomes the object of stigmatisation and blame. The empowerment of the individual runs in parallel with a progressive erosion of health care programmes and social and economic support at the state and government level, thus moving away from the interests of citizens and the ideal of public health as a common good. 3 . Greater self-awareness vs. reductionism and non-impartiality of numerical data. The promise of a more precise and extensive knowledge of one’s health based on the centrality of numerical data is presented as a necessary element to take forward not only scientific research but also our “sense of self-awareness”. The latter, no longer based on subjective experience (i.e. on how we “feel”) but on “measurable” data, is deemed more objective, reliable and comparable. However, as seen in Chap.12, the algorithms that create and manage data are not neutral tools but instead encapsulate policies and values, configuring ideals of health and well-being that reproduce normative stereotypes that users are induced to conform to. Sharon, however, distances herself from this polarised debate and calls for a more empirical approach that does not represent social actors in a simplistic way but that investigates the complexity of the user experience, focusing on the daily practices in which these instruments are used. Self-tracking tools, in fact, do not replace or counter incorporated knowledge but, gradually and dynamically, become an integral part of it (Zampino, 2019).

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Further Readings • Tutton (2012); • Sharon (2017).

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Leach, E. (1964). Anthropological Aspects of Language: Animal Categories and Verbal Abuse. In E. H. Lenneberg (Ed.), New Directions in the Study of Language (pp. 23–63). The MIT Press. Lock, M. (1993). Encounters with Aging: Mythologies of Menopause in Japan and North America. University of California Press. Lock, M., & Nguyen, V. K. (2010). An Anthropology of Biomedicine. Wiley- Blackwell. Lupton, D. (2012). M-Health and Health Promotion: The Digital Cyborg and Surveillance Society. Social Theory & Health, 10(3), 229–244. https://doi.org/10.1057/sth.2012.6 Merleau-Ponty, M. (1945). Phénoménologie de la perception. Gallimard. (transl. Phenomenology of Perception, London: Routledge & Kegan Paul, 1962.) Merz, S. (2020). Global Trials, Local Bodies: Negotiating Difference and Sameness in Indian For-profit Clinical Trials. Science, Technology, & Human Values, 46(4), 882–905. Mondada, L. (2018). The Multimodal Interactional Organization of Tasting: Practices of Tasting Cheese in Gourmet Shops. Discourse Studies, 20(6), 743–769. https://doi. org/10.1177/1461445618793439 Montgomery, C.  M. (2017). Clinical Trials and the Drive to Material Standardisation: “Extending the Rails” or Reinventing the Wheel? Science & Technology Studies, 30(4), 30–44. https://doi.org/10.23987/sts.59226 Morgan, G. H. (1868). The American Beaver and His Works. J. B. Lippincott. Paxson, H. (2008). Post-Pasteurian Cultures: The Microbiopolitics of Raw-Milk Cheese in the United States. Cultural Anthropology, 23(1), 15–47. https://doi.org/10.1111/j.1548-­1360.2008.00002.x Pink, S. (2009). Doing Sensory Ethnography. Sage. Quarantelli, E. L. (1993). Disastri, in Enciclopedia delle scienze sociali. http://www.treccani.it/enciclopedia/disastri_%28Enciclopedia-­delle-­scienze-­sociali%29/ Raffles, H. (2010). Insectopedia. Pantheon. Shaping, S. (2012). The Tastes of Wine: Towards a Cultural History. Rivista di estetica, 51(51), 49–94. https://doi.org/10.4000/estetica.1395 Shaping, S. (2016). A Taste of Science: Making the Subjective Objective in the California Wine World. Social Studies of Science, 46(3), 436–460. https://doi. org/10.1177/0306312716651346 Sharon, T. (2017). Self-Tracking for Health and the Quantified Self: Re-Articulating Autonomy, Solidarity, and Authenticity in an Age of Personalized Healthcare. Philosophy and Technology, 30(1), 93–121. https://doi.org/10.1007/s13347-­016-­0215-­5 Sims, B. (2007). Things Fall Apart: Disaster, Infrastructure, and Risk. Social Studies of Science, 37(1), 93–95. https://doi.org/10.1177/0306312706069429 Szymanski, E. A. (2018). What Is the Terroir of Synthetic Yeast? Environmental Humanities, 10(1), 40–62. https://doi.org/10.1215/22011919-­4385462 Timmermans, S., & Epstein, S. (2010). A World of Standards but Not a Standard World: Toward a Sociology of Standards and Standardization. Annual Review of Sociology, 36(1), 69–89. https://doi.org/10.1146/annurev.soc.012809.102629 Touzard, J.-M., et  al. (2015). Innovation Systems and Knowledge Communities in the Agriculture and Agrifood Sector: A Literature Review. Journal of Innovation Economics and Management, 17(2), 117–142. https://doi.org/10.3917/jie.017.0117

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Conclusion

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For some decades now, STS have established themselves as a sector of autonomous investigation and research, with their own schools, institutions, associations conferences and a dozen specialist journals.1 With this book we have sought to propose a summary of the many theories, reflections and tendencies, starting from the philosophy of science in which, historically, this area of studies has its roots.2 Today the movement of STS is distributed and dispersed across a myriad of specific areas and micro-topics and it has become truly difficult to summarise each and every one of them. In fact, Bucchi states that in the sociology of science, especially from the beginning of the 1990s, a certain situation of impasse came into existence. With the growing popularity of case studies and with ever increasing internal specialisation, there was no corresponding theoretical growth [and we moved towards] a relative isolation from the general sociological theory, preferring instead to develop intersections with other disciplinary sectors. (pp. 122 and 131)

 To recall only those that expressly refer to STS, we can indicate the following (in alphabetical order): “Bulletin of Science, Technology & Society”, “Engaging Science, Technology, and Society”, “Science & Society”, “Science & Technology Studies”, “Science and Engineering Ethics”, “Science and Public Policy”, “Science as Culture”, “Science Technology and Society”, “Science, Technology, & Human Values”, “Social Studies of Science” and “Tecnoscienza”. 2  It is, however, interesting to note that these roots seem now to have entirely disappeared from the reflections of STS scholars. Some academics, who could be considered their founding fathers such as Enriques, Duhem, Bachelard, Quine, M. Polanyi, Toulmin and Hanson, seem to be completely unknown; Feyerabend is infrequently cited and Fleck only receives the barest of mentions. Creating the illusion that everything began with Kuhn. 1

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An accusation often levelled against STS is that their constructivist and relativist theories have contributed—albeit indirectly—to delegitimising science. It is thought that their deconstructions of scientific practices, within the context of a post-modern intellectual climate, have generated (also in the public opinion) a widespread scepticism regarding the products of science with a tendency to d­ issolve the boundaries between experts and the public, thereby resulting in undermining of the reputation of the former and the viewing of science as nothing else but another form of politics. As such, according to Collins et al. (2017), STS also should take on a certain amount of responsibility in the emerging era of post-truth3 and anti-scientific populism. It is only by reaffirming the possibility of distinguishing a good method of conducting science from a bad one, recognising “that science has a distinctive form of life and that there is a reality to expertise” (idem, p. 584), that STS can divert from the risky ambiguity towards which they are headed. Conversely, Latour and Woolgar (1991, p. 31), Knorr-Cetina (1995, p. 149) and Sismondo (2017a, 2017b) reject this accusation. Their agnostic approach, the wish to suspend judgement on matters of truth, reality and rationality in order to maintain a position of impartiality and symmetry, in no way means that all pieces of knowledge are the same as each other and that reality is a mere figment of our imaginations, much less to conclude that STS are against science. Therefore, the placing between brackets, the phenomenological suspending of judgement on the natural world, precisely on agnosticism, is therefore not defined as atheism and must not be confused with it. Another uncertainty that has troubled STS for some time is what their contribution to the development of scientific knowledge might be. In other words, a sceptic might wonder: what can STS give to science? Is it just to be the critical conscience, to open the black box, to identify the social elements of technological artefacts and, in general, to encourage greater reflexivity? Or is it to foster a constructive dialogue between STS and physical and natural scientists (as attempted in Labinger & Collins, 2001), a more substantial contribution, in the sense of collaborating with scientists to produce knowledge in a different manner, to construct scientific facts in a less positivist way and less dominated by the logic of the market, the practices of power and domination, and to democratise science?

 An expression that indicates that condition according to which, in a discussion relating to a fact or to a piece of information, the truth is considered a matter of secondary importance. As such, the information would be perceived and accepted as truth by the public on the basis of emotions and sensations, without any deep analysis of the actual veracity of the narrated events. 3

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Perhaps STS might also be able to take on the role of mediators in scientific dissensions, disagreements and opposing visions, including the issues of gender and of discrimination in general. Based on their knowledge of how conflicts in science come about, are developed and are historically resolved, STS could propose themselves to scientists as mediators to positively manage conflicting dynamics and to reactivate the dialogue and communication between the parties. Through specific techniques (that can be identified in the “process consultation”,4 in the “non-violent resolution of conflicts”,5 in “transformative research”6) STS could allow the conflicting parties to understand the reasons of the contenders, move beyond the conflictual situation through the mutual recognition of the various points of view, needs and emotions, reopen closed dialogue and reactivate communication, facilitating agreements and shared negotiations, and also prevent the exasperation of the conflictual dynamic and the possible negative consequences. Finally, STS leave as a legacy a very strong message: the idea that the content of scientific knowledge has an unavoidable social component (fairly large, depending on the various approaches). This defines science as an activity of construction, negotiation, redefinition and, above all, boundary work. We can recall this latter aspect with a concluding example: between the end of the nineteenth and the beginning of the twentieth century, the German chemist Fritz Haber developed, together with his colleague Carl Bosch (German chemist, engineer and entrepreneur), 4  The philosophy underpinning the process consultation (Schein, 1998) considers that the knowledge useful for the resolving of organisational problems and of conflicts is already present in organisations. What is often missing is a method to facilitate its emerging through a dialogue between the social actors. Therefore, the consultant is not a contributor of substantial knowledge but instead of a formal and procedural framework to activate and stabilise the communication processes. 5  One of these is the Transcend method (Galtung, 2000), proposed as a path for the resolution of conflicts using peaceful methods. The premises for this method were drawn from the Hindu, Buddhist, Christian, Taoist, Islamic and Jewish religions. 6  Transformative research refers to an alternative method of conceiving research.  It starts from the assumption that every act of knowing is already an intervention. Hence, its aim is not only exploring particular theoretical knowledge but also to introduce improvement and changes in communities, organisations and individuals. Examples of this type are the experimental and psycho-social approach of action research of Lewin (1948) and of his collaborators Festinger and Kelley (1951) that had a significant influence on the birth of other approaches which ideally refer to it, such as the corporate “cooperative research” of Lippitt and Lippitt (1978), the “participatory research” of Whyte (1991), which follows the sociotechnical model of the humanisation of organisations, the “action science” of Argyris et al. (1985), which is situated in process consultation, the “empowerment” of Rappaport et al. (1984), which deals with the strengthening of the individual abilities of actors, the “intervention research” (intervention sociologique) by Touraine (1984), etc.

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the process of synthesis of ammonia at high temperature and pressure. The process—thereafter known as the Haber-Bosch process—used as a raw material hydrogen, nitrogen and iron (the latter acting as a catalyst), thus making the process extremely simple and economical. Haber’s research, unfortunately, also makes possible the use of chlorine and phosgene, two toxic gases, as weapons of mass destruction. In fact, these lethal gases were used during the First World War, ­causing more than a million deaths despite their use being banned by the Hague Convention of which Germany was also a signatory. In 1918 Haber was awarded the Nobel Prize in Chemistry (despite the protests of many scientists who considered him to be the father of chemical weapons) “for the synthesis of ammonia from its elements” before being charged (unsuccessfully) as a war criminal. In the 1920s, to help his country pay off its war debt, Haber frantically sought a method to extract gold from sea water and published a series of scientific articles on the topic. After years of research, however, he concluded that the concentration of gold dissolved in sea water was much lower than that reported by previous researchers and that the extraction of gold from sea water was uneconomical. We can now ask ourselves: who was Haber? A scientist or a pseudoscientist, in some ways reminiscent of the alchemists of past centuries intent on transforming lead (and metals in general) into gold? A criminal or a benefactor? Where does the boundary lie? Perhaps he was all of these things at the same time. From this episode (of the many that exist), we can understand the need to adopt a different attitude, both pedagogical and moral, for the new generations of citizens and scientists. In fact, the theories and research of STS on the one hand encourage teaching of science (in schools, in universities, in museums, in the mass media, etc.) from a different perspective, far removed from the neopositivist myths that are still dominant in scientific practice and in public opinion that fuel the scientistic imagery. On the other, through the lesson that can be drawn from the study of controversies, STS remind us of a more tolerant, open, possibilistic, curious, empathic and less dogmatic attitude towards those who present ideas, hypotheses and theories that are still uncertain or marginal. This awareness might seem, on the one hand, abstract and without practical implications; on the other (as we have just seen) it could appear sceptical of the scientific undertaking. However, it is actually the scientistic idealism  or scientism  (that portrays scientific research as ahistorical and universal) that fuels scepticism and distrust of science (Gobo 2023)  especially when it fails or falls short of the expectations of a situation. The intellectual undertaking of research and of the production of knowledge can, instead, be reread in light of its historical path and of its social dynamics. The result will be a richer, more human and more stimulating understanding of the scientific undertaking.

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What we take from STS is a positive message, a new scientific humanism, in which all the objects and living beings mutually recognise each other as examples of bio-cultural hope. We are encouraged to learn new methods of being in the world, of relating, adapting and co-habiting, especially in this age of ecological disasters. Will we be able to change before it’s too late? And, above all, how? STS are signposting the way. It’s up to you to follow it.

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Index

A Abduction, 60–62 Abortion, 13, 14 Abrahamsson, Sebastian, 271 Actant, 108, 187, 188, 196 Action, 19, 20, 22, 26–30, 35, 39, 50, 66, 92, 97, 102, 108, 114, 125–128, 131, 136, 137, 152–155, 157, 168, 170, 185, 188, 191, 202, 203, 224, 226, 229, 235, 241, 242, 250, 255, 268, 273, 275, 276, 278 Activist movements, 164, 166 Actor-Network Theory (ANT), 107–109, 123, 184, 187–191, 196 translation, 107, 108, 187 Agency, 76, 154, 254, 266, 276 Agriculture, 171, 266, 268, 269 organic and biodynamic farming, 270 pesticides, 269, 270 Alač, Morana, 243, 274 Alchemy, 49, 50, 55, 115, 128, 129, 137 Algorithms choices, values, ideologies, 236 Google, 236, 278 objectivity, 237, 238

Al-Qaeda, 11 Analogy, 29, 65, 66, 69, 70, 72, 82–89, 105, 106, 112, 202, 233, 256 Anarchism (methodologicy), 78 Angier, Natalie, 202 Anomalies, 56, 63, 67–69, 76 Anthrax, 107, 108 Anthropocene, 227–230, 233, 267 Chthulucene, 267 Arbitrariness, 23, 43 Archilochus, 21 Arendt, Hannah, 229 Aristotle, 10, 21, 22, 31, 61, 81, 85, 95, 129, 206 Artefacts scripts, 188 Artificial intelligence, 241–245 Artmann, Stefan, 233, 234 Asimov, Isaac, 245 Astrology, 48, 49, 55, 128 Astronomy planets, 148 Atherosclerosis, 250 Atom, 85, 112 Austin, John Langshaw, 87

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2022 G. Gobo, V. Marcheselli, Science, Technology and Society, https://doi.org/10.1007/978-3-031-08306-8

315

316 B Babbage, Charles, 234 Bachelard, Gaston, 36, 285 Bacon, Francis, 36, 94, 124, 129 Bacteria, 84, 86, 107, 108, 110, 159, 187 Ballatore, Andrea, 243 Barbercheck, Mary, 203 Barish, Barry, 149 Barnes, Barry, 53, 92, 126 Bauman, Zygmunt, 2 Beck, Ulrik, 2, 276 Beer, David, 237, 238 Behaviourism, 39, 93 Benedetti, Giovanni Battista, 59 Berlin, Brent, 1, 24, 84 Bertoni, Filippo, 271 Bicycle, 30, 185, 186, 189, 195 Big data, 238–240 Bijker, Wiebe, 184–186, 196 Biology (synthetic), 242, 259–262 biotechnologies, 2, 160, 171, 249–262, 266 engineering approach, 260, 261 mapping of genome, 110, 258 Biopolitics/biopower, 253–255, 261 Biosociality, 259 Black box, 151–156, 236, 286 Blair, Tony, 256 Bloor, David, 53, 87, 88, 93, 96–99, 101, 102, 106, 108, 110, 115–117, 147 Body and biopolitics, 254 dualism body-mind, 209 Bohr, Niels, 56, 95 Boltzmann, Ludwig Eduard, 36 Boriosi, Gino, 5 Boroditsky, Lera, 24 Botany, 83, 85, 129, 201 Boundary of science, 123–140 Boundary work, 124–131, 140, 184, 271, 287 Boyle, Robert, 49, 114 Brahe, Tycho, 49, 137, 138 Brante, Thomas, 155 Brentano, Hermann, 36

Index Bridgman, Percy Williams, 84 Bridgmanite, 84 Bruni, Attila, 235 Bruno, Giordano, 81 Bucchi, Massimiano, 170, 171, 173, 174, 176, 285 Butler, Judith, 212 C Callon, Michel, 107, 175, 184, 187, 188, 190 Campo, Enrico, 5 Carey, Susan, 24 Carnap, Rudolf, 1, 36–38, 40–42, 45, 47 Carothers, John Colin Dixon, 23 Carson, Rachel (Silent Spring), 180, 224 Causality (principle of), 37 Cerroni, Andrea, 72, 91 Chemistry, 54, 85, 114, 115, 129, 138, 201, 288 Chomsky, Noam, 31 Churchland, Patricia, 112 Churchland, Paul, 112 Ciccozzi, Antonello, 275 Cicerone, 27 Circle of Vienna, 1, 36 Cisalpino, Andrea, 81 Citizen science, 173–176 Civic epistemologies, 167, 168 Clarke, Arthur, 244 Classical Modernity, 109 Classifications, 15–18, 23, 24, 27, 29, 35, 99, 104, 236, 265 Climate change, 2, 164, 168, 219, 220, 222–227, 229, 276 Clinton, Bill, 256 Cognitivists, 31 Collins, Harry, 5, 31, 53, 62, 92, 100, 101, 110, 148, 150, 151, 156, 161, 165–167, 190, 191, 242, 286 Common-sense, 4, 15, 16, 79–82, 86, 192, 202 Communication of science, 170, 175 and public opinion, 4, 169, 170 Communitarism or communism, 92, 125

Index Computer, 19, 103, 106, 187, 195, 223, 233–235, 239, 241, 242 Confirmation, 38, 45, 47, 73, 149, 150 Conjectures, 105, 116 Connotation, 167, 210, 212, 229 Conseil Européen pour la Recherche Nucléaire (CERN), 56, 158, 163, 195 Constructivism, 98, 110 Context of discovery, 42 of justification, 159 Controversies (scientific), 100, 102, 150, 155, 160, 167, 275, 288 Conventionalism, 10, 13, 19, 23, 73, 81, 112, 114, 165, 222, 270 Cooper, Lane, 95 Copernicus, 71 Cowan, Ruth Schwartz, 212 Crisis of science, 229 Cronon, William, 221 Crutzen, Paul Josef, 227, 228 Culture/nature, 109–110, 152, 265, 266 epistemic, 156–160, 164 and inculturation, 157 oral cultures, 22–23 written cultures, 22–23, 94 Cumulability of knowledge Cyborg, 109, 210, 211 D Darwin, Charles, 58, 150 Data hubris, 240 De Mauro, Tullio, 19 de Saussure, Ferdinand, 13, 19 Death, 5, 43, 50, 59, 101, 110, 154, 155, 257, 288 Dedekind, Richard, 97 Deduction, 41, 47, 60, 61 Deleuze, Gilles, 102 Demarcation criterion of, 48–49, 55, 56, 126 problem of, 124–131 Democracy and decision making, 165–167

317 Democritus, 10, 85 Denotation, 19, 39, 40, 112 Descartes, René, 3, 31, 208, 272 body/mind dualism, 209 Design, 106, 138, 170, 181, 184, 186, 188, 192, 234, 236, 237, 254, 261 Determinism (technological), 182–184 Deviance, 93–96 Dick, Philip K., 245 Dicks, Bella, 273 Digital humanities, 239 and methodological challanges, 238–240 Digital societies /information society, 233–245 Discourse (public), 1, 5, 87, 186, 210, 251, 261 Disinterestedness, 92, 125 Dodds, Eric R., 22 Dreyfus, Hubert, 242, 245 Drugs, 5, 43, 108, 165, 277 Duhem, Pierre, 36, 54, 149, 285 Dulbecco, Renato, 102 Duprè, Sven, 261 Durkheim, Émile, 92, 93, 96, 103 E Earth System Science, 223 Ecology of infrastructure, 190, 191 of knowledge, 190 political ecology, 109, 229 Economics, 168 Edge, David, 92 Edison, Thomas, 110 Einstein, Albert, 3, 66, 72, 79, 95, 143, 148–150 Empirical reality, 38, 98 Energy nuclear, 96, 180 Engineering, 54, 127, 192, 202, 203, 260, 261 Enriques, Federigo, 36, 285 Environmental humanities, 229 Epicurus, 85

318 Epistemology, 35–50, 53, 78, 114, 115, 225, 229 Epstein, Steven, 164–166, 175, 277 Ethnography Malinowski and participant observations, 156 multi-species, 265–268 Ethnometodology, 273, 274 Ethos (institutional), 124–126 Evans, Robert, 165–167 Expectations (sociology of), 192–196 Experience, 15, 16, 19, 20, 26, 30, 31, 37, 39, 40, 42–45, 47, 54, 57, 60, 63–64, 75, 76, 80, 95–98, 150, 157, 158, 160, 174, 191, 203, 221, 223, 225, 226, 236, 249, 251, 253, 266, 272–274, 276, 278, 279 Experimenter regress, 148–151 Experiments, 132 activities (experimental), 76, 103, 105, 132–134, 157 on animals, 42, 43 mental experiments, 95, 181, 242 method (experimental), 94–96, 113, 132 tower experiment (Galilei), 79, 95 Experts and expertise, 163, 171 interactional and contributive, 166 lay expertise, 166 Exploration (of space) NASA, 195 space race, 76 Expression (linguistic), 13 F Facts factish, 105, 152 institutional, 112 scientific, 63, 101, 102, 107, 151–153, 156, 222, 225, 286 specialist, 104 Falcon, Andrea, 5 Felt, Ulrike, 175, 176 Fermi, Enrico, 96 Ferrier, James F., 35

Index Feyerabend, Paul K., 3, 4, 53, 54, 67, 73–81, 285 Fleck, Ludwig, 36, 54, 62, 63, 89, 102, 115, 285 Fludd, Robert, 81 Fochler, Maximilian, 175, 176 Foucault, Michel, 237, 254, 255, 258, 261, 273 Fox-Keller, Evelyn, 262 Fracking, 167 Frege, Gottlob, 1, 36, 39, 40, 97, 98 Fresnel, Augustin-Jean, 65 Freud, Sigmund, 30, 48, 152, 250 Fromm, Erich, 30 Frontier, 221, 243 Fujimura, Joan, 191 G Galilei, Galileo, 3, 35, 49, 56, 59, 76, 77, 79, 80, 94, 95, 104, 112, 113, 129 Gallino, Luciano, 30 Garfinkel, Harold, 102 Geddes, Patrick, 205 Geertz, Clifford, 27, 29 Gender inequalities, 205, 208, 209 sex / gender, 205, 207, 209 Generalizations (empirical), 204 Genetically modified organisms (GMO), 42, 164, 173 Gestalt, 58, 60, 63, 70, 80, 115 Gibson, James, 188 Giddens, Anthony, 137 Gieryn, Thomas, 124–128, 135–138, 140, 143 Ginkgo biloba, 85 Giusti, Enrico, 97 Globalisation, 228 Gnoseology, 9–32 Gobo, G., 5, 84, 86, 151, 203, 204, 249, 250, 288 Gödel, Kurt, 36 Golem, 5 Goodfield, June, 58 Gordon, Peter, 24

Index Guicciardini, Niccolò, 5 Gutenberg, Johann, 94 H Habermas, Jürgen, 3 Hacker spaces, 174 Hacking, Ian, 160 Hallberg, Margareta, 155 Hanson, Norwood R., 4, 53, 54, 57–63, 79, 285 Haraway, Donna, 109, 113, 208, 210, 211, 213, 228, 266–268 Harding, Sandra, 114, 149, 207, 208, 213 Harvey, William, 81 Health, 94, 99, 140, 165, 206, 223, 235, 237, 249, 250, 253, 255, 257, 258, 277–279 medicalisation of everydaylife, 278 Helmreich, Stefan, 259, 261, 266, 268 Henrietta Lacks (HeLa), 256, 257 Hesiod, 21 Hesse, Mary, 53, 113, 114 Hessen, Boris, 91 Heuristics, 15, 73 HIV/AIDS, 43, 82, 164, 257 Hobbes, Thomas, 36 Holton, Gerald, 72 Homer, 21, 22, 27, 57 Hong Kong, 12, 13 Hooke, Robert, 83, 114 Horkheimer, Max, 3 Hospital, 136–138, 249–251, 254, 257, 277 Howes, David, 272 Human Genome Project (HGP), 255–259 ethical legal and social impact (ELSI), 258, 259 Humanism (scientific), 5, 289 Humans and non-humans agency, 266 animal turn, 266 cfr. multispecies ethnography, 265 Hume, David, 36, 37, 59 Hutchins, Edwin, 242 Hypothesis, 3, 18, 42, 45, 60, 61, 85, 107, 129, 149, 150, 187, 239, 242 Hypothetical-deductive model, 40, 60

319 I Illusion (optical), 58, 74, 75, 79 Imaginary (sociotechnical), 192–196, 220 Impartiality, 286 Incommensurability, 62, 64, 70, 125 Induction, 37, 38, 41–42, 46–47, 60, 61, 114 Information deficit model, 170–173 Initial baptism theory, 84–86 Inscriptions, 102–105 Institutionalisation, 123, 229 Interdisciplinarity, 123, 229, 261 Intersubjective/intersubjectivity, 251, 274 Irrational, 2, 77, 99 J James, William, 102 Jamieson, Dale, 225, 226 Jasanoff, Sheila, 167, 168, 194, 196, 222, 224, 226 Jenner, Edward, 85, 86 Jung, Carl Gustav, 30 K Kaempfer, Engelbert, 85 Kant, Immanuel, 83 Kay, Paul, 24 Kepler, Johannes, 235 Klein, Jacob, 99 Knorr-Cetina, Karin, 113, 134, 156, 157, 159–161, 179, 286 Know-how, 30, 126, 153, 157 Knowledge scientific, 2, 3, 9, 35–50, 63, 81–82, 87, 93, 102, 123, 133, 155, 157, 167, 179, 185, 205, 224, 226, 249, 286–288 situated, 138, 207–210 sociology of, 91, 93 tacit, 29–31, 35, 104, 157 Koffka, Kurt, 58 Kohler, Robert, 143 Köhler, Wolfang, 58 Koyré, Alexander, 59, 95 Kripke, Saul Aaron, 84, 85 Kubrick, Stanley, 244

320 Kuhn, Thomas, 4, 53, 62–74, 76, 77, 79, 87–89, 92, 96, 113, 124, 125, 285 Kühne, Wilhelm, 85 L Laboratory, 31, 43, 56, 68, 96, 100, 102–108, 127, 134, 137–140, 147–149, 156–160, 174, 190, 202, 222, 242, 249, 256, 257, 259, 266, 270, 277 studies, 147, 156–161 Lakatos, Imre, 54, 72, 73, 77, 113 Lakoff, George, 82, 89 Language, 9–13, 17–31, 35, 37–39, 41, 42, 58, 63, 64, 66, 67, 79, 83, 84, 86, 102, 112, 156, 174, 235, 242 scientific, 37, 39 Latour, Bruno, 5, 30, 53, 101–111, 113, 114, 117, 152, 153, 156, 161, 179, 184, 187, 188, 190, 191, 196, 266, 274, 286 Laudan, Larry, 93, 113 Law (scientific), 40–41, 44 Law John, 107, 143 Leenhardt, Maurice, 22, 23 Leibniz, Gottfried Wilhelm, 234 Leonardo da Vinci, 59, 81, 193, 251 Leucippus, 85 Levinson, Stephen, 24 Lewis, Gilbert N., 66 Libavius, Andreas, 137, 138 Liberalism (political), 46 Life and artificial living systems, 260 and complexity, 226 definition, 88, 261 Locke, John, 36 Logical problem of induction, 47, 125 Lorimer, Jamie, 227, 229 Lovelace, Ada, 201, 234 Lovelock, James, 224 Lowell, Percival, 75 Lupton, Debora, 279 Lurija, Aleksandr Romanovič, 11, 22 Lutero (Martin Luther), 71

Index M MacDonald, Sharon, 174, 175 Mach, Ernst, 36 MacKenzie, Donald, 54 Mairotte, Edme, 114 Malcolm X, 18 Mammals, 206–207 Mannheim, Karl, 91, 92 Marradi, Alberto, 10, 15, 17, 18, 20, 30–32 Marx, Groucho, 113 Marx, Karl, 182 Marxism, 1, 48, 55 Masterman, Margaret, 64 Mathematics, 64, 72, 91, 96–101, 114, 147 Maxwell, James Clerk, 65, 66 Mayr, Ernst, 74 Mazzolini, Renato G., 5 McCarthy, John, 241 McLuhan, Marshall, 23 Meaning, 9, 11, 15–18, 20, 24, 32, 37–40, 44, 46–48, 55, 99, 102, 110, 116, 156, 157, 185, 186 Medicine personalized, 277 traditional chinese, 249 Western medicine or biomedicine, 249, 250 Meinong, Alexius, 15, 36 Melanesians, 23 Merchant, Carolyn, 230 Merleau-Ponty, Maurice, 272 Merton, Robert K., 91–92, 124, 125, 180 Metaphors, 82–88, 128, 153, 185, 202, 207, 208, 210, 221–223, 241, 242, 256 Metaphysics, 2, 37, 43, 48, 65, 71, 93, 94, 96 Meteorology, 235 Method (experimental), see Experiment Method (scientific), 3, 63, 96, 101, 113, 129, 130, 135, 147, 151, 156, 170, 261 Metonymies, 82–88 Michael, Mike, 194 Microorganisms, 76, 107, 159, 190, 260, 262, 266, 267, 270, 271

Index Midazolam (drug), 108 Mill, John Stuart, 76, 97, 98 Mol, Annemarie, 143, 250 Morgan, Gareth, 86, 88, 265 Motion of the earth, 79, 80, 148 Muir, John, 222 Mulkay, Michael, 92 Multispecies Saloon, 266 N Nagel, Thomas, 135 Nagel, Ernest, 50 Natale, Simone, 243 Nature natural phenomena, 137, 147, 148, 152, 159, 222 nature/society (see Culture/nature) Naylor, Ronald, 95 Neo-positivism or logical positivism, 1, 2, 35–44, 46, 54, 63, 69, 87 Neresini, Federico, 170, 171, 173, 174, 176 Network, 5, 16, 18, 62, 66, 72, 86, 107, 108, 136, 187, 188, 190, 191, 196, 211, 225, 235, 240, 245, 267, 275 Neurath, Otto, 36, 87 New Economics Foundation (NEF), 25 Newton, Isaac, 49, 50, 65, 66, 91, 95, 129 Nigel, Gilbert, 92 Nobel prize, 168 Normalisation, 73, 183, 253–255 Normality, 211 Norman, Donald A., 26 North Atlantic Treaty Organization (NATO), 11 O Objectivity, 2, 95, 109, 208, 237–239, 273 Observatory (astronomic), 137 Observer (problem of), 97 Ogden, Charles Kay, 18 Oldenzie, Ruth, 210 Ong, Walter J., 22, 23 Oppenheimer, Robert, 96 Optics, 49, 65, 77, 129

321 Organization, 11, 23, 26, 29, 43, 58, 86, 88, 96, 104, 109, 127, 130, 132, 133, 135, 136, 159, 170, 174, 191, 201, 203, 205, 251, 269, 270, 287 Organized scepticism, 92 Ørsted, Hans Christian, 95 Overview effect, 223 Oxygen (discovery of), 67–69 Ozone, 5, 110 P Paradigm, 62, 64–72, 74, 75, 80, 125, 169, 206, 239, 253, 256, 269, 277 and incommensurability, 62, 64, 70, 125 Parisi, Domenico, 31 Parisi, Luciana, 236 Particle accelerators, 134, 179, 195 Pasteur, Louis, 107, 108, 110 Patients, 250 Peirce, Charles Sanders, 60, 61 Peiris, Hiranya, 56 Perception, 21, 24, 27, 37, 57, 58, 67, 77, 80, 82, 98, 114, 202, 221, 272, 273, 275 Philosophy (natural), 124, 129, 130, 147 Physics of gravitational wave, 148–150 Pickering, Andrew, 115, 182 Pinch, Trevor, 5, 54, 100, 150, 151, 184–186, 254 Place building, 135, 137 topoi, 220 and “truth spots” 138, 139 Planck, Max, 66 Planet Earth, 148, 192, 223 Mars, 75, 76, 128, 224 Plato, 129, 272 Polanyi, Michael, 4, 30, 31, 62, 285 Polarisation of points of view, 2 Pontzen, Andrew, 56 Popper, Karl, 2, 3, 19, 40–42, 44–50, 53–57, 60, 62, 63, 69, 72, 73, 76, 77, 87, 88, 96, 113, 115, 116, 124, 125, 129 falsificationism, 44–45, 55, 72, 125, 149

322 Postmodernism, 10 Post-traumatic stress disorder (PTSD), 250, 251 Post-truth, 1, 171, 286 Price, Derek de Solla, 233 Problem of induction, 47, 125 Protocols, 38, 40, 75, 249 Pseudoscience, 1, 48, 100–101 Psychoanalysis, 1, 48, 55 Public engagement, 173–176 Public Understanding of Science, 4, 170–172 Publications (scientific), 134 Putnam, Hilary, 3, 113 Puzzle, 66, 67, 69, 88, 113, 149 Q Quarantelli, Enrico, 275 Quark, 83, 85, 115 Quine, Willard Van Orman, 53, 54, 63, 87, 149, 285 Quine-Duhem (thesis of), 149 R Rabies (desease), 107 Radical relativism, 111 Ramírez-i-Ollé, Meritxell, 140, 225 Rationalism (critical), 3, 44–49, 55, 62, 73 Rationality, 10, 42, 44, 49–50, 56, 77, 87, 93, 94, 105, 109, 135, 155, 157, 159, 237, 286 Realism, 44–49, 62, 110, 113 critical realism, 73 Reality, 9–13, 15, 18, 20, 21, 23–26, 29, 35, 38, 39, 56, 64, 81, 83, 87, 93, 97, 98, 104, 106, 109, 113–115, 152, 154, 160, 172, 236, 286 Reasoning (scientific), 37, 41, 43, 44, 60, 61 Reductionism, 38, 39, 62, 251, 279 Referent, 9–11, 13, 15, 16, 18, 19, 21, 24, 32, 39, 41, 58, 60, 83, 85 Reiss, Claude, 43 Relativism, 101, 113, 115, 116 Relativity (theory of), 67, 148–150

Index Religion, 13, 14, 43, 81, 92, 96, 106, 124, 127, 152, 287 Representation (problem of), 47, 267 Research programs, 73 Restivo, Sal, 98 Revolution Copernican, 62 scientific, 62–63, 67, 69, 70, 72, 129 Richards, Ivor Armstrong, 18, 19 Rickert, Heinrich, 24 Risk and resilience, 276 risk society, 2, 276 Robot, 241, 244, 253 Rorty, Richard, 24 Rosenberg, Charles, 190 Roux, Pierre, 108 Royal Society, 130, 132–135 Rules (methodological), 61, 71, 73, 77, 92, 95, 96 Russell, Bertrand, 36 S Salk, Jonas Edward, 102 Sapir, Edward, 24 Sapir-Whorf (hypothesis), 18, 24 Sartori, Giovanni, 15 Schaffer, Simon, 128, 132, 133, 147, 161 Schiaparelli, Giovanni, 75 Schiebinger, Londa, 206, 207 Schlick, Moritz, 36–38, 40 School of Edinburgh, 93–94 Schütz, Alfred, 15, 24, 31 Science characteristics of, 124, 126, 129, 130, 132 cognitive science, 95, 242 normal science, 62, 66, 67, 72, 74, 88, 125 organisation of, 130, 132, 205 Science fiction, 128, 193, 210, 212, 244 Scientism, 2–4 Scientist scientific community, 100, 108, 131–135, 151, 163–166, 168, 169, 175, 220, 228, 256, 270 Searle, John, 112, 242, 244

Index Seeing and looking, 20 Self-Tracking (tools for), 277–279 Sellars, Wilfrid Stalker, 53, 54 Sena, B., 250 Sensoriality and objectivity, 273 sensory turn, 272, 274 Serres, Michel, 102 Serveto, Miguel, 81 Shapin, Steven, 53, 115, 128, 132, 133, 147, 161, 274 Sharon, Tamar, 278–280 Sight/vision and objectivity, 208 professional vision, 273 (see Sensoriality) and “view from nowhere” 135 Snell, Bruno, 22, 27 Social Construction of Technology (SCOT), 184–186, 191, 196 Social media Facebook, 238, 240, 245 Twitter, 239, 240, 245 Social Shaping of Technology (SST), 182–184, 187 Sociology of Scientific Knowledge (SSK), 93, 123, 184 Sontag, Susan, 86 Sprengler, Oswald, 97 Standpoint theory, 207–210 Star, Susan Leigh, 32, 131, 190, 191, 196, 266 Statements, 19, 37–41, 44–49, 55, 103–107, 275 Statistics, 56, 155, 203, 255 Steiner, Rudolf, 270 Stoermer, Eugene Filmore, 227, 228 Strong program, 154 Subjective/subjectivity, 2, 19, 21, 43, 55, 98, 152, 201, 273, 279 Sublime, 221 Suchman, Lucy, 242, 245 Sudnow, David, 27 Syllogism, 46–49, 61, 105, 106 Symmetry (principle of), 110, 154, 187

323 T Tabula rasa, 37, 47 Tarde, Gabriel, 102 Tarski, Alfred, 36 Taxonomies, 18, 29, 259 Teaching hall, 181, 182 Technician, 132, 133, 175, 187, 237, 270 Technology, 180, 181 and progress, 76, 180, 183, 243 and science, 4, 91–116, 123, 153, 179–196, 201–213 technoscience, 164, 179, 211, 266 Tesler, Lawrence, 244 Testimony (problem of), 132–134 Thèmata, 72 Thompson, Arthur, 205 Thorne, Kip, 149 Todorov, Tzvetan, 3 Tolstoj, Lev, 107 Toulmin, Stephen Edelston, 53, 54, 58, 72, 285 Trust (epistemic), 164, 171 Truth, 172, 237 Truth-spots, 3, 13, 26, 38, 39, 45, 46, 48, 56, 87, 96, 112, 113, 135–140, 154, 286 Tutton, Richard, 194, 277, 280 Twin Towers, 11, 19, 20, 39 Tyler, Stephen A., 20 U Universalism, 92, 125, 132 V Vaccine, 85, 102, 107, 160, 257, 277 Valverde de Amusco, Juan, 81 Venter, Craig, 256 Verifiability (principle), 40, 44 Vileisis, Ann, 268, 269 von Ehrenfels, Christian, 58 von Hayek, Friedrich, 2

324 W Wajcman, Judy, 54, 183, 212 Waldeyer, Heinrich W. G, 84 Weber, Joseph, 148–150 Weber, Max, 24, 91 Weinberg, Steven, 112 Weiss, Brian, 30, 149 Weiss, Rainer, 149 Werner, Heinz, 24 Wertheimer, Max, 58 Western medicine or biomedicine, 136 Whewell, William, 62, 129 Whitehead, Alfred North, 102, 129 Whorf, Benjamin Lee, 20, 24, 63 Wildelband, Wilhelm, 24 William of Ockham, 71n3 Winner, Langdon, 180 Wittgenstein, Ludwig, 1, 20, 36–38, 40, 53, 54, 63, 97, 100, 103

Index Woolgar, Steve, 30, 92, 103–106, 156, 161, 189, 243, 286 World Wide Web, 235 Wynne, Brian, 170, 171, 176, 224, 226 X Xu, Fei, 24 Y Yearly, Steven, 190, 220, 223, 224, 227, 230 Young, Allan, 250, 251 Young, Thomas, 65 Z Zolo, Danilo, 87