The Future of the Self: Understanding Personalization in Childhood and Beyond 9781800439450, 9781800439443, 9781800439467, 1800439458

Table of contents :
Half-Title Page
Series Page
Title Page
Copyright page
Contents
List of Figures
About the Author
Introduction
1. Personalization–Pluralization
The commercial and educational use of personalization
Personification and anthropomorphism
Name-based personalization
Personalization based on diverse personal data
Personalization and Early Childhood
Personalized Education Nomenclature
Personalized Design
What is Not Personalization?
PluraliZation
The P–P Balance
Nature and Nurture in “Self”
2. Quantity and Complexity
The Scale of Datafication
Children’s Use of Technologies
Persuasive Design of Technologies
Extreme Amplification
Internet for Children
The Quantities of Personal Data: Is More Better?
Data-driven Education
Assessments and Personalized Education
The Complexity of Personal Data
Optimal quantities of personal data
3. Agency
What is Agency?
Agentic and Automatic Personalization
Agentic and Automated Choices
Open-ended Design
The Agency Hypothesis
Optimal Levels of Agency
The Privacy Paradox
The 5As of Agentic Personalization
4. Acceleration
Personalization and Power
Correlates of Personalization: Inequality
The Beginnings of Commercial Personalization
Moderators of Extreme Personalization: Neoliberal Capitalism and Meritocracy
Personalized Time
Screen Time
Personalized Space
Mediators: Collective and Personal Migrations
Personal Migrations
Causal Factor: Acceleration of Change
Symptoms of Extreme Personalization: Confusion
5. Density
Body-related personalization
Replicating instead of extending our bodies
The extended self theory
The networked self
Congruence between our ideal and actual “self”
Abstraction
Desired difficulties
Adaptive personalization and adaptive learning
The personalized brain
The Relational Self
Selfies: A Digital Self that Extends and Relates
Personalized Mnemonics
Optimal Personalization Density
The Computer as a Human Brain Metaphor
Alternative Metaphors
6. Sequence
Myth 1: personalized versus standardized education
Personalized and standardized assessments
Myth 2: educational technology versus human teaching
Myth 3: personalization versus pluralization
The Sequence Myth
Engagement and Personalization
The P–P Curriculum
Dialogue in Education
Educational Futures
A Meteorological Metaphor for P-P education
7. Distance
Stories and Narratives
Children’s Story Books
Children’s Digital Story Books
Personalized Story Books
Shared Book Reading
Commercially Produced Personalized Books
The Distancing Hypothesis
The Techniques of the Distancing Hypothesis
Contextualization
Conversation
Personal Resonance
Future Personalized Books
Conclusion
Notes
Introduction
Chapter 1
Chapter 2
Chapter 3
Chapter 4
Chapter 5
Chapter 6
Chapter 7
References
Index

Citation preview

THE FUTURE OF THE SELF

PRAISE FOR THE FUTURE OF THE SELF

‘An astonishing amount of information for educators, other professionals and parents on almost every aspect of technology’s impact on children’s development of “self” and sense of agency. Dr Kucirkova has written a powerful book about the growing impact of technology induced personalization on children and our collective future. The book contains rich information to how children learn that is embedded in context including social science, child development, philosophy and literature. A must read!’ – Barry Zuckerman MD, Boston University School of Medicine, USA ‘Anyone concerned about the impact of technology on their life and the lives of children should rush to read The Future of the Self, by Natalia Kucirkova. This book captures the multiple, interacting forces shaping the sense of self in the digital age and encourages readers to reflect on the implications. The book explores how technologies personalize our experiences using data collected by search engines documenting our activities, educational software guiding our learning, and social media monitoring our interactions. This book will motivate teachers, parents, designers, policy makers, and users of technology to re-examine the implications of personalization in their lives. Drawing on technological advances, research findings, and theoretical insights Kucirkova identifies trade-offs, dilemmas, and paradoxes that deserve our attention. The book gives readers tools for thinking about the interacting factors determining how experiences are personalized. In one example, Kucirkova identifies the trade-offs that ensue when balancing personalization targeted to the individual and pluralization targeted to the overall audience. This distinction arises every time teachers make decisions about whether to assign the same book to their class or to let each student select their own book.’ – Marcia C. Linn, Evelyn Lois Corey Professor of Instructional Science, Graduate School of Education, University of California, Berkeley, USA

THE FUTURE OF THE SELF Understanding Personalization in Childhood and Beyond BY

NATALIA KUCIRKOVA

University of Stavanger, Norway and The Open University, UK

United Kingdom – North America – Japan – India Malaysia – China

Emerald Publishing Limited Howard House, Wagon Lane, Bingley BD16 1WA, UK First edition 2021 © 2021 Natalia Kucirkova. Published under exclusive licence by Emerald Publishing Limited. Reprints and permissions service Contact: [email protected] No part of this book may be reproduced, stored in a retrieval system, transmitted in any form or by any means electronic, mechanical, photocopying, recording or otherwise without either the prior written permission of the publisher or a licence permitting restricted copying issued in the UK by The Copyright Licensing Agency and in the USA by The Copyright Clearance Center. Any opinions expressed in the chapters are those of the authors. Whilst Emerald makes every effort to ensure the quality and accuracy of its content, Emerald makes no representation implied or otherwise, as to the chapters’ suitability and application and disclaims any warranties, express or implied, to their use. British Library Cataloguing in Publication Data A catalogue record for this book is available from the British Library ISBN: 978-1-80043-945-0 (Print) ISBN: 978-1-80043-944-3 (Online) ISBN: 978-1-80043-946-7 (Epub)

CONTENTS List of Figures

vii

About the Author

ix

Introduction1 1. Personalization–Pluralization

17

2.  Quantity and Complexity

39

3. Agency

65

4. Acceleration

89

5. Density

123

6. Sequence

157

7. Distance

183

Conclusion209 Notes

219

References

237

Index

277

v

This page intentionally left blank

LIST OF FIGURES Fig. 1: Conceptual model of adjusting practices, processes and products at the macro-, meso- and micro-levels. 4 Fig. 2: Examples of categories and sub-categories of personal data. 6 Fig. 3: Explanatory diagram of differences between individualization, customization and personalization. 33 Fig. 4: A mnemonic for remembering a balance in P–P. 35 Fig. 5: Examples of how diversity and multiplicity make up data complexity. 60 Fig. 6: A schema of the bi-composition of agency. 67 Fig. 7: An illustration of how agency develops over time. 80 Fig. 8: The relationship between agency and optimal, minimal and extreme levels of P–P. 82 Fig. 9: A simplified account of the emphasis on personalized time and space in different eras. 106 Fig. 10: Distance combined with types of literature and examples.194 Fig. 11: The four quadrants of social cognition. 196 Fig. 12: The four quadrants of immersion/identification options in stories. 196 Fig. 13: The four quadrants of empathy options in relation to stories. 197

vii

This page intentionally left blank

ABOUT THE AUTHOR Natalia Kucirkova is Professor of Early Childhood Education and Development at the University of Stavanger, Norway and Professor of Reading and Children’s Development at The Open University, UK. Her research concerns innovative ways of supporting children’s book reading, digital literacy and exploring the role of personalization in the early years. Her research takes place collaboratively across academia, commercial and third sectors. She is author of Digital Personalization in Early Childhood (Bloomsbury) and How and Why to Read and Create Children’s Digital Books (UCL Press) and currently blogs for Psychology Today.

ix

This page intentionally left blank

INTRODUCTION

You and I are the first generation to see children growing up with a paraphernalia of digitized personal data. Children’s fragmented selves begin before they are born with embryo images, and in some cases with recorded genome sequences. The diversity of data that exists on today’s children is unprecedented, as are the mechanisms for this data to be deployed for strategic educational, marketing, medical, biological and state-sponsored ends. While with the previous generation the self was unbound, today’s generation cultivates inner worlds that are fragmented, with diverse identity markers, such as archived photos, real-time text messages or records of movement, amplified by diverse networks. The Generation Alpha, that is, children born between 2010 and 2025 are the first generation to pioneer digital personalization that significantly fragments and augments their “selves.” This book provides you with some thinking tools to consider your own contribution to the rising levels of fragmented and amplified selves. In the first decade of the twenty-first century, the personal data economy enabled personalization to grow from a cheap manufacture model to a highly sophisticated practice. The technological know-how of the personal data economy, however, has accelerated faster than general understanding of what constitutes “self”. I want to challenge the technological representation of self which currently dominates debates about personalization and focus on the mechanisms of personalization that can inform a comprehensive theory. In this theory of personalization, the basic unit is choice – we are 1

2

The Future of the Self

who we are because of the choices we make. Choices communicate our identities and, therefore, the practice central to the study of personalization is identity. Education scholars, including myself, understand identity as a verb, as an action that is performed in dialogue with others. It follows that “personalization” is both a noun and a verb. Simply defined, personalization is a nexus of products, services and practices tailored to one human being. Personalization is undeniable when we think about our everyday modern lives. Personalized education, personalized news, personalized medicine, personalized gifts … the adjective “personalized” changes the meanings of the nouns it qualifies. There are different conceptualizations of personalization in different contexts. To some, personalization is simply tracking an individual’s behavior with adaptive technology, to others it is about empowering young children to explore and be creative. Whether we frame personalization in a deficit or opportunity frame, personalization by its very nature speaks to the “personal” in an individual human being. In education, attention to the individual child can motivate students to learn. In commerce, personalization can persuade customers to buy a product or to be hooked on a pointless game. Contextualizing activities as your journey, your story or your education affects how you perceive their value, and how much attention, intrinsic motivation and material resources you allocate to them. This is why personalization techniques are of great interest to designers, psychologists and educationalists for decades. The current version of the Internet, the Web 2.0, with its social networking sites and user-generated content in blogs and private emails, is designed in a way that makes personalization indispensable: how else could we find relevant information in the large swaths of information contributed by every user? In education, however, the pendulum has been swinging between standardized and personalized education for decades. While marketing and global advertising have perfected the techniques of commercial personalization, educational approaches to personalization have been less successful. This is important to realize if we want to progress personalization that is not only engaging but also enriching. Adaptive and automated personalization enabled through personal mobile technologies that collect and algorithmically process personal

Introduction

3

information has scaled up (and in some cases, supplemented) possibilities for personalization. These possibilities can be leveraged for not only motivating people but also for manipulating them. Yet, personalization techniques are not unique to digital marketing or technologies: human beings individualize their speech, thoughts and behavior in relation to the personal information they hold about individuals. If you know that your partner likes coffee, you will offer them coffee instead of tea (if you want to please them), serving it at the time of day you know they usually wake up and addressing your partner by their name. Alexa provides similar personalized service with digital information. Digital personalization, or personalization mediated by technologies, can be more intense and in some instances, more precise than human-mediated personalization. If we understand technology as a tool that “organizes knowledge for practical purposes” (Mesthene, 1997, p. 75), then we cannot overlook the extreme pace at which it has evolved the sophistication of its software (e.g., apps) and hardware components (e.g., iPhones) in comparison to the development in other industry areas. On one hand, digital personalization offers greater precision with flowcharts and decision trees using personal information to make predictions and expand our “selves” with precisely defined values and exponential growth. On the other hand, digital personalization is a bedfellow of surveillance and commercialization tactics and as such, breeds the battleground for opponents of digital authoritarianism and critical edtech activists. I do not aim to add fuel to the techlash against Google, Amazon and Facebook. I want to engage in a research- and practice-informed discussion about what the benefits and limitations of digital and non-digital personalization are now, for children of today, and what they could become for future generations. If we want to understand personalization in its entirety, we need to consider personalization not only in terms of what it is but also what it is not. In education, personalized learning is sometimes confused with differentiated learning and in business, personalized products are at times confused with customized merchandise. A simple way of understanding the difference is to think of the number of people that a product or activity is tailored to. Differentiated learning and customized products are relevant to groups of

4

The Future of the Self

people, while personalized learning and personalized merchandise are uniquely made for individuals. If we think of the sphere of influence in micro-, meso- and macro-terms, then you can locate personalization at the micro-level, customization/differentiation at the meso-level and generic/standardized products or processes at the macro-level (see Fig. 1). If we agree that personalization is about adjusting products and processes to one single human being, then we need to ask who drives these adjustments. Are personalized products user-generated and managed by communities or the technology provider? Is personalized learning led by the teacher or the child? This is the point where we need to consider the techniques of personalization and ask who personalizes for whom. Personalized products and services can either be developed around, or with, the user/recipient. The level of user participation determines the quality of personalization and the extent to which personalization is “­agentic,” that is, whether it reflects genuine choices of an individual’s identity, or spurious choices offered by someone else. Today’s generation is unique in the amount of non-agentic personalization steered by commercial and political forces as opposed to agentic personalization led by the individuals who produce the data. In my work, I have focused on approaches that cultivate personalization with children’s agency Fig. 1.  Conceptual Model of Adjusting Practices, Processes and Products at the Macro-, Meso- and Micro-levels.

Introduction

5

in mind. This is not to undermine the agency of adults: a Goldilocks solution which includes both child and adult agencies is necessary for holistic learning. Nevertheless, I foreground children’s agency and agentic personalization in this book as it is these techniques that need to be most urgently developed and implemented. Despite the popular belief that technologies provide equity of access, digital personalization carries the same biases as any other technology-mediated practice: as I will outline in this book, it can reproduce and amplify socio-cultural inequalities. By the advent of the personal data economy, the diversity and sophistication of using personal data have matured significantly. Not only are there new forms of identifying a person but there are also more precise ways to collect and strategically deploy the digital fragments of an individual. Here is a simple way of understanding the large and heterogenous landscape of personal data: from a research and statistical perspective, data can be numerical (e.g., number of students in a class, test scores and speed of a car) or nominal (e.g., someone’s ethnicity, hair color or gender). From the broader personal data economy, any piece of information that identifies an individual, counts as data. The commercial, health and education sectors use these types of data: body-related (somatic), psychological (personality traits), experience-related (likes and dislikes), needs-based (educational and developmental), demographic markers such as children’s names, gender, address and date of birth and modal data, which can be further sub-categorized into linguistic and textual modes or in terms of sensory engagement into visual, auditory, gustatory, olfactory and tactile modes. The key personal data points that are (or soon will be) used by the data economy are summarized in Fig. 2. Within a diverse and plural understanding of data, “digital” personalization becomes a misnomer. Data are generated both from humans and non-humans and data are processed by human and artificially intelligent non-human brains, not only in interaction of humans with humans but also humans with the natural or artificial environment. Yes, there are some activities that are exclusively digital, such as, for example, watching videos, but digital as well as non-digital products can be personalized, such as books, for example. Indeed, all data, visual, audio or textual, can be either personalized or not, and this distinction is more sustainable than the

6

The Future of the Self

Fig. 2.  Examples of Categories and Sub-categories of Personal Data.

digital/non-digital distinction (what is not digital today might be digital tomorrow). It is also a more complicated distinction because it relates to an understanding of the world that is defined by time and space boundaries. My understanding of this relationship has arisen from many sources; however, one that stands out in particular for me is the following experience from 2011. I was field-testing the “Our Story” iPad application which I codeveloped as part of my postgraduate studies at the Open University in the UK. I was proud that we had a working prototype and took the iPad to a small primary school to see how the children would use it to make their own multimedia stories. A child named Annie attended the class with whom I was testing the app. She was a soft-spoken, six-year-old pupil. This was before tablets and smartphones had become ubiquitous, but little Annie already had an iPad at home – accustomed to the device, she volunteered to give my app a try. She seemed entirely absorbed in using “Our Story.” Her peers looked on mesmerized, so I let her explore the functions without interrupting for about 10 minutes. Annie began composing her own multimedia story – she took pictures of her classmates, added her name to the title of the story and audiorecorded her friends’ giggles. After she had completed about six

Introduction

7

pages, she proudly typed in “The End.” The teacher called Annie to stand at the front of the class and hold the iPad high to show all the children her story. The teacher pressed “Play” and bang! – the app had crashed. She pressed “Play” again but the story was no longer there. I tried to retrieve it but there was a bug in the code which had made Annie’s story disappear. Annie began sobbing, and all eyes in the classroom were on my red, embarrassed face. “Don’t worry Annie, you can make another one,” the teacher tried consoling her. “But it won’t be the same one” Annie replied crying. Annie was right – it would not be the same story – time determines the value of personalization. Had the app worked as it should, it would have preserved Annie’s story, and she could have shared it with her classmates, her family at home and grandparents in Australia. Annie could have made another story, but the quality of the content would have been affected by her initial experience. The photos of her classmates, their giggles and perhaps Annie’s typed text too, would be different. Authentic personal data are locked in time–space convergence. Digitization can grant personal data posteriority and mobility, but digitization is subordinate to the amplification possibilities of time and space. The higher the precision of personalization, the more acute the loss of a personalized product and inability of reproducing it in the future or in another location. This is an important realization not only for research or design but also for everyday life. If we think of personalization as a practice based on collecting and curating personal fragments of individuals, then there are different approaches to personalization in different research disciplines. In computer sciences, the personal fragments are called personal data and are analyzed in relation to the possibilities of datafication, while in social sciences, the core focus is on ethical and social consequences of personal information. Psychologists study personalization related to identity, and specific cognitive phenomena, such as self-reference effect or self-referential speech. Personalized medicine is studied in medical sciences, and personalized education in humanities. The effects of personalization on consumer behavior, such as to act on a product recommendation or make a repurchase, are studied by economists. Personalized design or custom cosmetics are studied in schools of design, fashion and art. The study of personalization is thus a rich but disjoint field

8

The Future of the Self

and my attempt at a broader perspective should be understood as part of an endeavor that seeks to break new ground in a crossdisciplinary study of personalization. Still, as much as I wish, I cannot represent all disciplines in one book and may have to gloss over some disciplinary nuances. My own research interests bridge both the humanities and sciences and draw on evidence from various sources including qualitative observations, quantitative experiments and theoretical analyses. Please refer to the Notes at the end of the chapters for more details on individual studies and links to the cited articles (Note 0.1). I am concerned about the rise of personal economy and digital personalization in the twenty-first century and the extent to which personalization is becoming the defining feature of modern childhoods, but I cannot discuss personalization in simplistic positive/ negative terms. The reasons why adults personalize products and services for children are motivated by a social justice agenda to ensure that all children feel that they belong (to a family, to a classroom and to a society) or a political ideal that aims to empower everyone to make a choice, or a profit-driven agenda for developing long-term clients. These motivations can overlap and we need to study their proportions in different circumstances rather than their end points. So that you understand the conceptual relations, it is important you understand that personalization is both an outcome and a mechanism. Poverty is another such hybrid. Researchers interested in poverty study how poverty arises, why it is perpetuated and what its impact is. The same applies to the study of personalization. This may be confusing but it also ensures the enduring nature of personalization: new technologies grant personal data new forms but technologies are just a part of the broader socio-material mechanisms, and outcomes, of personalization. When I try to explain what actually matters for our understanding of the impact of personalization, I use a simple story of “determinism” versus “relativism.” The story starts with the legendary American physicist, Heinz Pagels. Pagels (1982) made several connections between Jean Piaget’s theories of child psychology and the foundations of quantum physics, and inspired me to think about the synergies between the history of physics, and the history of personalization. Here is the

Introduction

9

shortened story: back in the seventeenth century, Isaac Newton assumed that there are direct causes which can predict regularities and these regularities can be measured to make prediction. In contrast, in the twenty-first century, quantum physics assumes that any measurement can only give probabilities of reality and, therefore, probability is all we ever know. In this simplified understanding of physics, Newtonian determinism is more akin to current datafication trends, while quantum physics is more akin to long-standing identity theories. I want us to adopt the quantum physics perspective on personalization, so that personalization is understood as a phenomenon within complex transactions between human and non-human entities, across time and space (see Greene, 2007). Such a perspective allows us to move beyond a myopic outlook on the role of individual technologies or technology companies that dominate the current market. It helps us understand why blaming social media and labeling the current generation as the “Me Generation” is misplaced. There is no causal evidence that having more personalized items implies having less tolerance toward difference. Personalized books or “Me Mobiles” in kindergartens were here well before apps and they may have contributed to children’s selfcenteredness as much as to their sense of belonging. We need to move beyond the immediately observable examples for Newtonian measurements (i.e., technologies) and accept that the ultimate origin of personalization is not known (just like the ultimate origin of the universe is not known). Personalization needs to be considered in relation to socio-cultural parameters and we need to peer deeply into the foundations of what it means to be human to reveal its complexities. The physics analogy may be stretching my argument slightly, but I hope you will understand that assuming a direct causative model of personal data on children’s identities would be a simplistic model and would return outdated results. To make it very clear: this book is not a manifesto for policy-makers to invest their energies into fighting technology giants, nor for educators to draw up lesson plans for personalized learning. Inspired by the quantum dictum, I frame this book as an inquiry into personalization. I strongly believe that questions, not answers, direct our thinking and that well-formulated questions can enlarge scientific

10

The Future of the Self

interpretations. I am not interested in the question like “is personalization good or bad for young children?” but in questions that are open to possibilities and draw on research evidence to build some viable hypotheses. As you try to approach personalization within your research discipline, educational or design practice, or indeed, everyday life, consider asking the seven questions that I ask in this book’s seven chapters. My first question is: “what is and what is not personalization?” Reflecting on the patterns and practices of datafication in an era of considerable technological shifts, I propose that any meaningful expression of “self” needs to be connected to the “other” within the personalization–pluralization balance (Kucirkova & Littleton, 2017). Pluralization is about human differences, diversity and collectivism. When yoked together with personalization, the ­ personalization–pluralization continuum provides an ideal structure that is both personally determined and collectively coconstructed. Throughout the book, I foreground personalization in my questions but remember pluralization in my answers. This is because for optimal outcomes, personalization needs to be complemented with pluralization. If education leans more toward the pole of personalization, a competitive “me first” attitude will dominate over collaborative learning with others. If we lean more toward pluralization, the collective will be commended at the expense of celebrating individual achievement. It follows that ­personalization provides the foil against which pluralization is measured. The measurement parameters which I consider in this book are: q ­ uantity, acceleration, density, sequence and distance. In Chapter 1, I argue that the biggest mistake we make in all applications of personalization, whether design, education or the socio-political arena, is to act as if personalization can be separated from pluralization. Personalized education combined with standardized (pluralized) education offers the most challenging as well as the most rewarding experiences for children. Similarly, for a child’s holistic development, personalized design, personalized merchandise and personalized resources need to be offered in conjunction with products which are purposefully different from what the child wants or likes or is familiar with. Indeed, we learn most from people who are different from us and this difference creates the most fertile

Introduction

11

ground for nurturing empathy (Kucirkova, 2019a). So that humans can survive as a species of wisdom, personalization and pluralization need to be in close dialogue with one another. In Chapter 2, I consider the quantity of personal data available to us in the twenty-first century and the personalization practices connected to datafication. From the philosophical perspective, we live in the information age, the so-called “Infosphere” (Floridi, 2014). Infosphere is characterized by the presence of big data networks that self-generate information from connected devices, and from the individual human beings using these devices. The information is collected online and offline and creates a “sphere,” a three-dimensional space, which envelops our everyday lives. The question I address in this chapter is: “what is the optimal quantity of digital data for children to be able to thrive in the Infosphere era?” I argue that the twenty-first century is characterized by large quantities of complex personal data and that, therefore the unique challenge faced by Millennials and post-Millennials is a mindful and effective management of their own personal data. In addition to data shared by their family members and friends, children generate data by cataloguing their lives themselves. As a result, children’s data are sprinkled in various places, supervised by various unconnected institutions, including private companies and schools. I argue that the current datafication of children’s lives is uncoordinated, unsystematic and unregulated. Moreover, through non-transparent deals between large corporations and education departments, children’s education is datafied using a “Netflix-inspired” commercial model, which has been popularized by edtech companies but criticized by many educational researchers (e.g. Perrota & ­Williamson, 2016; Selwyn, 2016). These researchers lament the lack of accountability of the “data colonialism” (Williamson, Bayne, & Shay, 2020) that has reached unprecedented levels in Western countries and has aggressively expanded to the rest of the world. Some commentators argued that global health pandemics, such as the Covid-19 outbreak, that rely on Internet-based communication, contact tracing, remote education and remote working, provided additional opportunities for such data colonialism to take place. Other commentators argue that the pandemic brought to light the so-called new media humanism, where technology use is seen

12

The Future of the Self

through rose-tinted spectacles as entirely positive. In Chapter 2, I make some theory-based suggestions for driving a more instructive evolution of the Internet (Web 3.0 and Web 4.0), and more optimal quantities of datafication. I see agency as a moral thread running through the book but dedicate Chapter 3 specifically to agency to explain how I see it central to personalization. Agency is the universal human competence to volitionally take control, and to personally determine and influence one’s own existence (Ortner, 2006). Agency has become a frequently uttered word in relation to digital personalization and I therefore review children’s agency in light of the prospect of automated futures. I argue that whether it is children’s use of digital media, playing with friends or learning at school, agency is a double-ended arrow between the self and the other. Agency is the expression of answering the quintessential questions “what life will you craft for yourself?” as well as “how will you show up in other people’s lives?” The answer to these questions requires both powerful self-determination and vulnerable belonging to others. Building on my previous work, I expand the theoretical framework of the “5As of agentic personalization” (Kucirkova, 2018): Autonomy, Attachment, Authenticity, Aesthetics and Authorship. These five aspects tap into children’s motivation, creativity and empowerment. The presence or absence of agency in these five As determines whether personalization is bottom-up, led by its receivers or top-down, imposed by those in position of power. Authorship is about children’s own content when agency is present. However, when agency is absent, authorship turns into consumption. Without agency, children’s Autonomy in making their own digital artifacts turns into dependency. If there is no agency, then Authenticity of genuine personalization fades away into counterfeit products. In agency-absent models, digitally perfected Aesthetics are paraded as superior to hand-made art. Personalization provided by algorithms does not foster Attachment but a desire to dominate. In contrast, agentic personalization is underpinned by the desire to belong to other human beings. I draw on the example of classroom-based story-telling developed by Paley (1991) to illustrate how the 5As and agentic personalization play out in early childhood education.

Introduction

13

Chapter 4 attempts to answer the questions: “what causes and what mediates extreme levels of personalization?” Reflecting on when the so-called personalization revolution started, it is no coincidence that the personal data economy mushroomed in the era of industrial capitalism, characterized by high consumption and high production (Sandel, 2012). The path for this era has been paved by lack of intellectual supremacy on the governance level of democratic nations, undermined by a large amount of vested interest money, voting rights violations and, most recently, social media manipulations that preclude real political action (Hay & Beaverstock, 2016). In a highly volatile macro-world, individuals crave the comfort of micro-worlds. A significant additional mechanism for the global interest in personalized micro-worlds was mass migration, both on the basic geographical and deeper psychological levels. Accelerated changes to collective and personal identities in the 2000s have meant that there was no one leading narrative for individuals to converge around. Nicholson (2013) and Best (1991) have recognized the loss of a grand narrative in the 1940s but the first two decades of the twenty-first century have introduced multiple narratives through global and personal migrations. Changes to online and offline communities got validated by capitalist and technological dominance and a burgeoning personal economy. The seeming function of these systems was to give choices to ­individuals to manage their personal lives. In reality, however, the acceleration of externally imposed personalization possibilities has created a breeding ground for uncertainty, resulting in deeply confused and anxious state of mind (documented as mental health issues). I propose that accelerated identity migrations, on personal and collective levels, are the reason why data-driven personalization became the preferred tool for fragmenting and amplifying the twenty-first century self. In Chapter 5, I draw on the extended self and relational self theories to discuss the question: “how might personalization be used to enlarge the good in us?” Belk’s (1988) notion of “extended self” began with the idea that individuals can extend their identities into material things that they buy and into artifacts they own. Similar to the concept of a networked self (Papacharissi, 2010),

14

The Future of the Self

the theory assumes that there is a core self-concept, the sum of the parts we call “me, myself and I.” Our relationship with other living and non-living beings seeps through the layered nature of this core – each encounter leaves a new layer in our memory and an imprint on our body, increasing the potency for activating and growing the “self.” We then assimilate and project these extensions onto others. In contrast, the Relational Self Theory is part of a family of socio-cultural theories that explain how our ideal and real selves ­co-exist in an intricate web of connections with others (Andersen & Chen, 2002). This “other” can be another human being but it can also be abstract characters or material objects (Bailey, 2007). The relational self-perspective stands in stark contrast to the ­linear model of identity that governs the current models of digital ­ personalization. I argue that data-driven resources, such as ­personalized edtech, are dense with personal data and this makes them replica rather than extensions to children’s thinking. Chapter 6 debunks three myths that speak volumes to the metaphors buried within personalized education. The first myth proposes that personalized and standardized education are mutually exclusive. The second myth relates to the mistaken assumption that educational technologies can transform children’s learning in ways that teachers cannot. The third myth is a misunderstanding related to the personalized–pluralized division that assumes that an individual’s motivation to belong is separate from the individual’s motivation for self-determination. All three myths circulate around one powerful myth that combines them all: the sequence myth. The simplistic binary that underlies the sequence myth is that personalization–pluralization can be separated and if they are separate, then they can be sequenced (first we personalize children’s education and then we standardize it). Socio-cultural researchers follow a different metaphor: that of dialogue that assumes that each individual has some knowledge to offer, regardless of their background or life experiences, and this knowledge is negotiated and enriched in conversation with others, without any particular sequence. This is why Chapter 6 highlights dialogical approaches to education as promising methods for future, non-sequential, education models. Drawing on observed examples, I present this model as an achievable and

Introduction

15

desirable basis for exploring policy and practice related to educational change. Chapter 7 synthesizes the literature which shows that stories provide a unique context for studying the distance between personalization and pluralization. Stories can take many forms: oral story-telling, films, comics or literary novels. Reading stories is a special case because of the connection between written words and imagination. The distance between authors and readers establishes a unique theater of mind that stretches the mental imagery. The personal resonance theory (László & Larsen, 1991) designates the concept of self–other distance in texts that evoke personal resonances through personal “remindings.” Two distancing techniques tap into the personal resonance theory – contextualization and conversation. In Chapter 7, I exemplify these techniques with children’s personalized books. I argue that an optimal distance between readers and protagonists is essential for ensuring that children are motivated to read and that they also learn something new in the process (cf. Oatley, 1999). An optimal distance is essential between the “self” and “other” not only for educational outcomes but also for building empathy toward out-group members. For example, children’s names, pictures and sounds can be used to motivate children to read radically impersonal texts, such as historic novels. Rather than positioning children as story heroes in personalized books, children can be portrayed as heroes in their local communities, helping and saving those they would typically not think of as their “friends.” With its focus on out-group empathy, Chapter 7 touches most strongly on ethics and the ultimate question of optimal distance between self and the other in the human story. These seven chapters are my attempt to propose seven thinking steps that lay the contours of an emerging theory of personalization. I frame my propositions as inquiries, underscoring that plausibility is always ahead of verification. This might sound “poetic” rather than “scientific,” but sometimes poetry anticipates science. Research is as much about thinking as it is about knowing. In the last stanza of one of the most beloved poems ever written, Wild Geese, the poet Mary Oliver(1986) yields to the “harsh” but

16

The Future of the Self

“exciting” call of wild geese to reclaim a place “in the family of things” that constitute life. Mary Oliver may have not anticipated that within her lifetime the “family of things” would become an interconnected family of nature, people, devices and virtual reality (VR), but she has certainly anticipated that we all belong to a “family of things,” no matter how harsh and exciting its call, and that is the core of my first proposition on personalization.

1 PERSONALIZATION–PLURALIZATION

The root of personalization is “person” – as in an individual human being but there are at least 10 definitions of “personal” in the Latin dictionary (Note 1.1). The verb “personalize” means to “design or produce (something) to meet someone’s individual requirements1” (Oxford Dictionary; Note 1.2) and its derived noun “personalization” was found in almost all of the contemporary dictionaries I searched. As a multi-dimensional phenomenon, personalization is likely to undergo a transformation associated with multi-dimensional concepts (e.g., intelligence and multiple intelligences, Gardner, 2008), or the need for multiple adjectives, as it has been the case with “literacy” (e.g., visual literacy, emotional literacy) and pre-fixes, (e.g., multi-literacies, biliteracy). A disadvantage of the multi-­ dimensionality of personalization is that it can be associated with different meanings when used by different stakeholders. In this chapter, I clarify some of these varied definitions but I strongly remind readers that different cultures, contexts and circumstances will attach different values to the meanings of personalization. The individualism–collectivism dualism still pervades a great deal of contemporary writing, and individualism, in particular, is often associated with personalization. The human mind likes to simplify definitions and organize things into opposite categories (objects are either digital or non-digital, cultures are either individualistic or collectivist, Haste, 2013). Conceptualizing the world in binary terms (e.g., urban vs rural or Eastern vs Western differences)

17

18

The Future of the Self

might be useful for developing policy measures in proportion to real need. However, binary categories are not favored by sociocultural researchers (Note 2.3): we see reality as the glue between dichotomies. Nevertheless, the popular claims that today’s generation is a “selfie generation” or “Generation Me” (Note 2.2) prompt important questions that we cannot skirt around. In individualistic cultures the “self” is described as autonomous, seeking freedom at all costs, and placing personal goals above the interests of others. In collectivist cultures, the self is interdependent, seeking social cohesion (Markus & Kitayama, 1991). Triandis (1990) describes individualism as ice and collectivism as water. He explains that as cultures are becoming more modern and dynamic they are also becoming more individualist (Singelis, Triandis, Bhawuk, & Gelfand, 1995). Some researchers consider individualism as a defining feature of the American culture that explains US nationalism and drives for self-reliance (Bellah, Madsen, Sullivan, Swidler, & Tipton, 2007). Others argue that individualism and collectivism co-exist in larger social groups of cultures as well as smaller groups of families (Tamis-LeMonda et al., 2008). Following my study of personalization in Japan and the UK (which could be arguably labeled as collectivist and individualist cultures), I perceive the connection between personalization and individualism as a red herring that muddles the waters of individual differences (more on this in Chapter 6). The values connected to individualism co-occur with extreme personalization but with my socio-cultural hat on, I argue that personalization is about individuality, not individualism. In other words, personalization is not a menacing force that splinters society into millions of individual islands but it is a technique that highlights the uniqueness of every individual. This uniqueness is what we share with other people. If personalization were to be described with Triandis’ individualism– collectivism metaphor of ice and water, then it could be said that personalization reflects the innumerable forms of water, for example, raindrops, vapor, glaciers, dew, and recognizes an individual in every single one. But the water analogy remains just that – an analogy, because humans are more than water molecules. The edges of our own selves are permeable and leak into others whether we like it or not. When we cross these borders, the self merges with the

Personalization–Pluralization

19

other. The exact breaking point is different for each individual, and that to me, is the most exciting part in the study of personalization.

THE COMMERCIAL AND EDUCATIONAL USE OF PERSONALIZATION This book is not an analysis of industry trends, but I must note some important differences between a business and educational approach to personalization. To start off with, in early childhood studies, the question is “whether” to use digital personalization in schools, but in business the question is “when” and “how” to personalize individual journeys. In education, personalization starts offline and with the right software, it can continue to online learning. In business, personalization soars the other way round: online recommendations are moving to personalized offline shopping experiences, with physical shops and Internet of Things used to cater for every customer wherever they are. From the educational perspective, business personalization is paying lip service to the deeply personalized practices followed by educators: knowing the children in their classroom is the starting point. Business target customers with personalized marketing even if they know just the customer’s name and demographic characteristics. Given that the business and educational approaches to personalization are different, they require careful thought before cross-application. For instance, while in business the bigger the company (in terms of revenue), the more sophisticated personalization techniques they can afford. In education, the smaller a school, the deeper its personalization possibilities. The commercial use of personalization is moving more and more in the direction of “deep” or “ultra-personalization.” Many online companies have realized that if they introduce personalization early, they can gain a distinct competitive advantage by getting new customers and retaining them (Boudet, Gregg, Rathje, Stein, & Vollhardt, 2019). These businesses provide one-to-one customer support, track the user’s transactions, likes, preferences, purchases and browsing history. With the commercialization trends at all levels of public education in the UK and USA, many educational

20

The Future of the Self

establishments are, unfortunately, adopting the business speak and desire of scalable deep personalized experiences for each child. Steve Jobs is known in association with personal technologies but he is also known for actively shielding his children from technology use at home – an approach adopted by many parents working in the technology industry. Perhaps the parents who promote “technology-free” and “data-free zones” do so because they are well-aware of the problems of extreme personalization associated with intense data harvesting by personal mobile technologies. In order to articulate what “optimal personalization” for children might be, we need to abandon commercial definitions in favor of solid childhood research studies. There are two terms – personification and anthropomorphism – that are related to personalization and that are in developmental psychology important for the study of children’s behavior.

PERSONIFICATION AND ANTHROPOMORPHISM Children often engage in anthropomorphism, that is attribute human-like characteristics to objects or animals. Adults have this tendency too; how often have you said “My phone battery died?” There are several documented associations, for example, people who feel lonely tend to attribute human characteristics to objects or pets more than those who are not lonely (Epley, Waytz, & Cacioppo, 2007). For young children, there is a clear association between anthropomorphism and their emotional attachment to specific objects. Children’s stuffed toys or small blankets, the “transitional objects,” as Donald Winnicott (1951) called them, are part of children’s identity and they love to anthropomorphize them. Children believe these objects and toys have thoughts and feelings and are irreplaceable (Gjersoe, Hall, & Hood, 2015). In contrast, children are less attached to their other toys, which they perceive in terms of the material properties, and which they describe as objects that can be replaced or replicated (Hood & Bloom, 2008; Hood, Gjersoe, & Bloom, 2012). An important concept in studying anthropomorphism is the human propensity to simplify reality. According to the French

Personalization–Pluralization

21

psychologist Albert Michotte (1945/2017), our perception of reality is often primitive and based on our senses, which gives us the impression of causality in events that are not linked to each other. Similarly, thinking of certain objects as having a soul and self-­ generated behavior, simplifies reality. The reason children – and in some contexts, we adults too – engage in anthropomorphism could be the desire to simplify a world that does not fit our limited schemas. A different philosophical explanation brings in a subjective sense of reality that is influenced by our creative involvement in shaping it. In his book Brainstorms, philosopher Daniel Dennett (1978) explains that people revert to personification when they cannot predict how objects will operate. People personify objects because they want them to behave rationally, they imbue objects with intentionality when they do not know how the objects work or how they are designed. Dennett suggests that this typically happens when people cannot predict an objects’ behavior from its size, weight and other physical characteristics. In the push to develop smart technology, designers have gone to some length to create technologies which would be compact, self-sufficient and difficult to fix by users. If we do not know how an iPhone or Alexa are designed, we then tend to perceive the technologies as autonomous and potent. We give them a “persona” – Alexa becomes “controlling” and an iPhone “clever.” There is an easy way to reduce this tendency: direct involvement in the making of technologies. An experiment with Israeli children demonstrated that when children were involved in creating their own robots, their tendency to personify the robots was much lower. Children who programmed the robots, thought of them in technological rather than human-like terms (Kuperman & Mioduser, 2012). Direct involvement in the creation of tools and a sense of choice in how the objects behave is part of agency and is discussed in more detail in Chapter 3. What is relevant here is the sequence of personification: once we personify something we can then personalize it. This is why when a customer shops online the retailer will collect the information on what the customers buy, and create a “customer persona” so they can send the customer personalized advertisements. Similarly, avatars in virtual games begin with basic personal characteristics (e.g., a white man

22

The Future of the Self

in his 40s) and, as players progress through the game, features are added for players to personalize the avatar (e.g., a white man with brown hair in his 40s, wearing glasses and speaking with a Scottish accent). Few people realize that their own use of smart technology will make their smart gadgets more personalized to their persona and, therefore, conditions them to feel more attached to them. This is partly why agentic personalization is so intensively discussed in this book. Agency to live is inborn but agency to live in a society is developed throughout life, with the support of others. One of the first information a child gets to individualize their place in a society is their name.

NAME-BASED PERSONALIZATION My broader definition of personalization as a nexus of products and processes encompasses the fact that, in research and business, personalization is a catch-all term for anything based on data that relate to an individual human being – the data could be a child’s voice, their date of birth or genetic sequence. However, name-based personalization holds a specific interest to commercial and research labs. It is rare to conduct any type of conversation or participate in any social transaction without disclosing your name: seeing and hearing one’s name is a vital identity-validation technique. We like it when people know our name and conversely, we get offended when they say our name incorrectly. There are thousands, if not millions, of songs titled with an individual’s name, Julia by Beatles or the composition For Elise by Ludwig van Beethoven – to name my favorite ones. The psychological concept “name-effect” refers to the extreme familiarity we have with our own names and the individual letters that make them up (Nuttin, 1985). A child’s first name is typically the first word that a child can write. Experiments show that out of all the 26 letters in the English alphabet, children and adults show preference for their own name letters (Jones, Pelham, Mirenberg, & Hetts, 2002). Commercial producers capitalize on this preference: customer services will end each phrase with a client’s name to emphasize that the client is getting a personalized, premium,

Personalization–Pluralization

23

service. Seeing your name on packaging, a piece of clothing or a website, engenders a considerable novelty effect because most resources are non-personalized (especially if you have a unique name). No wonder then that the Web 2.0 is designed to prioritize names to aggregate content about an individual online – if you wanted to search for information about yourself, you would not begin with your date of birth but your full name. Names help us navigate unknown territories online and offline. An example from educational practice is the use of children’s names for facilitating home-school transition. It is often recommended that on a parent’s first visit to school, practitioners ask them the history of their child’s name. A simple question “why did you give your child this name?” is a way of finding out the circumstances of a child’s birth and begin a conversation about the child’s background. The more the teacher knows about the child, the more personalized their pedagogy can be. Kindergarten teachers know many creative ways of making children’s names visible, with name tags and labels attached to a child’s belongings. This not only teaches children what is theirs but also strengthens the relationship with their own name. Children’s books teach children about names too – The Name Jar by Yangsook Choi recounts the touching story of Unhei, a Korean girl who has recently migrated to America. Unhei is initially upset because Americans cannot pronounce her name. She considers adopting a Western name, something that many immigrant children do (instead of Sachihiro or Jeong, they become John or Amy). The book, however, conveys the message that given names carry a specific meaning both for the giver and the receiver. Names associated with one’s country or culture of origin should be kept intact throughout one’s life, the book suggests. In Chapter 7, I will discuss children’s personalized books – a publishing success story of the 2000s. Personalized books use children’s names instead of fictional characters’ names; for example, Natalia instead of Cinderella. These books are a popular way to motivate children to read, as they instill feelings of ownership over the story and a sense of belonging to the world of literature. Ownership is particularly important for children who do not have many books at home. An example of how organizations can harness the

24

The Future of the Self

name-ownership association is from the “Imagination Library,” funded by Dolly Parton, which puts children’s names on the mailing label when sending them free books. An example from adult services is using customers’ names in email marketing. The flipside of all the hype concerning personal names is “namelessness.” In a poignant documentary about the mass murder by Anders Behring Breivik in July 2011, a sister of one of the 69 murdered Norwegians refuses to call the terrorist by his name, saying she will not say his name on TV or grant him any place in her language, in her body, in her memory: we de-humanize people by not naming them. Refusing to give a real name can also act as a precautionary or protectionist measure – criminal witnesses often receive a new name to protect their identity. Monikers, on the contrary, are used to manage expectations. In Episode 1 of the series Doctor Who, the main protagonist tells Martha Jones that his name is “The Doctor.” The shroud of mystery around this name immediately hooks viewers. From a capitalist perspective, different names carry different values – those who are less famous or in a lower position of power want to be associated with the “bigger names.” We are all guilty of occasionally name-dropping during conversations to impress others. In an era of celebrity endorsements personal and corporate names are highly valued commodities that are actively traded for their reputation. Thus, names can be also understood as a personal brand that reflects tenure associated with family, class and other forms of social capital (Bourdieu, 1986). Given the personal and social significance of names to children and adults alike, it is perhaps no surprise that name-based personalization is so heavily commercialized. However, attaching a name to a generic product or mentioning it at the end of every line in a sales conversation is a very basic method of personalization. More complex personalization – and more sophisticated (mis)uses – occur with diverse personal data.

PERSONALIZATION BASED ON DIVERSE PERSONAL DATA The amount of diverse digitized personal data is unprecedented in human history: digitized personal data are multimodal (audio,

Personalization–Pluralization

25

visual, tactile and olfactory), they include an individual’s identity markers (name, date of birth and address), biomarkers (voice, fingerprint and health records), measurement and behavioral records (educational test scores, online browser history, purchasing habits and travels to various locations), as well as private history documented in photos and videos. In terms of amount, with almost five billion people online in 2020, there are so many zeroes in the big data statistics that they are hard to compare to anything similar. People tend to trust numeric data more than other forms of evidence (see Porter, 1996). This tendency can turn into a cognitive trap (especially if the data are not accurate). To break this cognitive trap, we need to compare different sources and types of data. It is in comparing diverse personal data that numbers gain on value: a child’s test scores need to be compared with the scores of another child or of the same child from a previous or different test. From a commercial perspective, value is created when data are in motion, or transactions, to use the business language. It follows that “big data” are the new “gold” because the personal data economy monetizes their mobility and exchange among individuals: your credit card details are of value only if these data can be used for transactions and exchanged for money. This explains why Google, Twitter, Facebook and Microsoft are investing in large data portability ecosystems but it doesn’t explain why most citizens voluntarily jumped on the bandwagon of non-transparent data exchanges by these tech giants. The Cambridge Analytica Scandal is one in a series of reports documenting the misuses of personal data by Facebook and yet, users continue using it, even though they report low level of trust in the platform in national surveys (e.g., Ofcom, 2019). The fines imposed by the European General Data Protection regulation may have made some adults aware that Facebook or Instagram are not only peer-to-peer communication tools but also massive advertising platforms. Nevertheless, even with the best higher media literacy courses, data privacy scientists are unlikely to change the popularity of Facebook use. This is because there is no equally powerful alternative. Government regulation could help with protection against unfair competition but government regulation often has questionable privacy practices, with most governments

26

The Future of the Self

pursuing protection from terrorism with large “drag nets.” Several libertarians (e.g., Morozov, 2012) dismiss the danger of personal data economy would be a willful blindness to the legacy of corporate control. While it is important to know who surveys the surveyors, it is also important to distinguish data regulations that are concerned with data protection, and those dealing with data collection. It is data collection that requires a comprehensive reappraisal. Moreover, because governments approach the problem of personal data use in a reactionary modus operandi, regulations require ongoing updates and auditing. Critics say that the social consequences of political manipulation via social media are far greater than the fine imposed on Facebook by the UK and US governments (Wong & Morse, 2019). The psycho-social consequences of the collection and manipulation of massive diverse personal data are that the “self” is getting fragmented and amplified with both human and non-human agents. We are only beginning to understand what this might mean for today’s children.

PERSONALIZATION AND EARLY CHILDHOOD Personalization has many positive non-commercial uses – think of the many parents, caregivers, teachers, social workers, pediatricians, doctors and nurses who provide personalized services, thanks to the knowledge they have about individual children. Personal data and algorithms can augment the capabilities of caregivers and professionals to more accurately support those children. For example, no human teacher can remember as many authors and book titles as a digital library can. With access to a child’s reading logs in a digital library, which record children’s comments on books they liked or disliked or books they discussed with their peers, teachers have an overview of that child’s reading preferences. In addition, a digital library contains a large database of books which children could potentially read. With access to such a digital library, a teacher can thus make a personal book recommendation to a child which is more precise than the recommendation based on the teacher’s knowledge of children’s literature alone.

Personalization–Pluralization

27

If human and artificially mediated intelligences worked together in schools, they could empower teachers to do a better job. As I explain in Chapter 6, this is particularly important for children from dysfunctional families, or those with a history of educational, social or health disadvantages, as these children are most vulnerable to missing opportunities of human- mediated personalized education. As a way of introduction to personalized education, let us briefly look at its definition and nomenclature.

Personalized Education Nomenclature There are various versions of personalized education out there. The popular understanding of personalized learning is an “­individual-comes-first approach, usually aided by laptops” (Kim, 2019). I focus on David Hartley’s (2007, 2008) definition of personalized education, which follows comprehensive and not marketing values and is built on school cooperation (not competition) and student integration (not exclusion). The term “personalized learning” is standard in higher education where individual students select courses in alignment with their career aspirations. Students are positioned as self-aware individuals who finance their studies for a career that they choose (with some exceptions of students whose parents pay and choose their studies). The control in higher education is in the hands of the students – they are the personalizers of their own studies. This is different to early childhood education where the control is in the hands of the adults. These adults are the children’s parents/main caregivers, teachers and educators, who will adjust their teaching style and resources to individual children or who decide whether children can have “free play.” In addition, publishers and designers contribute to personalized education by developing personalized platforms that mediate a child’s learning. In early childhood, personalized education is frequently lumped together with “child-centered,” “differentiated” or “individualized” education. All terms denote a model where adults adjust their resources and practices according to a child’s needs and preferences. Educational approaches that position children at the center are also described in broader terms, such as “authentic,”

The Future of the Self

28

“child-oriented” or “student-focused instruction.” These terms and their associated philosophies are at the core of many early childhood education programs. An example of such a program is the Montessori Method, founded by the Italian physician Dr Maria Montessori in the late nineteenth century. In this method, learning starts from the child and the teacher is positioned as a guide in expanding the child’s creativity and inborn curiosity. Creative pedagogies or the so-called “playful curriculum” are rooted in the same idea – to empower children to take agency over their own learning. A child’s intrinsic motivation to explore is encouraged, together with autonomy, wonder and inspiration. The best child-centered education is led by the child but in unison with mediation from the teacher (Fleer, 2009; Vygotsky, 1978). However, the Western English emphasis on an autonomous self has led to a version of personalized education that puts the child in the center at the expense of communal learning. Many policy-makers misunderstand that personalized education that is offered without pluralization values, is a bastion of the privileged – as you will read later in Chapter 4. Just like personalized news should not supplant generic news, so should personalized information not replace general knowledge. If we do not heed this recommendation, personalized education will encounter backlash from educators (just like Facebook did from journalists) and push high-quality content behind paywalls, as we are already seeing with increased differences in quality between private and publicly funded schools (see Belfield & Levin, 2015). Personalized Design In addition to personalized education, there are several personalized entertainment practices in which children participate. Possibly no personalized practice is more popular among children than making. Whatever the game or app, if it invites a child’s contribution as a maker, you can be sure it will be popular with the children. Children love creating their own videos, games and uploading them to Snapchat or Roblox, they relish making their own worlds with Minecraft or embellishing their avatars in Skylanders. As with personalized education, personalized design is not new to the

Personalization–Pluralization

29

twenty-first century – the so-called “Maker Movement” has been around for decades. But while in the past, self-made things required an arduous trial-and-error approach, the Internet has created an international database of hacks, tricks and inspirational examples that others can learn from and emulate. Increased DIY capabilities of the general population means that they can subvert the generic for the personalized. Adults often assume that a child’s making is about producing something original, and that anything that does not produce a tangible outcome is passive consumption. On the contrary, “making” is a process through which children gradually assert their identity as an inventor and maker. Children’s video channels, such as those streamed on the Jellies App or Twitch, are over-populated with videos showing children playing video games. Children watch other children play not only because they enjoy the game but also because it is a way to learn from others’ playing strategies. With arcade games this occurred in closed rooms, with online games vicarious playing occurs virtually. Of course not all children aspire to be designers, and some simply enjoy watching. In some respects, online games evolved into an art form with important socio-­cultural messaging, similar to a spectator’s sport that is to be watched, not just played (Gee, 2005). Personalization can be applied not only at the creation stage but also at the interpretation stage when children relate to a product made by someone else. The question which divides educators and technologists, however, is how much emphasis should a personalized design give to a child’s agency. This is where we come to the realization that personalization has a meaning beyond design in our lives, in that it can connect us to our own selves and build relationships with others. Technology developers are excited by automatic personalization that sidelines or even overcomes human agency. Many websites run on algorithms which use personal data to adjust the content automatically to fit a user. Computer scientists and developers describe such personalization as “reactive and responsive” design. Almost all websites nowadays are designed as responsive – just as a teacher responds to a child’s question, an algorithm adjusts the look of a website to correspond with the user’s device. “Reactive” design takes responsive design a step further – it dynamically reacts to the user’s

30

The Future of the Self

interaction with the content. In immersive story-telling, for example, reactive design adjusts the content according to an individual user’s body rhythms and emotions, that is, the reader’s heartbeat and eye movements on the page. When combined with personal data (the reader’s preferences, names, past experiences and favorite items), reactive design can be highly adaptive and highly personalized (Note 1.3). Both responsive and reactive designs act as a potent antidote to generic design; they minimize challenges and maximize user engagement with a website, app, game or other digitized content. They create challenges that can be mastered with repeated practice, thus assuring the illusion of mastery. Such design is satisfactory. However, if personalization is automated through algorithms, then it usurps any personal volition. In an era when precise and dynamic personal data can be generated without an individual’s control (and often consent), the question of “who personalizes for whom?” is essential to ask. More on this will be covered in Chapter 3, which is dedicated to children’s design constructed with users. Now that we have established what personalization is and discussed some examples of its instantiations, we can ask what it is not. There is a simple and a more complicated answer to this question. The simple answer is that if personalization is about adjusting content to an individual, then its opposite is about relating it to groups. But there are several nuances to take into account: it matters how big the group is, whether the individual is part of a group or who is in control of the group. The more complicated answer, therefore, distinguishes personalization from its related terms: customization and individualization.

WHAT IS NOT PERSONALIZATION? Even though in ordinary conversation people use personalization and customization interchangeably, the two are not the same. Personalization is anything related to an individual, but customization is about anything related to a group of individuals. For example, a personalized shirt is a shirt uniquely made for your child. A customized shirt is a shirt made for a specific age group. Part of the allure of customization is that users, learners or game players can

Personalization–Pluralization

31

find their own paths in a shared universe. Customization is, therefore, baked into most of today’s services and successful products. Not just for humans, by the way. My Ollie Ltd. offers customized meals for dogs, based on the dogs’ “weight, age, breed, activity level and allergies.” Personalization is a step up as it tailors services to individual customers’ weight, age or activity levels. Customization is not “adaptation” or “contextualization,” even though all three words are often confused with personalization. A teacher can adapt a specific program to the needs of their classroom without personalizing it for individual children. Adaptation is less expensive than personalization and, by and large, adaptations to a program have been shown to yield more positive results than the same program delivered with no adaptation (Laurillard, 2002). If we plot personalization and non-personalization on a spectrum, then adaptation and customization are the middle-house between the two edges of personalized and generic design. Personalized recommendations rely on personal data; customized recommendations rely on group data. This is not simple semantics; designers and analysts need to know the exact difference between a personalized recommendation versus a customized one. Take this specific example: a generic book recommendation for a three-year-old girl would be something like: “Your child will enjoy ‘The Hungry Caterpillar’ by Eric Carles because it has high educational value and has been popular among young children since its first publication in 1970.” A customized recommendation for the same girl with the same book title, would be something like: “Your child is likely to enjoy this book because she is three years old and children of this age enjoy colorful stories with simple counting activities.” A personalized recommendation, however, would be something like: “Emily has recently enjoyed a board book about garden bugs with her daddy in the evenings, so this book would be a perfect addition to their bedtime reading routine.” The difference in these recommendations matters a great deal – both commercially and psychologically. Another term often confused with personalization is “localization.” Localization comes from the Latin “locus,” which means a place or position, so localization means adjusting content to a specific language or geographical area. Personalization is, therefore,

32

The Future of the Self

not localization. Personalization is also not “individualization.” Individualization refers in educational contexts to teaching materials relevant to an individual but, unlike personalization, it arises from the group and not the individual. The process of making an object individualized for a child consists of adjusting a generic product, for example, a book, to the individual’s needs. The individualization process thus starts from a generic model of education (which books are good for children of this age?), not from an individualized model (e.g., what does Maggie, this specific child, like to read?). The individualization process begins with a collective and ends with an individual, but the personalization process begins and ends with an individual. In his theory of educational transmission, Bernstein (2003) makes a distinction between individualization and personalization in terms of communication: while a child’s education can be individualized by any adult who addresses a child with attention to the child’s individuality, a mother develops a unique combination of symbols and meanings with the child during childrearing that makes their communication personalized. You may think I am being pedantic here, and that so long as something is about an individual child it does not really matter whether the tailoring starts from the child, adult or anyone else. I would partly agree – I am not against differentiation and think that we do need more of it in schools. But the origin of individualization matters because it sets the path for predictions we can make about a child’s learning. Personalization starts with finding out about the child and this personal information can be either supplied by the individual or someone who knows the individual (another human or artificial intelligence, AI). Customization starts with information from the group (e.g., a group of boys or a group of two-year-olds) and this information is used to tailor the content for individuals within the group. Conversely, individualization starts from generic content or standardized practice that were intended for everyone but got adapted to an individual. The subtle difference between customization, individualization and personalization is explained in this simple diagram (Fig. 3). The arrows clarify how the process of adjusting content occurs. The words “adaptation,” “customization” and “individualization” all revolve around personalization, but it is “pluralization”

Personalization–Pluralization

33

Fig. 3.  Explanatory Diagram of Differences between Individualization, Customization and Personalization.

which marks a radical departure from “self” to “other.” Therefore, the answer to the question “what is not personalization?” is pluralization. This answer is less factual and more conceptual and, therefore, requires your active participation. I am going to ask you to visualize two letters “P.” One P stands for personalization, the self, and the other P stands for pluralization, the collective other. Hold onto this image and keep reading. PLURALIZATION If personalization is a nexus of products, practices and processes related to one individual, then pluralization is the same nexus but related to all other individuals. Pluralization is about human differences, diversity and collectivism. Pluralization is a broad term and just like personalization, it carries different meanings in different contexts. Pluralization conceptualized as a process is highly valued in business and education. A quick example would be collective brain-storming, intended to generate many divergent ideas. Sociocultural researchers use pluralization when discussing differences between and within social groups (Donati, 2014) and in economics and policy studies, pluralization is used when discussing politics of difference or market diversification (Rice & Prince, 2013). Pluralization conceptualized as an outcome (rather than process) is called

The Future of the Self

34

pluralism. Aga Khan (2009), the founder of the Global Centre for Pluralism in Ottawa, defines pluralism as follows: Pluralism means not only accepting, but embracing human difference. (…) Pluralism does not mean homogenization, denying what is different to seek superficial accommodation. On the contrary, pluralism respects the role of individual identity in building a richer world. Pluralism means reconciling what is unique in our individual traditions with a profound sense of what connects us to all of humankind. Together, personalization and pluralization of e­ ducational provision provide an ideal structure that is both personally determined and collectively co-constructed. If education leans more toward the pole of personalization, a competitive “me first” attitude will dominate over collaborative learning with others. If we lean more toward pluralization, the collective will be commended at the expense of celebrating individual achievement. One might suggest that to strive for the personalization–­ pluralization is utopian. One might even say that personalization and pluralization are just new words for the old individual–­ collective dichotomy. But there are no cultural values attached to ­personalization–pluralization and the two are not divided into two camps that fight each other. Rather, they are a working method of dealing with the self–other overlap for an achievable ideal. It is achievable because of the Law of Enantiodromia. “Enantiodromia” is a Greek word for natural equilibrium, the inhale–exhale rule that defines our physical lives and the yin and yang that defines spirituality. I call it the P–P balance.

THE P–P BALANCE Please return to the two capital letters P that I asked you to visualize. You might have imagined the two letters in succession, as if there were a sequence to personalization and pluralization (first we personalize, then we pluralize). However, this option leads to hierarchies and the socio-cultural inequalities associated with

Personalization–Pluralization

35

them. You may have also imagined the two letters in neck-to-neck competition. However, this option assumes that we need to have personalization at the expense of pluralization or vice versa, which leads to conflict and tension. You may also have viewed the outline of the two letters with one becoming the other. Imagine one P upside down, approaching the other capital letter P, creating a “B” for balance. This option leads to harmony and is aligned with the Law of Enantiodromia. The law says that the two opposites are each other’s extreme and expresses the everyday saying “you are unique just like everyone else.” It is this last image, which depicts a balanced vision for P–P, that I would like us to cultivate for the future of the self (Fig. 4). “Aha,” you think, “here comes another naïve academic who advocates for an impracticably ideal vision of ‘balance’ and ‘optimum’. Doesn’t the history of humanity provide enough examples of pendulum-like rises and falls?” But not so fast – I have deliberately chosen to present the story of personalization within its pluralistic reality. It is not difficult to come up with simplistic models positioning personalization as either positive or negative but the perceptions of good/bad are different by people of different professions, culture and experience; they will not and cannot be settled by research. Similarly, asking whether personalization is better than pluralization is non-sensical because the two are intertwined and, therefore, mutually dependent. Personalization reflects pluralization, because the self reflects others. One provides the foundations against which the other is measured. At a fundamental level, P–P balance is about achieving the state that musicians call “polyphony,” that is many diverse voices coming

Fig. 4.  A Mnemonic for Remembering a Balance in P–P.

36

The Future of the Self

together. Education research reminds us that we need to nurture strong solo players as well as orchestra performers. The music metaphor underscores something essential here: the focus on personalization ought not to succumb to deterministic reasoning on how the personal is constituted. An unfortunate fallacy which prevails in the study of personalization centers on the outdated dichotomy of “Nature versus Nurture” in education and development. I follow a transactional model of development, where the person and environment are not separate entities but they mutually co-­construct one another (the so-called transactional model developed by Arnold Sameroff, 2009). A quick detour of explanation follows to ensure that there is no doubt on the focus of the P–P balance. NATURE AND NURTURE IN “SELF” More ink has been spilled over the question of nature versus nurture than any other question related to children’s development. We know that “It’s all about the context,” but the moment we need to make a decision about a child’s education, it is either the child’s inborn dispositions (“She’s always been like this!”) or their environment (“It’s the home they grew up in!”). Although most adults agree that each child has unique needs and talents, very many disagree on the extent to which education, and social policy more broadly, ought to be informed by nature or nurture. In contrast to educationalists, the proponents of behavioral genetics advocate DNA-driven personalized education. London-based Professor Robert Plomin and his colleagues argue that advances in genetics and biotechnology offer the possibility to predict, with a significant degree of precision, the risk of developing certain traits or diseases. According to the controversial view of behavioral genetics, genes explain differences in children’s cognitive ability and, by testing and diagnosing children early, more adequately personalized supports may be put into place. Opponents of genetics-driven personalized education, for example, Nathaniel Comfort warn against the mismatch between the goals of medicine and those of education. Most evidence for genetics in education comes from the longitudinal studies of twins and Comfort and

Personalization–Pluralization

37

others point out the deficiencies in generalizing from twin studies to the general population. The debate around whether personalized education should be informed by genes often slips into a partisan knife-fight between the “transhumanist” and “bioconservatist” perspectives. Through a simplified lens, transhumanists argue that merging human intelligence and AI can lead to breeding a master race, while bioconservatists urge against modern eugenics and designer babies. The concern of bioconservatists is that, once genetic sequencing becomes normalized, every child will be born knowing their full genome sequence and then be pigeonholed into a certain category of life trajectory. Genes will not only be used to inform subsequent development, but also to make decisions about whether some genomes should be edited at the embryonic stage or even whether a child should be born. What both sides fail to see is their reductive view of the personalization–pluralization balance. Instead of spending time ­ on identifying areas of common ground, they accuse each other of wrong turnings. Such accusatory debates can be easily seized by manipulative media or political parties that take a simplistic viewpoint. Similarly, the nature–nurture debate in education is a counterproductive distraction from the real issues underlying personalization. I can think of no better way to end the ongoing tugof-war between “nature and nurture” than the P–P Balance. On one hand, psychologists who study innate human needs would say that children are interested in personalized education for ontogenetic reasons. Certainly, the self-oriented patterns of personalization map neatly onto what Maslow (1987) called “self-actualization” in his hierarchy of needs. On the other hand, educational researchers would say that children’s self-oriented desires are informed by their limited experiences nurtured by the environment where they grow up. Thus, in the context of personalized education in early childhood, it is clear that nature and nurture reinforce each other. There is, therefore, no real conflict in studying personalization using biological influences (including genetics) or environmental influences (including school or home environment). The balances depend on the proportions, distances and sequences relevant in specific circumstances.

38

The Future of the Self

It is understandable that some readers may have a problem with my non-tendentious views. The nature–nurture and technology– human dichotomies have animated countless academic debates, referenda and lines of inquiry. I hope however that readers will see the deterministic debates as mechanisms to discuss contrasting viewpoints, not to silence either side. I repeat again: there is no need to resort to extreme positions in personalization – education can be personalized according to genetic endowment and environmental dispositions for each individual child. Book recommendations can be informed by a child’s IQ scores and social knowledge about the child’s culture (Note 1.4). If you learn anything from this book, let it be the lesson of ­personalization–pluralization interplay. With the P–P Balance, I am going to lead you into the essential socio-cultural mechanisms of children’s learning and development, so that we are asking, “How much personalization is needed for growing a student’s sense of belonging without transgressing into homophily?,” “How much personalization is necessary to design learning games that students will find both engaging and cognitively challenging?” and “What is the extent of a child’s agency in personalized education with standardized curricula objectives?.” In this opening chapter, I have asked ‘what is and what is not personalization?” and I have proposed that any meaningful expression of “self” needs to be connected to the “other” within the personalization–pluralization balance. The Law of Enantiodromia reminds us that to separate P–P would impoverish both the individual and the community. Personalization and pluralization do not threaten each other, they enhance each other. So that humans can survive as a species of wisdom, personalization and pluralization need to remain entangled with one another.

2 QUANTITY AND COMPLEXITY

The history of humankind progressed through four information revolutions: writing, printing, multimedia and digital information (Beavers, 2012). If we take the perspective that technologies remediate each other (new inventions synthesize previous tools into faster, lighter and smaller gadgets, Bolter, Grusin, & Grusin, 2000, Note 2.1), then each information revolution improved our communication: writing expanded oral transmission of information and computers furthered written information. Klaus Schwab (2017), founder of the World Economic Forum, described the twenty-first century as the Fourth Industrial Revolution and the philosopher Luciano Floridi (2014) labeled it “Infosphere.” The Infosphere is characterized by the presence of big data networks which self-­generate information from connected devices, and from the individual human beings using these devices. The information is collected online and offline and creates a three-dimensional space, a “sphere.” The speeding trajectory of digital data generated through twenty-first century technologies is unique to the Infosphere. The question I address in this chapter therefore is: “what is the optimal quantity of digital data for children to be able to thrive in this era?” The Scale of Datafication The arrival of the Fourth Industrial Revolution has been predicted by several communication theorists, including Marshall ­McLuhan. McLuhan (1962) wrote that computers will “flip into a private 39

40

The Future of the Self

line to speedily tailored data of a saleable kind” (p. 296). One could argue that datafication is a manifestation of the historical era we live in: there are more humans on Earth than ever before and personalization allows us to make smaller, more manageable worlds on digital platforms. Perhaps this is why we are so willing for every device we use and every online site we browse (or loyalty program we join) to record our movements and present us with a personalized version. For many people, however, the sheer volume of digitized personal information is an anxiety-provoking concept. Because we participate in the generation of personal data, a lot of these data are deeply personal. Moreover, because we all can generate data in many formats, these data are also very diverse. A child’s face can be part of a photograph, video, digital drawing or a sticker, for example. It can be digitized by the child’s parents, kindergarten staff, commercial producers or the child herself. It can be shared via social media with many other parents/family members, who further add to it with their comments and likes and who carry the data on their own devices. It is the accumulation of such diverse and multiple sources of digital data that paves the way for the beginning of an extreme datafication. Children’s data points are currently sprinkled in various places, supervised by various unconnected institutions, including hospitals, schools or private companies. If all these data were aggregated into one dossier of a child’s self-representation, it would contain an extensively detailed and illustrative account of that child’s progress over time and their movements across space. There is a lot of money in such a dossier. In fact, personal data are the most sustainable as well as most dangerous currency thus far invented because while the reserves of coal or oil are limited, personal data extracted from individuals are not (Zuboff, 2019). Whether FitBit steps, clicks on Google or test points collected by Class Dojo – all these data have a value to companies and individuals. In the Infosphere we live right now, the data profit-makers are a few individuals rather than the millions of citizens who generate the data. In the current “kingdom” of personal data, the kings are Google and Facebook. A Robin Hood-like distribution of the profits made from personal data is unlikely. To address the

Quantity and Complexity

41

issue of data ownership at a more radical level, we need to empower individual citizens with knowledge that could, over time, change their attitudes toward increasing the quantity and complexity of personal data. The beginning of this knowledge should start with a balanced understanding of the role of technologies in children’s lives. Many conversations about personal data are derailed by a lack of clarity around what we mean by technologies: iPads, Alexa or YouTube algorithms? Clearly these are different kinds of hardware and software, but all too often we lump them into a big black box labeled “technology.” Treating all technologies as though they were the same often leads to good/bad viewpoints with some parents expressing a nostalgic desire for a technology-free childhood and others raising their children with a new ABC: Always Be Charging [your device battery]. A middle ground might be possible if we understand the socio-cultural factors at play here. CHILDREN’S USE OF TECHNOLOGIES Several academics have warned against pathologizing children’s use of digital media (Przybylski & Weinstein, 2017) and are uncovering evidence about the complex associations between context and content of technology use. Nevertheless, the “technology is addictive” headline seems to constantly come back to us. Why? First, there is the novelty of technology and our natural fear of the unknown. Then, there is the parent/guardian’s duty of care, and the legitimate worry that technology might take away their control. Another aspect to consider is the influence of researchers who conduct small-scale studies, the results of which are sensationalized by the popular press, concluding, for example, that “iPads damage your child’s brain.” The popularity of technology-free kindergartens is rising in middle and upper middle-class neighborhoods, while more and more developing countries are using tablets to address shortage of teachers. This observation brings me back to what I highlighted at the beginning of the book, but it needs to be stressed continually – different cultures and different families have profoundly different

42

The Future of the Self

approaches to the appraisal and expression of children’s individuality and the technology tools supporting it. Whatever your ideological position on children’s technology use, one thing is certain: the option of completely removing children from screens is no longer on the table. Numerous national and international surveys (e.g., Ofcom, 2019 in the UK) show that technologies have become ubiquitous and indispensable in the space of a few years. Young children’s use of screens has increased both in terms of the number of devices they have access to and the time they are connected to the Internet. Conversely, the age at which children begin to access these devices has decreased over the years, with two-year-olds using iPads now being the norm rather than the exception. We need to ask, therefore, how we can best support individual and collective use of technology from cradle to grave. The message which collectively emerges from the family technology studies is that purposeful and creative use of technologies by parents together with their children is one of the most beneficial means of media use (Livingstone, 2018). In addition to adults’ influence, good technology design can enhance good practices, but bad technology makes bad practice worse (Note 2.4). To level the playing field, we need to increase the agency of children and their parents/teachers/educators in technology design and make diversity (and diverse family cultures) a design principle (Note 2.6). In many families, technologies are shared across generations and co-used by siblings who act as gatekeepers to specific games or co-players and role-models (Gee, Takeuchi, & Wartella, 2017). In some Latino families living in the USA, parents actively seek English content to help with their children’s homework, or cartoons in their native language to support their children’s bilingual heritage (Levinson & Barron, 2018). While many children associate shared family ­screentime with enjoyment (e.g., Guernsey & Levine, 2015; Kamenetz, 2018), during the Covid-19 lockdown, nearly all families experienced that video-conferencing calls, use of e-books or social media, are a valuable way of connecting family members and friends. Based on several observational studies conducted inside family homes, researchers have found that children’s daily experiences with technologies are far less uniform than as portrayed in

Quantity and Complexity

43

­ opular press. Yes, for some children, pressing the Apple home butp ton opens the virtual playground gate. For other children, however, the same button is associated with monitored and restricted access to homework and school tasks. Our national survey (Kucirkova & Littleton, 2017) conducted with British parents of preschoolers showed that young children’s use of technologies is contingent upon their family’s values and their parent’s personal theories about upbringing. A parent’s beliefs, attitudes and perceptions of what a good childhood should be about were found to be deeply rooted in these parents’ child-rearing practices, including the child’s use of technologies. For some children, a TV in the bedroom, a personal tablet and a smartphone are a given, for others technology is a fenced-off area. When conducting interviews with middle-class English children, I spoke to 12-year-old Jack from northwest England. Jack told me that he needed to ask his parents’ permission before he downloaded an app, a document or video on his smartphone. His parents were concerned not only about the quality and price of Jack’s digital files, but also about their size, as they shared devices on a limited broadband. When using Instagram, Jack knew that his parents would check later what he had posted. He couldn’t leave his phone on “silent” after school because his parents wanted to be able to reach him at any time. His time on the phone was controlled by parenting apps which locked and unlocked the device at specific hours. Jack’s case reminded me of Arkangel, one of the Black Mirror (Netflix) episodes in which a mother has her young daughter implanted with a chip to control what the girl is able to see and hear. The appeal of this Netflix series is its proximity to reality which in this case is not far from the surveillance tactics of some parents. This is an exaggerated example, but the point is that in some cases children’s use of technologies is a closely monitored affair. In understanding these nuances, it is essential that researchers work across disciplines and methodological boundaries to provide meaningful recommendations for practice (Note 2.5). Some apps and games, like those positively reviewed by Common Sense Media, should be celebrated by international institutes. But some software programs should be banned through international

44

The Future of the Self

regulation. Let’s cut straight to the latter kind: persuasively designed apps and technologies. Persuasive Design of Technologies Most popular games cleverly combine personalization with strong stories of individual survival (represented through killing/destroying and building/re-making) and community connection (team play or possibility to share progress with other players in multi-level playfields). The more the game becomes personalized (whether it is through tailoring the main story character or choice of story narrative), the more it represents the child’s persona and the more it draws the child’s attention. Personalization becomes the place where the devil of persuasive manipulation hides. It matters more if your avatar loses than a random character. With unknown story characters, there is a distance between reality and fiction and this distance creates a space for reflection and building an understanding for how narratives connect to our own lives. In textual narratives, literary theorists call this the stillness of deep reading and perceive it as an essential antidote to the bombardment of online information (Kuijpers, Hakemulder, Tan, & Doicaru, 2014). The problem with persuasive design is that it removes the stillness with speed and quantity of information that overwhelm users and manipulate their thinking. The manipulation happens through attention and adaptive behaviors (Ward, 2013). In Nir Eyal’s “Hook Model,” persuasive design contains four loops that hook the user: triggering mechanisms (for instance an email notification), an action linked to a reward (for instance the action of collecting a badge in a game), variable reward (next stage in the game includes different types of badges) and investment that becomes a trigger for the next loop (the creation of a mini Minecraft castle can be used as another data point for advertisement targeting). Personalization intensifies all four hooks: when I open my Facebook page I get a personalized notification (Dear Natalia) alerting me that my profile was “liked.” In my email, I find a personalized discount code for the company website of which I have recently browsed. The discount codes are varied every day and include vouchers, free tasting invitations or gifts in exchange

Quantity and Complexity

45

of reviews. I am unlikely to use the vouchers if they do not relate to products and services I want or used before. Ergo, the Hook Model would not be as persuasive if it was not personalized. You can think of personalization as a filter that can either improve or deteriorate existing design. If the design is participatory, then personalization can enhance the participation techniques with personal meaning. If, however, the design is persuasive, then personalization can render this design even more persuasive. Persuasive design is associated with pleasure, arousal and dominance, Mehrabian, 1996, Note 3.5). In addition – and here is the reason agency is such an important concept in personalization – persuasive technologies deceive users to believe that the agency in playing, shopping or communicating, is theirs. Users get instant gratification and acknowledgment of the choices they make but behind the scenes, it is the provider who is the main beneficiary of users’ participation. Persuasive design is a field of study, most famously at the Stanford Persuasion Lab led by B. J. Fogg (Note 3.6). The combination of psychology and design possibilities with personal data has perfected researchers’ understanding of the triggering mechanisms that habituate users to pay attention to new content constantly flooding their screens. Notifications, updates and alerts are part of these triggering mechanisms that keep the mind in a constant state of arousal. Older media, such as TV or radio, used alert mechanisms but these were nowhere as intense as the constantly increasing index of novelty (and threat perception) embedded in the persuasive design. Persuasive design is deployed by the most popular communication platforms, including WhatsApp, Facebook, Twitter or Snapchat. The platforms display posts according to the latest and most viewed items. Psychologists know that short-term memory is biased toward negativity and long-term toward positivity, so this design is not ideal for generating positive emotions. Moreover, the individual’s history of communication is hidden behind immediate and instant responses. Such a design is not conducive to deep reasoning but it instead encourages hyper social engagement, or ultra-amplification of self.

The Future of the Self

46

Extreme Amplification You will remember my insistence on the P–P Balance, the mantra that personalization always works in conjunction with pluralization. It follows that the contexts of extreme personalization co-exist with contexts of extreme pluralization. Vertovec (2007) described the population as being “superdiverse” when referring to the extremely high levels of diversity in the UK population. The online landscape is even more superdiverse, perhaps, although I want to highlight the hyper social engagement of individual groups, noticeable on most popular online platforms for communication (Facebook, Twitter, Snapchat, and Instagram). These platforms are designed with persuasive techniques to propel not only extreme attention to self but also extreme social engagement. Just as humans crave “me time,” they also seek and care about feedback from others. The feedback loop used in social media platforms resembles slot machines with a constant urge to be part of the conversation. Did others read your point? Did they “like” it? Did they share it with others? What are others saying? What do others think about what others are saying? These questions are the fundamentals of human communication, but persuasive design carries them ahead into the extreme of social interest. Influencers are increasingly less interested in the total number of followers per account than in the rate of engagement that indicates users’ participation in the conversation. If you have 100 followers on Twitter and two re-tweets, the proportion is the same as 10,000 followers and 200 re-tweets. A quick look through Twitter accounts shows similarly low proportions of dialogue across users. The engagement ratio illustrates the impossibility for meaningful conversation with a platform designed for massive advertising and virality (Note 3.7). With no conversation, the design mechanisms that could create “social proof” or “peer review” of information have dwarfed into self-propagation. We could blame the design (or social media) for hyper social engagement but a more nuanced analysis reveals that the technologies contributed to an ongoing, larger, erosion of connection in physical communities and family units. For friends and families who are dispersed across time zones, an online community is more

Quantity and Complexity

47

stable and satisfactory than the unknown community of people around them. In this sense, social media sponsor both the integration of small communities and segregation of larger communities. Understanding this issue requires the understanding of P–P, that is, that participation is inseparable from personalization; the personal is social (Milardo & Wellman, 1992). For that reason, the allure of personalized persuasive design is hard to resist not only because of the design techniques but also because of the human relationships surrounding technology use. Just like extreme personalization amplifies individual flaws, so does hyper social engagement amplify societal flaws. This includes amplification of bullying in a small classroom to cyberbullying on social media, or misinformation distributed by leaflets to misinformation distributed by Tweets. Some former technology industry employees have become disillusioned with the exploitation of primary psychological needs in persuasive design used for commercial ends and have switched to being fervent adversaries. One of the “converts,” James Williams (2018) (formerly of Google and now at the Oxford Internet Institute) makes it clear that the systems are designed to pander to the fear of missing out, social comparison, stereotyping and in-group bias. The preference for personalized communication accords with our tribalism roots (Haidt, 2002). Capitalist corporations, or “The Attention Merchants,” as Professor Tim Wu calls them, are interested in profit above and beyond their ability to provide quality. I would say that they have perfected a design that colonizes our agency. Just like in the gambling industry, players lose awareness and a sense of self (see Natasha Schüll’s, 2012 fantastic work in this area), so do many social media users. Some social media platforms are waking up to the fact that their design is not neutral but can, over time, affect users’ behavior. As a society, however, we are slow to acknowledge that persuasive design contaminates the Infosphere with data that get the worst out of their users and propagates this information across billions of devices. A curious by-product of persuasive design with educational and social implications is the rapid rise of the so-called “influencers,” that is, social media individuals with massive online followings. These YouTube entrepreneurs or Instagram stars are not studied

48

The Future of the Self

experts on a given topic, but they have harnessed the social media stage to draw attention to their unique solo act. Through ongoing persuasive opinion-voicing, the influencers attract millions of followers to their accounts. The reason why I single out the example of influencers is that it is not enough discussed and examined in relation to young children. National health services report on persuasive design in relation to gaming but rarely in relation to children following other children and adapting their behavior. Of course, peer learning has always been important for children’s development, but peer learning driven by the persuasive design of social media is not really about learning. Consider the example of “kidfluencers” – child social media stars who advertise various child merchandise on social media in countries with poor legislation (child advertising is illegal on children’s television in most countries, but social media are only beginning to be regulated). Of course, commercialization per se is not bad but monetization that exploits children’s insufficient understanding of commercialization is. There is little doubt that it is capitalist values that govern the design of Web 2.0, and are the reason why the Internet has been denounced by progressive liberal commentators as harnessing children’s creativity to the interests of capitalism (see, e.g., Barber, 2007; Williamson, 2017). We need policy instruments to make persuasive design unlawful for children’s media and to hold technology companies accountable in their duty to develop ethical and better design. But I want us to be careful about using the word “addictive” in relation to Internet design. In the 1950s, there was a lot of interest in the “addictive” nature of TV but experiments showed that when TV was removed, children had no painful symptoms and did well without the screen, that is, they were not addicted. The word addiction has a specific clinical meaning and it implies a problem with an individual. The design and use of the Internet, however, is a societal and structural problem. It is our duty as citizens and human beings, to fundamentally rethink the design of tools and platforms that make us different from other species. Increased legislation and citizen awareness have pushed companies to introduce incremental changes to their design (e.g., adding “soft prompts” in the forms of quick questions warning users before they post a nasty comment on Instagram). Yet, we need

Quantity and Complexity

49

changing not only how we interact but also why we interact online. This implies changing the current metrics of online communication into different value mechanisms (e.g., from number of clicks to number of positive community acts) and replace self-promotion and advertising with social inclusion and community building. Internet for Children The first step in rethinking the underlying infrastructure of how the Internet operates needs to be the fact that Web 2.0 was not designed for, or with, children. There are some notable web-based exceptions, such as, for example, the Children’s Digital Library project that involved children in designing the website interface. But by and large, children’s involvement in the design of online spaces has been more through the advocacy of academics than through industry common practice. And yet, lamentably, most popular apps and websites appear to be destined for young consumers. As Rowan Moore wrote in a perfectly worded observation: “Graphics – rounded corners, lower case, Google’s primary colors, Twitter’s birdie, Facebook’s shades of blue – enhance the innocence and infantilism.” Moreover, the most popular apps use face- and name-based personalization, which are well-researched memory cues that enhance children’s memory of new content (Symons & Johnson, 1997). With no appropriate guidance and support, the “free” provision of information through these media might be democratic but it is definitely not democratizing, that is not everyone has the same opportunity to benefit from it. This does not mean that we should completely denounce the Internet and advocate for Internet-free zones for children. The Internet is fundamental for participating in the civil and democratic society. Well-designed online spaces enhance children’s understanding of the world, and on many occasions, bring them experiences they could otherwise not have, like when they e-visit a remote online gallery, for example. However, there are no age-related locks by design that would prevent children from accessing content that could traumatize or upset them. It suffices for a child to type in “porn” into the YouTube search box or to use the same device on which porn was viewed by an adult before, and free porn videos play in loop, or come up as automatic adverts before a child’s video

50

The Future of the Self

is played. Worse even, inappropriate content is often “smuggled” within content described as child-friendly, so young children can simply stumble upon it (as it once was the case with the Youtube Kids app). These incidents do not happen by coincidence, they are the result of bad design. They force parents to control rather than connect children with technologies. Personalized algorithms can help with some content curation relevant for children’s Internet use. Even crude personalization that involves pre-selecting content for the child, blocking certain sites and logging into the device with a personal profile, addresses some of the Internet safety gaps. The crucial gap related to children’s Internet use is lack of protection from commercialization, politicization and militarization. Over the decades, democratic nations have developed rules and regulations to protect children against companies that cross these red lines. However, children’s programs available on the Internet are much less regulated than on TV (Note 3.8). Personalization alone will not fix bad design; we need to think of P–P design solutions, which are complex solutions. As Henry Louis Mencken, once said: “for every complex problem there is an answer that is clear, simple, and wrong.” Although technologies concretize many trends apparent in the twenty-first century society, they are not their causes and we need to search deep and hard to understand the reasons behind current design trends. In what follows, I will try to convince you that there are two reasons that underlie negative effects of datafication and that can be addressed by P–P design and P–P practices. The first concern is related to large quantities of personal data and the second to the overall complexity of personalization afforded by these data.

The Quantities of Personal Data: Is More Better? The Holy Grail of the economy sector (including the knowledge economy or personal data economy) is a relentless pursuit of a “More is better” mantra. Progress is defined as an accumulation of more: more money, more knowledge and more data. On social media, more followers, likes and shares are a sign of progress and – the longer you live and the more you use the systems, the more those

Quantity and Complexity

51

numbers will be going up and the higher the revenue of companies that monetize these interactions. The social media platforms are designed on the principle of quantifying datafied selves, but the “more is better” assumption is apparent in extreme datafication practices in our society more widely, with CCTV cameras on every corner and billions of posts, tweets and shares on every social media platform. “The Beme” app which automatically streams everything that one individual experiences exemplifies how design responds to this trend. Young children often participate in the datafication involuntarily and unwillingly. In England, by the age of 13, a child’s parents would have posted 1,300 photos and videos of their children (England’s Children’s Commissioner, November, 2018). In addition to data generated by family members and friends, children digitally catalog their lives. Some smart toys and Internet of Things encourage children directly to speak to them. For young children, a robot’s request “talk to me” is as real as that of a stuffed teddy bear or their real friend. They voluntarily share large quantities of personal, often intimate, information with digital devices (Note 2.7), which is why children’s data protection is such a big concern to early childhood specialists. The push for more and more data triggers an ever-growing spiral of data-generation. In this spiraling ecosystem, each person is treated as a brand whose data are the currency paid for boosting that brand. For social media stars, more “likes” and more “shares” equate to actual money through the advertising connected to their persona. But the real winners are the so-called GAFA or FANG firms – Google, Apple, Facebook and Amazon. These companies are prime examples of how to monetize the “more is better” model to dictate new rules of materialist capitalism. The “more is better” concept does not only apply to the collection of personal data by these companies but also their application of personalization. The more the corporations’ algorithms individualize their products to an individual’s likes, the more the individual will want to engage with their product (and pay for it). Success is measured as an aggregate of more data that can provide a more precise personalization. A quantifiable definition of success has taken over other industries (e.g., major publishing houses, music or film production and fashion industry) and thus large groups of the population. We have become

52

The Future of the Self

accustomed to revering bestsellers, super-stars and celebrities. The ones on the top are not necessarily better or more accomplished than the others, but they are set up and marketed to dominate the charts. Literary critics point out that bestsellers are merely commercial novels that follow the business- and e­ ntertainment-oriented publishing model at the expense of deep engagement with literary craft, which by default sells fewer copies (see Asadoorian, 2007). They disempower the collective (the millions of readers/listeners/followers) to manifest the cult of the individual. Just like capitalism gets into crisis with over-production, so does the human mind with over-individualization. The design could be seen as a consequence of a broken labor system and rapid technologization of the workspace, where the survival strategy for individual workers is for each worker to become a company on their own. The gig economy illustrates this philosophy, and its connection to the capitalist drive for materialism. In 1984 in “Material Girl” Madonna sang that “we are living in a material world” as a commentary on lives defined by acquired and produced goods. The impact of materialism in the 1980s has not stopped at the US entertainment borders with the expansion of shopping malls replacing green fields on city outskirts and becoming family weekend outings. Large shopping centers with weekly and seasonal offers are the antidote to personalized online shopping with recommendations “just for you.” But they are popular because they are places for first-hand exposure to the global consumer culture that populations are intensively exposed to via mass media (Cleveland, Laroche, & Papadopoulos, 2016). Part of the more and more philosophy is “a constant speeding up” or “an ongoing time compression in order for capitalism to sustain itself” (Biesta, 2013). This is reflected in the production of short shelf-life goods that are affordable to masses and that are of low quality. (Just compare the quality of white goods produced in the 1970s with those produced in the 2000s or the Egyptian Hieroglyphs that have survived since 3200–3000 bce with ephemeral apps that end up in what geeks call the “app mass graveyard”). The philosophy underlying cheaper goods is that producing more is better for consuming more, and that consuming more is better for individual customers. Undeniably, with neoliberal capitalism, the idea of more is better has morphed into a socio-economical

Quantity and Complexity

53

system which, in order to sustain itself, recklessly disrupts established traditions. The consequences of a consumerist lifestyle are polluting industries that maltreat their workers and are lethal to the natural environment. In relation to the Internet, Jonathan Zittrain (2008) described such examples as “sterile” practices: they do not make us grow as human beings. In a similar way to the materialistic industrial system, algorithmic personalization turns identity questions into marketing questions, which vacate personalization of its wider social meaning. Profits justify unethical means of obtaining personal data, leading to the creation of products that are technically innovative but ethically backward. These issues are not petty: when states produce goods beyond national consumption, then bordercrossing involves military interventions. Why are we giving in to the greed of commercial models? There are politico-economic pressures and there are psychological reasons. I focus on the latter: first, the “more is better” consumption practices evident in the shopping-mall acculturation give the illusion of upward social mobility (Nagy, 2011). Second, the “more is better” personalization serves the primary psychological need of belonging. Algorithms that chisel sophisticated micro-targeting give users the illusion of belonging to a commercial product. This can be particularly appealing to individuals who perceive the lack of the ownership in other domains. For children, having a product that speaks to them, addresses them with their name and that in addition, brings together their learning happening at home and in the classroom, is of particular value. The difficulty with personalized technologies with persuasive design is that they manipulate an individual’s thinking and compromise their volition for elusive belonging. Such technologies do not connect individuals around technology but to technologies. Yes, the Internet was supposed to be about connecting people, but in a democratic, socially just manner - it was not supposed to be about autocratically controlled chains. This is the opposite to what the role of objects, material goods or virtual websites could, or even should, be in human lives. It is important to remember that objects enhanced with personal data are extensions of our “selves,” and as such they carry the thinking and values of their producers. Dusenbery’s (2018)

The Future of the Self

54

book on the use of predominantly male body standards in medical research highlights the bias in healthcare with often catastrophic consequences for women’s health. Historic biases are systematic problems that need to be resolved before they are continued in new (digital) environments. Unfortunately, the current algorithms processing personal data are fraught with racial, gender and economic biases (e.g., Noble, 2018). Given that data always carry a social value, they can be exploited by commercial producers for propagating their philosophies of learning at the expense of equitable education (Lupton & Williamson, 2017). A disquieting prospect is that we adopt wide-scale datafication for all children’s services without a society-wide discussion on its possible consequences. Some might say that we have already jumped on that bandwagon and that data-driven personalized education is one example. Data-driven Education In the UK and USA, children go through numerous tests before they leave the compulsory education system. The proponents of these systems argue that the more data we have on children, the better education we can offer them. I beg to differ: if an instructor tracks all students’ progress via personalized software analytics, it is just like a marketing company tracking an adult’s progress through their catalog of products. These design tactics work in the business sector where gathering data in real time can improve initial categorization and better tailor selected content. But in education, more data does not always lead to better outcomes. “Netflix-inspired” personalized education has been criticized by many educational researchers, including Neil Selwyn (2016), Perrotta and Williamson (2016) and Kenneth Saltman (2016), who militate against the idea of education systems that adopt approaches from the corporate sector governed by technophilia. These approaches follow an entertainment model of personalization – “If you like X, you will like Y” – which gets directly transferred to education dosages “if you perform X on this test, you should get Y.” Other educational researchers (e.g., Moss, 2015) argue that not all activities serve or need to serve a purpose, and by measuring and datafying

Quantity and Complexity

55

everything, we treat children as ­ predictable and programmable beings, leaving little freedom to children’s curiosity and creativity in shaping their own development. Data-based instruction can improve learning and online curriculum materials but it needs to be designed in close collaboration with teachers and sound educational models. As demonstrated by more than 25 years of research by Marcia Linn, Clark, and Slotta (2003) working on the WISE program at Berkeley, students’ learning personalized through problem solving strategies can be very effective for individual students, maintain equity of challenge and opportunity. This is different from the extreme personalization practices in companies-sponsored software, for example, the AltSchool program and the Summit Public Schools. In this example, teachers were initially enthusiastic about the accuracy of test results obtained through data-based assessments, but their enthusiasm soon ebbed when they realized that students’ progress is motivated by their results on “bubble tests” that focus on shallow learning, personalized to students’ own level. Moreover, the technology companies that collected all the students’ data provided little guarantee the data were not sold to third parties and were not misused for commercialization purposes. Put bluntly, more children’s data meant in this case worse outcomes. If we position education as an equalizing and humanizing force (and not an Edwardian model of education that maps skills on jobs), then there are some obvious problems with datafied education: the first relates to the incompleteness of conclusions based entirely on data. The second problem is a heightened perpetuation of social comparison. This ongoing, ubiquitous push for higher performance and attainment has a negative impact on children’s mental health. It undermines children’s self-confidence and places limitations on their expectations (Roberts-Holmes & Bradbury, 2016). It disadvantages children who might progress at a different rate and sends potentially incorrect signals to parents. The unfortunate fallacy of blindly propagating more and more data on children is parents’ and educators’ aversion toward testing and assessment all together (the UK and USA experienced several parent-led protests against tests in schools in the past decade). Yet, tests are essential for improving children’s learning; we need objective, standardized and

56

The Future of the Self

comparable assessments, as much as we need evaluations based on discussions, critical friends suggestions or qualitative observations. This brings us to a constant tension about the place of assessment in personalized education. Let me explain.

Assessments and Personalized Education Educators disagree not only what to assess but also how to assess knowledge. The logic of personalization could be that if we personalize the content of children’s learning (e.g., if a child is interested in dinosaurs, s/he will get recommendations for books about dinosaurs) and the form of delivery (e.g., if a child prefers to read digitally then s/he will be provided with a Kindle), then we should also personalize what and how we assess this child’s reading skills (i.e., measure this child’s knowledge about dinosaurs and provide the test on Kindle). The problem with this logic is that it ignores the P–P balance and focuses on personalization only. Assessment, just like learning provision, needs to be both personalized and pluralized to ensure long-lasting learning benefits. So that assessment does not undermine the richness of personalized content and at the same time, it does not limit the pathways of demonstrating children’s mastery, there needs to be some tests that are tailored to the child and some that are not. Some evaluations need to be based on children’s own data and some on the data of other children, some need to be aligned with the children’s preferred way of expression and some with the assessment structures that are valid in the wider learning environment. The question, therefore, clearly is not whether we need data and whether we need it for assessment but rather “how much” and “which data” we need. The other important question is “who has the right and expertise to translate the dossier of a child’s data into a personalized curriculum?” Researchers, teachers, designers, parents or students themselves? Facebook and Google already influence trade, production, and as we have seen in 2016, even elections. Should these companies make decisions about children’s personal data too? Not even teachers’ referrals of children to special education are accurate and change over time (e.g., E. Smeets & Roeleveld, 2016).

Quantity and Complexity

57

Algorithms replicate and do not remove biases of their designers, so the larger the quantity of children’s data in the cloud, the more urgently does the question of data ownership needs to be resolved. Given that data exist on very young children but these young children cannot resolve this question with full understanding of its implications, the question of ownership of children’s data needs to be part of design courses, family discussions and teacher professional development courses. All adults who care for young children need to know that personal data are of a different quality (Lupton, 2016) and that it matters which personal information we share with whom or where. Such understanding cannot be a tick-boxexercise but rather a reflective discussion. I offer here some pointers for what I have learned in such discussions with colleagues and educational professionals. On a simplified conceptual level, you can think of sharing children’s data related to objective evidence or subjective experience (or facts and emotions). Sharing of objective information is connected to formal learning and learning habits, which partly explains why the Internet has changed our memory habits. As we rely on finding rather than remembering information, our knowledge of facts shrinks (Sparrow, Liu, & Wegner, 2011) – you don’t need to know the years of Second World War because you can Google it. Researchers at the Kaspersky Lab call this phenomenon “digital amnesia.” Amnesia is perhaps too contentious as it implies complete loss of memory, whereas the real change is about remembering “where” to find information rather than “what” the fact is. Nevertheless, because factual information, such as children’s date of birth or address, serves identification purposes, children do not necessarily need to know what it is, but adults need to know where to find it when it is needed. When it comes to sharing subjective personal data, such as children’s expressions of emotions in a photograph, for example, then we need a much more participatory adult–child model. Children need to be involved in the conversation of what is shared, where and with whom because they coproduced the personal data (unlike with their date of birth). Such conversations contribute to trusting relationships in communities. In one of our community projects (Kucirkova & Littleton, 2017), children interviewed elderly community members about their war

58

The Future of the Self

memories and experiences, with the intention to create multimedia stories that could be shared in the local archive. Although the elders had only one or two photos from their childhood, the photographs prompted elaborate story-sharing and an emotional reminiscing session in the school. Personal stories shared by the elderly led to children’s focused search for digital images online, that they used to enrich their multimedia stories. The project highlighted how digital documentation of personal histories can forge intergenerational relationships. The participants showed us that even though there are big gaps in data quantity between younger and older generations, the ownership of a few (or sometimes just one) childhood photograph is sufficient for locating the “self” in the past. In revisiting the project data, I found myself wondering whether emotions can ever become quantified into isolated units of attributes (smile/positive, eye engagement, etc.) as it is currently advocated by the personal data economy. A socio-cultural view is that emotions cannot be quantified, because they are created in relation to others. It is, therefore particularly in relation to affective personal data that we need to take the quantification of self seriously and better articulate the fragments that we are digitizing. In 2021, we are lurching forward with a quantity-oriented mindset that neglects qualitative markers of personal data, which, I argue, carries significant implications for our emotional experiences. The current “more is better” model positions personalization as a technique to automatically reduce information overload: so that we do not drown in the ever-growing databases of data, we need to personalize our way out of it, so to speak. Such an application of personalization is a very basic and linear application, reminiscent of behavioral theory popular in the 1950s. As human–­computer scientists remind us (Janssen, Donker, Brumby, & Kun, 2019), the current automated technology is no longer for the use of trained professionals (e.g., aircraft pilots), but for everyday use (think of an automated car or household robot). These automated technologies replace humans for specific tasks but they still require a human-automation collaboration and interaction. A more visionary application of personalization is therefore that which acknowledges the complexity of data, propagated automatically and agentically in the Infosphere.

Quantity and Complexity

59

The Complexity of Personal Data Data are more complex if they are generated/encountered in many and varied places. This statement is based on a well-studied encoding variability hypothesis that was proposed by Edwin Martin (1968) and has been empirically documented to this day, including in recent neurological studies. According to the encoding variability hypothesis, a more complex stimulus has more potential associations – these associations help with the memorability of the stimulus. For example, if you see someone’s name written in various documents, there is a greater variability in the settings in which you encountered the information. Therefore, there is a higher likelihood that you will remember the individual’s name. Through ­Internet-connected toys and devices, in particular, we can have parts of ourselves (our favorite song, our name or our address, say) encoded in different locations and stored on multiple platforms. These platforms offer a complex representation of an individual’s choices, experiences and identity. Such a representation of self is then more memorable, as explained in Martin’s hypothesis. Encoding variability is used also in mathematics teaching, though with no explicit focus on personalization (as yet). In this context, multiple representations of the same maths construct were found to lead to more conceptual and less procedural knowledge (Ainsworth, 1999). With commercialized personalization setting a precedent, it is foreseeable that future (digital) textbooks will feature multiple and personalized representations of learning topics to enhance students’ memory of all learning subjects. It is not only the multiple and varied locations but also diverse types of personal data that make up their complexity. This leads us to another theory: the Theory of Diversity initially formulated by Nehring and Puppe (2002), which is based on a multi-attribute approach. The gist of the theory is that diversity can be quantified according to multiple attributes. In other words, higher personalization value is not achieved by adding more and more personal data of the same type – rather, higher value is achieved by increasing various and diverse types of data relevant to “self.” Some innovative research projects experiment with the inclusion of more senses in personal data exchanges (e.g., possibility to transmit touch or

60

The Future of the Self

Fig. 5.  Examples of How Diversity and Multiplicity Make Up Data Complexity.

smell). Fig. 5 illustrates the pathways to increase data complexity with a few current examples of personal data points for children. An interesting question, although beyond the scope of this book, is when the diversity of personal data becomes communal and not unique to the individual. The question will be answered differently by different generations given the different amounts of personal data available for different age groups. For most Millennials and post-Millennials, visual data in the form of pictures and videos capture their past and recent experiences. This is likely to have some memory-related effects: memory for the places and objects depicted in the photos will be higher than those that have not been photographed. Psychologists Sui and Zhu (2005) found that children as young as five recall objects associated with a photo of their own face more than objects associated with photos of other children. The effect should not be interpreted as evidence for putting a child’s face on everything we want them to remember. In fact, there is a hypothetical concern among psychologists that over-­personalizing children’s environments will downplay the personalization advantage for increased memory performance. These concerns direct our attention to crucial thresholds: extreme and moderate personalization. My wager is that, over time, the quantity and complexity of personal data will render Infosphere dense enough to constitute an actual parallel reality. Complex data will be generated by individuals as well as the data themselves through machine learning. As we move to the twenty-second century, children will be exposed to ongoing 24/7 highly personalized micro-worlds

Quantity and Complexity

61

that will not only be self-controlled but also enriched with automatic personalization. The key challenge will be to negotiate the optimal amount and the optimal complexity of personal data in each micro-world as well as their shared macro-world. The tension that needs to be tempered in relation to large quantities of personal fragments is a critical discussion of what “self” means to us now and possibly in the future. The current technological model of personalization trivializes individuality to a set of individual data points. Digital personalization techniques fragment the “self” into individual markers and assume that the “self” is stable and consistent. The more individual points companies have, the better they can target the individual. Yet, research is clear about the instability of personal and professional identities (Day, Kington, Stobart & Sammons, 2006). We need to contemplate these trends in light of the future of humanity. I therefore close this chapter with a brief reflection on the P–P Balance in achieving optimal quantities of personal data.

Optimal quantities of personal data I began this chapter by arguing that the unique problem of Infosphere is a persuasive design combined with large and complex sets of personal data. From the personalization perspective, the “more is better” model of consumerist and materialist cultures affords more opportunities to individuals to craft their individuality through material goods. We have become accustomed to the use of cameras to monitor professional integrity and provide evidence in conflict resolution: police and health workers wear cameras on their uniforms, airline pilots have cockpit cameras, teachers have CCTV cameras on the classroom walls and white collar workers are monitored with all communication recorded on company servers. Sexual consent apps record “no means no” messages to provide evidentiary record. In some contexts, such as, for example, during protests, collective surveillance ensures protection from abuse of power and transparency, while in other contexts, digital surveillance erodes intimacy and trust. This is a problem because intimacy is the cornerstone for close, long-lasting relationships between

62

The Future of the Self

peers, family members and romantic partners (Fletcher, Simpson, Thomas, & Giles, 1999). In negotiating the optimal amounts of personal data, we need to be constantly asking: how does massive data collection affect how we act toward each other? The Internet is driven by data. It is a living bank of personal and collective data in dynamic transactions. Putting the genie back into the bottle would not work: we need personal data for audience analysis to support the functionality of services we rely on every day. Clearly, the push for “more is better” by the personal data economy has resulted into a situation where selected groups periodically misuse personal data for means that are not essential for their services. The reason that Facebook or Google are technology giants is because they have reduced the size of many smaller networks to aggrandize their own proportions. But perceiving one political group or the technology industry as a culprit for everything wrong with digital personalization would just insert fictional values into gaps between multiple socio-cultural explanations. Vincent Cerf (2018) put it precisely: The internet has become a mirror of our global societies. Some people are not happy with what they see in this mirror, but make the mistake of thinking that correcting the mirror will fix the problems reflected therein. (p. 24) I would take it even further and contend that the Internet, and technologies more broadly, do not just reflect socio-cultural trends but refract them as a prism. A consideration of big data deployment for adults may help in opening discussions about the kind of “data future” we want for our children. Perhaps the Silicon Valley dreamers would say that data drives innovation and innovation drives humankind. But from a socially just perspective, not all innovations are good for humankind. History tells us that technological inventions follow a predictable sequence of deployment first in the military sector, followed by the entertainment and medical industries. The gap between military and high-end commercial solutions is in the 2020s considerably smaller than in previous decades. For example, the latest design of immersive video games includes a fabric wiring

Quantity and Complexity

63

system that runs all the way through the player’s vest; it records the player’s bodily responses and provides customized responses just like a military super-charged uniform. With the relentless race for more and more data, body-related monitoring technologies might soon enter schools. Not to sound like a luddite, but I do think that if we lose sight of the humanity underpinning innovative ideas, we create an inhumane future of large and complex sets of personal data, led by transhuman intelligence. I could simplify my concerns around extreme personalization with the popular question “when will robots take over humans?” but that would misplace the focus on technology and not on identity. Humans will neither unquestioningly nor unanimously relinquish personal control to robots. Neil Selwyn once jokingly wrote that teachers being replaced by robots is unlikely but teachers having to work like robots is far more likely. Humans need other humans to survive. Personalization and pluralization need to be in dialogue – personalization is breathing in and pluralization breathing out “the self.” Currently, there is very little dialogue between technology developers and technology users. Yet, the scale and sophistication of the data-driven economy are so large that they require a multi-tiered dialogue. In this dialogue, we need to acknowledge that what is optimal for one might not be optimal for the other one because people have different values and worldviews. For instance, if you believe in the merits of meritocracy or plutocracy, then you might love the current set up of “more is better” on social media. If you believe in top-down control, then you might suggest that the unlimited numbers of followers, shares or photographs taken by and recorded on your smartphone, are controlled by quota and caps. We are unlikely to agree on the optimal amount of personal data but we can agree that the answer to the cosmic question of “what does it mean to be human?” requires an engaged ­personalization–pluralization dialogue. In the next chapter, I propose agency as the essence of an engaged P–P (Note 2.8). I return to some tried and tested theories to explain how the “more is better” of personal data economy struggles with personal and collective engagement, the so-called agency paradox.

This page intentionally left blank

3 AGENCY

Agency has become a frequently uttered word in relation to the recent automation of routine tasks and the “shallows” of the Internet (Carr, 2011). Even so, the apprehension that machines will remove human agency has been a recurring fear in the history of human invention. The German poet Raine Maria Rilke (1922) wrote in his Sonnet to Orpheus that: All achievement is threatened by the machine, as long as it dares to take its place in the mind, instead of obeying. In this poem, Rilke was responding to the industrialization fear that machines would take over humans and subsequently extinguish humanity. His lucid explanation was clear: so long as humans retain their own agency, they will make progress and survive on Earth. In this chapter, I discuss the role of agency in relation to personalization and the datafication of children’s experiences. What is Agency? Agency is the universal human competence to volitionally take control and to personally determine and influence one’s own existence (Ortner, 2006). All human beings are born with agency. Agency is not free will, although the two are very closely related because of their shared foundation of choice (Note 3.1). We all

65

66

The Future of the Self

have volition and power to live our lives to fullest and change an outcome. But while we are all born with agency, we do not have equal opportunities in exercising it. This is why we need societal measures for the vulnerable, as outlined in the Universal Declaration of Human Rights (UNG Assembly, 1948) and in the UN Convention on the Rights of the Child. From an academic perspective, agency is a conglomeration of various attributes, including the child’s volition and active involvement in creating or co-creating personalized resources destined for them. How exactly to evaluate and support agency is a slippery ­exercise - David Oswell’s (2013) comprehensive summary of children’s agency concluded that the topic was too complex to be unified with one theory. Oswell stated that agency needs to be debated and seen from multi-disciplinary perspectives but there are disciplinary differences in how researchers define and study children’s agency. In psychology, agency is discussed in terms of self-efficacy and control. The theory developed by Albert Bandura (1977) states that if people believe they can influence their own lives then they have high self-efficacy levels. Self-efficacy is related to a mutually reinforcing cycle of self-image, self-worth, self-esteem and self-regulation which sustain the “self.” People with a high self-efficacy have a high internal locus of control believing that the power to alter events resides within themselves. When applied to education it means that students who believe that they can do well on an assignment are more likely to be motivated and persist in completing the task. Socio-cultural theorists view agency as negotiated in dialogue between people or among larger collectives, where meanings are dynamically co-created. A leading social anthropologist, Jean Lave, views agency in terms of the extent to which children can make decisions, take initiatives and use their own strategies to tackle problems. Researchers in childhood studies might examine children’s agency in schools and define it as children’s perceived or actual participation in classroom activities. I venture to argue that the underlying reason for agency is the human desire to actively negotiate belonging in a shared world. Beyond that, though, because agency lies deep at the core of our being, it is associated with vulnerability. To borrow from Brené Brown (2015), agency is the courage to act. To show up in life means to be brave, to give up comfort and to invest in the battle

Agency

67

of our own worthiness. All this means that whether it is children’s use of digital media, playing with friends or learning at school, agency is a double ended arrow between the self and other. Agency is the expression of answering the quintessential questions “what life will you craft for yourself?” as well as “how will you show up in other people’s lives?” The answer to these questions requires both powerful self-determination and a vulnerable belonging to others. The Janusian face of “self,” looking simultaneously outwards and inwards is the dual face of agency (see Fig. 6). The double-arrow in my simplified figure is intended to capture the deep psychological processes which occur when people negotiate the space between their imagined and real selves, as defined to their own criteria as well as the criteria of the society where they live. Children move through this pulsating space as they grow up. They learn to consolidate their rights and responsibilities from a young age, and perhaps most keenly when they enter school. For most children, classrooms provide the first socially constrained setting in which they need to negotiate the tension between their inner and outer self – between the persona they present to their parents and the persona they present to their peers, the smaller and larger versions of themselves (see Materson, 1990). If their classroom is governed by democratic principles, children learn that personal autonomy needs to be negotiated in relation to the needs of the community. To instill such values, teachers need to act at times anti-democratically, in that they need to restrict children’s personal freedoms to be inclusive of all children (Mardell & Kucirkova, 2016). In doing so, educators teach children about the non-negotiable association between personal freedom and responsibility. Fig. 6.  A Schema of the Bi-composition of Agency.

68

The Future of the Self

Vivian Gussin Paley, one of the most influential early childhood educators of our times, explored how stories help negotiate this social contract in early childhood education. Paley’s story-telling curriculum was officially adopted in the Massachusetts Curriculum Frameworks for Pre-K and also some kindergartens in the UK. The core of Paley’s story-telling curriculum is children’s sharing of stories: first privately with the teachers and then acting the stories out on a shared classroom stage. Through stories – oral, digital, written on the page or acted out – children learn how to control their impulses and act toward others with sensitivity (see Chapter 7 for more). Paley’s story-telling curriculum reminds us that we would be killing the golden goose of what makes children “children” if we undermined their agency in telling and sharing the stories they carry inside them. The reverse of Paley’s ideal is to treat children as minors whose actions are pre-determined, and should be policed or constrained. Such practices not only go on in some formal education settings but also in some peer or family relationships, in overt, universally condemnable ways, and also in subtle, less discussed ways. The latter kind in relation to children’s use of personalized technologies has been documented in relation to children’s rights (see Chaudron et al., 2015) as well as trends to “datafy and schoolify” children from early age (Bradbury, 2019). I cringe when I hear that parents should “ban” children’s phones from their bedroom or “police” their children’s screen time. No one is suggesting that adults do not have a duty to protect children from harm, but we must not confuse protection with the inhibition of children’s agency. Particularly in light of how personal and personalizable today’s technologies are, it is important to cultivate children’s understanding of how these technologies work from a young age and let them respond to the universal desire to be self-reliant when connecting with others. The preoccupation with agency and technology use is no more profound than in the context of automatic personalization. Agentic and Automatic Personalization Agentic personalization is personalization predominantly led by the individual user. For example, if I use my own photos to make

Agency

69

my own digital wallpaper, then I made that decision, I acted on that decision and I personalized my wallpaper. However, personalization which is done to users without their involvement, and sometimes even consent, is devoid of the user’s agency. For example, the iPhone’s “Memories” functionality automatically selects my photos according to dates or the photos’ location. It is not as black and white as it sounds though, because users can in many cases opt out of automatic personalization, or they can be partially involved in its creation. Yong Zhao (2018) suggested making a distinction between agentic and non-agentic personalization in terms of children’s education. According to Zhao, personalized education is education that is created by someone else for the child, whereas personalizable education is driven by the students themselves. In both cases the recipient of personalization is the learner, but the agent of personalization can be the teacher, the technology provider, the learners themselves or a combination of all three agents. Using the adjectives of agentic and automatic in front of personalization is to emphasize that personalized is not personal: while personal relates to a particular person, personalized relates to the activity of making something personal. Personalized can, therefore, be made by others or by self and it is important to distinguish who the agent of personalization is. Automated or automatic personalization is the use of personal data by artificially intelligent technologies. When such automated personalization becomes part of the design of social robots, it is easy to mistake robots for agentic creatures. On the positive side, social robots fulfill various positive roles, for example, in autism therapy – these robots can be strategically designed to contain a limited number of social cues, which makes them more predictable and easier to relate to by children on the autistic spectrum (Cabibihan, Javed, Ang, & Aljunied, 2013). On the negative side, when social robots perform emotional roles that replace real human interaction, we risk abdicating humanizing duties to AI. The growing list of social robots designed for playing and comforting children (Jibo Ltd., Cozmo Ltd., Snoo cot Ltd.) is a slippery slope down the wrong road. Robots cannot raise truly “happy” children, at least not in my definition of happiness, inspired by the Nordic concept of happy childhoods (Note 3.2).

70

The Future of the Self

There are social, moral and emotional reasons why the distinction between automated and agentic personalization matters. While anyone using the Internet contributes to the bank of automatically collected data traces, such as cookies or browser fingerprinting, the extent to which individual’s data are used for commercialization or security purposes depends on individuals’ privacy settings and the legislation followed in the country they are browsing from. The so-called “user profiling” that is performed by algorithms run by individual websites and inferred from automatically collected data is becoming not only increasingly sophisticated but also more monitored by national governments. Citizens give up their privacy to governments and national agencies in exchange for the promise of personal protection (O’Hara & Shadbolt, 2014). Crime is nowadays more unpredictable and lethal than ever before, with unprecedented possibilities for sophisticated global cybercrime (as well as primitive acts of terrorism, see Miller, 2018). Therefore, citizens want to protect their identity (online or offline), and their degree of agency in this process matters hugely for their well-being. The bigger picture that emerges then is this – agentic personalization is a mechanism to protect our privacy and personhood. It is also a creative endeavor with a humanizing potential to enlarge our own selves. Educationalist Anna Craft (2012) goes further still, incorporating agency into a framework of everyday creativity. She distinguishes between “Creativity” and “creativity,” with capital “C” “Creativity” reserved for original works produced by highly talented individuals, and small “c” “creativity” for everyday endeavors that make an individual’s life more enjoyable. She argues that creativity can reignite the sense of agency necessary for constructing one’s personal identity. If adults position children as creative makers, children will willingly exercise their agency to take part in collective action. That said, we should not mistake children’s agency with a push for productivity. This is particularly important in relation to children’s creative efforts with technologies. As historian Helle Strandgaard reminds us, a participatory approach to media production was ripe in Denmark in the 1970s. At that time, child-centered media production was driven by a Marxist vision to give production back to the people. Children were encouraged to make their own films with state-sponsored video cameras. It is

Agency

71

easy to spot the parallels between the 1970s video production and the “coding movement” in the UK and USA in 2000s – both government-sponsored schemes designed to support children’s production of adult inventions, in the name of “creative making.” This brings me to an important issue which cannot be overlooked: the political side of agency. Self-representation, selfdetermination and volition are each a political act. While in some countries the support of individual expression (whether children’s story-making or freedom of speech) is widely accepted, in other countries it is not taken for granted. One of the most basic ways for women to assert agency is to have control over their reproductive rights – but even this choice is questioned in some countries. Social norms change across time and space and the perceptions regarding children’s agency change over time too. My little epiphany happened when I visited Japanese kindergartens in the Osaka Prefecture. The teachers I interviewed proudly showed me some books produced by children in their class, with cut-outs and handwritten hiragana of the children. They explained to me that while children’s story-making is today considered a creative, imaginative and empowering activity, it was actively discouraged in the 1940s (some teachers were even jailed for instructing children to write their own story). In my work, I have been developing resources and pedagogies to support children’s agency in digital story-making but children can be makers and designers in various contexts, including outdoor spaces, food, clothes or art. The skills necessary for making are closely related to the desire to leave a personal mark on the world. This doesn’t just apply to children, of course: the essence of creative therapies for adults is based on the idea to heal traumas by encouraging individuals to take back control and produce a poem, painting or any other piece of art (Mazza, 2016). Morris (2018) describes how adults develop “personalized life hacks” to make technology work for them, and in doing so, boost their self-esteem. In the projects I have been involved with, we documented the positive effects of children’s story-authorship on children’s interest in reading, self-esteem and reading comprehension (Kucirkova, 2018; Kucirkova, Messer, Sheehy, & Flewitt, 2013). When children make their own games, avatars or multimedia stories they are volitionally

72

The Future of the Self

and intentionally changing a shared virtual space. This gives them a sense of purpose and self-assurance. Individuals who personalize a shared environment grow their own selves (metaphorically speaking), and through this growth, they enlarge the setting they share with others.

AGENTIC AND AUTOMATED CHOICES I mentioned at the beginning of this book that choice is the basic unit in an emerging theory on personalization. Choice and agency are bedfellows but they are not the same. Choice is a misleading marker of agency because making a choice is a demonstration of agency and not making a choice is also a demonstration of agency. Choice animates moral questions about personalization, for example: “who chooses the personalized realities we experience?” The Stoic school of thought reminds us that some things are within our control and some are not and that knowing the difference contributes to happy lives. An individual’s agency is essential in understanding even this distinction. People will make a choice when they are given a choice but not all choices are offered under favorable conditions. Thanks to Barry Schwartz’ (2004) illuminating work on the “paradox of choice,” the phrase “less is more” has become a research-substantiated fact. Having some choices is vital for finding a purpose in life, but too many choices can lead to confusion, indecisiveness and, over time, to depression and unhappiness. “Less is more” stands in stark contrast to the “more is better” mantra of the personal data economy discussed in the previous chapter. However, before jumping to the conclusion that restricted choices is the perfect solution for fostering agency, it is important to realize that not all choices are genuine choices – the truthfulness of choice matters. A first example that comes to mind in relation to false choices is commercialized personalization. Here, choices are rarely designed to creatively extend the customers’ thinking or social contributions. So that the company/provider survives, all customer choices need to be linked in some way to cashing in on the customer’s engagement. This should be clear to anyone entering a shop, but still we like to think

Agency

73

that Walmart caters for our individual needs when it sends us personalized recommendations. When elevating specific topics for our personalized news on Google we often feel that we are in control of our reading – scratch the surface and you will find revenue-driven algorithms under the banner of “customer choice.” The illusion of agency in commercial personalization has gone on for decades, the difference with automatic personalization is that the choices are more relevant to individuals (more deeply personalized), and that they are offered via multiple channels anytime and anywhere. The discussion of the relationship between personalization and choice points to the complex psychological processes in agency. Gunther Kress (2009) clarifies the difficult transaction model here: individuals have agency in choosing how to communicate (online or offline), but the market shapes the communication choices that individuals make. In what social semiotists consider a bible of the multimodal approach, Kress provides some of the most groundbreaking insights into reading images in the digital age (Note 3.3). The grammar of visual design proposed by Kress and colleagues breaks away from hierarchies of representation and points out that meaning-making with images is as deep as it is with linguistic structures. The written mode of communication dominates the academic world, but image-based communication has taken over informal communication. Schools are restricting children’s agency in communication possibilities because if schools were genuinely open to all semiotic modes, they would equally value children’s oral recounting, drawing, acting, singing or dancing, for example. The education system needs to be reformed to ensure children do not merely participate in the reproduction of literacies but that they “live literacies” (Pahl & Rowsell, 2020), as acts of meaningmaking experienced between multimodal texts, bodies and minds. While the theoretical understanding of multimedia/literacy choices has advanced significantly in the past two decades, the variety and opportunities to personalize literacy experiences lag behind in public schooling. The gap between what is possible and what is available exists also in relation to children’s personalized educational resources: many personalized products that use the word “personalized” in fact offer “customized” if not outright “generic” products with a few choices. You will remember from Chapter 1

The Future of the Self

74

that customization relates to groups, not individuals. To give an example: if a publisher tells a child to “be the author” but then provides guidelines to follow and templates to fill out, the child is not really the author. Instead, the child’s authentic artifact is more or less a customized version of the publisher’s vision. Of course, every product is, in a sense, limiting and offers a template for behavior. But while simple customization models will offer users choice within a limited story-world/pre-determined design (e.g., choose your own adventure from this series), personalized design is not restricted and directly involves the user in the process of production (e.g., be the author of this adventure). Put simply, agentic personalization is not a cookie-cutter exercise. Agentic personalization adds the individual’s passion and creativity to a common story. Such personalization represents a unique personal investment that makes a story interesting to others. The type of design that accommodates agentic personalization is open-ended design.

Open-ended Design Open-ended design is design that invites users’ participation, with space for their own creation. A good example of a platform that follows open-ended design is Minecraft (but see many more examples in Kucirkova, 2018). Minecraft can be thought of as a virtual version of Lego. It is a globally popular video game which allows users to make their own story worlds. The business models of Minecraft or Lego stand on the pillars of personalization. With Lego, children can visit Legoland, buy Lego clothing, multiple types of Lego sets and Lego toys. In the biggest Legoland (in Billund, Denmark), visitors can create their own Lego avatars. Diverse customers can make the gadget their own and use it for their own purpose. The more versatile the uses are, the more the gadget feels like the customers made it. Psychologists call this the “IKEA effect” in reference to the Swedish retailer who came up with the idea of do-it-yourself furniture. If customers are involved in co-creation of products they buy, it gives them the illusion of co-ownership and higher appreciation of the final product. Psychologists also know that the involvement of “self” in the creation of objects elicits a

Agency

75

positivity bias. If you assemble a table yourself you will like it more, or at least so the theory goes. We tend to over-estimate the value of things we own, a phenomenon that psychologists call the “endowment effect” or “mere ownership” effect (Beggan, 1992). If we endow objects and animals with human characteristics, we lose the possibility for a wider frame of interpretation. From this perspective, anthropomorphism and emotional attachment to objects are mechanisms that overprotect agency, at the detriment of its benefits. Commercial designers often exploit the loopholes of the endowment effect: shopping websites give easy options to put things in your basket and keep them there – until you hit the last step of having to pay for the goods. Physical proximity further increases endowment effects. In a study that compared shopping from the same site using a mouse, wireless touchpad, and touchscreen, most shopping occurred for the touchscreen (Brasel & Gips, 2014). The study authors hypothesize this was because the distance between reflection and impulse reaction was shortened with a touch-surface. Unlike with desktop computers, with touchscreens, users are closer to the item they buy, and this proximity might induce feelings of owning (or the desire to own) items literally under their fingertips. While open-ended design and personalization drive creativity, self-esteem and other positive identity outcomes, customization and template-based design drive sales. Amazon or Ebay are examples of commercial providers who successfully harnessed this combination, with some personalization features: these platforms offer multiple ways in which consumers can pick and choose from fashion, books, food, cosmetics, household items, while being addressed by their name and provided with “personalized” recommendations. The design of these platforms neatly fits the multiplicity and diversity theories discussed in Chapter 2 in relation to data complexity. Only a few companies can afford such personalization on scale. Indeed, scaling up personalized businesses is as difficult as scaling up personalized education. Why? One likely reason is that only big companies can rely on a multi-sided market. If you happen to be a devoted Amazon customer, you have multiple devices that furnish diverse personal information about you: Alexa on your kitchen table connects to your Amazon shopping account that you use on

76

The Future of the Self

your phone on the way to work. You generate new data anywhere and anytime and a big provider of commercial personalization has wide webs to capture data about your movements, contacts or household. But small companies cannot afford such deep personalization with their niche products. Schools cannot afford it either and this is both their achilles heel and their crutch: schools only capture the data on the school premises, they rarely harness the learning that happens outside the classroom walls, which limits the personalized education they can offer to a child (if the teacher doesn’t have the information that Popi got a YA thriller for Christmas, the teacher cannot tailor recommendations to Popi based on this book). At the same time, however, not having this information creates a shared classrooms ground from which teachers can make recommendations that are suitable for all (or most) children. This is perhaps a somewhat less obvious reason why it is so difficult to achieve fully personalized education at scale (by “fully” I mean oneto-one tutoring for every pupil in every subject with both human and digital support). Think of this: a personalized (and not customized) software program needs to offer individual students more than what it offers to a group of students, which means it needs to accommodate also those students who largely deviate from the average because they are lower or higher achievers. To do this well, the software would need to contain a giant database which is continuously updating itself, based on the individual as well as collective knowledge. This is possible for learning topics with clearly defined outcomes and factual basis, but not for subjects with sociocultural ramifications (Pane, 2017). This is why personalized education tends to be most beneficial to the students at the extreme ends of a large pool: low- and high-performing students (see Chapter 6). Back to design: HCI studies tell us that most optimal design is design that is neither fully open-ended nor fully template-based (not too loose and not too controlling either). Think of a wardrobe with a few high-quality pieces of clothing that can be used to dress down or dress up, depending on context. Such a minimalism design concept is well-known not only in the fashion industry but also in art and media. In his “comic about comics” Scott McCloud (2006) demonstrated how in comic art, simple images and minimally detailed characters offer more room for readers’ creativity.

Agency

77

The worldwide success of minimalist characters such as the little rabbit Miffy from Finland, come immediately to mind. While the manufacturer can offer direct personalization by adding customers’ names to Miffy bottles, tea towels, placemats, pencil tins or lunchboxes, the answer to scalable ethical personalized products is not producing them en masse. Rather, the answer resides in agentic universal design that can be adopted by the customers themselves. The origins of universal design are multiple: some sources cite Western architecture and some Japanese manufacturers of children’s toys. My starting point was the Tomy Corporation in Tokyo that I visited during my fieldwork. In 1980, the manufacturer embarked on a mission to produce toys for all children, including children with sensory difficulties. The company quickly realized that they would be out of business if they did not offset the higher costs of specialized toys by producing toys that can be enjoyed by all children, including blind or deaf children. Such toys are multi-sensory, for example, they are likely to have a convex dot/bump near the switch on/off button, vibrate and flash a light when they make a noise and have affixed Braille labels. Such toys can be labeled as inclusive (or at least more inclusive than standard toys) and to me, are an example of how universal design exemplifies personalized design that has pluralization at its heart. Some accounts of universal design couch in different terms what is known as the neurodiversity movement in education (see Baron-Cohen, 2017) which proposes that neurocognition and cognitive functioning vary among all individuals. My account is that there needs to be a ratio between personalized and pluralized engagement and learning possibilities. This claim is what lies at the heart of the agency hypothesis.

THE AGENCY HYPOTHESIS The benefits and limitations of children’s agency are hard to measure with tests, but they can be gauged from individuals’ attitudes and perceptions, which is the approach we took in our studies. As I was analyzing the interviews with teachers and parents about their views on children’s personalized technologies, I noticed that there was a sharp divergence between what they perceived as beneficial

78

The Future of the Self

and what as limiting personalization, and this difference seemed to be dictated by the absence or presence of agency. When the child was positioned as author or co-author of personalized products (toys, books and educational programs), or when the teachers could decide which story characters children could choose in a story-making app, they perceived the activity as “creative” and supporting the child’s playful learning. But when the teachers’ agency was threatened by choices suggested by the commercial provider, the teachers said the app was about “consumption” and its use was “not worth it” (Kucirkova & Flewitt, 2018). Reflecting on these findings and on previous research, I postulated the agency paradox (Kucirkova, Toda, & Flewitt, 2020) and proposed the hypothesis that agency mediates the extent to which personalization is perceived as positive or negative. Put simply, if agency is present, personalization is perceived as beneficial, but if agency is absent, personalization is perceived as a limitation to children’s learning. If children use story-making apps to make their own stories, adults comment enthusiastically about how technology supports children’s creativity. If children use apps that automatically personalize their stories, adults comment that technology turns children into passive consumers, “damaging their free childhood.” It is a paradox because agency implies a sovereign choice as well as a choice that is governed by others and their material extensions (objects and their design).What is at the root of the agency paradox? One interesting pattern that I noticed in the interviews not only with British parents (Kucirkova, 2019a) but also with the teachers and designers in the UK, Japan, USA and Norway (Kucirkova, Flewitt, & Toda, 2020) was the close relationship between agency and fear. The more a personalized product was endowed with its own agency through AI (e.g., that automatically made personalized suggestions for the user), the more our participants described it as “scary.” Surely a talking teddy bear cannot be really scary for adults, I thought first. In my quest into the possible sources of this fear, I reviewed the agency principles of humanistic psychology developed by Carl Rogers and implemented by child-centered education. While these approaches explain the moral importance of agency, they do not explain the ambivalence that occurs with

Agency

79

personalized technologies that have human agency. The entertainment industry endlessly enjoys exploring this question in relation to romantic relationships with human-like robots (think of the film Her) but it is the Uncanny Valley Theory that explains this fear. The Uncanny Valley Theory, put forward by Mushimo Mori in 1970, was built on the notion of specialness and the need for humans to be recognized as distinct. Uncanny Valley Theory is often applied to the design of immersive games and the thresholds at which these lose the gamers’ interest. On a more philosophical level, however, the Uncanny Valley theory posits that robots represent a threat to humans’ distinctiveness because we humans are most fearful of their replacement. It is the fear of irrelevance, of being buried alive, so to speak, that makes us quit a game or shiver when we are immersed in a VR experience replicating reality. Existential psychotherapy developed by Irvin Yalom (1980) further explains that psychological equilibrium is disrupted by fear of dying. The coping mechanism for this fear is specialness – ­specialness is Yalom’s term to describe the inextinguishable hope for eternal life even though everything has a limited shelf life. When you take the specialness hypothesis to design and replace death with life, you get to the design of robots and robotic toys. Robots with a higher resemblance to real humans will be perceived as more valuable (worthier of being alive) only to a certain extent of their specialness. When the robots cross the threshold, they will be perceived negatively because they are too similar to a real human being. Optimal design strikes a fine balance between a robot that can do more than a human does but that does not threaten the human’s perception of specialness (and the human fear of replacement). This can be neatly mapped on our focus group interview data with primary school teachers: these teachers were concerned that the personalized software could replace teachers’ role in the classroom. An app which knows the child’s likes, test scores and even addresses children by their first names, would make the teachers redundant, the teachers feared. A similar line of reasoning was found in relation to the parent’s role with personalized toys. A smart toy that responds to the child’s questions, reads the child a goodnight story or instructs children that it’s time to brush their

80

The Future of the Self

teeth could act as outsourced parenting and take the place of the parent (Kucirkova & Flewitt, 2018). The tendency for agency to initially rise but decline when a saturation point is reached is similar to a multiple parabola. Picture the Stone Arch Bridge across the Mississippi River in Minnesota, but upside down, or this schema in 3D.

Fig. 7.  An Illustration of How Agency Develops Over Time.

The U shape is reminiscent of the Uncanny Valley theory but the sinusoid shape of agency proposed here is a parabola that repeats over time – when it reaches the saturation point, it drops, however when the conditions are right, it rises again. What influences these rises and falls? In the Uncanny Valley the theorized explanation was the perception of specialness. With agency the lows and highs are directly proportional to the mental price of choice. This mental price is paid in the time each individual invests in deciding whether to make a choice. When individuals make a choice, they will feel high levels of intrinsic motivation and sense of self. These are the perceived benefits of having agency. However, after a while, these feelings will level off and decline. More choices imply greater responsibility for decision-making, and the ability to cope with this burden cannot rise forever. Psychologists explain similar processes in terms of the cognitive load which occurs when people have many options to choose from (Hogarth, 1987). Our capacity to

Agency

81

process many stimuli at once is limited, and so is our capacity to enjoy the positive feelings attached to feeling in control and sense of agency. The mental price of choice is inexorably linked to time, to the chronological time that shapes attitudes of individuals and society as a whole. What was so evocative for me in researching the agency hypothesis was the time dimension in children’s studies where agency has been historically viewed as a static issue. An old, Rousseaunian view of childhood is that all human beings are born free and imbued with agency, but that society puts them in chains. From this Romantic viewpoint, an inevitable dip in agency occurs as soon as a child starts participating in the social and civic life. A more contemporary view on children’s agency is that it is not always society or adults, there are also material and immaterial resources, such as school curriculum or a particular software, which can constrain a child’s agency. The golden question is: “how to nurture and sustain optimal levels of agency for children and adults?”

Optimal Levels of Agency The question of optimal agency gives rise to one of the deepest concepts in personalization: personalization is not linear. While more agency indicates more personalization, there is a point where personalization drops and converts into pluralization. The thresholds will be different for each individual, but the formula for optimal agency is the same for all: the sum of agentic personalization needs to be greater than the sum of personalization generated by others (Note 3.10 has a formula to explain this in relation to the P–P Balance). Given the P–P Balance (remember the Law of Enantiodromia from Chapter1) where the two opposites are each other’s extreme, optimal levels of personalization are mirrored with optimal levels of pluralization. Having high personalization levels means having high pluralization levels too. So, for example, excessive selfie-taking (a personalization practice) is linked to extreme sharing (a pluralization practice). Smart mobile technologies have increased the possibility for personalization to be executed without individual or collective choice and control. But when we remove agency from the P–P process, we reach extreme

82

The Future of the Self

Fig. 8.  The Relationship between Agency and Optimal, Minimal and Extreme Levels of P–P.

levels of both personalization and pluralization. This is precisely because agency behaves in a sinusoid fashion with rises and falls, which cut across P–P. This graph not only shows the obvious point that optimal levels of personalization lie between the two extremes, but also a less obvious point: agency falls down when P&P reaches extreme levels. It follows that optimal personalization executed well and precisely for each individual requires investment from both the individual and others. When the individual or collective investment is too costly, the tipping point occurs. There are millions of years of evolutionary evidence of such periodic tipping points when a dominant narrative (instantiated in a political system) is dropped in favor of another one (Gladwell, 2006). While I don’t think we can describe an entire era with one adjective as either personalized or pluralized, it is worth noting the P–P tensions in the current design and current discourse about individual freedom and children’s agency. I sympathize with data scientists and protection lawyers who have to answer urgent agency-related questions in relation to AI

Agency

83

technologies, while the public discourse has for a long time treated the agency question with the simplistic yes/no dichotomy. In the case of children, we need to ask, of course, not just who has control over their personal data (children themselves, parents, teachers, social workers, governments?) but also for how long, in which contexts, for which purpose, under which type of consent, etc. For us, personalization researchers, such micro-questions are the daily bread and butter but for many policy-makers, even simple rules such as the cut-off age for signing up to social media is a headache, despite the same software being globally available (e.g., in 2019/2020 you could find cut-off points at 16, 15, 14 and 13 years in European countries, and at 13 years in USA). The difficulties in obtaining the optimal levels of agency (and their cut points through the P–P balance) are comparable to the centralization/decentralization tensions that have been historically institutionalized in the political governance of societies and accumulated in design. In the twenty-first century, the tensions resurface in discussions about centralized and decentralized data solutions. Transparency is the moral mantra of individual data management, as is the notion of a society of sovereign individuals who demolish companies sitting on a gold mine of personal data. Technology futurist Nova Spivack (2013) predicted that the design techniques used by Web 2.0 operators will be replaced by a more individually controlled, decentralized Web 3.0, which operates with open blockchains and privacy by design, with data owned and managed by individuals (Note 3.9). My personal future prediction, based on the agency hypothesis, is that in the second half of the twenty-first century, design emphasis will be on decentralized systems and collectively driven vertical structures. Evidence of this trend is already available with companies that develop their own ethical advertising platforms and harness collective innovations – if you are not familiar with Ravelry or Kickstarter, they are good examples of the collective power of community design (Note 3.4). However, given that centralized and decentralized systems have different purposes, the power of the collective can dwarf technology giants (and their concentrated power in personal data ownership) only in some areas. The (de)centralization efforts are embedded in social relationships (think of the many

The Future of the Self

84

private tech contracts to politicians), so they will vary in relation to context. Perhaps pluralization principles and centralized design will dominate the 2,050–2,100 educational design. At any rate, the final solution to the entangled issues summarized in this chapter will need to be more than purely technical. It will need to be a combination of decentralized and centralized systems for data processing and such a combination will need a re-think of the underlying principles of how the Web 2.0 operates. The instantiations of agency in the current, highly personalized, Internet, is very different from what human rights organizations (see Amnesty International, 2019) and privacy scholars have been advocating for. Some commentators found it puzzling that during the Covid-19 pandemic, there were strong privacy concerns about “coronavirus apps” surveilling the population and at the same time, huge enthusiasm for the use of Facebook or Instagram that contain known data privacy holes. For personalization scholars this was not puzzling, but the effect of the privacy paradox.

The Privacy Paradox In the field of marketing and economics, individual choices are watched with respect to economic returns and in relation to the benefits/costs ratio. If people were rational beings, they would be making their choices after carefully weighing up the costs against the benefits. But given that we are not (always) rational, it is more realistic to think of choices in relation to the thresholds that tip over to either higher costs or higher benefits. From the vantage point of digital personalization, these thresholds are sub-optimal in relation to privacy. The gist of the privacy paradox is that, on one hand, individuals report high concerns about privacy, but on the other hand, they reveal intimate details about themselves for a small return of investment. They voluntarily enter personal details onto a site promising say $3 in return, but they are unlikely to say that the information about where they live is worth $3. When it comes to privacy we say one thing but we do another thing, basically. Personalization compounds the privacy paradox. You are unlikely to give your family photos and

Agency

85

transcripts of your conversations with friends to a complete stranger, but you give it voluntarily to Facebook. When you then get a personalized recommendation on your Facebook wall, you find it scary. There is a complex combination of cognitive biases and the previously mentioned persuasive design that drives these behaviors (Waldman, 2020). Market research shows that personalized design not only enhances consumers’ interaction with online retailers, but also heightens their privacy concerns (Aguirre, Roggeveen, Grewal, & Wetzels, 2016). To psychologists, the privacy paradox and its accompanying contradictory behavior is not interesting because individuals share personal data in return for commercial perks but because when you provide your personal data, you reveal parts of your identity. When others know about you, you are visible to them and when you know you are visible, and are being watched, you behave differently. This association is usefully applied in prevention programs. For instance, when people know that they are being personally watched by their bank, they are less likely to cheat (Schoar, 2012). Moreover, when people know they are being watched, they perform differently on learning tests and tasks. This difference in human behavior is a long-researched phenomenon in educational psychology called the Hawthorne effect. According to the simple version of the Hawthorne effect, if individuals know they are being watched they make a greater effort to perform well. According to the more elaborate version of the Hawthorne effect, if individuals know they are being watched, they develop the skill to watch similarly over oneself to perform better. This can be performance not only on end-of-the-year exams but also in non-educational contexts, such as social media. There is substantial variability in online behavior between anonymized and non-anonymized groups on social media (Zhao, Grasmuck, Martin, 2008). Depending on whether or not a user’s identity is revealed, individuals choose to portray their “now selves,” “ideal selves” or “possible selves” and also “tabooed and suppressed selves.” We are only scratching the surface of the identity changes introduced by personalized Internet. In the absence of empirical data, we need to adopt a framework that incorporates insights from solid theories and that is open enough to accommodate children’s

86

The Future of the Self

agency in personalizing a world that is inescapably shared and collective. To structure our thinking on agentic personalization for Web 3.0 and beyond, there are five words, all beginning with the letter “A”, which provide the vocabulary for optimal levels of personalization. The 5As of Agentic Personalization The 5As are: Autonomy, Attachment, Authenticity, Aesthetics and Authorship (Kucirkova, 2017). These five aspects tap into children’s motivation, creativity and empowerment. The presence or absence of agency in these five As determines whether personalization is bottom-up, led by users (children, in our case) or imposed top-down by companies and adults. Authorship relates to children’s own content when agency is present. However, when agency is absent, authorship turns into consumption. Without agency, children’s Autonomy in making their own stuff turns into dependency. Without agency, Authenticity of genuine personalization fades away into counterfeit products. In agency-absent models, digitally perfected Aesthetics are paraded as superior to hand-made art. Personalization provided by algorithms does not foster Attachment but a desire to dominate. In contrast, personalization led by an individual’s desire to produce something of their own is underpinned by the desire to belong to other human beings. In 2020, the 5As can be easily delivered through automatic and algorithmic personalization systems: Autonomy has increased with robots and AI-powered tools that automatically personalize online interactions. Attachment to self-selected groups has accelerated in a world uncertain of its own truths, as experienced in the collective human migration of the 2000s. As you will read in the next chapter, Authenticity has risen to the most evoked tagline of the travel, entertainment and glamor industry. In the past two decades, the obsession with Aesthetics has grown so much in importance that even the fruit and vegetables consumed in European countries needed to “look good” to be accepted by supermarkets (and a third has been discarded for aesthetic reasons, Porter, Reay, Bomberg, & Higgins, 2018). Of course, agency is not a magic wand that

Agency

87

will make all problems of extreme personalization disappear, but a focus on the 5As of agentic personalization bridges individualization and the equal humanity of all individuals. Early in this chapter, I noted that a powerful agency model contains both self-determination and belonging to others. And so it is to the self-determination/belonging dynamic that we must turn now to understand why assigning blame to technologies in propagating extreme personalization practices would be wrong. In the twenty-first century, individuals have far more choices than generations before, partially through the online world and partially through the social structures enabling mobility and opportunities. At the same time, these choices are constrained by wider changes triggered by global climate change or the lobbying force of a small number of billionaires. This creates a melting pot for an individual’s sense of self. On the one hand, the self is empowered and agentic in the choice of personalized services – but on the other hand, the self is controlled by opaque algorithms. As such, we have lost a sense of individual and collective belonging. An excessive use of personalized services is one manifestation of the loss. Since the rise of the personal data economy, the U shape of agency has thinned into a line with exponential growth toward a “me” world, then swung to hyper social engagement online, then back to individual agency again. Given that algorithms are increasingly combined with AI and through machine learning produce their own data about us, we are both the agents and slaves in these personalized bubbles. In the next chapter, I therefore return to agency with an eye toward acceleration in personal and collective identities in the early 2000s. To conclude, as more and more algorithms harvest parts of your and my “self,” we ought to remember the bigger issue of power in personalization. The traditional culture of supremacy in top positions (often typified by White young urban men) is reflected in the products that companies develop and market to us. From this perspective, agency is an essential mechanism for resisting unquestionable authority of power-hungry individuals. Anthony Giddens, one of the most prolific sociologists, wrote several books about the constraints imposed on agency by societal structures. He also acknowledged, however, that any structure “only exists in and

88

The Future of the Self

through the activities of human agents” (Giddens, 1989, p. 256). The disproportionate allocation of power to a few decision-makers is untenable in a progressive democracy. We must remember it is a result of the actions of all of us. The speed at which the swings in personal and collective agency occur can be lethal for a sense of who we are. The next chapter describes in detail the societal processes with their multiple ramifications for agency so that you, my reader, can identify opportunities for change.

4 ACCELERATION

When statisticians make inferences, they perform a power calculation with the data immediately available to them. Historians know that there is no test or statistical comparison that we can make on the living present, for we cannot know the causes of the experiences we live right now. In the twenty-first century, we are so immersed in technology-mediated lives that it is difficult to assess the extent to which we are passively participating or actively personalizing our cultures (Hobbs, 2018). What we can do is to precisely articulate the symptoms of societal developments and point out patterns. In this chapter, I attempt to do so with the question: “to what extent is the first half of the twenty-first century an era of extreme personalization?” As you may have gathered from the previous chapters, I do not see personalization as a static phenomenon confined to a timepoint. I thus begin my account with a consideration of one of the perennial drivers in human ­history: the thirst for power. PERSONALIZATION AND POWER Power manifests in personal lives with dominant partners who direct actions or in working lives with controlling bosses who micro-manage their employees. In globalized economies, power manifests through market movements: fast-food chains crowd out independent food outlets in the high street and Amazon puts

89

90

The Future of the Self

independent book sellers out of business by pushing down prices. Personal information and personal data, more broadly, give power to individuals and collectives. If you buy the idea that data are the new gold, then Google and Facebook are the most powerful companies because they harvest, package and sell personal data. The hierarchies that power generates are deeply ingrained in human nature (Note 4.1) but they are upheld societally by the values that we live by. If you are a techno-enthusiast, then you are likely to position technology as the solution to the problems of humankind, including overpopulation, aging or climate change. If you would rather see the power in people’s hands, then you might see the so-called “laborsaving” technologies as not a replacement for, but rather a repair of, broken economic, social and environmental impacts. The dominant narrative in the 2000s is the replacement ideology and the illusion of digital futures to which it panders. This narrative enabled smartphones to become a globally ubiquitous device and technology corporations to establish themselves as a significant lobbying force with influence in democratic elections or lockdown decisions. Just like the Italian philosophers Antonio Gramsci and Quintin Hoare (1971) criticized the ruling capitalist class which used collective cultural institutions to exhibit its power, so could we today direct our criticism at the billion-dollar headquarters of Apple, Facebook and Google. The parallels are as striking with historic palaces of kings (including the fact that while the king is there, public cannot visit the palace), as they are with the Apple “worshippers,” who hang on new iPhone releases and mass attend launch events. Technology giants place their products on the pedestal of success, not the collective identity these products stand on. Subtly but surely, they indoctrinate their users into the cult of neoliberal capitalism urged forward by the disparities between the haves and have-nots. Personalization throws an interesting twist into this: under the pretext of progressive democratization of access to ideas and goods, the individual consumer is under the impression that they are personally at the center of technologization/datafication, with the phone in their hand, and with the photos and messages that they produced. In reality, those in power are those who have aggregated masses of such personal information. While we get the impression that anyone with basic coding skills can create an app, in reality that

Acceleration

91

app’s survival directly depends on the gatekeepers’ permission to enter the app market and then to follow the rules of a hierarchical capitalist distribution system. So, from my perspective, when it comes to personal data, the game of power is played according to old rules on a new field: commercial groups and government security services hold the most precious personal data (or the most important “intelligence”). Power is essential for the discussion of personalization, but power in itself is not a variable that can be studied directly: power is embedded in relationships. A satisfactory answer to what fuels extreme personalization, therefore, must specify the correlates, mediators, moderators and causes that bring about a relationship. These are statistical terms but they can serve as useful thinking tools in a conceptual analysis. Let us begin with correlation and the question: “what is related to power and personalization?” The answer might surprise you: inequality.

CORRELATES OF PERSONALIZATION: INEQUALITY It is difficult to discuss inequality without subsuming into an ideology. I caveat this section with the admission that I follow an egalitarian account, although I recognize that inequalities are the cornerstone of great civilizations (Scheidel, 2017) and that according to some psychologists, hierarchies give our lives purpose (see Peterson, 2018). Historic comparisons show that overall and across nations, economic inequality is on the decline in the twenty-first century (Human Progress Institute, 2015). We are all getting richer – from the macro-economic perspective – but within individual countries, economic inequality is on rise (Pinker, 2018). In the Western countries, citizens born between the early 1980s and the early 2000s are gradually getting poorer, faced with rising housing prices, explosion of private rents and increasing university debts. The most visible consequences of utmost inequality are evidenced by the homelessness crisis in USA and UK cities but sharp economic inequalities are also present in India and China (Pinker, 2018). An increase in the overall affluence of all humans is good news on an individual level

92

The Future of the Self

but if it occurs too quickly, it is very bad news for the planet. In the twenty-first century, primary natural processes, including that of the extinction of species and loss of natural habitat, are moving faster than expected: extinction is happening at 1,000 times the normal speed (Boakes & Redding, 2018) which reflects the serious biodiversity crisis we live in (McCarthy, 2015). Crudely speaking, individual humans are better off but the welfare of individual animal species is getting worse because of the continuous shrinkage of wild natural spaces. In a liberal market society, recklessness toward the wider natural and social environment is swept under the carpet and individual wealth is placed on top of it. The insulating nature of billionaires’ fantasy projects (e.g., reversal of aging by Peter Thiel or preserving consciousness by Ray Kurzweil) are born and bred by the self-feeding cycle of natural resource depletion (Rushkoff, 2019). The aggressive urbanization which followed the industrialization revolution has continued in the 2000s, with air pollution levels dangerously high in the 80% of urban areas monitored by the World Health Organization. Polluted air and other environmental harms have irreversible consequences for all children’s health (Schwartz, 2004). Yet, even global pandemics have ­unequal consequences for poor and rich children. Broadly speaking, their lives are characterized by the following inequalities: the poorest children spend most of their time in indoor or crowded outdoor urban spaces, breathing polluted air and eating conventional, often genetically modified, foods. In contrast, rich children live in large mansions close to green spaces, attend private schools which provide extensive extra-curricular programs and food cooked by specialized chefs. It is easy to note the radically different environments of these children by comparing the social media posts of, for example, @ richkidslondon and @poorkidsoflondon. The super-rich children are wrapped up in couture, while the parents at the brink of poverty cannot afford their children’s school uniforms. Those who have extra cash to spare can design their own Swatch watch or bags on NIKEiD and have their initials hot-stamped on Louis Vuitton wallets. Those who are worse off cannot even choose the supplies for meeting their basic needs, such as the food they eat or place where they live.

Acceleration

93

Economic inequality can and should be controlled through regulation and political will. Brian Barry (2005) revisits inequality by spelling out the undesirable consequences of individualism and capitalism development after early industrialization in the nineteenth century. He states that the reason for endemic social problems is that system failures are being overlooked. For example, a socially just response to the US and UK homelessness crisis is not rapid housing (although of course it is a good immediate pain relief). A systemic approach prevents homelessness by intervening early and reducing the systemic structures that propagate it. Barry zooms out of the narrow focus on the benefits of personal responsibility and reminds us that given the systemic inequalities in society, choice is a sign of privilege. From the personalization perspective, it does not matter whether inequalities are innate, socially constructed or even necessary. What matters is that through the lens of inequality, personalization has a different taste for different children. The symptoms of social inequality are not only about income but also health and education, and they combine together to devastating effect on children’s lives. In a perfect world, we could personalize all children’s learning, play or healthcare equally. But the human world is not perfect, and personalizing without paying attention to inequality makes matters worse. This point is widely misunderstood by policy-makers. Millions of dollars have been invested into ­ technology-driven personalized education programs with the explicit aim of ­solving inequality. Programs that aim to provide personalized learning via laptops to developing countries or poor neighborhoods often assume that if they make children’s learning personalized, they eradicate the gap between poor and rich children. I do not mean the kind of personalized education that provides the necessary tutoring support where there is a shortage of teachers, or personalized healthcare that connects specialists to remote students or patients via tele-education or tele-health – these are positive disruptions that make expertise available on scale. What I am concerned about are personalized approaches that provide personalization with ignorance of its unequal consequences for individuals. This occurs with models built by those who have not lived or even experienced inequality and the culture that they are supposed to lift up with

94

The Future of the Self

personalization (Kraemer, Dedrick, & Sharma, 2009). I can understand where the misunderstanding comes from: personalization chimes with social justice agenda whereby equal attention is given to the rights and responsibilities of all citizens. Personalization can push humankind to ensure that more individuals can enjoy the personal freedom of choosing their education, career or religion, but this push is weighed down by the heavy baggage of ethnic, gender, economic and other historic inequalities. I hope I have convinced you that personalization can enhance or reduce inequality, but it can neither create nor completely remove it. I doubt, however, that we have a shared understanding of why it is so. I follow with some pointers on the imbroglio of correlations in regard to equal opportunities and the so-called personalization revolution.

The Beginnings of Commercial Personalization Personalized products and services have always appealed to customers. Before the advent of the Internet, sellers tailored their offers to individual clients because they knew them personally. Shops and communities were small, so person-to-person personalization was manageable. On a bigger market, it is the rich and returning customers who are addressed by their first name by the receptionist, chauffeur or retailer. But with diverse communities in large urban areas and global anonymous communities online, the authenticity of a customer–seller rapport has been lost. At the same time, given that globalization offers everything for everyone (ideologically speaking), individual customers crave the authenticity of bygone shopping experiences. To survive in the globalized shopping world, producers need to speak to customers on a personal level as if they lived in a small community. And here comes the idea of a personalization revolution in the twenty-first century. With user modeling, sellers can accumulate clusters of specific characteristics and shopping habits of individual clients. By recognizing customers with their name, a website can become as personalized as the favorite pastry waiting for you in a local boulangerie. The personalized Internet and the personalization revolution have their

Acceleration

95

roots and their most aggressive applications in commerce: personalized customer service builds rapport and customer loyalty and customer loyalty ensures market share and long-term profitability (Gommans, Krishnan, & Scheffold, 2001). The more the customer returns to the website/program/app, the more accurate the match between the service and the customer’s persona. Most important for this discussion, however, is that online personalization feels, on the surface, the same for everyone: an algorithm does not distinguish between rich and poor. While in the past specialists in the stores (buying advisors and make-up advisors) were reserved for those who could afford these premium services, in online shopping there are automated advisors for everyone’s shopping trip. While in the past only the rich had slaves and maids to jump to their commands, the modern-day equivalents of Alexa and Siri respond to anyone’s voice. In the personal data economy, everyone’s personal data count and everyone’s data are worthy of a special treatment. And here comes the but: online personalization follows this equality pattern only up to a point. When we dig deeper to identify the reasons why retailers personalize their services, we quickly realize that it is not to disentangle personalization and inequality, but to reinforce it. Yes, you can adjust the price range of the personalized shopping offers, but a lower purchase amount puts you into the customer group whose offers are less precisely personalized. This is simply because personalized goods are more laborious to produce and more expensive to acquire. Personalized products cannot be easily returned and personalized services cannot be directly transferred to another client – they are, therefore, reserved for those customers who can pay for them. Personalized healthcare is for those who can afford access to preferred doctors, specialized treatments and personalized nutrition, which is a cocktail of drugs, vitamins and supplements tailored to an individual’s defense mechanisms. The more personalized patients can make their therapy, the more they will benefit. Sure, even if you don’t buy anything, the companies are still interested in your data and send you “personalized” advertisements. Yet, we all know that ad-free Internet is for those who are used to much more precise personalization than those who stand in front of the paywall.

96

The Future of the Self

The only way around the personalization–inequality relationship is to pluralize access to personalized products and services. Digital personalized service could deliver quality at scale, both for healthcare or education, especially in countries with low gross domestic product (GDP) that face the double disadvantage of lack of expertise and lack of funds to pay for expertise. However, most countries with low GDP do not have the government infrastructure to ensure personalization for all. The digitization of products and services is unlikely to fix this. The early world wide web was conceptualized as open architecture network (Leiner et al., 2009) that would reduce social inequality by providing universal access to a greater choice of information. But choice is a triumph for equality only if the choice is fully informed either through the user’s own understanding or through external mediation. With the current version of the Internet, there is seemingly, but not actually, more choice in accessing and contributing information. From the moment the personalization algorithms entered the game, the Internet has turned into an inequality machine that filters and selects information based on an individual’s value. Whether the value is monetary or spurious does not matter – the distribution of information online is not value-free because it is ranked according to the “more is better” model. The commerce-oriented algorithms of GAFA impose “personalized” choices that standardize the diversity of human answers. Standardization allows companies better prediction, which is important for accurate services and also dangerous for inaccurate profiling and manipulation, as we have seen with fake news and online misinformation. Thus, although the Internet has democratized access to personalization possibilities, the design of Web 2.0 has reproduced the inequalities in experiencing its benefits. History taught us that when the individual and the collective legs march in opposite directions, inequality spins out uncontrollably. In a simplified account of the recent economic history, it is said that the nineteenth century was driven by coal, the twentieth century by oil and the new currency in the twenty first century is personal data (Ng, 2018). There are some speculations for the continuation of unequal personalization – it could be that with so many possibilities to produce and re-produce goods, we are ­running out of storage space

Acceleration

97

and people will store their wealth in the most personal way: inside their genes. There are already companies (e.g., Twist Ltd.) that develop technologies to encode data into human DNA. Without a shadow of a doubt, deliberate changes to DNA that treat genes as hard drives carry significant ethical implications (Doudna & Sternberg, 2017). How can we moderate this pattern and keep personal data within reasonable quantities? Moderators can be socially manipulated and, therefore, should be at the forefront of a constructive conversation about preventing extreme levels of personalization. In statistical calculations, moderators are the factors that reinforce or diminish certain relationships. I propose that the relationship between personalization and inequality is reinforced by neoliberal capitalism.

MODERATORS OF EXTREME PERSONALIZATION: NEOLIBERAL CAPITALISM AND MERITOCRACY It is no coincidence that the personal data economy mushroomed in the twenty-first century capitalism, characterized by high-­consumption and high-production. Capitalism cherishes the meritocratic principle that recompenses hard work according to “merit.” This is not the kind of moral merit that was envisioned by Aristotle or Confucius nor by Michael Young (1958) in relation to intelligence and skills free of social origins. Ethical meritocracy works only if there is sufficient social mobility. Without mobility, merit-driven rewards reach the privileged more than the socially/physically disadvantaged citizens. While as species we have become a highly mobile society with about 150,000 flights every single day, socio-economic mobility is increasingly stagnating in Western states (Chetty, Henderson, Kline, & Saez, 2013). The lack of mobility in socio-economic privilege might be less visible on polished homepages but it is clearly visible on the doorsteps of US cities. Despite the robust evidence that moving families from areas of high poverty to better-off neighborhoods improves children’s outcomes, economic mobility has been on decline across the USA for several years (Chetty, Hendren, Kline, & Saez, 2014). Meritocracy and capitalism are taken out of their ethical realm through neoliberalism. Neoliberal capitalism is a reckless version

98

The Future of the Self

of capitalism that has lost any ethical or moral principles (Sandel, 2012). Such capitalism does not propagate a market economy but a market society. While a market economy is a valuable tool for organizing productive activity, a market society is a way of life where everything is up for sale and money can buy anything (Sandel, 2012). The socio-political outcome is plutocracy, that is, politically organized wealthy individuals who use the state power for their own advancement. Plutocratic capitalism increases the possibilities for individuals in position of power to disproportionately personalize their lives (commercially, educationally or socially). When plutocrats sink their fangs into new forms of digital personalization, personal data turn into a crude quantitative marker of privilege. Masses are reduced to “big data” that can be organized by algorithms into predictable and controllable categories. Such an arrangement sets the stage for a structure, in which ranking, based on the philosophy that the latest is best, and quantitative comparisons, based on “more is better”, dominate all decision-making. Numeric rankings become the measure of success and value, rather than what the content is or how it was developed. Greatest advertising value is assigned to those who are the loudest on social media, not those who are the most innovative, wise or even interesting. Social media posts that manipulate purchasing behavior through persuasive design and AI-informed influencers become the new landscape. A meritocratic algorithm denounces nuance in favor of most “views” and “likes” (remember the “what is more” mantra from Chapter 2). A plutocratic system takes it a step further as it is set up to reward elite and wealthy individuals. Such societal structures have huge consequences for the quality of information we consume, the understandings we develop and the way we lead our everyday lives. Looking at the full scope of a capitalist society, we need to admit that the problem with the current society is not the few billionaires. Yes, some are convinced of their Ubermensch superiority but many rich people acquired their wealth through a personal sacrifice and many use their status to promote social causes. The difficulty with unethical meritocracy is that we are all culpable of propagating it, with the stories we like, click on, and the stories we live ourselves. We all participate in a spectacle that promises a better future to the

Acceleration

99

individuals who invest their maximum talent and effort into perfecting their own lives. This point was made perhaps most insightfully in Guy Debord’s (1994) critique of capitalism, titled The Society of The Spectacle (originally published in 1967). Debord provides insights into facets of existence which fittingly capture the 2000–2010s: fake and false images of self are multiplied through social media that enact a false reality. Such “spectacle” is marketed and served to each individual, but just as in a spectacle, it is merely a representation of reality, it is not the reality. Debord thinks that the most glaring manifestation of the spectacle is mass media (the book was written before the rise of social media). The only way to resist the spectacle is to resist the allure of a personalized reality. Applied to the current situation, the resistance would mean to stop the use of online technologies because, as I explained in the previous chapter, Web 2.0 is a personalized Internet. But hand on heart, who can afford to be disconnected in the modern world? We all spend increasingly more time with our personal devices because we increasingly delegate parts of our self to them: our work, entertainment, communication with family and friends. Corporate CEOs and celebrities make the headlines now and then when they announce they quit a social media platform or engage in a prolonged “digital detox.” They can afford to slide the privacy doors and unwind in their quiet world because they are cushioned in monetary security. If a Deliveroo driver, who works on commission, disconnected from her phone, she would lose a potential client. The meritocratic ideology has resulted into an unequal experience of personalized services, and a corporate culture of super-rich. In addition to billionaires, the next tranche – the millionaires – form a sufficient sector of society to exemplify the cult of inequality, characterized by individualistic and self-centered lifestyles. In Lauren Greenfield’s poignant documentary “Generation Wealth” a sixyear-old American actress and reality television star, Eden Wood, proudly proclaimed that her favorite princess was herself. I point again to the collective contribution concerning the unequal distribution of wealth: the Western acceptance of individualistic values gave green light to stars and celebrities to regularly and extensively document their hedonist lifestyles on social media. The disproportionate amount of attention dedicated to the lives of lords, sheikhs

The Future of the Self

100

and CEOs, documented by wealth correspondents in traditional media wouldn’t be there if we were not reading them. Remember: the best way to reduce the popularity of this “spectacle” is to reduce the demand for it. Jo Littler’s (2017) analysis of meritocracy is an invaluable read for all those who want to understand how the personal data economy (as well as housing and other industries in the USA and UK) have descended from meritocracies into plutocracies. Here, the social and political powers are assigned to a few mega corporations which dictate the rules of play. The game is an old game of privilege where marginalized minority groups, such as ethnic minorities, seek to claim their place in spaces traditionally governed by male power (Puwar, 2004). In doing so, they experience deep forms of injustice and are often compelled to engage in new forms of political resistance (Tyler, 2013). While some forms of resistance, such as the Me Too movement, showed that personal experiences can have consequences for the distribution of power, they also showed the deeply ingrained class and gender biases that reproduce power relations in modern society (Skeggs, 1997). Unfair and non-transparent algorithms are, in my interpretation, a reminder of the power of positionality (Maher, 1993). Positionality is a feminist term to capture the importance of reflecting not only on what knowledge is produced but also who the knowledge producer is and what sociopolitico-economic power structures govern this knowledge production. We must not forget positionality in discussing algorithms, digital personalization and their wider role in propagating personalized realities. It might help to reflect on reality. Reality is a time– space entanglement and I therefore justify my charge by outlining how neoliberal capitalism relates to personalized time – space.

Personalized Time You may have heard that the twenty-first century capitalism is “Capitalism Without Capital” with highest spending going toward branding and software rather than machinery or buildings. Customers pay for personalized experiences they want to have their individuality reflected in. In consonance with the personalized

Acceleration

101

realities permeated by capitalist values, globalization opened the doors to international markets and massive consumer base. In a capitalist mindset, personalized time is considered a commodity, “For time like money is measured by our needs” (Eliot, 2018, poem). Sociologists know that time is not experienced equally, despite the illusion of all clocks following the same hours and minutes (Leaton Gray, 2017). Even in countries with a national health service, such as the UK, individuals with private health insurance get their appointments scheduled more quickly with minimal waiting time. Children from poor neighborhoods have their time taken away by social media more than those who have a solid alternative in extracurricular activities to which they are driven in their parents’ cars. Public transport takes more time and Snapchat speeds up time if these children are bored or want to take away their attention from harrowing issues that often arise in the communities where they live (Leaton Gray & Phippen, 2017). These children are more likely to receive advertisements that are not educational and download games that deceive them into spending more time online with their persuasive design. Sociologists would wager – but they cannot know it for certain – that the capitalist industry thrives on appropriating the individual’s time. If you can entertain this possibility, then you may have noticed that employees of big corporate organizations can enjoy the company’s free gym, cafeteria and bar. The employees do not pay in monetary terms, they pay with their attention to what the company provides them with (I do not mean here enhanced child-care services for highearning workers – these should be provided for all-but the “free” services that expect corporate loyalty in return). Time spent on company premises is time not spent at home or elsewhere of their choosing. This “clan-like” philosophy translates into the design of personal smart devices. On the surface, personalized design with instant and constant alerts gives individuals more autonomy in the management of their “own” time. But deep down, the design colonizes private time. Even if you do not use social media, you are likely to use services that follow the model of personalized time. Since the Internet started, services that needed to be previously scheduled in advance, such as watching favorite TV shows or attending a lecture, can be

102

The Future of the Self

experienced anytime online (Keating, 2012). Subscription-based ondemand services (such as Netflix for films, Spotify for music or Scribd for books) removed advertising breaks that used to be reserved for the shared experience of a large segment of population watching the same film at the same time. Similarly, services that needed to follow a generic schedule of the food or transport industry can be in the capitalist society ordered at the point of demand and personalized to one’s preferences: if you have the capital, you can have your meal, taxi, entertainment exactly when you fancy it. The capitalist invention for establishing such monetization of personalized time is the so-called Uber economy or gig economy (sometimes mistakenly called “sharing economy,” Note 4.2). Services on demand, whether it is accommodation, cleaning or hairdressing, are very convenient for the customer and are a great way for earning extra income for the provider. But with Uber, Airbnb, Etsy or Deliveroo, the one who benefits most is the platform owner. Similar to freelancers and those on zero-hour contracts, the gig workers need to trade flexibility over their personal time for their individual rights (e.g., no right to paid sick or maternity leave). To increase their profits, the employers reduced their liabilities, especially in countries that have fewer social benefits assured by job security legislation. For those who rely on the gig economy as their sole or primary source of income, the customer’s flexibility is a form of capitalist exploitation. A capitalist society without a social welfare model replicates the problems of an old industrial capitalism: it appeals to personal liberty without the provision of community obligations and individual security. Coupled with unfair taxation and ineffective use of tax revenues, it turns into a disastrous social policy. The consequences of such economic models directly escalate to home environments. A leading researcher in the field of family/work life balance, Ellen Galinsky (1999) shows that child’s well-being relies on active implementation of childcare policies to reconcile production and women’s employment. The gig economy is a slap in the face of female employees whose time is experienced differently because of biological differences or childcare demands. In brief, the gig economy, as an instantiation of neoliberal capitalism and the meritocratic philosophy, propagates disadvantage and offers inadequate reward for the most precious resource parents can give to their children: their time.

Acceleration

103

Time cannot be counted like beans in a jar, yet, the question of how much time should children spend with individual activities continues to perplex parents (and challenge academics). I cannot discuss the topic of time without mentioning one of the most hotly debated topics in relation to children’s use of technology: “screen time.”

Screen Time Surveys with parents show that children growing up in the Global North countries spend increasingly more time on and with screens, from an increasingly young age. Adults are, and adults should be, concerned about the time children spend with screens. But as much as some media commentators would like the screen time question to be resolved with a universally agreed recommended length of time for everyone, the actual solution is bound up in social and economic systems. Consider this socio-cultural perspective: it is a shared Scandinavian understanding that screens rob children of time. Technologies schedule children’s activities and compromise their imagination, which is considered timeless (Jensen, 2017). From an economic perspective, it is considerably cheaper to cater for children’s education and entertainment through screens than by driving them to various after-school activities (e.g., it is cheaper to view Velázquez on phone than to visit Museo del Prado). The difference in experience is significant but not everyone can afford a physical experience. Shaming parents for letting their toddler use a tablet would be ignorant of the socio-cultural differences between families. Scientists know that targeted interventions are more sustainable than non-selective guidelines and the same applies in the context of guidelines on children’s use of screens. Several scholars/thinkers (David Kleeman, Sonia Livingstone and Jackie Marsh) have attempted to reframe the screen time debate by suggesting that the term is unhelpful as it suggests that time is more important than the content and context of technology use. Not everyone would agree, however. There is a lot of medical and pediatric research that divides screen time into good and bad, passive and active and treats it as a static variable that can predict

The Future of the Self

104

a number of health outcomes such as obesity (Lanningham-Foster et al., 2006), sleep disorders (Hale & Guan, 2015) or depression (Kremer et al., 2014). Professor Sonia Livingstone has been a strong voice of reason in interpreting such “screentime evidence” by reminding us that correlation is not causation (i.e., if a measure of children’s time spent on iPad is related to a measure of their feeling of loneliness it does not mean loneliness is caused by iPad) and that piling up confirmatory evidence is not the best way to test a hypothesis. Indeed, there are substantial differences in results depending on how we measure things, with drastic consequences for different ethnic groups (Curran, 2020). To understand the pros and cons of children’s lives with technologies, researchers need to combine traditional measures of established outcomes (such as health or learning effects) with new measures of technology engagement. While time spent on watching linear TV programs may have worked in the 1940s, it is an unsuitable measure for technology that is ubiquitous, serves the purpose of entertainment, learning, communication and more. The situation gets even more complex with personalized time spent on screens that offer feedback tailored to the child, opportunities to create their own content and connect to friends of their choice. Any arbitrary guidelines about how much time children should spend on such identity-­ defining activities would be an insult to their agency. This is why we have been arguing that to answer the question of optimal screen time, we need to rephrase it and abandon the focus on the dichotomy of benefits/harm in relation to time because “Calculating the incalculable puts unnecessary pressure on parents, who end up looking at the clock rather than their child” (Kucirkova & Livingstone, 2017, online). If you still need convincing that screen time is not a helpful concept then maybe we should talk about “screen-space.” In what follows, I lay out the personalized space afforded by modern technologies, which can be enjoyed with or without screens.

Personalized Space Capital buys not only more private time but also more space. In the past, kings had castles, while the modern rich have mansions.

Acceleration

105

Today’s millionaires have private lounges at entertainment venues and extra legroom on planes or trains. The inequality in personalized space bred by capital is also reflected in the production of personal devices for mass consumption. As individuals have become more affluent, TVs have replaced shared cinema spaces, and radios have replaced shared concert halls. The more commodities individuals have, the less they need to participate in shared public spaces and the more they can personalize their own space. The Handbook on Wealth and the Super-Rich (Hay & Beaverstock, 2016) is an academic exploration of the patterns you may have noticed when browsing Instagram or celebrity magazines. Openly exhibited not only by the urban US culture, but also exported to billionaires in China, India and Russia, the 1,500+ billionaires currently living across the world consume bespoke products in exclusive spaces. When technologies personalize time and space at the expense of pluralizing it, identity changes ensue. Consider the example of maps, as a clear and concrete representation of a shared space. For centuries, maps required you to find yourself in a collective space. You needed to look around to identify the environmental markers around you and match them with the depiction on the map. Today, your online map starts with “YOU are here”; you are located in relation to the small blue dot that moves with you simultaneously as you explore the space. The individual does not need to locate himself/herself: orientation in online maps starts from the individual. The map is automatically personalized (Kucirkova & Mackey, 2020). This is a giant conceptual change. Similar conceptual change happened to time: clocks used to be shared (e.g., on church towers) and their time unamendable. Today, individuals follow their own digital clocks, synchronized to their own movements across the globe and work/personal priorities. In previous eras, personalized time and space were only available to a few privileged individuals. In the twenty-first century, time and space are personalized en masse (Fig. 9 illustrates this pattern in a very simplified visual). The personal data economy accommodated by the technology industry have democratized access to such personalized realities. I return to the example of the gig economy as it elegantly illustrates how we all participate in personalized time–space served by

106

The Future of the Self

Fig. 9.  A Simplified Account of the Emphasis on Personalized Time and Space in Different Eras.

meritocratic capitalism. Most popular on-demand services offered under the gig economy are delivered in private spaces: a hairdresser comes to the millionaire’s home, so does the cleaner or gardener. If the worker cannot come, an app provides the client with recommendations of “similar” cleaners who can replace the worker. It would be naïve to expect a socially just model of economy based on privileges tied to responsibilities, but there is something seriously wrong with treating workers as disposable goods who can be flexibly swapped depending on the client’s demands. Dating apps are another example of how personalized design puts wealthy individuals into a position of power. In case you didn’t know, free dating apps are for casual and quick acquaintances, while premium services are “for those serious about finding love.” A collective acceptance of trading romantic love according to monetary privilege leads to a model where partners are matched according to not only psychometric characteristics (as it is currently possible with most matching websites), but also according to genetic compatibility (Kucirkova, 2019c). In such a model, love based on a belief in happenstance is a nostalgic stench. With extremely personalized time and space, there are losses on all fronts, rising incrementally for all individuals. This is because

Acceleration

107

the more personalized the time and space of an individual are, the more constraining they become (see Andrejevic, 2003). Celebrities, whose face is owned by the public, have their movements controlled by millions of fans’ and paparazzi’s lenses wherever they move. The push for appearing perfect and authentic on social media creates a pressure cooker for our minds. Perfection is predicated on limited exposure and limited radius of movement. This target of perfection is impossible to achieve with constant surveillance. Every generation battles the capitalism–socialism ideals and meritocracy–democracy tensions and this book’s aim is not to offer solutions to the ills of capitalism or meritocracy (Piketty, 2018 does a very good job of this). What is clear is that that personalization mediated by meritocratic capitalism weaves inequality deeper and deeper into its fabric. You might be thinking that if the capitalist version of personalization is exploitative, then a viable alternative is a socialist version. Or perhaps that if a meritocratic ideology propagates inequality in personalized realities then we should revert to class and privilege-based systems. Oppositional discourses get flesh-and-blood support in crises, with short-term impact. A more worthwhile step would be to consider the mobility possibilities between the by-products of capitalist and communist economic solutions. You will recall from Chapter 1 that mobility is what keeps in check personalization and pluralization, the two “Ps” approaching each other to form a “B for balance.” The P–P balanced solution lies not in swinging the personal data economy to the other extreme of collective data economy – instead, mobility can blend the two together. We do not have such a blend yet. To create it, we need to know the constituting parts of each and how fast we need to mobilize them. The first step in this identification is finding out the mediators, which explain the relationship between two variables. From my psychology perspective, I am most interested in the mediators that are related to identity and the psychological core of self. I propose a perhaps counterintuitive mediator but consistent with the model of personalization that I have proposed so far: identity migrations. I divide my account into forced (externally imposed) migrations and voluntary (intrinsically motivated) migrations. I chose the word migration to map onto the geographical

108

The Future of the Self

and geopolitical changes that occur in parallel to personal transformations and that alter collective and individual realities.

MEDIATORS: COLLECTIVE AND PERSONAL MIGRATIONS Migration refers to the movement of people from one group to another, or from one stratum within a group, to another stratum. Migration in its pure sense is neutral – when something moves from point A to point B it can have both positive and negative consequences. For postmodern philosophers, volitional (or in the language of this book “agentic”) migration defines one’s sense of self and sense-making (Deleuze & Guattari, 1987). However, the forced movement of two million refugees between 2015 and 2016 was driven by the life-saving necessity to escape from Syria, Afghanistan, Myanmar, Somalia and South Sudan, wrought by war conflict and poverty. Europe and USA have a long history of migration but in the first half of the twenty-first century, an unprecedented number of children (31 million in 2015 reported by UNICEF, 2016) grew up in countries different from where they were born. Many children have lost, or they witnessed how other children had lost, their friends and relatives when crossing the Mediterranean, the Mexican border or the British Channel. The refugees from wartorn countries had no choice other than to flee the country they used to call home. Both the US migrant crisis which peaked during the Trump administration and the European migrant crisis which peaked in 2015 have impacted the core principles of democratic nations. The problem had become too complex to be solved by means of a technological solution. Modern technologies imposed as many new challenges as they solved. Phones enabled migrants contact with relatives and access to information, but they also contributed to their vulnerability to organized trafficking and false promises of better lives delivered by social media. Forced and accelerated migration occurred in the 2000s for varied reasons and was experienced in fundamentally different ways for different children. For instance, the economic and social consequences of adapting to the climate change and its more frequent weather-induced disasters were experienced more acutely by

Acceleration

109

children in target zones. Similarly, the international recession and rise in crowded urban spaces have impacted the migration of children differently if their parents had suffered a job loss than if they had to move with a generous employer relocation package. Despite these differences, the shared sentiment for both newcomers and citizens of the receiving countries was the sentiment of change to their local knowledge of self and others. In 2017, 50% of Europeans reported they felt like a stranger in their own country (NpfE, 2017). In urban spaces, the cohesion of small communities who used to share history and physical space got replaced by a metropolitan heterogeneity. A metropolitan heterogeneity with social, economic and religious migrants, heightened everyone’s sense of otherness. When faced with interpersonal otherness, the human brain needs to work out whether a new situation constitutes a threat with the need for protection, or is a new opportunity to be explored courageously. In the first two decades of the twenty-first century, a significant proportion of Western voters experienced terrorist insurgencies which have shaped their perception of others. Without an opportunity for prolonged cohabitation with individuals of a different ethnicity and origin, the human mind displays a bias toward the fear of the other (Banaji & Greenwald, 2016). Fear of the other is alleviated with a microworld personalized to “self.” The global changes in local communities intersect with a reduction of intergenerational co-habiting and learning from each other (Heydon, 2012). With little time to adjust to the community changes brought about by forced migration, intergenerational divides have deepened and families have become fragmented. Austerity has exacerbated conflict in urban areas, which has also had an impact on domestic abuse rates. For many single parents this has resulted in homelessness, particularly in states that have little or no funded social welfare programs (Mallett, Rosenthal, & Keys, 2005). The parallels between the lack of national support and individual revolutionaries in the nineteenth century and the gang-related violence triggered in London, Detroit, Los Cabos and other cities in the 2000s are striking (Mishra, 2017). While in statistical terms, violence has historically decreased (Pinker, 2012), in real terms, it has evolved into new forms such as cyberattacks or environmental destruction

110

The Future of the Self

(Antonelli, Hunt, & Fisher, 2015). In addition, the failure of national and international bodies charged with defending democratic values empowered authoritarian leaders to systematically defund and denigrate publicly funded regulatory and growth-fostering bodies (court of justice, free press, education and healthcare, see Albright, 2003, Note 4.3.). Traditional institutions, which were in desperate need of reform but with little cash and know-how to do so, paid lip service to rising authoritarianism in the USA and isolationism in the UK. Both hard right- and left-wing parties exploited the immigration issue to gain votes: the ruling parties in the so-called Western democracies became averse to diversity because they were insecure in their own homogeneity. In a divided society, both the ruling and opposing parties needed to promise a big change to convince their voters. Contrast-driven elections are never good news for a society, and less so for the holistic development of children. Indeed, one-sided political choices fuel one-sided educational policies and disrupt learning continuities. What is more, the lack of multi-dimensionality in the political arena is a fatal ingredient in times of austerity. In the 2000s, childhood poverty in developing countries stood in sharp contrast to the amount of wealth amassed by individual tycoons around the world. In a highly volatile macro-world, individuals crave the stability of their own micro-worlds. These large migration-related factors are, in my view, the reason why personalization reached extreme levels on the collective level in early 2000s. Concurrently with massive demographic shifts, the first two decades of the twenty-first century have seen accelerated global voluntary displacements of people in pursuit of work, adventure, relaxation and enjoyment. Global business travel has increased steadily since the 1960s, expanding the transnational movement among business partners, distributors, suppliers and customers. The ability to arrange remote meetings has had minimal impact on the value placed on face-to-face meetings in business life and jet-setting across the world has been highly in vogue in the business world (Derudder & Witlox, 2016). Furthermore, with budget airlines and low-cost holiday agencies offering affordable travel packages, leisure travel to foreign places has become more democratized. The lockdown measures during the 2020 public health crisis produced substantial economic and business losses because they were sudden

Acceleration

111

and because they were applied to a system that relied on increased migration (traveling) habits of the worldwide population. Whether you see digital solutions as a response to the “portable self” or the portable self as a consequence of digitization is a chicken-and-egg question. My argument here is about the extension of the agentic personalization concept explained in the previous chapter. One of the 5As, “Authenticity”, became the new buzzword for tourists and travelers seeking immersion into novelty. Authenticity was in the 2010s defined by the absence of others. Tired by globalization and its predictability, the travelers sought the thrill of authenticity in travel experiences uniquely crafted for them. In a highly interconnected world, with reviews and tips on every restaurant and tourist attraction at their fingertips, the modern travelers sought out the unexplored and mysterious trails. Personalized travel consultants, planners and itineraries replaced mass-trodden paths to bring some sparkle into travel. In 2016, the UK leisure market was worth £117 billion in revenue and was growing nearly twice as fast as the retail sector (Deloitte, 2016). With personalized offers for almost all holiday memorabilia, individuals self-­ determined their experiences through their selected travel paths. I am generalizing here to connect to the notion of the “new global nomads” in 2010s, with large groups of adolescents choosing to travel and learn about the world through direct, personal experience (Richards, 2015). They traveled to disconnect from their familiar environments to re-connect to themselves – a transformation that can happen with a spiritual journey too. With backpacker journeys, the travellers intended to go back home, so on a psychological level, they underwent temporary disguises rather than deep identity changes. But given that leisure trips became more affordable and thus more frequent and accessible to larger sections of the population, more individuals could temporarily experience the identity spiels enabled through personalized travels.

Personal Migrations It might appear conceptually daring to link the rise in migration on a geographical level with individual migrations on a deeply

112

The Future of the Self

personal level, but collective changes do not happen in a vacuum. Longer life spans and progress in reproductive health have offered young and old alike more opportunities to experience different versions of themselves. For some, this included starting a family or re-training and entering the job market in a new capacity. Changes in parent identities and new social arrangements have directly impacted family lives (Connidis & Barnett, 2018). Depicted vividly and truthfully by Maggie Nelson in her memoir “The Argonauts,” adults migrating from one gender to another (or refusing to commit to either) were in the 2000s not an exception but simply another gender category. Changes to biological markers were paralleled by socially enacted gender choices. In many progressive states, gender neutral spaces were considered to be more democratic than those that separated children’s clothes into boys’ and girls’ sections, or that did not allow for boys to be princesses, or for girls to play with robots. Gender norms fluctuated hand in hand with changes to traditional family structures. Significant changes in the ways families were started and formed (lesbian couples using donor sperm, straight couples using a surrogate, single women adopting or gay couples fostering) and rising proportions of divorced families, have had profound implications for dynamics at home. This was not about “performing” gender in unisex salons, but about a significant proportion of children growing up with new models of parenthood. Extreme biological interventions went in parallel with radical social changes, as illustrated by, for example, personalized marketing of genes and research into babies born through artificial wombs (Kleeman, 2020), and legalization of polyamory as a valid form of marriage in some US states. As the parents of Millennials were opening up to more plural religious ideas, to co-habitation with different ethnicities and the gender revolution, they also jumped on the treadmill of higher expectations in interpersonal relationships. Biological anthropologist Helen Fisher makes a valid point that higher expectations had repercussions for the pressure partners put on each other and for the level of perfection sought in prospective partners – and also the pervasiveness of disappointment that followed (Note 4.4). These personal migrations are part of the explanatory background, as it were, to the heightened interest in micro-worlds

Acceleration

113

governed and controlled by the individual. The trend manifests in all kinds of behaviors, among young and adult: one might apply this thinking to the rise of the ripped teen-body and extreme perfection-seeking among gym-obsessed urban youth. Data-­ ­ processing technologies facilitate diverse micro-worlds and together with social media offer a fertile ground for people to portray themselves as somebody else. The design of the platform (e.g., anonymous vs verified users), and its main purpose (dating, commercial or leisure) have been found to be directly related to the extent to which users display their true, real or hoped-for selves (Zhao et al., 2008). Sure, Instagram stars know all the make-up tricks to look their best online but for anyone else, the possibility of choosing an online persona or avatar has broken life-imposed restrictions on self-representation. However, lest not forget that the resources for “identity chameleons” were in the 2000s as available online (virtually) as they were offline (physically). A boom in cross-dressing, hair styles and makeup kits allowed for rapid and temporary age, skin color or gender make-overs by those who sought to play with every look under the sun. On a completely different level, sex reassignment surgeries and low-cost plastic surgeries facilitated body changes with no return journey. If an individual had the resources and lived in the USA in 2018, he or she could get low-cost face-lifts, injected lips or augmented breasts. Perhaps more hair-raising, with a few clicks, money could buy a new identity not only for the adults but also their unborn children, with genetic material as available as a new make-up. The increased affordability of the so-called “designer babies” or genetically modified babies was no longer only about preventing genetic diseases but also about creating babies who had the characteristics that their parents wanted. Could there be a lower moral point for extreme personalization than the example of designer babies? Social scientists can easily adduce more international evidence pointing to how personal and collective migrations have fragmented the self. The effects of this fragmentation rippled through mindsets and societies. For many, the confluence of accelerated and massive personal migration exacerbated the desire to choose a different life. Technology has facilitated the achievement of

114

The Future of the Self

these social expectations. The collective comparison embedded in always-­connected-lives stood in tension with the personal and private choices (see Schwartz, 1992). That is why the rise in excessive online lives also saw the rise in excessive social disconnection. Disconnecting from social media meant disconnecting from the pressure of conforming to expected lifestyles and the perfect lives depicted online. It is no surprise that Brené Brown’s (2015) call for embracing vulnerability as a way of renouncing perfection, developed into a widespread movement across the USA. The rise of capitalist micro-targeting, the meritocratic personal data economy and the massive technological change in the 2000s have all been part of the personalization story. As a result, smart technologies, capitalism and meritocracy sound like a plausible reason for extreme personalization levels in the twenty-first century. Indeed, in some quarters, data-enabled technologies are viewed as the primary reason for the “personalization revolution.” However, extreme personalization practices are not caused by technologies. Personalization becomes extreme when changes to personal and collective identities happen at extreme pace. I posit that it is the extreme acceleration that leads to the crisis of a personal and collective sense of “self.”

Causal Factor: Acceleration of Change Where do we pinpoint the spark for accelerated personalization? With the technologization that has globalized meritocratic values? With Richard Dawkins’ (2006) selfish gene theory? With the Protestant Reformation? My brief historical exposé is a simplified civilization account of human migration changes that have occurred between 2000 and 2018 in Western countries (mostly USA and UK, see Note 4.8) is an arbitrary focus. One could argue that the acceleration in personalization started after the Second World War. Geo-engineering researchers described that era as the period of transformative changes of human activity on global environment and called it the Great Acceleration (Hibbard et al., 2006). Since then, the Western nations (and I focus here predominantly on the trends in USA and UK) have

Acceleration

115

tempered with the pace of recycling old narratives of neoliberal progress and socialist measures. On surface, the Covid-19 pandemic brought a temporary halt to these eruptions, but deeper down, it merely illustrated the underlying dysfunctionalities of the two discourses. As Thomas Friedman (2017) wrote, the world is always in a state of accelerations, which, since late 2006, and early 2007 have taken the markets by storm. Within one year, the launch of iPhone/Android/Kindle/Watson, social media (Facebook, Twitter and YouTube) and processing of Big Data through algorithms has become a focal point of a vast digitized and globalized acceleration. Post-human theorists have intellectualized the argument in terms of socio-­material inflection points that transform individuals into transhumans. The personalization perspective and digital personalization, in particular, highlight the market as an engine for fueling inequality of experience, which on one hand, greatly empowers and amplifies individual voices, and on the other hand, depletes resilience and deepens an individual’s vulnerability. Mobility transformed the Earth into a planet imprinted with straight lines both on the ground and in the air. Mobility transformed the self too, but with a web of invisible interconnections to others. The pace of mobility has accelerated exponentially in the early twenty-first century on both a collective and personal level, and in both physical/embodied and virtual/online spaces. As we move to 2030s, the time lag between moving from thinking to doing is considerably smaller than it used to be in previous centuries, perhaps most acutely experienced by the accelerated pace of everyday communication. With AI-enhanced technologies, humans are able to invent gadgets, set up organizations and build structures much faster than ever before. Arguably, the reduced gap between thinking and doing means faster concretization of thoughts, which, Jean Piaget argued, is the essence of learning. We might thus feel that evolution calls for ever faster and more intense personalization – but perhaps this is a misleading understanding. Perhaps accelerated personalization means we are running faster to our own demise. Shorter distance between thinking and doing means there is less space for others to mediate individual reasoning. Individuals repeat mistakes because there is no time to self-reflect and learn from the past.

116

The Future of the Self

Reflecting on the 2010s, you and I may disagree on the mediators, correlates and causes of extreme personalization. You may locate the problem in the technology, some in the government structure, or in lack of societal support or something completely different. We are likely, however, to agree on the symptoms of extreme personalization. In my account, I focus on the symptoms and consequences related to personal identity, but read the “Notes” section for details on the alternative focus on collective identity (see Note 4.5).

SYMPTOMS OF EXTREME PERSONALIZATION: CONFUSION We might disagree on whether liberal democracy or globalized technocratic world-order are adequate systems for preserving human dignity (see the nuanced discussion by Fukuyama, 2003; 2006 on these issues ), but we may agree on some shared symptoms we have seen or experienced ourselves in the 2000s. If there is one shared symptom experienced by the individuals who have lived in the 2000s, it is confusion manifested in high mental stress. Accelerated changes to collective and personal identities in the 2000s have meant that there was no one leading narrative for individuals to converge around. Postmodernists and philosophers (e.g., Best, 1991; Nicholson, 2013) have recognized the loss of a grand narrative in the 1940s but the first two decades of the twenty-first century have introduced multiple narratives validated by capitalist and technological dominance and a burgeoning personal economy. The seeming function of these systems was to manage personal data, to give choices to individuals and everything related to these choices. But in reality, the acceleration of externally imposed personalization has created a breeding ground for uncertainty, doubts and confusion. The Japanese theoretical psychologist, Koji Komatsu (2016), proposes that people cannot make commitments without a consistent identity. In a rapidly changing world it is difficult to know what is the same and what is new, what belongs to the self and what to the other. The lack of differentiation triggers confusion, – a loss of understanding of what is significant and what is valid (see Lodge, Kennedy, Lockyer, Arguel, & Pachman, 2018).

Acceleration

117

Personal confusion often results in signs of self-centeredness and indifference toward others. Personal confusion is also referred to as uncertainty about one’s place in the wider society. In his poem Zürich, Zum Storchen, the Romanian-born German language poet Paul Celan (1963) wrote to his friend, poetess Nelly Sachs, that after the Second World War everyone lost a reference point and was unsure of whom to trust: “Wir wissen ja nicht, weisst du, /wir wissen ja nicht,/was/gilt” (We don’t know, you know, we don’t know what matters). The confusion of Second World War survivors following their experiences is comparable to the disorientation experienced by many refugees in the first half of the twenty-first century. For those communities accepting migrants, there has been some confusion around their shared identity. For about 350 million children living in war zones in South Sudan, the Democratic Republic of the Congo, Syria and Myanmar, mental stress has been the daily bread and butter. In other places across the world, people might not be stressed physically but suffer high psychological trauma and traumatic stress, which have profound effects on their entire being (Van der Kolk, 2003). It is foreseeable that people exposed to such traumas become vulnerable targets for operators who offer simple reconstructions of the self, such as terrorist or extremist propaganda. Without a doubt, the origins of the loneliness pandemic in the twenty-first century need to be sought in these social factors. In a world that is too complex and rapidly changing to pin down, who do we turn to for explanations? Not knowing where we stand and what counts is more stressful than knowing what is wrong and who the enemy is (Harari, 2018). The Covid-19 pandemic identified a single enemy – a virus. However, soon enough the blame game switched from an uncontrollable disease to controlling individuals (politicians, government advisors, neighboring countries or countries far away). People craved simple answers and singular scapegoats. The philosopher Alain De Botton (2012b) touches on the difficulty for humans to believe multiple truths in relation to religion. Multiple destinations are disorienting and puzzling. Religion allows for a third “self,” as it were, for an external force around which collective identities can be organized (and polarized too, of course). Both USA and Europe have seen drops in religious affiliation in the early 2000s, particularly among the young (BBC, 2015).

118

The Future of the Self

For a significant proportion of young people, social media sites replaced face-to-face social communities of shared belief. This had a dual by-product well-known to behavioral psychologists: groupthink (Janis, 1972) and in-group bias based on false narratives, as described by Eric Weinstein in relation to Intellectual Dark Web. In like-minded groups, the collective worldview is condensed into a narrow Weltanschaung, and the benefits of cognitive diversity are gone. The consequence of this tendency calls to mind Haruki Murakami’s iconic quote “If you only read the books that everyone else is reading, you can only think what everyone else is thinking.” When groupthink escalates – as it often does on online news sites driven by shock values – the herd-mentality ensues. Personalization becomes not about following personal interests but chasing sources that perpetuate survival instincts. It becomes about personal beliefs rather than informed decisions , and these get reinforced in neverending personal recommendation loops of social media algorithms. When group mentality is rooted in deep insecurity, it shows up as outward confidence and becomes what psychologists termed “collective narcissism.” Studies show that collective narcissism fosters inter-group conflict (Golec de Zavala, Peker, Guerra, & Baran, 2016), which is exactly why designers of communication platforms should be trained in avoiding it. Sadly, the social media platforms are designed to generate bubbles which fuel not only short-term inter-group conflicts but also long-term in-group bias. In-group bias can easily erupt into nepotism and homophily (Bloom, 2017) that demonize difference and portrays out-of-group members as opponents who need to be defeated rather than understood. The danger of personal confusion becomes most acute in environments that propagate homophily. Anxious and confused individuals struggle to define their own sense of self, which can manifest as incapacity for rational compassion towards those who are different from them (Bloom, 2017). This is a real challenge for modern societies that failed to systematically address the biases linked to the most visible group difference – one’s skin color. Further manifestation of confusion is envy and its related c­ oncept – “ressentiment” – first introduced by Rousseau, then used by ­Kirkegaard and recently elaborated upon by Pankaj Mishra in relation to Western democracies. Any psychologist will tell you that if

Acceleration

119

you feel yourself to be on equal footing with someone (which is the aim of democracy) but the other individual has demonstrably more success, then your immediate reaction is envy and “ressentiment” (resentment). Ressentiment can be traced back to individual helplessness in achieving equality through systems such as democracy. It follows that this feeling is even worse in democratic societies governed by meritocratic capitalism. From a young age, children are told that everyone has an equal chance for success – as long as they try their best (see, e.g., Melania Trump’s Be Best campaign in 2018). Numerous guidebooks, courses, free videos and entire educational systems instruct individuals on how to achieve personal and professional success. One thing they do not promote in these “inspirational” campaigns is that they enculture children into aiming for what Epictetus described as “wishing for a fig in winter” (see Dobbin, 2008), that is, not being able to accept their natural limitations and boundaries. This philosophy is embedded in the social media usage where 24/7 display of success and happiness is almost mandatory. The “always on” lives enabled by smart technologies contribute to the feeling that anything might be possible, and to the elevated stress levels connected with unlimited possibilities. The false narrative of capitalism pushes a pursuit of triumph at all costs, depicted by examples of “heroes and legends” in traditional media and enabled by algorithms on social media. This relentless pursuit of success generates a hierarchy where those on top face deep loneliness, as their position inevitably gives rise to a lack of reciprocity and consequently increased prevalence of mental brokenness. For Millennials and post-Millennials growing up in the UK and USA, the pressure experienced in the classrooms and in success-­ oriented families often condensed in the form of FOMO (fear of missing out) and fear of failure. Unrealistic expectations of what young may achieve individually and collectively were fueled by allowing digital identities to act as benchmarks of aspirations, and this was combined with the manifold choices opened up through globalization and digitization of social lives. In a twisted version of social mobility promoted by meritocratic capitalism, the failure of not becoming a high-net-worth individual got perceived as personal choice. Conversely, not knowing what to choose, or failing to get satisfaction from the choices made, have led to children’s

120

The Future of the Self

and young adults’ intense dissatisfaction with their own lives. In national ­children’s reports, for example UNICEF (2018) with 572 children and young people in Australia, we find repeated mention was made of feeling “invisible,” “irrelevant” and “worthless.” In the 2010s, stories of children’s mental stress, including depression, feeling overwhelmed, anxiety, agitation and unhappiness have become a frequent occurrence in schools from primary all the way to university. It needs to be acknowledged that the manifestations of mental health difficulties have become both more widely recognized and reported in this period. But there is also clear longitudinal evidence showing an increase in mental stress over time in young adolescents (Siraj et al., 2019, Note 4.6). For this aspect, personal technologies with their apps and social media sites have introduced two negative things: they discontinued many dinner conversations and intimate talk that used to happen in families and they carried over divisions and aggressions from schools to adolescents’ bedrooms (Turkle, 2017). I add with the same breath that the same technologies also became a life-saver for those who needed to connect. At times of personal or social crisis, increased social media traffic is blatantly visible for those who are lonely and who feel invisible in their private lives. The collective mental health crisis in the 2000s has spurred some powerful counter-movements. Calls for Mr Rogers’ calm appreciation of time, community food-growing projects, celebrations of traditional family structures and appreciations of the present moment have been designed to counteract the accelerated personal and collective migration with a “slow down” movement (Note 4.7). Public figures have become vitally concerned with spirituality, and many countries saw a surge in “voter nostalgia,” opposing changes. Although some celebrities use the adjective “mindful” to preface almost every practice, several schools have embarked on serious mindfulness interventions, some of which emerge as a positive influence on children’s resilience toward stress (Zenner, Herrnleben-Kurz, & Walach, 2014). The “caring and sharing” scheme offered through various charities and organizations to those who experienced traumatic events, abuse or bereavement is based on the idea that helping others is the best way to help the self. In Chapter 7, we will learn that the crux of the scheme is to

Acceleration

121

distance one’s own pain by assisting others. What is relevant here is that citizens who look after each other can address an ensuing mental health crisis (Russell, 2018). Evolution tells us that living organisms can adjust to new conditions, but the pace of evolution determines their survival rate. The pace and speed of changes to personal and collective identities can easily make our raison d’être chaotic and our accounts confused. If the key mental health symptom of extreme personalization is confusion and uncertainty, then agency can offer a viable solution. The loose ends of my account about the rapid changes to “self,” therefore need to be tied up with the humanistic principle of agency. As we learnt in the previous chapter, the evolution of human agency follows a horse-shoe like loop, with periodic peaks and lows. The socio-technological changes in the 2000s accelerated the highs and lows of human agency and disrupted the foundational components of progress. We have agency in ensuring that the ideal of human progress in the form of an upward-facing helix does not degenerate into a line for self-destruction. Understanding the mediators, moderators, causes and correlations gives us power to construct alternative realities.

This page intentionally left blank

5 DENSITY

As we are getting more data on our children, we need some big theories to interpret the value of ever-increasing density of personalization in the online and offline worlds. Physicists need to measure the weight and volume of an object to predict whether an object will float or sink. Density of personalization is not immediately obvious. There is a simplified formulaic way or an elaborate conceptual way to measure how dense the personal data are within products and services. The former follows the Newtonian analogy of personalization described at the start of this book, according to which density can be calculated based on a number of observable characteristics. For example, I could calculate the amount of personalization in a personalized smart toy and compare it with a standard toy. The volume of a toy is the multiplication of its length by width by height. Let’s assume the standard toy is of the same volume and matched to the child’s skin, hair and eye color. The personalized toy has the same characteristics, but in addition, it responds to the child’s commands; it audio-records what the child says and responds with a suitable reply. In terms of personal data, the personalized toy has a bigger mass. The standard toy can be personalized by the child’s imagination but the toy itself has no storage capacity of personal data. The smart toy is, therefore, denser in personalization than the standard toy. The other, in my view, a more conceptually appropriate, way of approaching personalization density is to think about the different types of personal information which can be used to define “self.” 123

124

The Future of the Self

The current commercial model of personalization pays little heed to the different values attached to different pieces of data. The commercial model of personalization does not even care whether the individual is still alive, – with QR codes on tombstones, it grants posteriority to an individual’s data circulated in the cloud. The consequences of this push will loom large in this chapter.

BODY-RELATED PERSONALIZATION The denser in personal data an object or a service are (i.e., the more personal information they hold about an individual), the more exclusive they can be and the higher their perceived value. This logic works well for commerce: a customer’s experience is more personalized if the company can aggregate dense customer segments in its databank (e.g., likes/dislikes, point of time and duration spent on device; browsing history, GPS location and weather of places they visited and intended or completed purchase behavior). Taken to another level, dense personal databanks can work well for clinical applications too. Personalized donor–­ recipient matching can be used for more effective organ transplantation, with predictions on organ acceptance based on a pool of aggregated individual characteristics and medical history (Yoon, Alaa, Cadeiras, & van der Schaar, 2017). However, the different motivations behind the close body-match models raise important moral questions, resolution of which is fundamental to understanding the underlying reasons for personalization practices. The first moral question to ask in relation to data density is: where are the moral limits to collecting, digitizing, utilizing and re-using personal information? Current body-related personal data (biometrics) include: voiceprint, fingerprint and face recognition. All three are acting as the password of choice for accessing secure documents or office spaces. Psychometrics (measures of personality characteristics used for user profiling) and psychographics (same as psychometrics but related to lifestyle choices) are used for tailoring online advertisements. The normalization of these terms into everyday use shows the conviction that human thoughts, flesh and behavior can be turned into data points that can be leveraged for action.

Density

125

Over the course of human history, humans have developed sophisticated devices to record the “secret games our bodies play” (Kennefick, 2015, poem), but the range, wide availability, ease of use and level of sophistication of devices available for body monitoring are unprecedented. Adults keen on “densifying” the cloud with their body-related data can in 2020 purchase Activity & Fitness Trackers; digital weight scales, breathing trainers, monitors for blood pressure, body composition, fat, heart rate, etc. These various technologies use body-related data to establish the body’s current status in relation to a database of existing data (you can only know what a “normal” heart rate is if it is compared to heart rate norms). But there are also many technologies that use bodyrelated data to establish the body’s possible status. Such technologies are popular among children and parents alike. With the app Toca Hair Salon, for example, children can choose a digital haircut. Snapchat filters and lenses can enhance a selfie with facial features that make them look funny, younger, thinner, tanner; or that can make them look like a baby, man or woman. Then there are VR body apps, with which you can enlarge or shrink your body or try on digital clothing. While in the 1990s children (and adults) could dress up in costumes in game centers or borrow them for special occasions, today’s children are inoculated into virtual body extensions early on. This is a much more intense play experience with appearance than that afforded by scarce photographic booths of previous generations. We do not know what the implications are yet, but we know enough to anticipate some possibilities. Let’s take apps such as Everywear or Apple Watch that measure heart rate, duration of sleep in relation to the number of calories and log blood glucose levels. These technologies are not simply enhanced pedometers, but as shown in doctoral work by James Gilmore (2016), they are also social tools. The gadgets are advertised to motivate individuals by setting up their personal goals. Adolescents who used the Fitbit apps reported, however, that such intrinsic motivation reduced their autonomy and competence over time (Kerner & Goodyear, 2017). At the same time, because there is direct synchronization between personal data and social data (such as the possibility to share progress with others), the gadgets motivate extrinsically. Comparisons based on personal

126

The Future of the Self

data (achievement scores or photos shared online) have been with vulnerable individuals linked to higher suicide rates among teenagers (O’Keeffe, Clarke-Pearson, & Council on Communications and Media, 2011), and higher anxiety and stigma for adult users (Owens & Cribb, 2019). So, on one hand, digital body extensions can help us achieve our full potential, but on the other hand, external tracking and competition can be constraining. One could thus claim that data-based body extension can both save and destroy lives. The question of a useful density of personal data carries the subquestion of social implications of denser data. It is well-established that there is already inequality in access to benefits of healthcare across and within countries, and these will be only exacerbated when healthcare becomes personalized fully and forcefully (see Harvey, 2012). Moral limits of data density are connected to the sub-questions of who they apply to and why. Personalized treatment used to be reserved to individuals with unique needs (or individuals with disabilities or special needs, as we used to say some years ago). These people needed to rely on personalized technologies for participating in the social life. Nowadays, many of the wearable technologies initially developed for those who needed them are used by those who want them. For instance, the FingerReader™, originally developed for visually impaired readers, is now used by second language learners: anyone learning a new language can use the device to translate a piece of written text. Users just need to place their finger on a line of text and the device reads the line to them aloud, either in original or translation. Thus, with some body-related personalization, the technology is the same but the purpose of use is as diverse as its user base. In addition to purpose, we can distinguish between external and internal body extensions. Body extensions such as, for example glasses are external, while an eye surgery is internal. Many external body extensions use personal data for aesthetic reasons that are connected to psychological benefits (e.g., breast implants to boost a woman’s self-esteem). Overall, though, external body extensions are an example par excellence of agency (the combination of self-determination and belonging) in personalized practices. Take tattoos as an illustration of individuals choosing to signify their personal preferences or experiences externally and

Density

127

allegiance to a group of like-minded individuals. Tattoos are a personal ID (Ferreira, 2009) and their unique design generates strong feelings of ownership for those who have them (a customized tattoo is worth much more than one copied from a website). The US tattoo industry has been described as booming, with $2.3 billion yearly revenue and growing year on year (The Week, 2012), which has wider implications from the personalization density perspective. Perhaps the next step from tattoos is what the New York based company “A Human” sells as fashion implants, that is, accessories implanted into the body. Products include necklaces and ruffs that grow right out of an individual’s neck and light up to the heartbeat rhythm. They connect the internal body data with external aesthetic preferences of the wearer. With the personal data economy pouring us more and more choices to “personalize,” maybe such implants signal the future for “ultra-personalized” body extensions. As humans we may share the same set-up of organs, but with implants and permanent marks we make our bodies distinctively different from the rest. The manifold data outside and inside us can be culled for the betterment of our own selves and others. But that requires a social contract that ensures ethical and moral approaches to personalization. We run into a serious problem if personal data are used for replication rather than extension of our own selves.

REPLICATING INSTEAD OF EXTENDING OUR BODIES Capitalizing on the interest in miniature objects and the buzz around the film “downsizing,” personalized figurines are getting on with the hype of creating a faithful replica of an individual. Personalized figurines by Kloneworld™, which replicate the customer’s body shape, posture, clothes and face in a small toy, are popular among newlyweds, expecting mothers and others wishing to mark a specific life event. Personalized figurines might lead to some raised eyebrows, but from the perspective of dense personalization, they indicate a significant trend to squeeze human bodies into artifacts. These artifacts can easily combine personal data with AI and

128

The Future of the Self

become “alive,” as the personal companions currently popular in Japan. Such personalized figurines look like a miniature replica of your ideal girlfriend or boyfriend, “living” in a glass tube in your home and sending you personalized messages to wake you up, ask how your day was and wish good night. Such messages can be texted to your phone or be spoken with real human voice. Watching these trends, we can see why they dismantle the moral boundaries that have been dividing trans-humanists and bio-conservatives. We hit the Gordian knot when personal data technologies augment and enhance intellectual and somatic experiences to the extent that they are no longer an added but primary identity. The bleak prognosis for a fully personalized Infosphere is that it spirals into a hunt for self-replication. We all have a moral imperative to articulate our own role in this trajectory. Although empirical knowledge on digital identities is in its rudimentary stages, we have many theories that answer questions on transhuman, neohuman or simply the human “self.” The theories I give voice to are not socio-political theories about production, neither are they evolutionary theories about re-production. I go into detail of the extended and relational self theories because they speak most directly to the question of dense personalization. In the spirit of extensions, I extend the theories to the specific question of moral boundaries in personalization density. I want to set aside the distracting question “what drives the human desire for extension?” and replace it with a more exciting question “how might personalization be used to enlarge the good in us?” THE EXTENDED SELF THEORY Consumer behavior professor Russell Belk (1988) was the first to make the connection between identity and material extensions. Belk’s notion of “extended self” began with the idea that individuals extend their identities into material things they buy and into artifacts they own. These objects are perceived as their own and include not only tangible things but also hobbies, pets or family members. Psychologists and economists have traditionally drawn boundaries between the human and non-human, material and

Density

129

non-material extensions. For postmodernists, however, there is no boundary between material and non-material things; the self is a hybrid of associations that shift between material and non-­material entities (Prout, 2000). Belk (2014) revised his theory, with the claim that the self is “unbound.” Unbound implies no boundaries, which I think fits very well the ever-rising trajectory of personalization density, but there are some boundaries that I think are important to highlight, namely how transitory many of the bodily extensions are. A significant trend in the 2020s is to rent rather than buy clothes, books, music, films or even Christmas trees. AirBnb flats or cheap rental of cars make temporary ownership more affordable for larger populations. Temporary ownership of material extensions is on rise not only because of increased awareness of sustainable development but also because of digital environments fostering the transient nature of being and the authenticity of alternative egos it affords. We cry for such an authenticity at times of need, be this in personal or global crises, when a virtual “life for rent” is a desirable alternative to the physical life. In turbulent times, transient experiences are more valuable than material possessions as experiences are more flexible to accommodate the multiple lives experienced in a state of chaos. These experiences enlarge and extend our identities far more than physical possessions (Gilovich, Kumar, & Jampol, 2015). Not for everyone, of course. You will remember Jack with his regulated and supervised use of technologies. For him, the unboundedness of online self was a strong motivational factor to play virtual games, but it was constrained by his parents. The coveted status of many personalities that used to be reserved to writers, actors or spies can be enjoyed by millions on the Internet. But the extent to which our identities are extended through avatars, virtual possessions and the unprecedented possibility to easily construct an alternative virtual self, depends on the differences in access to the “enticing menu of selves” (Belk, 2014, p. xxiii). The extended self theory does not explain the connections between various selves. However, its sister theory – the networked self (Zizi Papacharissi) – cuts right to the heart of dense personal connections.

The Future of the Self

130

THE NETWORKED SELF The networked self (Papacharissi, 2010) is housed in the view that identities are a system of personal data interconnected with the data of others. These networked identities are connected through digital and physical artifacts, such as the Internet of Things, or in the case of young children the Internet of Toys. From the networked self-perspective, the era in which we live now, the Infosphere, is an entire environment of networked selves. What is illuminating in the networked self-concept is the notion of interconnection among others and self, objects and flesh. Density of self is not the quantity of different material things we extend ourselves to, it is the dense connection between these things. Our identities – and especially the identities of younger generations – are enmeshed in digitized networks. This is not a passing fad but an expanding network that keeps growing with every single individual. The connections build on each other, creating thicker threads among individuals who cannot be uncoupled from the networks that sustain them. From this perspective, the progress line toward future selves is unlikely to become thinner in the future, as there will be more and more data points on individuals and on the networks they belong to. Now both the extended and networked self theories stand on a shared foundation of self-growth, assuming that there is a core self-concept, the sum of the parts we call “me, myself and I.” But is there really one “principle of being,” as the poet Stanley Kunitz says in his poem The Layers, a principle of being, the core self, that we return to after journeying to other possible selves? In posthumanist theory, these possible selves do not only inter-act but also intra-act with each other, that is, they become entangled in their material and immaterial extensions (e.g., Kuby, Rucker, & Kirchhofer, 2015). Our relationship with other living and nonliving beings seeps through the layered nature of this core – each encounter leaves a new layer in our memory and an imprint on our body. Are these layers compatible with each other? Or to put it less philosophically: are our practices and relationships a reflection of who we are and of who we would like to be? The answer to this question lies in understanding the (in)congruence between an ideal and actual “self.”

Density

131

CONGRUENCE BETWEEN OUR IDEAL AND ACTUAL “SELF” Congruence essentially means agreement or correspondence between one or several things. The idea of congruence/incongruence permeates a lot of childhood research: if babies encounter a new thing that is incongruent with their previous experience, they might show fear and cry or they might show surprise and laugh (see M. W. Baldwin, 1992). Personalization enhances congruence, as shown with several experiments related to the “self-reference effect” (Symons & Johnson, 1997). The self-reference effect can be evoked by showing people photos of their own faces, telling them they own objects associated with the new information or mentioning their name. The more the new information is about them, the better they remember it, and this applies to both children and adults (Schacter, 2002). Why exactly this memory effect exists is not known but a strong hypothesis is that self-referential information creates correspondence between new information and a personal schema. Cognitive neuroscientists showed that during the processing of self-referential information, a separate region of the medial prefrontal cortex gets selectively activated (Kelley et al., 2002). It might be that self-referential information activates the connection not only between new and familiar but also between shallow and deeply encoded information. As for the question of congruence in relation to adults and their behavior, we need to look no further than the various versions of self which adults portray on different media platforms. Unless you use automated (pre-scheduled) posts for promotion, you are unlikely to have the same photos on your personal Instagram and professional LinkedIn page, for example. As Baumeister’s theory of self-presentation postulated back in 1982, people are motivated to selectively present their “self” in relation to social situation and what they believe others perceive as appropriate behavior in a given situation (Baumeister, 1982). These selected self-presentations are not a lack of integrity but a reflection of social expectations and conventions. With this understanding, it is no coincidence that even with more stringent verification systems,

132

The Future of the Self

Facebook records millions of fake and false identities. Multiple identities illustrate the tension that personality psychologists Carl Rogers and Karen Horney identified between the real and the “ideal self.” The ideal self is the illusive self we wish we could be one day. The real self is the repeated pattern of our behavior over time in different contexts. For some people the ideal and real self are fairly congruent, for others they are miles apart. The ideal self is based on often subconscious comparisons we make with others. These others need to be similar to us for the comparison to work. The closer in appearance and status the other individual is, the more likely we feel jealous if they achieve success (De Botton, 2008). A dog doesn’t want to be a cat, but a stronger dog, so to speak. Ideal selves have more comparison points online than offline: with daily updates from selected followers, pop stars, easily accessible photo filters and cheap designer fakes, there is a dense pool of identities to choose from. Cover songs on YouTube, deep fakes, look-alikes and professional impersonation on Instagram are examples of performing desired selves. The number of followers, likes or re-shares are valuable because of the social status they grant an individual. This social status is compared to that of others of a similar status. The social value of personal data, therefore, lies in ascertaining the difference between the number of re-posts, shares or likes of a real and fictional desired self. The problem related to personalization density arises when the self-outshoots grow too large for an individual to handle. The escalation results in a curious phenomenon: rather than extending their core self, individuals start creating alternative selves. Again, Web 2.0 is an ideal platform for accommodating such alternative egos. Social media researchers have found that on Facebook, US students typically present three types of identities: “true selves” “real selves” and “hoped-for possible selves” (Zhao et al. 2008). In light of these manifold opportunities, Chaudron and Eichinger (2018) concluded that changing and re-creating new identities on the Internet is what it means to be human in the twenty-first century. Following a detailed analysis of art-making and communication of diverse participants via Skype across the globe, the authors showed that online platforms play a significant role in mobilizing

Density

133

the desire to be someone else. In video games, for instance, individuals tend to create their “ideal selves” almost automatically, as they combat enemies and build their own virtual worlds (Przybylski, Weinstein, Murayama, Lynch, & Ryan, 2012). On social platforms, individuals present different parts of their self depending on whether the platform is for dating (Tinder), success sharing (Instagram) or networking (LinkedIn). It is difficult to hide your true self in physical life with the people you meet face-to-face every day, but online there are different platforms catering for different types of self. Despite these technical affordances, pretending to be someone else online is negatively correlated with face-to-face relationships and conversely, expressing the true self is more likely to convert to long-term relationships (see McKenna, Green, & Gleason, 2002). Yet, despite these psychological consequences, the personal data economy is set up to fragment the “self” into individual data points that can be distributed across multiple digital devices. Indeed, the personal data economy and modern technologies are set up to fully accommodate the manifold extensions of our diverse selves. VR accommodates the experience of a different self through a whole body experience. In professor Mel Slater’s world-famous lab in Barcelona, participants wear a VR headset and adopt the persona of someone else. When hearing, seeing and feeling through touch and occasional movement across the room as somebody else, the participants can experience the empathy of “being in someone else’s shoes.” This can be used for building compassion with others as well as one’s own self. Emerging research shows that when the experience is strategically manipulated, participants can forgive themselves for mistakes of the past and become less regretful. Conversely, if the manipulation involves embodying somebody else, participants can feel empathy and compassion. Importantly, these feelings persist over time (Herrera, Bailenson, Weisz, Ogle, & Zaki, 2018; Slater, Usoh, & Steed, 1994). Proponents of VR suggest that the possibility to be someone else could be leveraged for managing traumatic experiences, phobias and pain. It could also be leveraged for educational experiences of visiting geographical locations that children couldn’t otherwise visit (e.g., visiting a tropical forest through a virtual trip). Such applications of personalized technologies enlarge the good in us.

The Future of the Self

134

But VR opponents rightly point out the other side of self-­ manipulations. VR interventions could be also used as “undo buttons” for the past, which remove regrets (Krotoski, 2018), and thus remove the opportunity for self-correction, cognitive rumination and psychological adjustment (Lecci, Okun, & Karoly, 1994). With children in particular, VR researchers are cautious about immersing children into alternative realities for a number of reasons: ethical – will a child understand that they can withdraw from a study if they are immersed in the experience?; developmental – will a three year old understand the difference between virtual and physical reality?; and technical – the technological development in virtual and augmented reality is currently geared toward adults. Emerging findings with 6 to 7-year-olds, 8 to 9-year-olds and 10 to 11-year-olds show that although the youngest age group could identify with their virtual physical self, the older age group did it more consciously (Cowie, McKenna, Bremner, & Aspell, 2018). This indicates that for younger children the boundary between different versions of self is more fluid than for older children, and thus requires extra caution with interventions and manipulations that strategically disrupt this fluidity. Moving on to possible answers to my initial question of “how might personalization be used to enlarge the good in us?,” there are two notions that are helpful in clarifying the process of learning about the parts of self we extend in congruence with others and our own alternative selves: “abstraction” and “desirable difficulties.” I zoom in on these two learning mechanisms as they can help us gauge the density of personalization in fragmented selves.

ABSTRACTION When you see children playing with miniature replica of themselves, you may understand on a gut level that this might adversely affect their development. A research-informed answer focuses on the importance of pretend play during which children use objects and toys to pretend a different reality. In pretend play, children invent answers for their toys and often say these answers aloud to enact different characters. Stones can speak and a Barbie can have

Density

135

an argument with mummy. The children decide what their toys do: they imbue the toys with their own agency. This is why play, and pretend play in particular, is an essential vehicle for developing children’s volition (Bullock & Lütkenhaus, 1988). Pretend play is also an essential vehicle for developing children’s language and social understanding (Garvey & Kramer, 1989). During pretend play, children borrow words from others (“I’m your mummy and you must put your shoes on!” sounding exactly like their mummy) and this language borrowing, with its linguistic and social repertoire, is an essential tool for language development. From a developmental perspective, very young children gradually learn that the rich fantasy world inside their heads is not the real world around them. An evident sign that children are processing this distinction is when they engage in self-talk. Self-talk occurs when people talk to themselves rather than others. In an iconic book put together by Katherine Nelson (1989), researchers analyzed the self-talk of Emily, a two-year-old girl. This young girl was audio-recorded talking to herself aloud each day. The recordings happened before Emily went to sleep in her crib, which is why psychologists sometimes refer to children’s self-talk as “crib narratives.” Emily’s self-talk provides a fascinating window into how children’s self-talk scaffolds a personalized version of the world. Children are so much in their own world that they don’t seem to perceive the need to use speech to refer to others. Nelson describes monologue as the linguistic construction of Emily’s identity, and notes the change in Emily’s talk after 24 months when the girl began to acknowledge in her speech her parents or the doll she played with that day (referencing others is typical to start at the age of two, Fein, 1981). For psychologists, this indicates a separation between the child’s “self” and the “other”. Now imagine that there is a toy that records a child’s crib narratives and uses the child’s talk to program what the toy says back. From a corporate perspective, a smart teddy provides a personalized service just like Siri. A voice-delivered command is matched with an appropriate answer from Apple’s database to create the illusion of a real-time conversation. The make-believe conversational characters give children the impression that they can speak and understand them because they respond to what they say.

136

The Future of the Self

And here comes the “but” you would be expecting – if the doll is a smart doll that runs on algorithms programmed by someone else, then the child has less choice in personalizing it. Even though the toy producers call their smart toys “personalized,” the more “alive” the doll appears, the less work there is for the child to bring it to life. In addition to subverting children’s agency, the automatic personalization might negatively impact the natural progression in children’s abstract and rational thinking. We do not know this for sure (there haven’t been studies that would compare children growing up with smart dolls vs ordinary dolls) but we can predict outcomes based on strong theories. According to the classic developmental theorist Jean Piaget, pretend play diminishes as children develop more logical thought. For pretend play to work, children need to engage in illogical thinking. You might be startled by this suggestion, so let me explain. Illogical sounds negative in a fully rational society but it cannot be dismissed for the sake of creativity and arts. Children make many illogical suggestions during make-believe play. It is perfectly normal for children that during pretend play, a doll’s tears fall from feet up to her eyes. However, the algorithms in smart toys are programmed to deliver logical behavior and logically personalized answers. If child says “x,” the algorithm responds “y.” The answer–response model is linear: speech–responsive software can only provide relevant answers if the child’s sentences match the templates/database used by the software. In the developers’ eyes, any deviation is an error, triggering a “try again” command. Yet, abstract thinking, creativity and curiosity are not linear. I mentioned in Chapter 3 the importance of open-ended design for nurturing children’s agency. The importance of illogicality and serendipity within personalization connects to this point. The best toys for children are abstract toys that offer open-ended choices. Think of natural objects, simple story characters or Montessori minimalist toys. Smart toys are far from the open-ended design ideal. With toys that are designed to reply with tailored suggestions, children cannot conjure up answers to their hopes and fears. In all fairness to the developers of smart toys, it is possible that once fully developed, calibrated and secured, smart toys could act as personalized one-to-one vocabulary teaching assistants. This is how

Density

137

it could work: smart toys could tailor a database of pre-­recorded stories or specific narrative arcs according to the child’s utterance. It is conceivable that the smart toys could be programmed to tell children stories that are customized to children’s language levels. They could help with language learning for second language learners or children struggling with oral language. Imagine an AI-driven story-teller that children can carry with them and relate to. But even this prospect calls to mind an objection from developmental psychologists because of the well-established evidence concerning conversational turns (Romeo et al., 2018). Children need to be listened to and engage in a ping-pong-like conversation to practice both language input and output and this ping-pong cannot be automated as in a computer game but embedded in social relationships. If family bonding times are replaced by children conversing with smart toys, then the benefits in vocabulary learning will be outweighed by the losses in social domains. These concerns would be resolved if smart toys and their personalization capabilities were simply a gimmick, but they have taken on the children’s market and children take them very seriously. From field experiments, we know that children engage with personalized technologies differently than with those that have no customization or AI capabilities. One study found that the extent of personalization influenced the extent to which children’s questions were varied and how rich the interaction was between the child and technology (Wolters, Georgila, Moore, & MacPherson, 2009). Retailers were quicker than some teachers and parents to grasp that children voluntarily extend their conversations to objects that respond to them. Smart toys do not make children smart if they minimize abstraction and concretize their thinking too early on. Another reason is that they remove difficulties in learning yet some difficulties are actually desirable in a child’s education.

DESIRED DIFFICULTIES The illuminating concept of desirable difficulties was introduced by Professor Robert Bjork in the 1990s (see Schmidt & Bjork, 1992). Bjork and colleagues noticed that if they varied the conditions of

138

The Future of the Self

practice and strategically introduced difficulties into their students’ learning, there was a higher post-training retention. They established that adding a specific hurdle to a well-tested study process enabled deeper cognitive processing by students. As unintuitive as it sounds, this simple idea proved to be key in aiding students’ long-term retention of information. Desirable difficulties can be instantiated in various forms, including introducing errors in maths instruction (Adams, McLaren, Mayer, Goguadze, & Isotani, 2013) or increasing text difficulty for skilled readers (Mcnamara, Kintsch, Songer, & Kintsch, 1996). Desirable difficulties are used in many cognitive acceleration programs but mastering the art of desirable difficulties is difficult – forgive my pun. Desired difficulties are variations depending on the learner’s prior understanding and context of their learning. In addition, a task needs to be perceived as difficult by an individual learner, it cannot be objectively imposed on all learners. This concept holds great promise because results are seen even with small design alterations. For example, Diemand-­ Yauman, Oppenheimer, and Vaughan (2011) tested the idea in both laboratory and classroom settings and showed that information presented in hard-to-read fonts was better remembered than information presented to the participants in a preferred reading font. Brown, Roediger, and McDaniel (2014, p. 3) summarized decades of empirical work to conclude that “learning is deeper and more durable when it is effortful.” In the experiments that led to this conclusion, harder versions of the same task yielded better results long-term (Brown et al., 2014). This strongly suggests that we need difficulties in order to think harder. Whether it is a piece of technology that stopped working right in the middle of a teaching lesson, or a missing ingredient in a half-way finished batter -– as annoying as we might find these moments, they provide great teaching moments. Seymour Papert, the founder of “constructionism,” maintained that cognitive challenges were the essence of children’s self-discovery learning. Papert (1995, n.d.) emphasized the need to offer children “more challenging opportunities than was conceivable in the pre-digital era.” Research bears out Papert’s recommendations. For example, Kelly and Tangney’s (2006) work on the EDUCE adaptive educational system and showed that contrary to developers’ expectations,

Density

139

students learnt most in the least preferred condition: not aligning the content with students’ preferences taught students the most. The logic of the learning process is something like this: the less we find something aligned with our preferences, the more effort we need to make to understand it. And the more effort we make, the more engaged we are, involving our memory and thinking in the process. The key design principle is to find the spot between desired difficulties and learner’s disengagement. In my recommendations to designers, I detail the technique programmatic pluralization (Kucirkova, 2019a), which is the opposite of programmatic personalization that most designers are familiar with. Instead of more and more personal data for more and more precisely personalized product, programmatic pluralization is about selecting content units that are dissimilar from users’ past browsing history or preferences. While personalized design has been successfully monetized, pluralized design remains the domain of educational research design. Nevertheless, the questions asked in relation to programmatic pluralization are very similar to those of personalization: for example, how many categories are needed to keep users’ engagement? The diversification is not about random information that might offend and disengage users but about engaging them with content that is socially and collectively relevant. Ergo: the insertion of random recommendations into a list of personalized suggestions is not programmatic pluralization but randomization. There has been some speculation that the success of dating sites such as Cupid or Tinder lies in striking the balance between matching profiles in a like-like model and occasional “wild card” suggestions. Programmatic pluralization is not about match-making but about deeper engagement. Many educational games foster deep engagement in that they are appealing to individuals by drawing on the players’ preferences, and they introduce them to something new that requires solving a cognitive challenge (Gee, 2005). The idea of edutainment (education and entertainment combined) is that the designer needs to introduce a challenging concept to the child, and at the same time ensure the child wants to play the game and be motivated to learn the new concept. The challenges need to be strategically designed to build on, but not prioritize, individual progress over that of other players.

140

The Future of the Self

In a programmatic P–P, the best of personalization and pluralization techniques are used for the advancement of knowledge and cultivation of humane progress. In addition to abstraction and desired difficulties, the P–P design uses other psychology concepts that, unlike in persuasive design, empower individual users. For example, surprise and violation of expectations are sensible techniques to probe users’ assumptions that lie outside factual evidence or outside their knowledge schema. In one experiment, students were asked to make predictions, such as, for example, to predict the result of a soccer match, and those who predicted the results wrongly better remembered the event (Brod, Hasselhorn, & Bunge, 2018). The surprise element is a cognitive mechanism that can be activated not only through software programs but also by teachers, parents or fellow students, in classrooms of any size and anywhere in the world. While researchers are piecing together the effective mechanisms for an ethical and sustainable design of technologies, manufacturers are releasing products that lack agency, equity and transparency (Tsai, Perrotta, & Gašević, 2019). The idea of programmatic pluralization is to disrupt this trend and develop models of content diversification that are based on ethics and strong theories. The personalized Internet follows only the programmatic personalization part of the P–P ideal. Personalized news are selected according to the user’s preferences (combined with information selected on commercial grounds). There is no purposeful intent to diversify a user’s knowledge by introducing thought-provoking content. This means that personalized information is denser than pluralized information, and the P–P balance is off. There are no desirable difficulties or suggestions for abstract thinking in other software design either. With Gmail’s Smart Compose, users are given a “smart” choice between three possible short answers to respond to their emails. Why should systems that make everything easier be an innovation? Adults change their behavior in order to fit with different social groups, for example, some adults smoke only on social occasions (Bahl & Milne, 2009). Adults present different parts of their selves in different social contexts, even if it leads to higher levels of anxiety and insecurity later on (Querstret & Robinson, 2013). So why not present web users with recommendations

Density

141

that do not accord with what they like and did before? This is one of the crucial crossroads where entertainment parts company with education. One of the wrong turnings we took with personalized education was adaptive learning that eradicated desirable difficulties. To me, adaptive learning is an example of neglecting the danger of the “thick” personalization. In what follows, I consider not only the limitations of adaptive learning but also its own possibilities.

ADAPTIVE PERSONALIZATION AND ADAPTIVE LEARNING As we know from Chapter 1, adaptive and personalized learning are not the same but in the UK and US educational government policies, adaptation, especially adaptation provided through technology (learning analytics), is perceived to be the core of personalized education (Note 5.3). Adaptive learning works well for specific, clearly defined domains of learning. For instance, incremental learning with the personalized reading apps in the European iRead project has been found to support children’s acquisition of phonology, orthography and grammar (Berling & Gilabert, 2019). Adaptive edtech is a good antidote to static personalization techniques as it uses personal data to adjust products and gradually evolving activities, all based on the user’s progress. This is a more educational application of personal data than simply taking a child’s name and pasting it inside a book. However, the use of adaptive learning in domains which do not follow a linear progression of knowledge acquisition is problematic for three reasons. First, most adaptive learning software adapt student’s progression by drawing on the students’ learning behavior and personal learning style. The smart students can quickly figure this out and adopt a learning style that helps them complete the task but not advanced their knowledge or learning behavior (HCI designers call this the “production paradox”). Sure, the system can include comprehension questions to check if the student has truly understood the learning topic, but the knowledge model of a software program is more constrained than that available to a skillful teacher

142

The Future of the Self

(unless we are talking about adaptive learning in countries with a significant shortage of teachers but that is a different problem all together). The second problem is ethical. With adaptive learning, students are presented with gradually more difficult content according to their progress and learning preference. Those who succeed in the system get to the top of the pile by receiving more difficult and enhanced content, standing out from the masses. Those who do not succeed are left with their own data – there is no group power to lift them up. From a sociological perspective, adaptive learning is an insult to democracy because it adapts to the student’s experience (LeatonGray & Kucirkova, 2018). It follows a fix-it rather than heal-it mindset; it pre-supposes that by offering different doses of a pre-defined “medicine,” a child’s learning can be ameliorated. A systemic propagation of a selected elite is a meritocratic, not democratic system and we saw in Chapter 4 the social consequences of meritocratic practices. From this perspective, adaptive learning is ill-conceived for social progress as it perpetuates historic inequalities of achievement. The third problem is technological. As in many areas of educational technology, learning analytics got to the market before being properly evaluated by scientists. The science of learning specifies the importance of combining students’ cognitive profile, learning abilities and behaviors, context, time perception and many other factors for effective learning (Williamson, 2017). Without shaming individual companies, there are many learning analytic programs out there that do not indicate learning progress but merely motivation to master a specific task. They are popular because they pander to the currently popular rhetoric of education that equals learning with a service delivery (just like Amazon delivers a package home, so can an educational software deliver a personalized knowledge package to the child’s brain – the educational entrepreneurs seem to think). Treating learning as a commodity that directly feeds into individuals’ career trajectories and the job landscape is a step back in public education, not a step forward. Adding more layers of data to a linear model that adapts to its own faults is not extending but shrinking the self. This brings us to the notion of personalized brain, which provides a clarion call for those concerned about adaptivity and dense personalization.

Density

143

THE PERSONALIZED BRAIN In her book The Private Life of the Brain, Susan Greenfield (2002) describes how the building of the personalized brain begins the moment children are born: experiences stimulate brain cells, which grow branches and increase the brain surface area. The larger a child’s brain, the more connections they can make, and the more personal the interpretation of the world around them. Each autobiographical experience is a personalized update for the brain connections, generating new thoughts. Even though the sensory and physical experiences might be externally perceived as the same for two (or thousands) of people, they are never the same when perceived internally, from the brain’s personalized perspective. Neuroimaging studies with adults have shown that the brain’s spontaneous resting state favors information related to self over information related to the other. In the 1970s, the neuroscientist David Ingvar showed that when participants thought about themselves undisturbed, specific brain regions became activated. The undisturbed part matters because the relevant brain regions are activated only if the self-relevant mental explorations happen in a passive, unconstrained state of mind. Later on, the self-attention brain network that encompasses several cortical networks, took the name the “default network” (Buckner, Andrews-Hanna, & Schacter 2008, see Note 6.5 for more). A popular (but not scholarly) concept in the default network is “mind-wandering.” In popular literature, mind-wandering is recommended as a technique to awaken one’s very deep personal memories. However, from a scholarly perspective, mind-wandering is a vast concept that needs to be qualified: it matters where and for how long your mind wanders to different thoughts and what these thoughts are (e.g., composing poems vs traumatic memories). Most recent neurological evidence suggests that the brain operates more like time-division multiplexing. Caruso et al. (2018) describe it as the GSM telephone system, whereby the brain encodes several stimuli at a time, with neurons fluctuating between encoding one and encoding the other. The reason this is important for the present discussion is that according to time-­division multiplexing, there is no such thing as a “personalized brain”: the latest research evidence does not support the division

144

The Future of the Self

between thoughts related to self and thoughts related to the other, or the claim that a specific brain region is uniquely responsible for thoughts related to self (Preston & Hofelich, 2012). What the brain imaging research does show is that when individuals make judgments about themselves versus others, there is a different brain activity in either the ventral or dorsal regions in the medial prefrontal cortex (Denny, Kober, Wager, & Ochsner, 2012). Yet, even though there is higher neurological activity in these specific areas, this doesn’t mean that other areas get activated with other types of self–other stimuli (remember that research is like a spotlight and we should always remember the parts that our analysis torch does not shine light on). We have virtually no evidence concerning the brain activity for young children and thoughts dense with memories of their own or others’ experiences. A meta-analysis of several studies with adult readers found higher activity in the medial prefrontal cortex in relation to processing self-related traits, and in the posterior brain regions in relation to the traits of others (Araujo, Kaplan, & Damasio, 2013). While there is no neurobiological evidence on children’s processing of personalized media, imagery or texts, the cognitive processing of generic, non-personalized, media, imagery and texts has been carefully studied and analyzed by psychologists for over a century. The key finding here relates to the density of information. If there is too much “noise” in the information that brains need to process, the signals interfere with each other and the processing of the signals becomes automatic and less mindful (Patricia Greenfield, 2014). This can be information that is personally relevant or not. This relationship between information density and cognitive capacity has been verified in several domains of children’s interactions. For example, researchers compared children’s responses to a story presented to them via radio versus television. The audio version of the story led to more imaginative responses from the children than the animated version, but the animated version on TV led to more recall of story information (Greenfield & Beaglesroos, 1988). Applied to the context of reading, children’s processing of stories presented in audio, illustration and animation was evidenced with distinct activity in functional brain networks (Hutton, DeWitt, Horowitz-Kraus, & Ittenbach, 2018).

Density

145

Media scholars who follow McLuhan’s tradition would not be surprised by these findings: early in his career, McLuhan (1960) advocated that the “medium is the message.” Given its inherent characteristics, each medium transforms human perception in that it offers a different arrangement for the senses that process this information. An emphasis on audio in radio, for example, affects the meaning we derive from the audio medium (McLuhan, 1994). Similar conclusions have been reached by social semiotic researchers who analyze the layout of websites, books and other visual representations. Some ways of representation enrich each other, and some cancel each other out (London-based Multimodal Group, e.g., Jewitt & Kress, 2003). Personalization adds to the density of processing information. For instance, seeing a shadow is not only about processing the visual aspect of the shadow and the details and strength of its depiction of the body, but also about ascertaining whether the shadow belongs to you, someone you know or whether it is someone/something you are scared of. Again, the relational self offers a good interpretative framework here: the theory proposes that individuals understand themselves in relation to others (I’m the mother of my son, I’m the wife of my husband). Thus, on the theoretical level, when it comes to judging others, it matters hugely who the other person is and how close they are to us. Given that in the resting state, the human brain prefers to first process information related to self, personalized stimuli are likely to get priority in our perception and response. Overall, however, the individual’s response will depend on the interaction between type of stimulus, context of processing, individual differences and the extent of how densely the stimulus and context are to the individual. The conclusion from this research is that processing different stimuli interacts with an individual’s preferred way of information processing information and with the extent to which the information is dense (Note 5.4). Therefore, the notion of the personalized brain is appealing but it corresponds to an old Cartesian assumption that identity can be separated into brain and body. For enlightenment thinkers, the mind and body were divided, and it was the mind not the body that made us distinctively different from each other (Locke, 1960/1975). For today’s thinkers, the boundaries between the mind and the body are as fluid as are the boundaries between

The Future of the Self

146

the “self” and the “other.” Personalization is, therefore, not an absolute but a relational variable, which brings us to the Relational Self Theory. The Relational Self Theory delivers a fatal blow to simplistic explanations concerning dense personalization and adaptive learning techniques for education.

THE RELATIONAL SELF The Relational Self Theory is part of a family of socio-cultural and personality psychology theories that explain how our ideal and real selves co-exist in an intricate web of connections with others (see, e.g., John-Steiner, 1999; Mischel, 2004; Surrey, 1985). Even though it might seem that people prioritize their attention for things they like and individuals who look, think and act like them, the Relational Self Theory says there are no absolutes – there is a self–other overlap in all neural and biological computations. Our identities are constructed in context and through an active process of negotiation between the self and the other (Andersen & Chen, 2002). This other can be another human being but can also be abstract characters or material objects. Professor Benjamin Bailey (2007) has researched the many ways in which identity is constituted through interactions in different groups. He explains that identity is made up of others’ judgments and activities, which are active characteristics (p. 258). Building on this, Japanese theorist Koji Komatsu believes that the development of a child’s self is not stable but dynamic. In other words, the development of who we are does not grow like a tree one inch at a time, but rather it emerges like stars from a giant shared molecular cloud. According to Komatsu, it is through conversations with their friends and parents that children establish their otherness and who they are – we clarify our “selves” in relationships. Komatsu’s perspective is an interesting critique of the exact sciences that the development of “self” as a sequence of milestones: by 3 months the child understands that they are separate from their mother, by 18 months they recognize themselves in mirrors, by 36 months they start having self-oriented emotions such as embarrassment and thus a fuller understanding that they are an individual human being.

Density

147

The sociological tradition, on the contrary, views children’s development of “self” as a response to specific time and location. As such, the Relational Self Theory is extremely well-suited for the ­personalization–pluralization ideal where individuality and sociability are not competing forces but in direct relationship to each other. With extended self on the one end and relational self on the other end, we can understand the tensions in education and technology design as a spectrum of density in self-representation, and we can more readily recognize the limitations of one-sided interpretations of contemporary phenomena. The phenomenon of selfies offers a fitting example of the overlapping explanatory powers (as well as their vulnerabilities) of the extended and relational self. Despite the focus on self in the very word “selfie,” the practice of taking photograph of oneself, is predicated on the assumption that identity arises from kinship to others (people do not take selfies to keep them in their drawer but to relate to others). In the following section, I use the example of selfies to illustrate the dual desire to extend the self for replication and to relate the “self” for assimilation with others.

Selfies: A Digital Self that Extends and Relates From the perspective of density of personalization in the portrayal of human face, a lot has changed in the last 1,500 years – while Australian Aborigines in Kakadu painted their own faces on caves’ walls, modern citizens can use their face to pay for their shopping. While in the Early Modern period, the distribution of self-portraits used to be the domain of monarchs and artists, nowadays we all are Rembrandts with a digital portrait hanging in the gallery of air. In case you didn’t know, there is an entire dictionary for the selfie collection. Usie is a group selfie, Shelfies show a bookshelf or collection of books with or without a human face. Bitmojis are customized versions of emojis that look like their sender. Social semiotic researchers have established that some selfies do not include the photographed face, but the face can be implied or inferred, such as when someone holds a glass of wine and tweets from a party, for example (Zappavigna & Zhao, 2017).

148

The Future of the Self

The accessibility to self-portraits and the collective engagement in sharing them heightens the risk for obsessive selfie-taking. Twoyear-olds do not use Facebook, but their faces are often part of their parents’ social media feeds. As they grow older, children are given direct access to “pop-up selfie museums” in their hands. Children love using Snapchat filters that add different hair/eye/skin colour to their own faces and get immediate feedback from friends or larger audiences. While there is nothing wrong with children taking occasional selfies, there is a legitimate concern over selfie-related deaths (Maddox, 2017). These trends illustrate the edge when the desire for an attention-grabbing picture exacerbates compulsive habitual patterns (Note 5.1). Adults take selfies for the same hedonic reasons as children but in addition, their selfies can have a political purpose (e.g., the Indian Prime Minister, Narendra Modi, effectively used selfies with himself, with celebrities, family and party members during the election period in 2014, Baishya, 2015), for virtue-signalling by, for example, standing next to a figure of power, or to draw attention to the environment, event or a social cause (Zhao & Zappavigna, 2018). The practice of selfie-taking has altered tourist photography, raising questions about sustainable tourism (Pearce & Moscardo, 2015), and it has also altered photography etiquette at mass events and entertainment venues. The reason that selfies matter for discussing personalization density is that the qualitative difference in volume (amount) and pressure (social purpose of selfies) have different consequences for mental health. Selfies afford an increased sense of purpose and achievement for people who share daily photos during a major life change. Selfies are a way to check in, I snap, therefore I am, as Katy Evans Bush wrote (http://farcryfromhackney.com/). There is also research that shows that higher number of selfies is associated with worse romantic relationship, particularly if the individual’s selfie-posting relates to promoting one’s body (Ridgway & Clayton, 2016). A beautyenhanced selfie from a sologamy (a marriage ceremony where a person gets married to himself or herself) is, in a theoretical sense, denser in personalization than a selfie with a facemask with a slogan “I can’t breathe” taken at a #blacklivesmatter protest. Selfies extend our good and bad intentions and they signal our belonging to others.

Density

149

Selfies are a well-known example of a self-extension, but there are other, less known, examples in the psychology literature. As someone who has worked with children with language difficulties, it was rewarding for me to find that researchers have used personalized self-extensions (personalized mnemonics) for language learning.

Personalized Mnemonics In the 1970s, researchers established that images could help children learn new words (e.g., Bull & Wittrock, 1973). A plethora of picture-based dictionaries, flash cards, annotated photographs and diagrams followed. The image-based method of word learning assumes that visual association helps in assimilating information about a written word. The method is limited in two major ways: first, it only presents one meaning of the word, but most words have several meanings. Second, it presents the words out of context, but words are used within contexts. Nevertheless, the word-learning technique is better than purely written text, as documented in several classroom-based studies (Levie & Lentz, 1982). When studying word learning with children who have profound educational needs, Professor Kieron Sheehy came up with an ingenious idea. He developed the so-called handle technique, which consisted of children drawing a small image next to a new word they were supposed to learn. The key to the handle technique is that the handle is abstract and simple, and often cannot be understood by another person (it looks like a squiggle or an odd mark). The handle encodes the children’s personal meaning of a new word. When children can’t read the word “chair,” for example, they are prompted by their small drawing of what the chair looks like, and to remember the sound associated with that image. Personalization allows this to happen as it is used with feedback cuing and draws on the self-referential effect documented in the memory research that I mentioned earlier. Sheehy’s (2002) handle technique addresses the limitations of the picture-based word learning technique and it also acknowledges its potential role in associating images and words (Note 5.2). Adults are not skilled at creating images (neither personalized

150

The Future of the Self

nor generic) that represent a child’s imagination of a word (Sheehy, Ferguson, & Clough, 2014), so they should leave the handle-drawing up to the child if they want to enhance their word learning. Personalized mnemonics are an example of optimal density used for educational benefits. So why isn’t it more widely adopted, you might be asking. Teachers need to work with children to help them with the handle and marry children’s imagination of a word with its actual meaning, contextual use, pronunciation, etc. This takes time, patience and dialogue. Commercial models of personalization provide children with pre-made, customized pictures instead. I wrote in Chapter 1 that customization lies in-between generic and personalized design. I want to spend a paragraph on explaining the perhaps counter-intuitive claim that customization is not optimal density in personalization.

OPTIMAL PERSONALIZATION DENSITY Optimal personalization design requires close collaboration with children and the adults looking after them. This costs time/money, and which requires child development expertise, following careful ethics of involving children in design, seeking their ongoing consent and sensitive moderation of discussions (see Druin, 2005). A personalized online world is a difficult territory to enter because of children’s hypersensitivity towards their online persona. Studies show how children’s subjective feelings as well as physiological markers such as children’s skin conductance levels, spike when playing virtual games that represent their persona (Bailey, Wise, & Bolls, 2009). Perhaps given these complexities, designers typically settle for the easier solution and replace personalization with customization. Children’s social media hide children’s identities behind avatars but the protection of children’s privacy does not need to be about hiding children’s faces behind cartoon characters. Children are tempted to use adults’ sites such as Instagram or Facebook and this is partly because these sites are fully open to the user’s own photos. Similarly, with physical resources, such as books, the tradition is to produce books according to group-level categories such as age, reading level and to anthropomorphize the

Density

151

main story characters. Children thus encounter personified animals that talk and feel as humans, as the people they know in real life. Yet, there is no clear-cut research evidence to support this practice. Some psychology studies show that blurring fantasy with reality in anthropomorphic books is not helpful for children’s knowledge about animals (Ganea, Canfield, Simons-Ghafari, & Chou, 2014) and that realistic storybooks support children’s story comprehension (Kotaman & Balci, 2017). Others indicate that it does not affect children’s factual understanding about the animal world (Geerdts, Van de Walle, & LoBue, 2016). Latest studies show that children strongly prefer stories that explain why and how things happen (Shavlik, Bauer, & Booth, 2020). Some publishers and children’s media producers may not even realize, but their set ways of portraying children and characters in their products might comprise children’s learning. Reflecting on the success of Sheehy’s handle technique, I have proposed that we should orient ourselves to develop educational resources that include children’s volitional, genuinely personalized, “self-­extensions.” In children’s books these could be children’s own drawings, for example, embellishing professional illustrations. In online games, these could be micro-servers (i.e., secure spaces for storing personal data) with children’s voiceovers. These do not seem as very difficult design changes to implement, so why is the drive for dense adaptive personalization so appealing to designers? There are two parts to the answer and the first part relates to an outdated metaphor concerning the brain-computer connection. The Computer as a Human Brain Metaphor Technologies are made by humans and technologies thus neatly replicate the mind–body understanding of self: the body is the hardware and the mind the software. Such a human–computer analogy was suggested by the American mathematician Norbert Wiener, who in 1961, brought to wider usage the word “cybernetics” and popularized war-deployed computer machines among engineers. Wiener described the functions of computers in relation to the workings of a nervous system. Wiener may have not anticipated how powerful his metaphor of the human body and the computer system would be for decades of computing research.

152

The Future of the Self

The current Internet works a little bit like a primitive nervous system: Web 2.0 stores personal memories and sends reminders. At the time of writing, Web 2.0 is very limited in making the unique personalized connections that individuals can make in their heads, but that is precisely why the web needs more personal data and more personally authenticated connections between those data. Web 3.0 is supposed to remember, predict and evaluate events more akin to the human brain. For some topics, Web 3.0 will be able to “think” in a more systematic and reliable manner than humans. Some technology utopians, therefore, believe that if they can digitize their brains, they will find the solution to happy and eternal life. Powerful metaphors can be dangerous too: if we portray the human brain as a computer, we imply the mind can be brought down to a set of commands. If we then extend the metaphor to all personal data belonging to the “cloud,” we mistakenly assume that our identities can be stored in a fictitious place that belongs to everyone and is free from socio-political ideologies, economies and power structures. Professor Rodney Brooks has been challenging the computer metaphor in relation to robotics design and AI: rather than thinking of robots as machines that replicate human brain with a set of commands delivered top-down from the head to the limbs, he advocates for embodied cognition theories (e.g., Louwerse & Jeuniaux, 2010), which situate knowledge-building in the interaction with the environment. The whole organism (the whole robot or the human body) interact with the environment, there is no body–mind dualism and there is no priority given to the mind in locating human intelligence or AI. The relational self-perspective is commensurate with this view. From the relational self-perspective, the human brain–computer analogy is an inaccurate metaphor: the human brain does not work without the involvement of other organs and other human beings. The second part of my answer is that dense personalization works well for economic applications that splinter the “self” into units that can be monetized and distributed across products and services. If the self is a network of distributed fragments, then it can feed into the establishment of multiple platforms, organizations and companies that compartmentalize a lived experience

Density

153

into a set of sellable units. Internet of Things for adults and Internet of Toys for children are an example of monetizing the fragmented self. The advent of genetic engineering pushed the boundaries of understanding the human nature as malleable. The self is not “distributed, dispersed, atomized” (Comfort, 2019) because even in strictly scientific terms, “you” are more than the contents of your chromosomes. The human body contains at least as many non-human cells (mostly bacteria, archaea and fungi) as human ones. The recognition that identity is relational has huge implications not only for how we study neurological networks but also what we understand as human consciousness. Dan Zahavi (2008) deals with one of the least resolved questions in science and philosophy – what is self and subjectivity. He sees the self as a narrative construction (Dennett’s tradition) and self as an experiential dimension (Husserl’s tradition), which brings him to a “non-egological” theory of consciousness. In the spirit of phenomenology, Zahavi asserts the inseparability and reciprocal illumination of self, others and the world. Understanding these interconnections gives us an abiding insight into the untenability of commercial and political models of personalized services. These approaches explicate the view that personalization can rise indefinitely, without any need for pluralization. In the current personal data models, the layers of self grow and grow, overshadowing the principle of being. It reminds me of the weed metaphor, captured delightfully by Helen Creswell (1973) in her children’s novel The Bongleweed: […] the weed frightens peoples as it spreads and grows at an arm’s length a day, invading other people’s gardens. But neither the physical nor the digital self is an uncontrollable weed. We have agency in taking care of our shared earth. We all need to act on a kinder and more sustainable world that respects socially just societies and natural resources. It is within this spirit that I end this chapter with my personal reflections on the growing density of personalization. The problem is not of whether personalized education should be led by technologists, governments or

The Future of the Self

154

for-profit companies, the question is more fundamental: “to what extent is the urge for dense personalization desirable?” Alternative Metaphors The “self” and the “other” are realized through countless gradations, that co-exist and overlap in different situations. The extended and relational self theories offer solid frameworks to structure an ongoing critical reflection on the density of “self” in relation to others. In the twenty-first century, we have surrounded ourselves with a thick cloud of data-based representation of our own selves that crowds out pluralization. Our main strategy to disperse the density should be by remembering who we are to each other. The autobiographical self is the “remembered self” (Neisser & Fivush, 1994) that is an accumulation of autobiographical memories and can be thought of as a life narrative. Specific and general memories of personal events. The extent of truth in these self-narratives and studied extensively by Robyn Fivush in parent-child reminiscing studies. In Neslon and Fivush’s (2004) “Social Cultural Developmental Theory,” the connection among narrative, language and children’s memory skills is directly relevant for the amount and kinds of memories we construct about our lives. Fragmenting our autobiographical selves into multimedia data points and letting automatic and human-driven algorithms amplify them gives rise to what I would term Pinwheel Selves. Those kinds of selves are not only fragmented and amplified but like the glitters in a big rotating firework, their sparks and flame make the wheel rotate at speed. This makes the display very spectacular but is suited for only short-lived experiences. We need to slow down to not end up in an ego-land. There is a lot of happiness in slowing down. The poet Naomi Shihab Nye expressed this with uncommon beauty in her poem Small Basket of Happiness by reminding us that if we quietly remembered all those “whom we loved,” we would not only slow down but also “bend.” Getting closer to our roots, to the soil where all life starts and finishes, provides a contemplative ground that needs to be trudged through if we are to survive the pace of digital developments.

Density

155

My examples of bodily self-extensions in this chapter are not a warning about a distant future but a short list of the risk factors that prevail in the desire for dense personalization. We risk jumping on a bandwagon heading to a super-intelligence utopia where algorithms relentlessly respond to narrowly minded algorithms. As we are transitioning into Web 3.0 we are thus faced with a choice: do we position the “self” as a set of fragments that can be digitized and replicated, or do we find its place in humble, unhurried connections to others?

This page intentionally left blank

6 SEQUENCE

The question of sequence fares best among historians and geologists, who seek to establish the origins and developments of humans and the Earth, but it is also a popular question in education. Before we ask the question “when should we introduce personalized education?,” I want us to ask a few prior questions. First, what makes personalized education different from standardized education? Second, what makes effective personalized technology (and educational technology more broadly)? Third, how can personalized and pluralized education co-exist? To answer these questions, I need to debunk some popular myths related to notions of sequence. These myths speak volumes to the sequence metaphor, which points to learning proceeding through stages and predictable changes. Sociocultural researchers follow a different metaphor: that of dialogue that assumes that each individual has some knowledge to offer (there is no blank slate), regardless of their background or life experiences, and this knowledge can be negotiated and enriched in conversation with others. There are three myths connected to the idea of sequence in education that rely on dichotomous thinking that separates one thing from another and ranks these things in importance. I will dispel these myths step by step so that you can build up your own chain of thoughts.

157

158

The Future of the Self

MYTH 1: PERSONALIZED VERSUS STANDARDIZED EDUCATION A lot of hype about tech-delivered personalized education forgets the strong pluralization values enshrined in standardized education. What seems further confusing to many educational visionaries is that personalization can be used both for personalizing the content and context of learning. An example of the former would be an individualized book adjusted to the child’s learning needs, and an example of the latter would be a child-centered education system that follows the child’s lead. Moreover, there are many mutually contradictory definitions of personalized learning (and personalization itself as outlined in Chapter 1). When school leaders explain personalized education they often blend a client-focused definition of personalization with the long history of child-centered education in developmental theories and the many sub-themes that emerged through it. As the MiT Integrated Learning Initiative specifies, personalized learning boils down to the optimal conditions that support individual development. The optimal conditions vary, and the task of educational research is to define them for individual children. The best part of personalized education – understanding human individuality – has been explored by Rose (2016), who rejects the idea of comparing children’s performance to an average. With his focus on individuality and human variability, Rose (2016) advocates for studying individual variability within individual contexts. He states that knowing what motivates children and why would help us abandon an education system based on unachievable averages. Rose’s thinking was influential for many personalized edtech providers, some of whom misinterpreted the idea of individuality by advocating that the cure for all ills of public education is professional coaching of children’s unique talents and abandoning the creativity-deprived standardized curriculum. However, this criticism of standardized education only sticks to its caricatured version. Standardized education standardizes learning activities and establishes children’s achievement by comparing their performance to an average for a reason. Professor Daniel Koretz (2017) makes it clear in his book The Testing Charade that US schools need standardized education to narrow the gap between minority and

Sequence

159

White students and to compare national performance versus international standards. Most effective education approaches, therefore, blend the best bits from personalized education (agency, choice and focus on children’s unique life trajectories) and the best bits from standardized education (valuable information on all children’s performance). The mistaken assumption is that the two are mutually exclusive. This point becomes obvious when we consider learning and assessment together – the two constituting parts of education.

PERSONALIZED AND STANDARDIZED ASSESSMENTS The aim of standardized tests is to verify children’s acquisition of fixed procedures and facts, which is important for guiding teachers’ efforts, Koretz says. He adds in the same breath that in a narrow application of standardized education, the “test-oriented education”, the focus is only on linear and quantifiable knowledge. It is impractical to assess everything, so standardized assessments measure a relatively narrow range of skills and knowledge, often sidelining other aspects of students’ learning. This creates systems where value is placed on what is easy to assess or evaluate, rather than deeper or more interconnected knowledge (Frede, Gilliam, & Schweinhart, 2011; Riley-Ayers, Frede, Barnett, & Brenneman, 2011). Tests that compare groups of children against each other place an emphasis on factual knowledge, basic literacy and numerical knowledge, and are thus a step away from, for example, arts, background character education, value-based education, philosophy or play. These latter non-quantifiable knowledge pursuits shape each child differently, away from the homogenization promised by standardized education. Narrowly defined, frequent and high-stakes testing contributes to a culture of stress that undermines students’ beliefs in their own self-efficacy (Abeles, 2015). If following standardized assessment is backing the wrong horse, then one might suggest that the solution is to flip back the coin and try personalized assessment. This idea is not new, in fact several educators have been advocating for age-adjusted scores in national exams, particularly for children under the age of 12 who often develop at a different pace (Sammons et al., 2004).

160

The Future of the Self

There are problems with personalized assessment too, however. Personalized content of assessment is a can of worms. It is unlikely to work if ­professionals are appointed through personalized certification models and awards. Moreover, if we pursued personalized learning and personalized assessment, we would get what Archilochus called many hedgehogs but not many foxes, that is, people who know one thing very well but do not have the flexibility and resilience that arise from knowing many things. If standardized learning content with standardized assessment and personalized learning with personalized assessment have significant flaws, then perhaps their combination is an optimal educational solution. One possible combination is to have the learning content personalized and the assessment standardized. This is followed in several UK-based academies and US-based charter schools. In these schools, parents pay extra to have their children enjoy student-led/studentcentered, project-based learning. Yet, at the end of the school year, the children sit the same tests as their peers attending traditional schools. During the school year, children with personalized education lead their own multimedia projects and at the end of the school year they are told to sit pen-and-paper exams based on dry international assessments. The academies teach children how to drive cars but the government assesses their horse-riding skills, as Professor Stephen Heppell blogged about. If you think that adopting game-based assessments for formal education would solve the issue, I might disappoint you by writing that it would actually negate both the game and assessment. Games are games because they are fun spaces in which children can explore, make mistakes, in their own way. Official rating and evaluation would turn the games into social competitions and offer a limited evaluation of what children actually know. Indeed, the disappearance of the creative element through the introduction of assessment may be one of the key reasons why LOGO fell out of favor in many classrooms (Agalianos, Whitty, & Noss, 2006). Instead of children coding the LOGO robot to play a loud tune to pull prank on their classmates, they needed to give the robot basic instructions to travel tidily around a pre-determined route which could be formally assessed. The other possible combination is to have standardized content and personalized form of assessment. The key difficulty here is that it would require significant investment in technological solutions that

Sequence

161

genuinely support the diverse ways in which children express their own meanings so that they can be objectively verified. Objective verification is difficult with commercial funding, especially because commerce is optimized for bias, while scientific research is optimized for objectivity and neutrality. So long as the personalized edtech is in the hands of commercial providers, this issue cannot be addressed because commercial providers always have a vested interest in continuing to provide the product to the target market, which means they operate with a mindset of market competition rather than an individual child’s potential. When such companies take over public education, they typically offer a whitewashed version of differentiated instruction focused on learning styles. Even though the learning style theory has been disproved by research as counterproductive (Note 6.1), many edtech providers equal their personalized technologies with differentiated learning, which accommodate autonomous learners driven to fulfill their own personal goals. Even though there has been sold scientific evidence on different cognitive styles since the 1970s (Witkins, Moore, Goodenough, & Cox, 1977) and multiple intelligences since the 1980s (Gardner, 2011), differentiated education is not about which category students fall into. Differentiated instruction, as explained by Carol Ann Tomlinson (2014), is about providing suitable alternatives to individual students, without assuming one universal model of instruction for all. Students compete against themselves, not against each other, and develop their own preferences and interaction style by reflecting on what they (dis)liked in the past. This understanding is not what you would find embedded in the so-called innovative edtech, indeed many are based on remarkably outdated behaviorist learning theories where a stimulus produces a response that gets categorized according to a simplistic framework. Even with my brief account of the blind spots in the co-mixing of personalized/standardized, form/content, assessment/learning you can hopefully see that unless their complexities are disentangled, wrong combinations can result in a conflation of learning and assessment, deliberate or inadvertent. The optimal solution lies again in careful adjustments made to the standardized and personalized content and assessment models. Such changes require patience and perseverance and a multi-disciplinary approach that combines learning sciences with latest technology design solutions.

162

The Future of the Self

It is one of the enduring perplexities of education that there is no one educational model that will ever work for all children (even though national governments strive for providing universal models of education that would work for all children). I have no intention of proposing a new educational utopia. One thing is certain, however, if we want to shift from the caricaturized versions of personalized and standardized education, we need to stop pitting the personalization/standardization ideals against each other. The history books tell us that the ideals of Western education has proceeded in a pendulum-like fashion between personalized and standardized education models: it started with personalization in the form of private tutors for emperors and kings, then turned to standardization during the industrial revolution and in the twentyfirst century, it returned to personalization with artificially intelligent personalized tutors (Kucirkova, 2017). At the beginning of the second decade of the twenty-first century, personalized education got advanced with quasi-market policies, such as funding schemes attached to individual learners (e.g., the Pupil Premium scheme in the UK) and the school choice system. National pursuit of privatization of the education sector and performance-based accountability measures enabled many schools to follow their own methods and teaching strategies. In academies and charter schools, children experienced personalized instruction but in traditional primary and secondary schools, students continued with standardized instruction. Is the education pendulum doomed to swing forever? At their core, both personalized and standardized education grapple with crucial issues around equality and equity. Standardization places more emphasis on equality, and personalization places more emphasis on equity. In order to qualify as two fair educational processes, we need to abandon the myth that they stand in a neck-to-neck competition. Both personalization and standardization need to approximate the two poles of individualization and universalism that define them. MYTH 2: EDUCATIONAL TECHNOLOGY VERSUS HUMAN TEACHING When it comes to technology and education, we need to distinguish whether we talk about technology-driven, technology-mediated or

Sequence

163

technology-enabled education. Technology-driven personalized education places emphasis on each child having their own personal technology, as encapsulated in the idea of bring your own device (BYOD). The obvious problem with the slogan is the emphasis on each child bringing their own device rather than their own knowledge. All children have knowledge to bring to the classroom but not all children have technologies. Despite initial enthusiasm of several local governments, many abandoned BYOD after it became clear that the set-up exacerbated the divisions between those who have and those who cannot have their own device (Parsons, 2014). On a broader level, the one child–one device policy suits corporate budgets but not collaborative learning in schools. Educational research shows higher learning rates with learning delivered in small groups rather than individually. The UK-based Education Endowment Foundation (Note 6.2) reports that if personal mobile device is used in small groups of three–four children, children’s mastery learning is higher. Mastery learning is a form of learning that breaks down the learning content into smaller chunks. Students take responsibility for supporting each other and directly instructing each other. Such peer support is particularly effective in subjects with exact measures and outcomes, such as mathematics. Again, the context matters. In classrooms of very high child– teacher ratio, the individualized instruction provided by a welldesigned app can offer children a learning experience that is richer than a classic teaching method (see Outhwaite, Faulder, Gulliford, & Pitchford, 2019). This is why in countries, such as Malawi, with lack of qualified teachers and high illiteracy rates, app-based teaching of basic language and numeracy skills is an effective way of tackling educational disadvantage (Outhwaite et al., 2019). Having said that, there are many classic teaching methods that cannot be replaced by an app, regardless of the context, for example, classroom debates on ethics, empathy or civic and moral reasoning. This example adds to the call for considering all 4Cs for children’s learning: the wider Context of technology use, the Content of the activity, the individual Child’s characteristics and the Community in which these children grow up. Those who make decisions about schools’ investment in educational technology should also remember that many, if not most,

164

The Future of the Self

edtech companies are driven by economic reasons. It is no secret that the edtech market is a lucrative global market, projected to be worth £252 billion in 2020 (EdtechEurope, 2019), with highest growth rate in Asia and India and increased globally after the Covid-19 pandemic. A technology-driven model of personalized education replaces human teaching by a digital tutor, while a ­technology-enabled model of personalized education is fundamentally about children’s agency: allowing learners to shape the choices they make, with or without technology. Just like “becoming brilliant” (Golinkoff & Hirsh-Pasek, 2016) involves both free play led by the child and guided play led by the educational professional, so does formal education involve both teacher-led and digital tutor-led subject teaching. Those who subscribe to the edtech myth often emphasize transformative learning experiences offered by digital tutors. When we lift the veil of such technology-driven transformations, we will see that the programs are not personalized but tailored to reach the same goal. The children might be learning at different sequence or pace, but they all learn the same set of facts. Such software programs are often bought by parents who want to accelerate their children’s learning. In doing so, the eager parents reproduce the inequalities between parents who “hoard opportunities” for advantaged children, and those who leave the learning to the public education system alone (see Reeves & Howard, 2013). From this perspective, technology-driven personalized education has re-introduced differences among students and exacerbated socio-economic disadvantages – an issue typically studied by economists on country-level in relation to mass-customization (e.g., Malhotra, Ulgado, Agarwal, Shainesh, & Wu, 2005). Educationalists need to tread carefully with socio-economic, cultural or learning differences among children. For the founder of the social identity theory, social psychologist Henri Tajfel (1974), the essence of inter-group relations is the psychological experience of difference. Belonging to one social group activates feelings of belonging simultaneously with feelings of tribalism and depersonalization of out-group members. The consequences of small-group formation can be both socially destructive (e.g., small gangs) and socially beneficial (e.g., local community projects).

Sequence

165

Technology-driven personalized education that increasingly uses learning analytics and machine learning for more precise personalization does little for harnessing the benefits of diverse groups. Let me go off on a slight tangent here to explain the core problem of the technology-driven personalization. The experience of a conflict between the self and the other is not a bad thing, in fact it can help with learning, as long as there is effective communication within and between the groups (Bahrami et al., 2010). Understanding the whys and hows of effective inter- and intra-group communication involves understanding the evolutionary preference for one’s in-group relative to out-groups. A large body of psychological research deals with the human tendency for dehumanization of out-groups. The ones that are relevant for us here are those that draw on deep personalization processes. For example, naming out-group members with their first names and describing them as feeling specific emotions (for example being disappointed) can help minimize the out-group bias (Leyens, Paladino, Rodriguez-Torres, Vaes, Demoulin, RodriguezPerez, & Gaunt, 2000). On a broad conceptual level, we can see similarities between what happens in approximating in-group and out-group members and a child’s learning more generally. The best personalized education programs are based on real-life scenarios and problems-solving tasks, so that children can relate unknown information to what they know. Authentic learning scenarios and texts that relate in authentic ways to students’ experiences are at the core of effective reading programs, such as the concept-oriented reading instruction and guided inquiry supporting multiple literacies (Snow & Biancarosa, 2003). These programs work because they approximate the learning content that is unknown to the child (and thus represents knowledge of the out-group) to what the child knows (authentic knowledge of the in-group). This is not what ­technology-driven education does. The third myth that circulates around personalized education professes that personalization and pluralization can be, and need to be, separated. The myth has far-reaching consequences for whether we conceptualize knowledge and teaching as a delivery-model or a relationship between teachers and learners.

166

The Future of the Self

MYTH 3: PERSONALIZATION VERSUS PLURALIZATION You will recall that in Chapter 3, agency was explained in terms of self-determination and belonging. Both aspects are related to motivation and academic achievement (Goodenow & Grady, 1993; Standage, Duda, & Ntoumanis, 2006). A manifestation of this relationship is visible in classrooms, where children are motivated to signal “togetherness” and belonging to the group by adopting the discourse and practices established by the teacher and their peers (Rodrigues-Leon, 2019). The promotion of competence, autonomy and relatedness nurture self-determination, which is closely linked to intrinsic motivation, which is also related to children’s competence, and which fosters stronger social development and well-being (Ryan & Deci, 2000). Democratic classrooms are, therefore, those that provide opportunities for children to exercise not only their “right to be included, socially, intellectually, culturally and personally” but also “the right to be separate, autonomous” (Bernstein, 2000, p. xx). Regrettably, the personalization–pluralization division is fuelled by the misunderstanding that an individual’s motivation to belong is separate from the individual’s motivation for self-determination. As you will remember from Chapter 3, the glue between the two is agency, so separating P–P is a negation of a basic human right. Belonging and self-determination are in a mutually reinforcing relationship to each other and a recognition of this reciprocity is a long-term goal of all good educational programs. In her interview with Krista Tippett (2018), Robin Wall Kimmerer said: “An educated person is someone who knows what is their gift and how to give it” and from this recognition, educated people “reclaim agency and responsibility.” This is why identity theorists have been studying for decades the psychological processes and educational outcomes connected to belonging and self-determination. In the classic social learning theory proposed by Albert Bandura, reciprocity occurs on all levels of human behavior. Bandura conducted numerous psychological studies that show that children observe and imitate others and use this knowledge to guide their action (Bandura & Schunk, 1981). Belonging theorists (Mcmillan & Chavis, 1986)

Sequence

167

explain that diverse individuals can form communities if they find a common ground and reciprocal understanding in shared values. Children are motivated to learn because they want to belong to the world of those who know more than them. At the same time, children are motivated to learn because they want to resist and challenge the more knowledgeable others and stand out from them (Litowitz, 1993). It is a two-way traffic system, a Jacob’s ladder of motivation, which individuals climb up and down to negotiate their place in society. Another important misunderstanding related to the ­personalized– pluralized division is that of the desired difficulties in learning that I introduced you to in the previous chapter. The popular saying “no pain, no gain” conveys that learning is more than simply fun and enjoyment. Desired difficulties are important to ensure there is a degree of dissonance and conflict for learning to occur. The psychologist Jean Piaget wrote about this in the 1950s in relation to the assimilation–accommodation process of knowledge acquisition (Note 6.3) and John Hattie’s (2012) synthesis of 800 meta-analyses mentions “challenging learning intentions” The optimum equilibrium has also intrigued philosophers, who like to juxtapose pain and pleasure in learning: We don’t really learn anything properly until there is a problem, until we are in pain, until something fails to go as we had hoped … we suffer, therefore we think, and we do so because thinking helps us to place pain in context. (De Botton, 2012a, p. 73) De Botton is right, there needs to be an element of painful de-­ personalization to bridge the private with the public or the known with the unknown. Cognitive psychology research shows that there needs to be a balance between contextualization and de-­contextualization, educational choices and challenges and specialization and generalization (Cordova & Lepper, 1996). The creation of an optimum equilibrium between the two antitheses is a long-standing goal for education but it is rarely discussed by technology designers. Educational myths can spread like a virus through the educational bloodstream, especially if the system is weakened with

The Future of the Self

168

short-sighted government policies. Technology determinism blocks school arteries and disempowers teachers. The human body has evolved to deal with both oxygenated and oxygen-depleted blood, so too schools need to evolve to deal with both personalized and pluralized ways of teaching. This means that teaching needs to meet minimal curriculum standards and mastery learning. It also means that the provision of learning needs to be at times individualized for each learner (personalized) and at times delivered in diverse groups (pluralized). All the three myths discussed so far circulate around one powerful myth that combines them all: the sequence myth. It is a difficult topic, so let me introduce it on a light note: When the 47-year-old rapper and actor, Snoop Dogg, received a star on the Hollywood Walk of Fame in November 2018, he finished his speech by thanking himself. His words were: “Last but not least, I want to thank me for believing in me.” You would have guessed that it was not the award but Snoop’s speech that made the headlines. Perhaps he meant it as a joke, perhaps he was insecure in his own self-confidence and needed to affirm it publicly. What Snoop clearly demonstrated is that the sequence in which we think of (and thank) us and others, matters hugely. THE SEQUENCE MYTH The simplistic binary that underlies the sequence myth is that personalization//pluralization ought to be separated. If personalized and pluralized learning approaches are separate, then they can be sequenced. Which one should go first, attention to self or attention to others? Those who believe in the sequence myth say that we should start with personalization. Young children in kindergartens should be allowed to play and experiment with anything they want. At the primary school level, the child’s individual learning plan begins shrinking and is eventually cut down in favor of curriculum standards. When children enter secondary schools, their choices are even more constrained. Yet, when they reach higher education, students can choose their own learning path again. There seems to be an assumption that learning works best if the less advanced learners get prescriptions and the more advanced students get choices.

Sequence

169

Psychologists tear their hair out at this idea, but many educators wrongly assume that learning proceeds in a sequence from the basics to advanced concepts and that this sequence is driven by an intrinsic motivation to proceed from less to more (Mehta, 2019). When teaching topics that some children find boring (but all children need to be taught), teachers can adjust the activity to make it more exciting to those who are less engaged. Such piece-meal personalization is more equitable as it can be adjusted to the activity as well as the group of children participating in it. Indeed, the teachers in our interviews (Kucirkova, Linn, et al., 2020) made it clear that effective pedagogy is far more complicated than giving children free reign in predictable stages. A variant of the sequence misunderstanding is that personalization is about novelty, and that, therefore, children’s motivation can be maintained with gradual introduction of new exciting items. Some go even as far as to suggest that personalization and novelty are the same. Persuasively designed technologies profit from design associated with compulsive and addictive behavior. This is supposed to be especially true for personalized learning delivered by the latest technology, because the dominant system has been standardized learning delivered by teachers. It is perhaps engaging but not more knowledge expanding – let me explain. Engagement and Personalization The sequence myth fits the mistaken assumption that engagement is the same as learning. For sure, novelty and motivation are close allies, as shown by hundreds of studies with technologies – for example, the use of iPads in pediatrics occupational therapy has been useful in making children more interested and engaged in therapy sessions (Coutinho et al., 2017). The children pay attention to the shiny new gadget rather than the environment they would normally find threatening. But personalization effects were noted with and without technology use, with books where both personalized and non-personalized versions were new (see Kucirkova, 2017 for an overview). Moreover, if personalization was about novelty, then it would have strong but short effects. That is, however, not what Walton and Cohen (2011) found in their three-year study,

The Future of the Self

170

which showed students’ prolonged sense of belonging in a school system that emphasized personalized approaches to their learning (Note 6.4). Similarly, in consumer behavior research with adults, personalization has been found to generate stronger response not because it offered something new but because it resonated with people. Simple interventions, such as, for example, adding a personal Post-it note increased the survey return rate (Garner, 2005). Novelty and personalization often co-exist because they are part of the filtering process of acquiring new information. This doesn’t mean that they are the same or that they are driven by the same mechanisms. Some recent neurological evidence suggests that when it comes to prioritizing which information gets processed in our brain first, its distance to the individual influences the prioritization. According to the so-called nearby-hand hypothesis, the nearness of one’s hands to the stimulus directs visual perception of the object and even visual memory of it (Tseng, Bridgeman, & Juan, 2012). What is near to us does not need to be new, it does not need to be personalized to us either. Human beings have evolved to pay attention to cues that are unique in their environment because such cues often represent threats that require action. Unique cues can take many forms, including rapid movement, strong visual presence, sound preceding the arrival of new content, unusual or odd objects, and indeed novelty and personalization. The aggregation of all these cues is the core business strategy of the persuasive design technologies that I lamented in Chapter 3. Persuasively designed technologies profit from design associated with compulsive and addictive behavior. There is no good to be gleaned from this strategy for the design of holistic education systems. Nevertheless, the increased attention I mentioned in relation to personalized novel information (e.g., your child jumped 7 meters) also works for unique information (e.g., a child jumped 7.5 meters, a new worldwide record). But whether or not personalization is a stand-alone category or a sub-category of “uniqueness” remains one of the most abiding empirical questions in the field of psychology. THE P–P CURRICULUM I will finish this chapter with a reflection on the creation of an education system which abandons sequence in favor of dialogue. Such

Sequence

171

a curriculum repairs the best of standardized testing and injects the best of the science of individuality. The idea of “dialogue” has been a catalyst for classroom techniques such as dialogic enquiry, dialogic teaching, collaborative learning, contingent tutoring, thinking together, collaboration and cooperation with peers and technologies, to name a few. All these educational approaches can be described as socio-cultural and have considerable literature to support their implementation in schools, so what I present is inevitably a short selection. DIALOGUE IN EDUCATION Dialogue is a thinking mechanism which is aligned with the dialectics of life and the relational nature of being. While sequential thinking simplifies, dialogic thinking reveals complexity. From a socio-cultural perspective, to learn how learning works is to learn how dialogue works. According to Bakhtin (1986, p. 89): “Our speech is filled with others’ words, varying degrees of otherness or varying degrees of our-own-otherness, varying degrees of awareness and detachment.” Bakhtin’s quote is a powerful reminder that the language we use is full of other people’s voices and intentions. An individual cannot exist in isolation of the world surrounding them. Whatever we do, say and think is to a greater or lesser extent influenced by others. For children, these “others” are typically children’s parents, teachers and friends, but also imagined others, such as the characters children encounter in the stories that they read or watch or listen to. Others’ voices are not neutral, they influence children’s thinking, provide schema and scripts through which children internalize knowledge of the outside world and develop their own ideas. This process is a dialogic process of symbolic exchanges. In the context of communist Russia in the 1920s, Bakhtin focused on the tensions between authoritative discourses and democratic participation in society rather than on children’s development. Yet, his foresight is closely connected to contemporary discussions about children’s agency, their expression of self and learning mediated by digital technologies. In addition to Bakhtin, dialogic and dialectical psychologists are inspired by Vygotsky and Alexander Luria, Plato, Socrates or

172

The Future of the Self

Hegel, and those who pursue cultural-historical approaches to children’s development (Note 6.6). For these thinkers, dialogue should be the base note on which to build learning environments, digital or non-digital. Just to clarify: a dialogue is not about confirmation of sameness and similarity. Some refer to this process as dialectics but given the controversy surrounding Marxist dialectics (see Brandist & Tihanov, 2000 for a full account), I foreground dialogue within dialectics. A dialogue is about a curious exploration of dissimilarities. As demonstrated by the assiduous work of Professor Mahzarin Banaji, our minds are designed to search for differences and similarities. If we know well who we are, we can better understand who others are. This is a dialogical process. The self is the gift of the other, to paraphrase Bakhtin, and the self enters into relationships through language which opens the door to the wider world. Bakhtin and Vygotsky’s criticism of the consequences of a privileged, change-resistant discourse in communist Russia are remarkably similar to those of contemporary childhood theorists. They too objected to activities in which children’s voices are submitted to adult’s guidance. They knew almost a century ago that to drive innovation, teachers needed to act as facilitators, not providers, of facts. Their facilitating role is what makes classrooms rich learning spaces. According to Vygotsky’s socio-cultural learning theory, the “more knowledgeable others” such as educators, and also parents, caregivers, grandparents or older peers, influence whether children enjoy the activity and how much they learn from it. Skillful parents support children’s learning in the so-called “zone of proximal development,” which is the space between a child’s actual and potential achievement. The adult’s role is to expand and stretch the child’s zone of proximal development, not to merely accommodate it. Langford, a Vygotsky scholar, makes this point particularly well. He specified that Vygotsky thought that “the teacher should provide various kinds of personal guidance, beyond the fostering of students’ interests” (quoted in Langford, 2004). This is important and relates to the notion of “scaffolding,” which was emphasized by Jerome Bruner in the 1960s. According to Bruner, adults should scaffold, extend and support the child’s knowledge and understanding (rather than merely accommodate what the child knows

Sequence

173

or wants). Both Vygotsky and Bruner remind us that no matter how innovative or interactive new media are, adults influence profoundly whether their affordances will be leveraged for learning or not. Good teachers use dialogue to support children’s curiosity and their own funds of knowledge (González, Moll, & Amanti, 2006). Children are naturally curious and they enjoy exploring and investigating things they are curious about (Engel, 2015). Curiosity tends to decline with age, which is why stimulating learning environments are key to lifelong learning. Young children also love repetition and feel more comfortable in familiar environments. We know from research that feelings of satisfaction are supportive of learning too. Therefore, giving children choice and enabling them to explore things they are curious about and feel comfortable with, is essential for their learning (Cordova & Lepper, 1996). A dialogue in Vygotskian tradition is typically a vertical knowledge exchange between a more knowledgeable other (an older peer, teacher or parent) while in neoVygotskian tradition, dialogue happens between people, people and things, without any hierarchy of more or less knowledgeable others (Mercer, 1994). The neo-Vygotskian tradition with its emphasis on large dynamic networks or relationships between people and resources is more suited to technology-­ mediated education and the transactional, quantum-physics-orientation I advocate in this book. The foundational research of how such dialogic learning functions in homes and communities has been pursued over decades of ethnographic research. Whether it is Shirley Brice Heath, Jennifer Rowsell, Kate Pahl or Cathy Burnett, these scholars draw on the idea of dialogue to deepen understanding of more complex concepts like the role of children’s funds of knowledge in expanding children’s horizons. Their sociological and anthropological studies point to belonging as the deeper reason for why individuals personalize their environments. Based on participation or observation of families, belonging is in these studies seen as a dialectical relationship between individual agency and socialization. From this point of view, children’s choices are shaped by the social practices within which they are embedded. These scholars argue for the

174

The Future of the Self

importance of free play, imagination and popular vernacular cultures as resources to capitalize on in early years. Sadly, the ethical obligations that these scholars highlight and that we owe to children, are not part of national curricula or even wider social orders of national cultures. Particularly relevant to my focus on how technologies can facilitate the expression of children’s individuality is Wohlwend’s (2015) perspective on children’s multimedia composing and Dyson’s (1997) work on children’s writing. The two scholars articulate the diverse ways in which children bring their linguistic and semiotic resources to the school and the standardized ways in which schools actively de-personalize them. Whether it is their play with digital media or writing texts in pencil, children negotiate complex issues of representation, inclusiveness, responsiveness in their expressions, and in doing so, they manifest a profound understanding of the principles of fairness and enacted ethics. When schools inculcate children to rigid, surface-level rules around composition, children start perceiving collaboration as undesirable and replace collaboration with competition. Those who resist and defend their social inclinations are perceived as troubled children who put at risk the classroom and school community (and who often end up in the ever increasing drop-out statistics and drug-related lifestyles). Against a high-stakes accountability regime in US schools (also in the UK, Australia, Shanghai and other parts of the world), Dyson, Wohlwend and other socio-cultural scholars poetically convey the many possibilities that all children can bring to the classroom. As Bakhtin knew so well, we tailor our way of being in relation to others. To be accepted into others’ worlds, we need to create environments that welcome relational acknowledgment of individuality. The key reason I mention dialogue in this chapter, however, is that it implies a radical departure from sequence myths in education (Note 6.7). Self is built through the dialogue with others, and learning is not a straight line but is an interconnected web of inherent associations that we constantly revise in light of new evidence. In light of this, Professor Marlene Scardamalia and Carl Bereiter from the University of Toronto co-developed the knowledge building community systems with which children grow their ideas with others.

Sequence

175

Scardamalia and Bereiter (2016) explain the mistake of conceiving learning as a linear path: Force the rat along a fixed path and it will learn that path but no other. Allow it to roam freely and it quickly learns the maze well enough that it can get to where it wants to go no matter where you place it. What sets humans apart is our ability to do this kind of “learning the environment” in non-physical environments – in conceptual or idea domains. (p. 3) The technological instantiation of the Knowledge Forum includes features that facilitate the non linear process of developing new ideas in concert with others. It is striking that commercially developed personalized algorithms have not changed their linear logic since 1990s: they were designed to ensure that what you search for is what you get. If personalized search replaces sifting through pages of irrelevant content, whether online or in a big printed encyclopedia, it undermines serendipitous discoveries, choice management and self-­regulation strategies. The personalized design of research-produced technologies is very different. In knowledge building, knowledge is innovated collectively, with relationships and associations built not as a by-product but essential product of the knowledge building. Professor Anne Adams and her colleagues at the Open University call the continuous process “juxtaposed learning.” In schools that follow the Juxtlearn approach, students are encouraged to take ownership of a scientific concept and at the same time, to compare and relate it back to its academic representation. For example, students are taught about the physics concept of surface tension and in a classroom discussion, relate it to the craft of a pond skater (addressing myth 1). In the Juxtlearn activities, whether it is drafting an essay on paper or posting a comment online, edtech and human technology work together (addressing myth 2) and an individual enters into a conversation with other learners (addressing myth 3). The Juxtlearn design is consistent with the Relational Self Theory you read about in the previous chapter, according to which the reality of an individual comes into existence only when

176

The Future of the Self

it is received by the reality of somebody else. There are different degrees to which others’ response is internalized by an individual, but learning cannot happen without the dialogue between personalization and pluralization. How can this principle be embedded in design? The design of a technology strongly influences how much dialogue can happen and how much personalization will be contributed by the user. It is now well-established that the more agency children have in crafting their own contributions, such as, for example, when producing their own texts on social networking sites, the more time and care they take in crafting their online identities (Dowdall, 2009). The design that accommodates such agency is not based on rigid templates that push children to insert their content into a specific box in a specific mode of expression, but that is open-ended. In one of our projects, we compared children’s use of open-ended versus template-based story apps in a classroom with 41 Spanish 4 to 5-year-olds. Template-based apps had a gap in text for children to insert the right word (e.g., from a choice of five) and a set of story props for children to make their own story. Open-ended apps had a space for photos for children to insert any picture they liked for their own story. We found that children’s use of the open-ended apps supported more dialogue among them and more joint discussions about what the final story should look like (Kucirkova, Messer, Sheehy, & Fernandez-Panadero, 2014). Dialogue by design is P–P by design: the more space there is for one’s own contribution, the more dialogue between children, and between children and the affordances of the technology, can happen. To support this process, designers and teachers need to aim for minimally viable design/lessons, which not only provide children with the necessary scaffolds but also lots of space to develop their own ways for climbing it. In a socio-cultural P–P model of learning, technologies are built to provide space for a conversation. This sets them apart from social media and other commercial platforms that misuse personalization for social divisions. With all this fantastic work by educational researchers and strong theories underpinning it, why have the powerful myths persisted in the education sector for so long? The reasons are several: lack of mutual engagement between teachers and researchers, the lacuna of joint education/

Sequence

177

industry-research funding streams; minimal professional exchange between educational researchers and designers (Kucirkova, 2017) and of course larger structural problems of culture and politics. Taking the position of change requires collaboration I, therefore close with a call to envision educational futures with multiple perspectives and collaborative P–P at their heart.

EDUCATIONAL FUTURES Many theorists are preoccupied with the looming question: “will education follow the technology sector, evolve into a distributed model of learning where AI take over human teachers?” In such a model, the learner would be autonomous but connected to other learners through selected points of shared interest. Tegmark (2017) believes that AI questions are the most important questions for the twenty-first century, since AI allows for breaking away from natural evolution. There is a danger that with technologies designed for compulsive engagement we may lose sight of our agency and humanity. Educational programs should, therefore, foster human intelligence together with AI (Luckin, 2018), with ethics embedded in the design process from the outset, not added as an afterthought or bolt-on. Professor Rose Lucking’s reminder is not a simple footnote: as AI becomes more embodied, that is available in both body- and mind-related intelligence, the more AI becomes truly intelligent. R. A. Brooks’ (1991) writings on the future of AI in the 1980s and 1990s do not feel a world away from current innovations that embed AI into embodied, situated interactions. As AI is approaching the merger with human intelligence, it behoves us to consider, yet again, who we are to each other and to our own selves. One thing is abundantly clear: learning is not fixed but constituted through interactive relationships between human and nonhuman entities. Understanding these relationships and directly responding to the pace of change driven by technological advancement necessitates some strong learning theories. New literacy studies and actor–network theories, which have been around since the 1970s, address the abiding questions around how knowledge

178

The Future of the Self

circulates and becomes constituted through such relationships. Latour’s account of the actor-network theory explains that the web of knowledge reverberates with relationships that constitute each other through mutual dependency (Latour, 2005). The hyphen in the “actor–network” description indicates that the actor and the network are always connected, one cannot be without the other. If this sounds familiar, it is because these new theoretical movements have the Relational Self Theory (Chapter 5) at their core. Also, Brian Street’s (2003) exposition of new literacy studies explains that literacy is embedded in relationships of power. This understanding of literacies replaces the old paradigm according to which literacy can be attributed to individuals (authors vs readers), quantified and fixed (literate and illiterate societies) and delivered in a specific sequence to guarantee success. Understanding literacy, and learning more widely, as a networked event requires a humble admission of an infinite range of possible connections to our past and future selves. Infinite, even if we tried to digitize all possible data we hold about the past of humanity and its anticipated future. The machines will always work only with a fraction of what humans have learnt about self and others, with the majority of data available from most recent eras. In brief, even the most sophisticated AI-enhanced machine cannot handle the infinity of human beings. If I was to take out my crystal ball, I would, therefore, predict that education focuses on nurturing what Krista Tippett (2016) describes as inhabited wisdom. Tippett reminds us that human beings are Homo sapiens, the species of wisdom, and that wisdom should replace knowledge as the highest educational ideal. Wisdom is not smart thinking and not a set of intelligences but what it means to be human in a moral sense of the word. There are multiple pathways children can take in any sequence to arrive at an understanding – wise people know this. Tippett, therefore, calls for a patient and quiet submission to the mystery of big questions to pull us toward inner wisdom. Some researchers call the entry into wisdom “critical thinking” that links content knowledge and evaluation of counter-points. Tippett refers to it as “discernment.” Discernment is necessary to help distinguish right from wrong, fake from authentic, biased from fair and subjective from objective. Education and schools are essential vehicles to learn

Sequence

179

rules about these binaries through dialogue. If we think of learning as a lifelong process, then we need to admit that new knowledge does not arise from thin air but from systematic thinking through arguments and incremental refinement of existing knowledge. By building on previous ideas and standing on the shoulders of giants, we all – young and old learners – develop our own mechanisms for making discerned choices about how we interpret the world. To conclude this chapter, let me sketch a possible shift in the research and practice on personalized education. Joseph Campbell said that “if you want to change the world, you have to change the metaphor.” The currently popular metaphor in many Western education systems is that of a “fix it” mindset, popular in engineering or medical sciences. Medical metaphors are useful in education when it comes to interventions, evaluations and precise remediations. However, the medical metaphor does not sit well with the dialogic approach, especially not when it occurs with educational “geneism.” Educational genomics emulate the so-called precise personalized medicine model, which aims to make a precise match between an individual’s biological profile and best available evidence. The proponents of the educational genomics and behavioral genetics model (e.g., Sara Hart of the Florida Center for Reading Research) use a child’s genetic profile to make predictions of academic achievement and for substantiating support and adjustment recommendations for individual children. This has a clear application for dyslexic students, for example, who can receive targeted support from the beginning of their schooling. In personalized medicine, a precise match between the medication and the patient’s illness is crucial. Incompatibility or poor matching could result in rejection of a transplant or compromise a healing process. But there is no need for full personalization in education: as explained throughout this book, education needs a careful prescription of personalization and pluralization. The optimal level of personalized education needs to ‘hook’ the learner, but mustn’t overstretch them to self-absorption. The “precise personalized education” errs far too much to the side of self-focused, extreme personalization. Precise personalized medicine is not without its critics, even in doctor circles where personalized treatments originated (Note 6.8). Perhaps not surprisingly then, many educationalists are skeptical

180

The Future of the Self

about the medical metaphor for education overall and personalized education more specifically. There are significant disagreements between those who adopt the gold standard of measurement in medicine – randomized controlled trials – and those who believe this is inadequate for classrooms (Note 6.9). These disagreements have been ongoing for decades, and the possibility to advance precise personalization through technologies have deepened the disagreements. In search of an alternative model, I have been following a different metaphor for education: meteorology. A Meteorological Metaphor for P-P education There are three reasons why meteorology could guide our thinking about visionary P–P education. First, there is the appeal of weather for the general public: education involves children and their families, teachers, publishers, social workers, designers and policymakers – everyone should be part of the conversation. A weather forecast is an indispensable component of every news coverage, small talk and newspaper spread. If the same happened with education, there could be much more public conversation about the values we teach our children in schools and examples of effective teaching celebrated in national media. Second, weather measurement has always been a crowdsourced activity. The historian Alexandra Harris (2015) details how in the seventeenth century, people were encouraged to record the position of sun, moon, or the direction and strength of the wind. Since the seventeenth century the meteorological measurements and instrumentation have evolved significantly, but unlike other natural sciences, meteorology does not solely rely on lab experimentations. It relies heavily on distributed data-collection tools, such as weather radars and satellites, which are strategically placed in specific geographical regions. These instruments collect data remotely and transmit it to central weather stations that analyze the data. The measurements are thus contributed through collaboration of multiple collectors, human and non-human, with precision that allows remarkable prediction. If we adopted crowd-sourced prediction for education, children’s education levels would be measured by various people, in various locations, and their aggregated scores would be

Sequence

181

used to make a reasoned prediction about the future of individual children and classroom ensembles. Moreover, meteorology measurements include multiple sources of data (pressure, temperature, wind speed, air humidity and amount of rain). Educational measurements could include various sources of data too, so that children’s efforts and current knowledge are represented fairly and holistically. The overall prediction of educational attainment could be based not only on the average scores of children’s maths and literacy scores, but also children’s typical style of helping community members, achievement in sports or in cooking/gardening, as random examples. Lastly, in meteorology, manual and automated observations are combined and used to mutually augment each other. The inspiration for education is obvious: teachers’ own judgment could feed into automated data collection and vice versa, datafication could inform teachers’ judgment in making predictions about a child’s educational success. There is no example of a unified system or of one educational practice that would instantiate all elements of my meteorological metaphor. There are, however, several interventions that tap into one or more of its main ideas. I am wary of highlighting a few programs from a rich landscape but I want to give voice to the exciting university–school collaborations led by The Open University and University of Edinburgh in the UK. The annual reports of these educational future research groups (Innovating Pedagogy at the Open University and Future Teaching Trends: Education and Society at the University of Edinburgh) connect social values with technology innovations. Their collaborative projects with local schools illustrate the innovation potential of technology (without the vested economic interests of a few edtech companies) and establish core standards for value-based education systems. The projects typically involve one or two schools, often have no or small allocated budgets and are maintained through sustained dialogue with local teachers. There is no outsourcing to external consultants because the emphasis is on building the existing school’s skill-base. Such projects are small in scope, but they are big in impact. As such, they demonstrate that it is important to compare costs of implementation in light of the significance of interventions. Educational researchers call this cost-utility analysis and advocate for their use

182

The Future of the Self

in decision-making in schools (Hollands, Pan, & Escueta, 2019). If we only focus on significance, we might leave out interventions that have smaller effects and are also cheaper to implement. To put it in the meteorological metaphor: you can take an umbrella if you know it will be raining – it will not completely help you avoid a drenched coat, but it is easier and cheaper to implement than if the advice was to professionally air-dry your wet garment. The meteorological metaphor illustrates the role of dialogue in education: rain converses with sunshine and often the two co-exist, giving rise to rainbows. With a meteorological understanding of education, we might find guidelines for personalized education and its affection with pluralization. The meteorology metaphor also extends to the social mission of education and a subjective experience of weather: the weather never stays still and no matter what the official prediction, we each react to it differently. Educational disparities around socio-economic background remind us that some members of society need extra support in extreme weather conditions. To put it bluntly, in freezing temperatures the rich have fun on sleighs, but homeless people die. The intersections of socio-economic background, gender, race or class do not exist in the experience of weather and they should not exist in children’s experience of education. So far in this book I have considered the close link between personalization and pluralization. This chapter explained that for educational benefits to occur, personalization and pluralization need to interact in multiple transactions and not in a sequence. In the next chapter, I will direct our attention to the final missing piece in the puzzle of personalization: the notion of distance. What do we know about the distance between personalization and pluralization and between the other and self? Meteorologists know that distant objects are more difficult to predict. Designers know that smart technologies minimize the distance between objects and individuals. Psychologists know that for optimal development, there needs to be some distance between the self and the other and between the physical and virtual self. Life in itself is a continuing negotiation of the self-other continuum, as Kegan wrote so eloquently in 1982. But how to pinpoint and negotiate that distance is the story of the final chapter.

7 DISTANCE

The distance between the self and the other is like an elastic band: it needs to be decreased in some contexts and increased in others. Stories occur in many contexts: oral story-telling, films, comics or literary novels. Reading stories is a special case because of the connection between written words and imagination. “Reading is the occasion of the encounter with the self,” as James Carroll wrote, pointing out that mental conversation between the author’s voice and the reader’s inner voice is the basis for all good stories. The distance between authors and readers establishes a unique theater of the mind that stretches the mental imagery. It is thanks to the distance between words we say and words we read that we can live the lives of others. When reading on our own, we conjure up unique spaces in our minds and let foreign voices inhabit them. These voices help us calibrate our feelings, gain knowledge and cement these memories in the mind. In this chapter, I will discuss how stories provide a unique context for increasing and decreasing the distance between others and self. There are several explanations for the coveted status of stories in the human psyche and human history, and a crucial component in this is narrative. STORIES AND NARRATIVES You might find various, often mutually contradictory, definitions of story and narrative in the popular literature. For history scholars,

183

184

The Future of the Self

the distinction is clear: narrative is a representation of a reality, whereas a story is the meaning: a narrative is the content of what happened, while the story is what content is told. There is also a third term – discourse – which is about how the content is told and narrated (Munslow, 2018, Note 7.1). Regardless of age, socio-cultural background, race or gender, narratives are a sign of a healthy mind: people who have experienced a deep trauma or those with a brain damage cannot put together a coherent narrative about their past (Van der Kolk & McFarlane, 1996). Conversely, ­narrative techniques are excellent healing tools for transforming mental health. We think in narratives, we develop tools and tactics that follow a structure, key characters, familiar story plots: narratives provide linearity to an otherwise unstructured system of ideas (Bruner, 1991). Adding the “self” to these narratives, either in the form of the teller or receiver, concretizes the connections in the mental web. A traditional Western narrative follows a filmstrip-like sequence with a beginning, middle and an end. There is a climax, a mystery or a main message in the middle and there are characters/­ protagonists, who have certain roles and characteristics. A narrative provides a chronological record of events in the past, but it can also hold imaginings together and thus hold the key to a human future (Parkinson, 2010). As attested by the book, film and video-games multi-million-dollar industries, stories are powerful in any form – in images, dance, music, artifact creation, gestures and eye-contact. Stories are used from early childhood classrooms to retirement homes to hide, seek and perform the self (Heydon, 2012). In theology, all stories begin or end with a god or deities. In business, international consultants make successful careers by advising corporations on how to integrate the company’s story into a larger services model. In early education, children are encouraged to tell and act out stories like, for example, in the Paley’s curriculum described in Chapter 3. While some people might struggle with coherent narratives, everyone can make up a story (Haven, 2007). When given the opportunity, children will recount a story to their parents, stuffed animals or Alexa. With the ubiquitous presence of stories and their known persuasive power on identity, it is incumbent upon adults to ask which

Distance

185

story they promote for their children and why. The Internet provides a massive stage for children’s stories. With platforms such as StoryJumper, StoryBird or Scribblitt, children can listen to/ view/read or make their own multimedia stories. Immediate and archived feedback on children’s stories online (either through a viewer’s comment, sharing or like features) provide children with an acute perception of audience. In an era of multiple story-making platforms, it is fair to ask how innovative and good the content of professionally produced children’s stories actually is. A literary scholar might reply that a good story engages the reader and influences the reader’s thinking. An educationalist would add that good stories need to be semantically and syntactically complex, so that children expand their vocabularies and learn to speak well. Story images and words need to work together to encourage children’s reasoning, drawing inferences and connecting associative and working memory. From the P–P perspective, I am interested in the extent to which the stories we offer to children are both locally relevant and globally conscious, whether they portray diverse characters and resonate with the individual child.

Children’s Stor y Books Books were first produced only for adults and it was not until the eighteenth century that books for children began to be illustrated and narrated in both pictures and words. Children’s books in the nineteenth century focused on didactic content, with little creativity on the part of authors to engage the child. Over time, publishers have nurtured beautifully illustrated and convincingly narrated storybooks. What the children’s publishing industry has been less good at is to address progressive content in children’s books. Children’s books that represent the realities of mostly White, middleclass children continue to dominate the market and are the reason why campaigns such as WeNeedDiverseBooks came about (Mabbot, 2017). Some progress has been made and in 2020, children’s books that represent racial equality, alternative family structures and even gay/trans rights are appearing on the book reviewer sites. Less progress has been made in terms of children’s book formats.

186

The Future of the Self

Children’s Digital Stor y Books A popular e-commerce business model is to provide a platform, rush its adoption among large populations and wait for others to populate it. The launch of tablets preceded the content it should hold. The initial wave of digital books and story apps released on the market in 2010–2011 was very low in content quality. Several researchers, including myself, advocated for more government and private investment in the development of original digital books for children (e.g., Sari, Takacs, & Bus, 2017). Digital books (also known as e-books, interactive picture books or story apps) are the stories that children can access on a tablet, iPad or reading device. Best children’s digital books are hybrids between print books and digital games. Unlike simple e-books available for desktop PCs, digital books have several new features. For instance, children can press buttons for the story to be played to them, they can activate hotspots which unlock extra features (e.g., rubbing the tummy of a story character makes it jump and laugh). There are also embedded dictionaries and hyperlinks which provide definitions/synonyms for specific words in the book. These are exciting new features but while there have been some creative digital books leveraging these design features, there are very many digital books with poor design and content showing romanticized realities in the story plots (Kucirkova, 2016). This has implications for children’s learning. Reading of poorly designed digital books, such as those that contain many bells and whistles, is correlated with children’s lower story comprehension, vocabulary learning and disrupted parent– child conversation (Takacs, Swart, & Bus, 2015). Fixing the problem of low-quality children’s digital books requires concentrated effort of everyone involved in the book production cycle (authors, illustrators, designers or publishers), as well as policy-makers supporting innovation and those who facilitate children’s access to books, that is, librarians, parents and teachers. Children enjoy digital books as much as print books and often, more: reading digitally is a preferred way of reading for reluctant readers, readers with few (or any) books at home and children who traditionally don’t enjoy reading on paper (Picton & Clark, 2015). The added value of digital books for children with special educational needs and language

Distance

187

impairments is well-documented (e.g., Korat, Graister, & Altman, 2019; Shamir, Korat, & Fellah, 2012) and well-designed digital books (developed by researchers or co-produced in research-design partnerships) that were shown to contribute to children’s vocabulary growth (Smeets & Bus, 2012), comprehension (Korat, Shamir, & Heibal, 2013), engagement and enjoyment of the story (Richter & Courage, 2017). In some cases, an e-book can be as helpful as a parent reading with the child (Takacs, Swart, & Bus, 2014). This is particularly important for parents who are not used to reading routines at home or who are expected to read books that are not in their native language. If I adopt a risk-averse (rather than solution-oriented) approach, I can understand why the American Pediatricians (American Academy of Pediatrics, AAP) heralds children’s print books as superior to digital books and advise parents to provide children with print books only (Tomopoulos, Klass, & Mendelsohn, 2019). For sure, in comparison to digital books, print books have benefits that have been documented over several decades by interdisciplinary researchers. But shunning digital books all together would fail the children who might need such books most. The restrictions of the Covid-19 pandemic brought the benefits of e-books into sharp focus and perhaps somewhat helped reframe the negative debate surrounding reading on screen (and children’s use of technologies more broadly). It might be that a more nuanced approach will replace the AAP guidance later on, as it was the case with the AAP’s initial guidance on children’s screen time. Let there be no doubt – print books are, and will continue to be, important for all children’s reading. For babies and infants, in particular, who treat books as objects and like to chew on them or hide behind them, print books are much better than e-books. However, as children grow up and learn the first letters and words, it is important that they are exposed to a variety of story types. This is not only about diverse story plots but also diverse story formats, such as e-books enhanced with AI or adaptive algorithms. The earlier children are exposed to such variety, the better they become at making discerned choices about the books they prefer and can make themselves. It is the cycle of reading–writing and not a binary digital/print reading that we should

188

The Future of the Self

be propagating among children. Besides, despite concerns in some quarters that the digital format will eliminate print books, the surge of digital books in early 2000s has been paralleled with a surge in a wide range of children’s print books, such as flap book, carousel book, pop-up book, fanfold book/accordion book and playbooks. Children’s books following the lives of unknown story characters allow for self-distancing and processing of difficult emotions (Nikolajeva, 2015). Whether this effect is limited to reading stories is open to debate. There is an increasing push in adult reading studies to examine the presumed unique benefits of literary fiction (reading long narrative texts such as classic novels) on what the reading scientist, Professor Maryanne Wolf (2018) defines as “deep reading” processes, which in her definition, consist of internalized knowledge, analogical reasoning and inference, perspective-taking and empathy. Wolf is concerned that the skimming that happens on screen with short texts transfers to skimming when reading all texts. Following hyperlinks for a deeper understanding of a text is essential for learning, but following hyperlinks with no real purpose (the so-called Wiki walking) is not good for the reading brain. Insights from adult studies cannot be directly applied to children given that children’s attention span is shorter and children’s literature has different traditions and values, but it is certainly an interesting proposition that reading, as opposed to listening or viewing stories as films, is more conducive to deep thinking. I am interested in meaning-making features that are not mediumbound, (such that they do not change with every release of a new reading device). Personalization is such a feature as it can be present in both print and digital storybooks (Note 7.6) and it can be studied both in terms of story content (a story where the main character is called your name) and story format (a story presented on Kindle because you like e-readers). Personalization is thus an elegant way of overcoming the digital–print dichotomies in children’s literature studies and in the next section, I summarize some exciting research in this area. PERSONALIZED STORY BOOKS No one has actually researched this, but it is possible that children’s literature started as personalized stories, with references to

Distance

189

children’s own lives. There are certainly many children’s authors who readily admit that the first book they ever wrote was for their own child. In all the different communities in which I have researched personalized books (Slovakia, Japan, Spain, USA, Norway or UK), there has not been a single incidence of a child who would not be excited when they got a book made by their parent especially for them. A wellspring of mutual joy unfolds when parents and children read together – personalized or non-personalized books. Shared Book Reading Adults rarely read to each other aloud. For children, though, having a story read aloud is the principal way of entering the world of literature. Some caregivers (parents, grandparents, older siblings and other adults significant in a child’s life) read the story-text from cover to cover without adding anything extra. Some use the story to make departures to talk about the child’s experiences or their own memories, and some invent their own stories. Experimental research shows that parents’ talk during book reading is one of the most, if not the most, important factors in children’s learning from shared book reading. Recent studies show that if a book is designed with suitable prompts for parents and their toddler-aged children to discuss new words, it can foster rich conversations around the book (Teepe, Molenaar, & Verhoeven, 2017; Troseth et al., 2019). In classic studies of parent–child reading of print books, contextualized talk is defined as talk related to the book being read by the parent to the child, and decontextualized talk is talk related to the there and then, which gradually evolves to talk about the non-present and that is detached from the physical context (Snow, 1991). The latter is extremely important for stretching children’s minds and learning. For example, when reading Cinderella to their children, parents can talk in very concrete terms about what color dress Cinderella wears in the illustrations or they can talk in more abstract terms about what it means to be kind to each other, what constitutes justice and poverty in life, etc. The latter are examples of decontextualized talk, which are active transactions between readers’ life and text connections, and which can lead to transformative reading experiences (Rosenblatt, 1994).

190

The Future of the Self

In contextualized talk, parents say things like: “Do you remember when we went to grandma?” or “Look, this football ball looks just like yours! You like playing football, don’t you?” These comments link the story on the page to the stories the children lived. They provide an essential mechanism for meaning-making as they connect memories and existing schemas to new information. Psychologists would say that this type of talk contextualizes the reading experience and caters for excellent conversation starters. Conversations about books are important conversations: as Maryanne Wolf (2008) says, there is no specific gene for reading. Reading and writing are skills that we need to nurture in children so that they can fully participate in the modern society. No wonder then that reading with young children is one of the most coveted and most researched areas of study in early childhood (Shapiro, Anderson, & Anderson, 1997). When policy-makers want to influence parents’ reading with their children at home, they typically spend money on donating books to homes where there are very few or no books at all, or on providing training packages that teach parents how to read to their children “effectively.” Nationally or privately funded book-gifting schemes such as Reach Out and Read in the USA or Bookstart across European countries have perfected different delivery models of providing free books and advice to parents. When I was a visiting scholar in Boston, I discussed with the founder of Reach Out and Read, Barry Zuckerman, the importance of parents identifying with the health practitioner who provides them with free books and book reading advice. If the advice to a Black low-income family comes from a top-earning White pediatrician, it is unlikely to be met with acceptance and identification. But if the encouragement comes from another family with similar background and struggles (e.g., if the suggestion to read books comes from a working-class father to another working-class father), the distance between the advice provider and receiver is smaller. A key ingredient in sustainable book reading interventions is to shorten the distance between parents-readers and parents-non-readers. Some immigrant, minority and indigenous communities perceive top-down instruction about book reading as a “punishment” (Janes & Kermani, 2001). Many families want to self-determine the books they read with their

Distance

191

children, according to their own esthetic and linguistic ­preferences (Vezoli, Kalantari, Kucirkova, & Vasalou, 2020). At the same time, they want to be supported with suggestions for books that can help with their children’s language development (Bus, Sari, & Takacs, 2019) and thus instill feelings of belonging to the dominant cultural group (Dummett, 2002). Personalized books shortcut the distance between the reader and the story.

Commercially Produced Personalized Books For the uninitiated, there is a thriving publishing industry of children’s personalized books in which personalized books feature a child’s data (the child’s name, date of birth and friends’ names) and typically position the child as the main story hero of a fictional plot (e.g., Natalia defeats the dragon to save her friends). Personalized books are mostly produced for the home, not the school market – there are unlikely to be two sisters called Jessica but there might well be two Jessicas in a classroom and personalized books are also more expensive than standard books. Personalized stories are personalized because they contain personal details but follow a fictional story plot. Although personalized stories may contain autobiographical features, they are not an autobiography (a story of an individual’s life written from the perspective of that person). With print books, personalized books combine children’s names, date of birth, drawings and in the digital format, they also incorporate children’s photographs and audio-recordings. Thanks to print-on-demand publishing, there is no need to store multiple copies in warehouses – this facilitates self-publishing and also the production of personalized children’s books. Personalization can be thus used for both digital or printed books, and popular children’s personalized books boast sales comparable to the bestselling children’s books of all times (see Wonderbly Ltd. in the UK or I See ME™ in USA). Unlike the long process of making your own personalized books with commercial personalized books, all that parents need to do is to send the publisher information about their children and the publisher pings them back a bespoke book made just for their child. With such streamlined and convenient ways of producing

192

The Future of the Self

personalized stories, publishers are inventing more and more persuasive personalization options. For instance, personalized books by the publisher I See Me™ feature children’s pets with illustrations and text matching their real furry companions. If the dog passed away, the publisher adjusts the text to past tense. With the Me Books™ app, parents can personalize any popular fairytale with their own voiceover and save it for the child to access later. Software programs such as the one developed by Hoot Ltd., bring together parent–child reading across distance: parents and children connect with their individual devices in real-time as in a videoconferencing call. They can access the same digital book as they swipe the digital pages on their individual screens, tracing each other’s finger movements. Then there are personalized books that feature the child’s photo on the cover, or books that incorporate children’s hand-made drawings as well as augmented reality books that project the child as 3D story hero. I have studied personalized books produced by parents as well as by commercial publishers and in both print and in digital formats. The emerging evidence is that personalized books produced by the child or by the parent (not a commercial company) foster parent–child dialogue (Kucirkova, Messer, & Whitelock, 2013). We also found that such personalized books support child-to-child dialogue (Kucirkova et al., 2017) and overall a positive reading atmosphere at home (Kucirkova, Messer, Sheehy, & Flewitt, 2013). This was both with digital and print versions and families reported reading their own personalized books on a repeated basis. In one study, children learnt more new words from personalized than nonpersonalized books but when reading these books, their talk was characterized by a higher frequency of mentioning “me, mine and my” at the expense of talk acknowledging the presence of others (Kucirkova, Messer, & Sheehy, 2014). In trying to explain the findings and make predictions for future studies of personalized books, I proposed the distancing hypothesis. THE DISTANCING HYPOTHESIS Literary scholars (e.g., Oatley 1999; Sikora, Kuiken, & Miall, 2011) have examined the optimal distance between story characters

Distance

193

(protagonists) and readers, and they came up with various literary techniques that either increase or decrease the distance (e.g., use of first person, strong portrayal of emotions, change of pace or tone in the text). The so-called utility value interventions are used in schools to increase students’ personal relevance of the teaching material. So far, these interventions have targeted – and also worked best – for students who have lower expectations for academic success than their peers. The theory that justifies utility value interventions is the expectancy-value theory (Eccles, Wigfield, & Schiefele, 1998), according to which students’ own expectations of success directly predict their achievement. The distancing hypothesis suggests that the smaller the distance between the content and the individual’s personal life, the closer the match in expectations and the higher the likelihood for engaging with the information/ story/learning material. The distancing hypothesis applies to other learning contexts, but I focus here on its application to reading engagement. If the story content resonates with the individual’s life, their reading engagement is higher. So, for example, a story about climbing Mont Blanc would be more interesting to me because I climbed Mont Blanc. If the story was written by a young woman who struggled with the climb, the distance between the author and the reader (me) would be shorter and the story would be even more interesting to me. Note that personal relevance does not equate to higher learning outcomes because, as I explained in the previous chapters, aligning children’s personal preferences with the content of learning works for engagement and motivation, but not necessarily for stretching their minds. The same principle motivates my formulation of the distancing hypothesis: the smaller the distance between the reader and the story character, the higher the likelihood for the reader’s interest/engagement with the story. Engagement is a step toward learning, so from this perspective, decreasing the distance between fictional texts and readers is a good idea. It is essential for ensuring children find themselves in books that they feel empowered to read and that books are culturally responsive. However, decreasing the distance between story characters and readers can also fuel parochial empathy (Kucirkova, 2019b). Parochial empathy, also known as in-group empathy, is empathy toward members of groups that

194

The Future of the Self

are socially, culturally or geographically closer to the self. The opposite is out-group empathy, which is empathy toward those who are unlike us (Bruneau, Cikara, & Saxe, 2017). We naturally gravitate toward those who are similar to us, so it is out-group empathy that is most difficult to nurture in young children (as well as adults). The greater the alignment between the protagonist and the reader, the greater the likelihood that the book evokes feelings of parochial (in-group) and not out-group empathy. The experience of reading about story characters who are different from the child and, therefore, members of the out-group, is hypothesized to constitute the highest empathy potential of children’s storybooks. Fig. 10 explains how these different distancing options correspond to different types of books and character constructions. The distancing hypothesis highlights the closeness between self– other as a significant factor in readers’ engagement and motivation. This process can be explained by the psychological factors identified in previous chapters in relation to self-referential memory effects and it can be also neurologically ascertained: a metaanalysis by Krienen, Tu, and Buckner (2010) found that different networks are activated depending on how close the individual is to the person they are thinking of. Moreover, the difference between whether the other person was a friend or a stranger was found to

Fig. 10.  Distance Combined with Types of Literature and Examples.

Distance

195

be a more important attribute in the neural activity than whether the other person was like-minded with the individual (Krienen et al., 2010). It is not clear whether humans are wired for such a “clan mentality” or whether the stories we tell ourselves propagate this mentality. What is clear from experimental studies is that when the other person is socially closer to the child, children feel more empathy toward them (Wynn, Bloom, Jordan, Marshall, & Sheskin, 2018). In addition to parochial empathy research, my theoretical starting point for the distancing hypothesis was work by Kross and Ayduk (2017), whose research shows that the ability to analyze one’s cognitions objectively is at the core of effective cognitive change (see Kucirkova, 2019b for details). It follows that the cognitive resources that children need to employ to understand a story character who is different from their in-group members or their own personal experience are higher than those required for identifying with a story character who is similar to them. The readers’ identification with characters dissimilar from them and the readers’ high immersion in the story requires most cognitive resources. This does not apply just to literature but also to good game design: the author’s or designer’s creative connection to the players’/readers’ agency is what makes the story successful. Immersion requires a lot of effort on the part of the author, who need to craft a narrative that is engaging for individual readers/players. The relationship that the hypothesis expresses is schematically outlined below, in three steps. The first step (Fig. 11) simplifies the complex theory of empathy into four possible social outcomes: out-group/in-group bias or identification. The second step (Fig. 12) in building our understanding here is to consider how these outcomes relate to the two key mechanisms of engaging children in reading stories: story immersion and identification with story characters (see the two axes crossing each other). Quadrant number 4 is the most desired quadrant as it combines a reader’s high immersion in the story with strong identification with the story character. This quadrant then (Fig. 13) is the most likely possibility to nurture children’s out-group empathy. It occurs when books include story characters that readers can identify with, but they are based on strong story plots that immerse readers in the narrative. Such a combination requires strong literary craft.

196

The Future of the Self

Fig. 11.  The Four Quadrants of Social Cognition.

Source: https://www.frontiersin.org/articles/10.3389/fpsyg.2019.00121/full

Fig. 12.  The Four Quadrants of Immersion/Identification Options in Stories.

Source: https://www.frontiersin.org/articles/10.3389/fpsyg.2019.00121/full

Distance

197

Fig. 13.  The Four Quadrants of Empathy Options in Relation to Stories.

Source: https://www.frontiersin.org/articles/10.3389/fpsyg.2019.00121/full

Where do personalized books sit in these quadrants? Although there is virtually no research on the effects of frequent reading of such personalized books, we have decades of research on non-­ personalized books to anticipate some outcomes. The first thing we can say is that positioning children as heroes of their own microworlds (Natalia saves the world) is not a small cosmetic change – non-personalized books are meant to expand children’s horizons and recognize heroism in others. Personalized books that portray children as super-heroes saving the planet or princes defeating all villains are examples of “dense” personalization in children’s products. As discussed in Chapter 5, in such products an idealized version of self is imposed on the child, accentuating the attention to ego. There is no space for the child to infer that the good story hero could be them – they are the story hero. With personalized search-and-find books, children look for themselves and not for fictional characters such as in Where is Wally? by Martin Handford. In these personalized books, personalization becomes an end in itself. A further prediction that we can confidently make about overly personalized story books is that they will engage children in

198

The Future of the Self

concrete rather than abstract thinking. I have already discussed loss of abstraction in relation to children’s personalized toys in Chapter 3, and the same concern applies to personalized storybooks: they concretize the child’s experience and reduce the possibilities for deep thinking processes such as abstract thought and inferencing. When adults impede inferencing by making many references to the story characters’ mental states during book reading (such as saying that the story character thinks this or knows that), then it is not helpful for children’s actual understanding of mental states. The researchers assume it is because children need to actively make sense of the story text and illustrations to learn about mental states (Peskin & Astington, 2004). In addition to reduced abstraction and inferencing, there might be also a loss of benefits for emotional outcomes. For example, based on the psychology studies concerning the use of “generic you” with children (Orvell, Kross, & Gelman, 2019), we could hypothesize that children who read stories about negative experiences that are about them rather than about a general normative context (referred to in stories with a generic “you,” e.g., That’s how “you” do it), are being less supported in making meaning from negative experiences. Moreover, as captured in the figures, personalized storybooks where the child is the main story hero are also less likely to support children’s out-group empathy. Traditionally, books are written from the point of view of the story character who is different from the reader. This allows for immersion– identification interaction and a vicarious experience of emotions – which has been studied extensively with adult readers (e.g., Koopman, 2015). However, if the story is written from the first person point of view and the story character is the child, then both immersion and story identification are greater. The children identify with story characters who are them – they feel empathy for themselves first and foremost, and then maybe for other characters unlike them. The distancing hypothesis neatly explains why there is a permanent concern attached to fully personalized books: with traditional, non-personalized books, readers get to collectively experience catharsis. Catharsis can happen through the distance between the actual and ideal self. Children experience an “emotional release”

Distance

199

(Stoodt, 1996) when they identify with a character who is different from them. In addition to catharsis, children benefit from engaging in perspective-taking when reading books. When reading, for example, about the Princess and the Pea, children understand that what the Princess thinks is different from what the reader thinks (the reader thinks the pea is in the princess’ bed, but the princess does not know that). By thinking as someone else, children can experience possible and imagined selves. Personalized books do the opposite: children read to find themselves, the perspective is their own (Note 7.7). My point in listing these limitations is to highlight weaknesses that can be addressed with good work and clever design, and very importantly, to make sure that they do not over-shadow the important benefits of personalized books. As mentioned, diversity in the content of children’s books is low and the strong focus on self in personalized books can help with identification, that is, evoke children’s feelings of belonging to not only the story but also the world of books and literature more widely. Personalized books can boost the child’s self-esteem and self-confidence and are, therefore, widely used for therapeutic purposes as social stories. Furthermore, personalized books produced by children could significantly enrich the literature canon with new voices not only in terms of diverse content but also format, especially as more and more children are becoming skillful designers at a young age. The idea of children as authors moves us toward the ideal of “ergodic literature” (Aarseth, 1997) where the reader is an active participant. The distancing hypothesis suggests that keeping a distance between “self” and “other” is the very reason why humans find fictional story worlds interesting. The closer the self to the other, the greater their affiliation and often, affection. The shrinking and enlarging of the self–other distancing can be managed with two techniques: contextualization and conversation. The Techniques of the Distancing Hypothesis Contextualization and conversation clarify the often-misunderstood difference between personalization and relevance. Content can be contextualized or presented in a conversation to be relevant, but

The Future of the Self

200

it does not need to be personalized. In what follows, I detail both techniques in relation to well-established methods in story-telling to expose the links between new forms of personalization and old story-telling techniques. Contextualization The explanation of what contextualization is requires some context (forgive the pun). The imaginary world frees the mind to wander in new directions which triggers visceral and vicarious feelings of being. Thanks to novels or films, we can explore paths we have not taken personally. Through fictional stories, we can imagine having the lovers we never had, the families we never belonged to. In children’s books, children battle together with monsters or dragons and experience fear or joy. Young or adult readers participate in these feelings through imaginary participation. The imaginary participation is at the heart of an esthetic satisfaction that people derive from art. Contextualization, then, mobilizes the imaginary participation and esthetic satisfaction by reducing the distance between the audience and the artist. It does so by, for example, adding some background information about the author, adding details about the time and place where the story originated, and by placing it in relation to other stories (the so-called inter-textuality, see Alfaro, 1996). Art curators are somewhat divided about how much contextualization is necessary for people to appreciate art. The older school of thought (still present in many contemporary art organizations) pledges allegiance to the capital-A Author, as the only guardian of truth. There is only one admissible interpretation of a poem, painting or novel and that interpretation is what the author says it is. The institutionalization of the reader and the rigidity of meaningfixation create a distance between authors and audience. As David Trotter (1983) points out in his wonderful observations on “making the reader” in poetry, it is this distancing that makes poetry inaccessible to young readers. The slogan of the newer school of thought is that “everyone has a story to share” and anyone can be an author, artist or poet. A popular export of the postmodern school of thought declares the author dead and welcomes everyone

Distance

201

to conjure up their own interpretation, and indeed their own works of art. To be an author does not mean to ignore what has been produced before; far from it, good artists need examples, models and constraints to be creative. For example, the French Oulipo writing method requires following rules that liberate the inner author in all of us. The constraint of the rules is assumed to be more generative than the terror of the blank page. Today’s authors use collages, remixes, “found poems” and word generators to constrain the thousands of words bursting in their heads. This management of choices might remind you of Chapter 3 where anxiety was linked to an overabundance of choices. This is partly why creative writing is an effective technique in mental health treatment (Hunt, 1998): it constrains the diversity of possibilities to specific choices. How can we explain the workings of contextualization? From a biological perspective, contextual associations facilitate visual perception (e.g., Bar, Aminoff, & Schacter, 2008). For example, if you see the contours of an apple in a grocery store versus an apple on a bathroom floor, the different contexts activate different neural networks, enabling or inhibiting immediate visual perception. The mental gymnastics we need to perform when something falls outside our schema differ depending on the gap between our personal expectations and the objective reality. First impressions and stereotypical reactions are activated through a subconscious response to certain visual stimuli such as skin color, and the actual response is very much influenced by the individual’s previous experiences. In an innovative laboratory experiment by Son and Goldstone (2009), contextualization was used to bridge the distance between students’ science understanding and their interest in popular TV shows. The researchers used a popular TV character who explained new scientific content to the students. This was a study with 64 undergraduate students, not young children, but what is interesting from the distance perspective is that the participants who were familiar with the TV character (i.e., the participants for whom there was a shorter distance between the character and themselves), had higher assessment scores than those who did not know the character (Note 7.2). Contextualization research supports the distancing hypothesis, but it does not tell us whether the context needs to be adjusted to

The Future of the Self

202

a group of children (i.e., customized) or to an individual child (i.e., personalized) to engage them most. Nor does it tell us what kind of contextualization technique works best for which types of texts and stories. Future studies will need to address the multiple ways in which contextualization can be evoked (e.g., through visual or verbal input, or less researched but equally important tactile and olfactory cues) to understand its impact on learning. Research on conversation, the second popular distancing technique, is geared toward verbal input. Conversation For some people, conversation is the same as dialogue. For socioculturalists the two are not the same: dialogue, remember, is at the heart of dialectics and exploration of the self–other continuum (as described in Chapter 6). The definition of conversation is simpler, you will be relieved to hear. Conversation is a verbal exchange of thoughts and feelings. A conversation typically involves more than two people but it doesn’t have to. Dialogue is studied by psychologists as a cognitive mechanism and as such, subject to elaborate theories, while conversation is more the domain of practiced arts, for example, poetry (especially of the poet David Whyte) or leadership programs. A good conversation is at the heart of all good stories but there is a lot of heavy-lifting behind a good conversation: listening, honesty, avoidance of judgment, flow. According to the cognitive theory of multimedia learning (Mayer, 2005), addressing the learner directly as “you” in a text, rather than using the traditionally neutral phrasing of “he, she, it or they,” sounds more “conversational,” which increases the learner’s interest in the learning content, which then encourages active and more mindful engagement with the new information (Moreno & Mayer, 2007, Note 7.3). Conversation thus reduces the distance and has documented learning benefits. In addition to the use of “you,” the cognitive benefits of conversation can be induced through the use of first or second-person talk. First person talk is self-talk and the kind of talk that Nelson observed in two-year-old Emily discussed in Chapter 5. When people engage in self-talk, they use self-references, such as “I,” “me”

Distance

203

and my.” In contrast, self-distanced talk uses “you” and “your own name” in reflecting on an event or situation. The degree of distance matters: the strongest memory effects are with referencing to self, less with referencing to a friend, and minimal with referencing to a stranger (Macrae, Visokomogilski, Golubickis, & Sahraie, 2018). VR could be used to find out whether self-distanced conversations apply to a whole-body experience. VR studies where adults who saw themselves from a distanced perspective had reduced levels of self-criticism and enhanced levels of self-compassion (Falconer et al., 2014). In a creative experiment with 180 four- to six-year-olds, researchers presented children with a long and boring laptop play session and an engaging iPad game. The trick was that they told the children to have an internal conversation about their work on the boring laptop in three ways: (1) in an immersed way (“Am I working hard?”), (2) in a third-person perspective (“Is Natalia working hard?”) and (3) from the perspective of a popular story character (“Is Batman working hard?”). Clearly, the children wanted to play the iPad game but were given three strategies to help with delayed gratification. Interestingly, it was the third condition, in which children took the perspective of the popular story character (Batman, Rapuntzel, Dora the Explorer or Bob the Builder) that led children to work longer and harder on the boring laptop task (White et al., 2017). From the distancing hypothesis perspective, the findings suggest that for children who are building their understanding of self, a story character that children are familiar with, is closer to them than a character they don’t know and this proximity might elicit more intense engagement. In a series of experiments led by David Turk from the Self Lab (Turk et al., 2015), children who were instructed to refer to themselves during a literacy task, produced longer and more accurate sentences than children who were instructed to refer to others during the same task. Turk and colleagues replicated the effect for both non-words and real words, which indicates that reducing the distance between the learner and the learning content is of added value to children’s learning of difficult as well as less difficult concepts. Psychologists Kross and Ayduk (2017) applied the idea of selfreferential and self-distanced talk to an area that we should be

The Future of the Self

204

aiming for with all educational interventions: wisdom. Kross and Ayduk used two measures of wise reasoning: dialecticism, which is about the recognition that the world is changing dynamically and continuously; and intellectual humility, which is about recognizing the limitations of one’s knowledge. With adult participants, they found that thinking about issues which have significant personal implications from a distanced perspective increases wise reasoning. Moreover, there were changes to participants’ attitudes and behavior when they reasoned from a distanced perspective (Kross & Grossmann, 2012). With human nature as complicated as it is, we need many more studies to understand the deeper learning processes underlying the conversation and contextualization techniques. From the personal resonance perspective, the contextualization and conversation techniques are a roundabout way of eliciting a personal reminder, as outlined in the personal resonance theory.

PERSONAL RESONANCE Personal resonance was theorized by Uffe Seilman and Steen F. Larsen (1989) who connected stories and autobiographical memory and argued that literature activates the “self” within us. They called such activations “personal remindings” and studied how the personal remindings make readers more engaged in reading. Texts which evoke personal memories remind the readers of an experience they have personally lived. Through this reminding, readers become interested in the story and can better understand and appreciate the text. Followers of the personal resonance approach have found that if there are more personal remindings at the story beginning, the reader is more likely to continue with the text (and finish reading the book). Seilman and Larsen also hypothesized that personal remindings are more likely to occur with texts that are written from the first-person perspective (i.e., a hero recounts the story from the “I position”). Personal resonance is not just a literary theory. Psychology research explains memory activation in relation to information that resonates with individuals. Psychologists distinguish two

Distance

205

systems for processing information: intuitive and reflective cognitive systems. Building on the work of Daniel Kahneman and Frederick (2002), the intuitive system is automatic and rapid and engages with affective and specific content. The reflective cognitive system is controlled, slow and rule-based and it processes neutral and abstract content. Based on this classification psychologists can make some predictions about the thinking that happens with texts rich in personal remindings versus texts that are more abstract. The logic goes like this: texts that have several pointers to what we have experienced before are more likely to stimulate the intuitive system with more concrete representations. Texts that are more removed from our personal experience are more likely to elicit the reflective cognitive system. Moreover, we can predict that the more a text is personally relevant, the more it corresponds to what the individual already knows and to the individual’s internal system of beliefs. Therefore, the more personally relevant the text, the more it provides the reader with coherence. There are various ways of examining these associations. Kahneman studied people seeking out coherence in stories when they were threatened, for example, in the situation of a conflict. Researchers in the field of humanities have shown that children with low self-esteem and confidence gravitate toward personalized texts that are about them rather than fictional characters (Note 7.4). The advantage of self-relevant texts on memory has been also demonstrated by (cognitive psychologists), who found that remembering an event in relation to self represents a significant advantage and creates a stronger memory trace (Cunningham & Turk, 2017; Symons & Johnson, 1997). In addition to memory and associated learning advantage, self-relevance is a key component in the readerresponse theory. This theory has been used by literacy scholars and charity programs who perfect the art of contextualization and celebrate differences among readers (Note 7.5). Instead of standardizing their responses to literature, readers are empowered to find their own critical response to a piece of text. The critical response is developed through searching for episodes, parts of text and images that resonate with them personally. The importance of personal remindings comes full circle with “rasa dhvani.” Hogan (2003) used rasa dhvani in interpreting the

The Future of the Self

206

meaning of Sanskrit poetics and Indian theories of language. In this centuries-old tradition, rasa is the soul, essence of emotion and dhvani is its communication. Rasas are universal emotional connections and dhvani is their transmission to individuals. Hogan suggests that semantic and emotional cues in literature prime readers’ personal memories and through this priming, generate emphatic responses. The reader is actively engaged with the author to establish the author’s “dhvani” in communicating the “rasa” that extends beyond the book pages to the readers. My proposition is that the key mechanism that makes conversational and contextual techniques successful is the self–other distancing. As you can see, there are many, disciplinary-specific variants of the personal resonance/personal relevance theory. The distancing hypothesis does not aim to unite them but it aims to provide a framework for converging findings relevant to children’s learning. The industry on personalized books, personalized textbooks and personalized learning resources is growing, and will become bigger with AI-enhanced possibilities for combining and dynamically adjusting large databases of personal data. I, therefore, conclude this chapter with an outline of my desiderata for future children’s personalized books. Future Personalized Books With the P–P lens, a question to be asked is: how can children’s books be both personalized and de-personalized so that children are motivated to read and they also learn something new in the process? For example, could children’s names, pictures and sounds be used to motivate children to read radically impersonal texts, such as historic novels? Rather than positioning children as story heroes in fictional tales, children could be portrayed as helpers in their local communities, supporting those they would typically not think of as their “friends.” If personalized books were more widely recognized and collaboratively produced, they could constitute an important new literacy genre. Any new literacy genre (Dore, cited in Nelson, 1989, p. 238) requires an uptake of readers and authors.

Distance

207

Personalized books created by communities of readers and nonreaders, in digital and non-digital formats, could be a source of abiding wisdom about our shared fantasies and individual histories. Participatory/collaborative and user-centered design need to widen their doors to recognize that the distance between the self and the other needs to be proportionate: in some contexts, the distance needs to be decreased to build a sense of belonging and in other contexts, the distance needs to be increased to expand one’s personal goals. While personalized book reading interventions level the playing field by empowering non-reading families with messages of belonging to families of similar backgrounds, they are more sustainable if they also enable identification with families they are dissimilar from. In the distancing hypothesis terms, personalization shortens stories to the familiar and pluralization expands them to the unknown. Personalized stories are a micro-example of the broader issues in personalization in childhood that I have summarized in seven chapters. The last chapter attempts to bring the lessons of the individual chapters together to propose a more direct explanation of why the twenty-first century is the era of fragmented and amplified selves.

This page intentionally left blank

CONCLUSION

In this book, I asked questions related to the “anatomy” of personalization and provided some tentative answers that I summarize in this chapter in relation to the fragmentation and amplification of identity occurring in the current era. Lesson 1: The P–P balance Personalization is a nexus of products, services and practices relevant to one human being that needs to be balanced out with pluralization for optimal outcomes. With various examples of personal data and uses of personalization outlined in Chapter 1, I tried to make it clear that personalization is not simply dropping children’s names or their profile photos into templates to get their attention or generate instant familiarity and emotional response. With the concept of personalization– pluralization balance, I think of personalization as providing tailored experiences that celebrate individuality within a shared context (not at the expense of collective values). This builds on the socio-cultural theories that explain how our uniqueness is enacted in the shared network of living and non-living “selves.” The fragmentation–amplification process within P–P happens as soon as you are born. In taking the first breath, you become an amplification of your parents in the biological sense, as well as in the social sense (if you are raised by the people whose genes you carry). Over time, you fragment your identity by fulfilling various

209

210

The Future of the Self

roles (daughter/son, husband/wife, father/mother, uncle/niece, sister/ brother, etc.) and the many hats you wear in the society (a citizen, a worker, collaborator, passionate hobbyist, etc.). The change that occurred in the twenty-first century is that your fragments are increasingly digitized and digitally amplified. These digital fragments and amplifications are being monetized, media-saturated, and systematically commodified to such an extent that they can grow new identities. The question that animates me for the future “self” is how we can repair what the P–P misbalance broke. How can we open-up spaces for our digital fragments to positively amplify the good choices we make for us and for others? Lesson 2: Quantity and complexity Twenty-first century citizens consume and produce unprecedented quantities of complex personal data. The pursuit of the “more is better” consumerist model in personalization corresponds to the personal data economy and profitdriven digital marketing. I argue that manipulating pieces of self through persuasive design is not only putting the cart before the horse but also endangering lives. The persuasive design that is embedded in social media sows seeds of division that serve hate groups, and those propagating transphobia, racism or sexism. In an economic system set out for aggressive competition (and not collaboration), super-companies came to power, with the GAFA companies owning the biggest metadata in history, and thriving on a lack of regulation/censorship. The modern economy (and the many consequences it carries, including materialism, climate and personal damage) tricked baby-boomers to believe that more is better, without any coordinated narrative for the many self-fragments scattered on multiple platforms. The centralization efforts by governments and big company mergers in 2020 are an emulation of the same model the companies envisioned when they conceptualized each human as one brand (so when you post a photograph on Instagram, you can push it at the same time to your other connected platforms, just like a brand charming multiple territories in parallel). Such a strategic amplification does not favor mental well-being, indeed it contributes to the overwhelming complexity of data. While I lament technology design that exploits human brain

Conclusion

211

and behavior for divisiveness rather than consolidation, I try to avoid a discourse of opposition (be this against the government or technology giants). We all are contributors to the fragmentation/ amplification that happens through social media use. We cannot stop the rising fragmentation of self into digital points, but we can avoid an amplification that gives power to either just individuals or selected groups. My vision for a desired future is to foster the recognition that these fragments within us and between us are diverse and we need to cultivate the diverse relationships that these fragments afford. On the data level, neither massive centralization nor decentralization would guarantee the P–P balance necessary for avoiding the rising density and quantity of personal data. To avoid extreme fragmentation of identities, we need to find the connections that amplify the best in us personally and collectively. We do not need to understand all the fragments that define others, indeed one connection might be enough to carry the conversation that is necessary to sustain a life of dignity. Lesson 3: Agency The constituents of agency – self-determination and belonging – rise and fall over time, in response to the individual’s motivation to be an Author and develop Attachment to other human beings as well as Autonomy through the production of Authentic content with unique Aesthetic qualities. We are who we are because of and in spite of others. Our desire for self-determination and belonging needs to be continuously calibrated as we move forward in life. Children’s use of technologies and other educational resources, manifests this calibration process in relation to the 4Cs: Context of use, Content of the activity, children’s individual Characteristics and the traditions of the Community they are part of. The 5As need to be at the forefront of developing sustainable personalization models and abandoning profit-oriented personalized technologies for children as well as their caregivers. In 2020, governments and private companies own multimedia fragments that they selectively amplify on their platforms. We have achieved tremendous progress thanks to the amplification of selective identities, for example, redefining gender within one generation. The amplification of underrepresented groups is

212

The Future of the Self

critical for a socially just future. The amplification of destructive fragments of society, however, is a very dangerous path for the P–P model. Individualized injustices can easily overlook systemic injustices. Some concrete 2020 examples: the cult of the individual is myopic toward human flaws that ended up with appointing narcissists to the highest states of national offices. Public trust has been fragmented into micro-parties, individual brands and products. Personalized education has in some cases escalated into elite sportsstyle education reserved for those who can afford it. Healthcare has splintered into care of large-scale investments into individualized medicine at the expense of safeguarding national and international healthcare organizations. Within Western medicine, focus on whole body got sub-divided into focus on individual body parts, with treatment plans tailored to individual organs rather than holistic care of body-mind. In research, many scientists, including myself, have developed precision mechanisms for examining micro-questions that have in many instances blinded us toward macro-questions such as climate change. As adult individuals, we have fragmented our social relationships into different social media platforms, diverse communication channels, with different modes (images, sounds or texts) amplifying different meanings. With minimal agency afforded to stitching together these fragments across time and space, individuals adopt a transaction model toward their own selves. Such new socio-economic contracts between “self” and others exploit the potential for self-transformation into pure transactions. Lesson 4: Acceleration Accelerated personal and collective migrations disrupt the P–P balance, and the extreme personalization practices in the twenty-first century have resulted into mental health problems, such as confusion and anxiety. Personalization correlates with inequality and is mediated by the philosophy of meritocracy that is accommodated by neoliberal capitalism. Consequently, when personalization becomes extreme, as it was the case with the personal data economy in the first quarter of the twenty-first century, it paints an ugly picture of economic inequality sponsored by technology giants. The baby-boomers’

Conclusion

213

acceleration for life has led to a three-fold increase in world’s population, lethal pollution levels and plastic waste clogging waterways. To sustainably address (and not to merely react to) the technocratic economy of personal data, requires slowing down the pace of individual migration (physical, virtual, psychological and physiological migration) to allow for its safe merger with the migration occurring in the society at large. Softening the edges of rapidly fragmented selves requires first of all the recognition that the sum of collective fragments is larger than that of any individual. The obvious follow-up question is not who you are to yourself but who you are to others. In a well-functioning society, neither of these P–P questions is optional. Lesson 5: Density The density of personalization increases through the paradoxical desire to resolve the incongruence between an ideal and actual “self.” The psychology behind the push for extreme personalization involves the tension of congruence between who we are and who we believe we could be, which is motivated by the dual desire to be similar to, and also dissimilar from, others. The more we succumb to the self-oriented side in this life-defining struggle, the more we risk “densifying” personalization to its extreme. Science can be a good companion on establishing the healthy paths on this journey. In the age of sophisticated precision neuroscience or arts-based post-humanist approaches, cross-disciplinary collaborations on the methodological front are essential to advance our understanding of which innovations count as self-replications, which ones as self-reciprocation and which ones as self-reflections. Researchers, policy-makers and practitioners need to urgently close the gap and time-delay between the translation of research to practice and establish structures that enable change on all the three “self-Rs.” In schools, there is a clear orientation toward understanding how others work but less our internal processes. Or in research where self-reflection is taken as a post hoc afterthought for qualitative researchers rather than a sine qua non for every project. The interest in the participant, patient or client, is essential for the fields to move forward, but they need to be balanced up with an interest in

214

The Future of the Self

the individuals leading those efforts. The denser the fragments of our own selves in the everyday spaces we occupy, the more difficult it is to turn the mirror of self toward those who have historically not been amplified in our circles. A recognition of the social value of data is a recognition of the dangers of amplifying fragments that perpetuate the replication of social privilege and personal power. Lesson 6: Sequence Dialogue is a powerful mechanism to oppose sequence myths that caricaturize personalization into novelty-seeking adaptations. Education is at the core of growing our own “self,” in dialogue with the “other.” This “other” can be our own self from the past or another human being or a non-human knowledge resource. Not surprisingly then, education is the most complex sector to innovate, with many competing ideas and myths circulating around what counts as best practice. Three long-standing myths in education have made it possible for the sequence myth to dominate educational approaches across the world. A sequence is possible when individual fragments are ordered in hierarchies of importance. When such hierarchies are driven by technologies and automatic algorithms, education is void of individual and collective agency and nothing more than a short-sighted information exercise. For education to serve its purpose of “bringing up or rising up” humans, we need to use personal data so that teachers know the children in their class and can engender trust and build rapport. The space that the knowledge of the other can open needs to be a safe space where all participants can feel comfortable enough to explore their potential and vulnerabilities. This space was successfully created for children and adults online. It is time to return it to, and run it in parallel with, the humanizing power of self–other teaching and listening. Chapter 7: Distance Stories mobilize the distance between the “self” and “other,” which gets shrunk by personalized and expanded by pluralized story-­ making/sharing practices. The philosopher Roger Scruton (2011), who specializes in ­aesthetics, argues that beauty is appreciated through the human

Conclusion

215

ability to keep a distance between the self and the object of beauty through what he calls a “disinterested interest.” Stories give us the distance between the qualities we have and the qualities we would like to have, between the realities we have lived and the realities we can imagine, laying the ground for disinterested interest. The tables are turning in the twenty-first century with the digitization of stories. Although I started my research with personalized books made by children or their caregivers, I have found myself piecing together the psychological and educational implications of personalized books produced commercially, by algorithms. I maintain, however, that it is not the focus on the story formats (digital or print) but on the story features (personalized or not) that should guide scientific investigations into learning impacts. Even more importantly, it is not the presence/absence of personalized story features but their distance to self–other that explains their appeal and potential to change our minds. The important qualification here is the extent of individual agency in influencing this distance – the psychological distance to a fragment of you (be this a piece of drawing or text) is greater if this fragment is your own creation. While the mode of representation of your fragments (a video instead of a photograph alone) might intensify its resonance, it is the distance to your own self that dictates the space and time you will want to amplify it within. With modern technologies being intimately inter-woven with our bodies and minds (and even living inside our bodies as micro-chips and outside as space missions), the distance between the fragments we own and the fragments that amplify us is, on one hand, extremely close, and on the other hand, incomprehensively large. The P–P is a thinking structure to help us understand the distance we have traveled in the human history. As modern Homo sapiens, we can travel cosmic distances through space tourism, but it is the calibration of distance between the “self” and the “other” that drives our species forward. The twenty-first century is the first century when human activity drives the Earth into a new geological epoch, the so-called Anthropocene. The large increase in temperature have accelerated much larger quantities of changes than ever before and these transform the relationship between humans and our planet’s climate and ecosystem (Steffen, Grinevald, Crutzen, & McNeill, 2011). While the term

216

The Future of the Self

Anthropocene is more known to global climate research community than the general public, most people are familiar with, or can derive meaning from, the term “personalization.” It is my hope and wish that the study of personalization moves forward as a multidisciplinary field with a strong orientation toward understanding what disrupts and what restores the distance between personalization and pluralization. Remember the combination of personalization with pluralization in light of the quantity, acceleration, density, sequence and distance between the “self” and the “other.” Beyond all, remember your own agency in this process. Our choices define not only our own but also others’ identities. The higher you climb the society ladder, the more choices you can access and the more complex the decision-making process. The amplification possibilities of self in today’s era means, however, that choices of each individual can have more profound consequences than ever before – a magnate can have a private drone in space spying on selected individuals, and a 10 year old can share a video that is viewed by millions across the globe. Our choices can amplify who we are but the key question is: “what will we do with this amplification?” As we choose from the palette of “selves” for our precious lives, we do not have one narrative to guide us. That is a dangerous vacuum as it means that technocratic, one-sided political narratives, criminal conspiracies or religious cults can fill the gap by strategically fragmenting and amplifying identity parts that suit their narratives. This creates what I termed a “pinwheel self,” a firework that when ignited, creates sparks and flames around its own center. After a spectacular display, there is nothing but carbon residue and a sense of burn-out and even more profound loss of meaning. During the Covid-19 pandemic, a large proportion of population viscerally experienced the clash and collapse of fastpaced opposing “selves.” Collectively, we oscillated between double standards for elites and the have-nots, the rise of populism versus a revival of socialism, decentralization of power versus state control and surveillance, atonement of online connections versus backlash against technology giants, scientific break-throughs on intellectual levels versus basic failures on pragmatic implementations, protests

Conclusion

217

against systemic racism, transphobia and homophobia in societies versus ephemeral successes of online manipulation. If I zoom out to see the competing narratives, I can see deep wounds on both sides, with a lot of repair work necessary for their reconciliation. Through the process of personalization, we assimilate and project fragments into the gaps left behind by others, and these fragments augment through their own prismatic fragments, layers after layer. How can we stitch these fragments together, personally and collectively, to amplify the best in us? In this book, I attempt to articulate a thinking framework for this work. There are seven thinking points because the number seven has a special significance: there are seven days of the week, seven notes in a music scale and seven items in the immediate span of attention. There are seven design principles in modern websites and it was the seventh day on which the Creator rested. The number seven indicates magic. We all can think rationally but we still get spellbound by magic, at least once in life. Some people call magic moments encounter with theological or romantic love. In such encounters, agency and belonging fuse together through a reciprocal harmony, seeding new visions and ideas. Perhaps the number seven appears magical because it indicates completion. However, this book is far from complete. A book on personalization can only scratch the surface of the story of pluralization. It is my hope that this book provides the basis for the living story that runs in its background – the diverse voices that make up the me in you. Together, we can grow datafied selves, autobiographical selves, true selves, ideal selves, alternative selves, expanded, unbound, relational and networked selves. These selves constitute a kaleidoscope of choices that move around in a circle as humans turn their own lens tubes. The next decade might be about reassembling dispersed confetti into coherent patterns and it might also be about evolving our pinwheels into multiple-color swarms of lighted drones. Our digital and “flesh” fragments create new 3D amplifications that can backslide us into seven sins or draw into the seven wonders of the world. The personalization–pluralization is the reality holding the homo fragmentum and homo amplificon together.

This page intentionally left blank

NOTES INTRODUCTION 0.1. Different disciplines provide different lenses for their interpretation. A few simple examples: socio-cultural education, on the one hand, perceives teachers and children (and their families) as cocreators of knowledge. Together, they “inter-think” their individual and collaborative competences (Littleton & Mercer, 2013). Classic psychology, on the other hand, has developed powerful techniques for studying individual differences. Psychologists know that more intense processing, that is, the activation of specialized neuronal circuits, can be predicted even with simple markers of identity, such as one’s name or picture of a loved one. Human–computer interaction (HCI) scientists ask granular “how” questions about the design of individual technologies. Such an approach allows them to repair past mistakes and ignite new perspectives and breakthroughs. Findings from HCI studies can help us to understand that for children with dyslexia, for example, seemingly small design changes (e.g., letter, word and line spacing personalized to each reader) increase their reading speed (Sung et al., 2015). In this book, I synthesize evidence and perspectives from studies in these three disciplines and that relate to typically developing children aged between two and twelve years. This does not mean that other children are excluded from my considerations, but they are not fully represented in the studies that I have chosen to discuss in this book. It is also worth highlighting that in my book I focus on children up to the age of 12. To get a detailed insight into Generation Z’s thoughts and actions (i.e., children who were teenagers in 2010), it is worth reading “Generation Z: Their Voices, Their Lives” by Chloe Combi

219

The Future of the Self

220

and “Hello Gen Z: Engaging the Generation of Post-Millennials” by Claire Madden. CHAPTER 1 1.1. While the main definition, “personalis, personalis, personale,” relates to an individual as already established, “personal” can also be translated as: 1. Personal possession, which explains why there is an interest in the themes of belonging and ownership with personalized products. 2. Secret, intimate, mysterious, which is closely related to the theme of trust with personalized services, and also originality when it comes to art production. 3. Private and personal, which is directly linked to privacy and debates around personal data.* 4. Domestic, familiar, native, which connects to studies on intrinsic motivation, familiarity, local knowledge and heritage. 5. Personal as a noun, translated as direct contact, which explains why personal technologies follow haptic navigation. 6. As a personal attendant or servant (who of course looked and spoke very differently in Ancient Rome than today’s Alexa). 7. As a first name, which is the most frequently used technique to personalize children’s products. 8. As personal doctor of the emperor, which foreshadows the popularity of personalized medicine as the first large-scale application of personalization. 9. As experience or personal knowledge, which is why the commercial use of personalization needs to draw on an individual’s personal knowledge. http://www.latin-dictionary.net/search/english/personal *I want to clarify the relationship between personal and private, indicated in the third meaning of the word. Many assume that sharing personal information or personalized products means losing privacy. However, personalized anonymity models are commonly used in situations where the user needs or wants to protect their privacy but still benefit from personalized services. For example, a common strategy

Notes

221

in advertising and emergency alerting services is to keep users’ profile private but to continue providing them with location-specific information. Smart devices make available different degrees of privacy. Some are more vulnerable to abuse while some offer deeper anonymity than that available without smart gadgets. On social media, celebrities like to share details from their private lives and monetize the attention they get from millions of followers. In anonymous massive online games, users enjoy privacy and possibility to customize their avatar that represents their persona in the game, for example. 1.2. https://en.oxforddictionaries.com/definition/personalize 1.3. In addition to the reactive/responsive distinction in personalized design, researchers distinguish between personalized design that uses data dynamically or statically. Dynamic personalized design uses personal data to continuously tailor the content in response to the user’s activity. An example of the dynamic personalized design is the iRead system (see: https://iread-project.eu/) that offers children content at varying levels of difficulties depending on children’s progress in specifically designed games. An example of static personalized design is the Wonderbly’s book Lost My Name (see: https:// www.wonderbly.com/) that uses the letters that make up individual children’s names to adjust the story plot of each individual book. However, once the book is printed, it cannot be further updated. These distinctions are more familiar to HCI researchers. In educational research, dynamic personalization is referred to as adaptive learning. 1.4. I want to remind the reader that even Alfred Binet, the French psychologist who invented the IQ test in the nineteenth century, did not advocate nature-driven determinism. He advocated for training and practice to move children’s IQ scores up. In other words, he saw the IQ test as a measure or device for social change. In a lot of follow-up work, Binet’s IQ test has been interpreted as social fatalism. We need to be careful about not mis-interpreting contemporary scientists’ work. Robert Plomin, professor of behavioral genetics at King’s College, London, advocates for tailor-made education according to children’s polygenic score. He has been heavily criticized for viewing children’s genetic past as a way to determine their future learning paths. To get a balanced perspective

The Future of the Self

222

on the view advocated by Professor Plomin in his book Blueprint, How Our DNA Makes Us Who We Are, it is worth you combine it with reading the article ‘The Science of Human Perfection’ by Nathaniel Comfort. CHAPTER 2 2.1. Remediation might suggest a linear evolution from one technology directly mapped onto the next one. Here it is important to acknowledge that the remediation process is different for different technologies. Certainly communication technology has been shaped in anticipation of a particular audience and reshaped through response and uptake, that is, it was not a linear progression. 2.2. For influential work in this area, it is worth looking up work by Jean Twenge and Keith Campbell (2009) and a contrasting perspective offered by Jeffrey Arnett and Sonia Livingstone. I recognize the concerns embedded in the “Me Generation” term. However, the focus in my work is different. I emphasize that the change we are witnessing in the early twenty-first century is not just a technological change and that extreme levels of personalization occur not only with children and in the young population, but the society as a whole. 2.3. You could compare the personalization approach to individualism/collectivism with cultural psychology, where the interest is in how culture dynamically changes according to different contexts and times, not what its enduring characteristics are. In both approaches, the question of “individualism–collectivism” is subverted as is the assumption that the world can be neatly divided into two homogeneous groups. Many studies show that the picture is more mixed than what is expected by the individualist–­collectivist comparison. Here are three studies to indicate some of that variation. Schreier et al. (2010) showed lowest social anxiety levels in Latin American students and not in East Asian undergraduates. A comprehensive comparison of perspectives by Chinese, Japanese and American mothers published in 1990 showed American mothers’ greater support for children’s abilities, which they perceived as innate and which they praised more frequently than the Chinese

Notes

223

and Japanese mothers (Stevenson & Lee, 1990). Further, the length of stay of the parents in a given country matters: European American parents were found to be supporting children’s self-esteem more than immigrant Chinese parents (Chao, 1996). Another popular dichotomy used in relation to technology is to compare urban versus rural communities/cultures. Targeted online services are more difficult in areas of poor mobile phone signal or slow Internet connection. Such areas are typically thought of as an urban versus rural issue but there are many urban metropolitan areas that have poor connectivity, for example, the London boroughs of Bermondsey and Old Southwark, Bethnal Green and Bow (Ofcom, 2018). 2.4. The OECD (2015) has a refrigerator-magnet-quote about this relationship in educational technology: “Technology can amplify great teaching but great technology cannot replace poor teaching” (p. 4). 2.5. Vygotsky (1978) would say that “our criticism of current views concerning the essential nature and development of psychological processes must inevitably result in a re-examination of methods of research” (p. 58). Old methods cannot do justice to new phenomena. If we are to understand the added value of new tools (new technologies) to children’s lives, researchers need to update their Method Toolkit. Innovative research methods often emerge from cross-disciplinary work. However, while multi-­disciplinary and multi-method research is desired by researchers, it is hampered by three structural reasons: researchers’ monodisciplinary training and consequent affiliation to a specific university department (researchers are very rarely based in, e.g., experimental psychology and arts); mono-disciplinary publication outlets and mono-­ disciplinary research funding streams. 2.6. There is no blueprint for the use of technologies in diverse families and this book is not offered as a guide to children’s positive technology use (but if this is your interest, please check the recommended reading references in my book How and Why to Create Children’s Digital Books). There are also some wonderful organizations that provide what the English pediatrician Donald Winnicott describes as the most effective parenting advice: providing examples of inspirational

The Future of the Self

224

practice. The Joan Ganz Cooney Center, New America, Fred Rogers Center, Technology in Early Childhood Erikson Center, National Literacy Trust, Connected Learning Research Network and Essential Parenting are a few centers from an expanding list of organizations that fill the gaps created by underfunded public services (such as professional development training for teachers and social workers, or libraries in the UK). 2.7. For example, the company ToyTalk Ltd. has developed a suite of Internet-connected toys with which children can have a “conversation.” The toys recognize simple commands, they feature songs, lines of dialogue and games to provide children with entertainment. 2.8. In the context of international relations, researchers have come up with the concept of “engaged pluralization” (Lapid, 1989), which highlights the importance of dialogue for reaching sustainable solutions. CHAPTER 3 3.1. Brian Greene’s (2007) iconic quote about free will explains that free will is a useful concept but based on the modern physics laws, it is illusory: “Free will is the sensation of making a choice. The sensation is real, but the choice seems illusory.” The debate about what free will is and is not, will more than likely keep on going for years to come. New inventions, such as AI, pitch into the debate. In the context of specific, narrowly defined problems, well-designed AI can provide a more accurate assessment than the human brain. This has powerful application possibilities in diagnostic contexts that are prone to human error. However, it is the combination of AI and human intelligence that provides the strongest synthesis for informing decision-making. Unless humans evolve into a new form of life, their agency in making decision cannot be diminished. This might sound trite but this is why contemporary philosophers, such as David Hodgson (2012), assert that free will is a combination of human rationality together with human consciousness. 3.2. See the following publications for inspiration: Alexander and Sandahl (2016), Partanen (2017) and McGurk (2018). 3.3. Kress and Van Leeuwen (1996) outlined a theory of visual communication, which goes beyond 2D images to communicating

Notes

225

and “reading” 3D objects such as toys, sculptures, buildings, as well as icons and virtual spatial representations. From their perspective, media representation, films and children’s literature all merge in a visual continuum. It is to be hoped that over time more researchers will become more precise about the different modes used in personalized design. For example, one study might focus on the visual mode of personalization (e.g., the use of children’s selfies) and compare it to the audio mode (e.g., the use of children’s voiceovers). Specific facets of personalization would generate data that can be used for building predictions and a comprehensive theory of personalization. 3.4. The Wordpress blogging site is another example of community design. There are millions of original blog posts authored every day. Bloggers can create their own writing space and decide on the content and its appearance. The community contribution can be used for continuous innovation: Spaulding and Perry (2013, p. 2) explain that companies that offer customization are able to use consumers as merchants – continuously gaining insights from customized designs and finetuning products in a feedback loop that helps companies stay one step ahead of the competition. 3.5. This is the trio of emotions which elicit an immersive pleasurable experience in gaming, the so-called PAD emotions. 3.6. At the Stanford Persuasion Lab, behavioral psychologists study the ways in which Computers act As Persuasive Technologies (a phenomenon the scientists call CAPTology). Other captive techniques include the instantaneity and randomized delivery of rewards and constant representation of novelty. If novelty and threat are personalized, humans pay even more attention because the threats are personally threatening or personally rewarding. 3.7. Did you know that in 2017, there were already approximately 60 billion messages sent per day by 1.5 billion users of WhatsApp? (This was according to an interview with the Facebook CEO Mark Zuckerberg in 2017 so the numbers must be higher at the time of you reading this book.) It is not about the total number

226

The Future of the Self

here but the proportion of use that should be worrying you. We used to have a few photos from holidays but nowadays, an unprecedented amount of visual information is exchanged every day, by all of us. This brings me to an important caveat: I want to be very clear that these design criticisms are about hyper or extreme personalization and pluralization, and not their moderate values. It follows that my critique is intended to prompt you consider your own agency in using social media for hyper personalization and hyper social engagement. With a design limiting the number of followers or the amount of pictures per year, would you be paying more attention to what you share? 3.8. Children’s TV programs follow clear rules to ensure that there is no product placement and no selling offered in the middle of the story: advertising is presented in easy-to-identify snippets (Children’s Media Foundation). This is different with apps and videos produced for the Internet, where automatic advertisements play before a video starts, interrupt a story in the middle or even place a product within a game that does not advance to the next stage unless a purchase was made (the so-called in-app purchase). At the time of writing this note, the pervasive presence of persuasive design in children’s technologies is poorly regulated by national and international organizations. 3.9. The use of decentralized data servers was pioneered by the Diaspora founders who aimed to counteract Facebook with a system that would be built on individual freedom and privacy. The HAT Foundation that I work with is interested in rebalancing the economic power and change the asset of data. Professor Irene Ng, who has led the HAT Consortium since its inception, makes a compelling economic argument: when individuals can directly generate and monetize their data, the data will be, in the long run, of higher value. Web creator Tim Berners-Lee has been working with the Massachusetts Institute of Technology on a similar project, in which users can create their own personal online data store. Micro-servers work like this: If I have in my HAT micro-server data on what I ate for lunch last month, for example, I can decide to share this information with a lunch provider in a local area. The provider can then personalize their offer for my lunch. Such a personalization is transparent and agentic, co-produced by the provider and the user. Time will tell

Notes

227

whether decentralized data models can fix the problems of personal data economy. 3.10. Personalization and pluralization generated through users’ own agency (agentic P–P) need to be greater than the sum of P–P generated automatically. This graphic simplifies the formula. 1A is the personalization process led by the individual and 1B is the personalization process led by someone else using the individual’s data. For example, in 1A, a child self-selects a book from the school library. In 1B, Amazon sends the child a personalized book recommendation. 2A shows the pluralization process whereby a group of people agree on a set of characteristics/data points about them and use these data to create resources/objects relevant for their and others’ groups. For example, a school uses their students’ data to create a school improvement plan and shares the plan with the children/their guardians and local inspection officers. 2B occurs when collective data that are not attributable to an individual or a specific group, but that are still used for creating objects and resources. For example, population statistics are used for developing global risk protocols. Optimal levels of P–P are ensured when agency dominates, that is, when 1A + 2 A > 1B + 2B.

CHAPTER 4 4.1. Jordan Peterson’s controversial claim that hierarchies are innate has been criticized by Burston (2019) who notes multiple interconnected hierarchies in the society (socio-politico-economical

228

The Future of the Self

one) and Carl Miller’s (2018) insightful evidence from social media research shows how traditional power structures morph under the weight of new technological infrastructures. 4.2. A sharing economy is an informal economy that started in the nineteenth century Europe. Unlike the Uber economy, it supported direct sale of skills, products or activities. 4.3. Many people don’t realize that an increasing substantial proportion of undercover policing includes investigating data leaks and personal data laundering. Many data scandals were first reported by undercover journalists, some of whom paid for their journalism with life. The Committee to Protect Journalists reports that 1,323 journalists were killed between 1992 and 2018. Fake news and data-based scandals (e.g., the Cambridge Analytica scandal) showed that personalized services can be easily manipulated to sway large populations into believing biased, unverified and sometimes outright inaccurate, information. An insightful analysis was undertaken by Brian Ott (2017) in relation to President Trump’s Twitter use. 4.4. Based on her analyses of dating history and the data from the dating site Match.com, Fisher makes the point that children’s experiences of parents’ divorce hits them doubly hard because of the lack of local community to support single mothers. Fisher’s historical analysis shows that the level of intimacy with immediate local community is not as high as it historically used to be, which means that more single parents are seriously lonely. In addition, more couples seek higher levels of intimacy in their primary relationship. 4.5. There are many and better books that discuss pluralization in the twenty-first century, written by scholars dedicated to the study of collective values. Excellent feminist and sociology scholars (e.g., Gayle Letherby) speak about the politics of belonging and the experience of otherhood. 4.6. The biggest longitudinal study in the UK, the Effective Pre-school, Primary and Secondary Education Project, which has followed the academic and social-behavioral development of approximately 3,000 children from the age of 3+ years since 1997, found increasing levels of anxiety among the participating children over time. When the researchers examined in detail

Notes

229

the children’s anxiety levels at the age of 14 (Year9 in the UK school system), they noticed that there were significant differences between girls’ and boys’ reports (Sammons et al., 2012). Mental health issues typically start around the age of nine and ten and peak when children transition to secondary school. Among the 15 to 25-year-olds anxiety levels have soared even in the happiest countries of the world such as Finland or the Netherlands. On the positive side, there are several inspirational research programs illustrating how mental health can be tackled. For example, a program called FRIENDS designed to prevent anxiety led by Professor Paul Stallard (2014) tackles the question of preventing, rather than curing emotional problems in young children and adults. If not tackled, anxiety and low-mood problem can affect family lives, friendships and academic achievement and conversely, if schools help children identify and manage their emotions in a proactive way, children can grow more emotionally resilient. The 24/7 access to online comparisons with others (mostly fed through persuasively designed social media and news outlets), constant flow of negative information and notifications for attention, are incompatible with the optimal conditions for well-being described by Ed Diener (2009) in his works. 4.7. In the USA, Mister Rogers’ Neighborhood, an educational TV series for preschoolers that ran from 1968 till 2001, was known for Mr Rogers’ calm and kind style of connecting with his audience. In Norway, the NRK2 national television broadcaster made it into international TV channels with their so-called “slow TV.” In 2009, it released a seven-hour-long program of the train journey from Bergen to Oslo, which was followed by videos of burning fire logs. There were no commercials, no accelerated images, no intention to “hook” the viewer. 4.8. There are also substantial Hindu and Chinese migrations for different reasons and to different destinations all of which present separate “cases” to be examined. CHAPTER 5 5.1. Another headline-generating selfie practice is the so-called “disaster selfies”: selfies taken at the scene of trauma or tragedy

The Future of the Self

230

(e.g., a selfie taken right after an earthquake or a terrorist attack and shared on social media). 5.2. It should be noted that pictures might help with word recognition only for some groups of children. Sheehy’s work has established whether the use of personalized pictures could support word learning of children with severe/profound difficulties. 5.3. The UK and US political definitions of personalized learning equate personalization with adaptation. The U.S. Department of Education (2018) defined personalized learning as a system that “allows students to progress as they demonstrate mastery of academic content, regardless of time,” which, Dockterman (2018) argues, builds on 200+ year continuous efforts of US education reformers to develop effective and sustainable personalized education models. David Miliband (2004), the then UK Minister of State for the Cabinet Office, proposed personalized education as his vision for future education with tailor-made student-centered education that accommodates children’s unique learning styles, motivations and needs. 5.4. A focus on personalization might, inadvertently, unify a long-standing feud in media studies between metacognition (what people think about the message in a medium) and the modality of its representation. Take the example of reading on screen versus reading on paper. Many researchers (and members of general public) are concerned that children’s activities with screens replace reading of books. There is a concern that reading on tablets is inferior to reading on paper. And there is a concern that reading habits on screens will carry over to reading on paper. These are valid concerns but collapsing all three concerns can lead to the erroneous conclusion that the source of all evils is the screen. I wrote about the fine balancing necessary here in Kucirkova (2019d). CHAPTER 6 6.1. Folk wisdom suggests that some children prefer to learn by listening, some by reading, some by drawing sketches and mind maps. Some teachers like to categorize their students into “visual” or “auditory” learners and believe that such categories reflect students’

Notes

231

abilities. However, there is enough empirical evidence (summarized in a widely cited article by Kirschner, Sweller, & Clark, 2006) that shows that learning styles do not support better learning outcomes and that students need a variety of approaches to learn well. It is unfortunate that some personalized learning programs tailor learning based on the children’s preferred learning style. Children can either self-categorize themselves or the system automatically puts them into relevant categories. Such systems standardize children according to pre-defined categories based on models of an average or ideal child. This is the exact opposite of what personalized education should be about, as argued in Kucirkova (2018). 6.2. The Education Endowment Foundation is a UK-based independent charity that aims to improve the educational attainment of the poorest pupils in English schools. 6.3. The Swiss psychologist Jean Piaget explained that there are two processes for learning: assimilation and accommodation. Put simply, assimilation, on one hand, is about incorporating previous knowledge and experiences into an existing bank of knowledge. Accommodation, is about changing the existing knowledge in response to new experiences. Piaget used the term “equilibration” to explain the process of balancing previous and new knowledge. You can think of equilibrium and agency as follows: if a child can decide what they are about to learn, the distance between assimilation and accommodation is smaller than if the child is asked to assimilate information, which is not consistent with their previous knowledge, or cognitive schema, as some psychologists say. In those circumstances, the child enters the state of disequilibrium, which requires more thinking resources. This is challenging for the child because the new information is not aligned with what the child experienced before and accommodating it takes time and effort. The child enters the state of disequilibrium, which, when mastered, is the primary condition for cognitive growth. So, although supporting children’s agency is important for encouraging their intrinsic motivation for learning, it is also important to create learning conditions where children’s choices are limited and purposefully constrained by the learning situation. 6.4. Walton and Cohen (2011) conducted an ingenious longitudinal experiment with two groups of African-American and

232

The Future of the Self

European-American college students in the second s­emester of their first year. The researchers hypothesized that if they can increase the feelings of social belonging among socially stigmatized individuals such as those represented by the African-­ American students, they might reduce the inequality between the students in the college and boost these students’ performance. Their prediction proved to be true. The intervention was surprisingly simple: at the beginning of the study, the researchers presented African-American and European-African students with invented survey results. The results told the story of students who reported concerns about belonging in the college only in the initial period of transition to the college but over time, found lasting friends. The students were asked to read and internalize the survey results by writing an essay and deliver a speech about the results. The impact of internalizing the positive belonging message had a dramatically positive effect on the African Americans group: not only did it close the achievement gap between them and the European Americans group, it also had a lasting positive impact on their perception of how happy and healthy they felt during their studies. The ingenuity of the experiment from the personalization perspective is that three years after the intervention, none of the students attributed the positive results to the intervention they could remember from the past. This indicates that the “treatment” worked outside the students’ conscious awareness. They did not feel as a group that needed help, in fact that very feeling would have likely undermined the positive results. 6.5. As reported by Buckner et al. (2008), these areas are: ventral medial prefrontal cortex, posterior cingulate/retrosplenial cortex, inferior parietal lobule, lateral temporal cortex, dorsal medial prefrontal cortex and hippocampal formation. 6.6. Socio-cultural perspectives on education have been elaborated not only by Vygotsky but also by post- and neo-­ Vygotskian theorists in Russia such as Luria, Leontiev, Davydov and have later evolved into the cultural-historical activity theory that draws on Bakhtian dialectics and Cole and Engeström idea of active ­learning networks. These approaches are similar

Notes

233

in their focus on social interaction but there is an important difference between dialogue and dialectics. Interested readers should consult writings by Dr Anna Stetsenko as well as Wegerif (2008), Marchenkova (2005), Shotter (1993), Matusov (2011) and Emerson (1983). 6.7. From the dialogic perspective, the current public education system is a restricted place that functions according to linear schedules of lessons and exams. The structure of schools and the expectations around them position knowledge as a localized, time-bound entity. Meyer and Land (2003) capture an alternative vision of knowledge, by using the term “liquid liminal space.” The liquid liminal space is an ongoing reciprocal negotiation of learning in which learners get transformed and in doing so, transform the learning space. The methods of educational research and the practice of educational establishments do not correspond to this metaphor. If students encounter a concept they do not understand, they are either pushed through the threshold to “get it” or they get depicted as those who “do not get it.” And yet, the key characteristic of wisdom is to create an open space in which opposing ideas can be accommodated and dialogically explored. Dialogue occurs in the foreground of cultural discourse, the common ground of shared understandings. 6.8. Precision personalized education, such as the one offered at the Precision Institute at the National University, USA, is more personalized than “just” personalized education because it first establishes the student’s strengths and weaknesses, and based on the result it recommends a learning path. Individual students’ characteristics, such as the students’ neurobiological, genetic or behavioral markers, are integrated into a learning profile, which is precisely matched to and dynamically adjusted with ongoing measurements of the students’ progress. Ongoing measurements include not only cognitive gains (e.g., how many words has the student learnt) but also affective measures (e.g., how concentrated is the student’s eye gaze) when reading a piece of text, for example. Establishing a baseline is a good idea. It helps identifying which children profit from which types of learning supports when learning specific concepts, such as letters or numbers. Students coming

The Future of the Self

234

from unfavorable learning backgrounds or students who are not physiologically predisposed for learning specific concepts can benefit from precisely tailored learning supports. One issue, however, is that such learning supports are by and large developed and optimized in the form of digital technologies (e.g., adaptive software) and not pedagogical strategies for human teachers. The other issue is that precise education might work for vocational learning but not so much for comprehensive academic learning that fosters broader understanding of complex socio-economic, geo-political issues – not all skills should be vocationalized. Yet another issue is that such a personalized education nurtures a fixed mindset, forcing children into a specific category, or one vision of what learning and achievement are, which ultimately limit their horizons and society gain. 6.9. In medical models, randomized controlled trials (RCTs) are the golden standard, but in socio-cultural models of education, RCTs are questioned. The unsuitability of RCTs becomes evident at the point of implementing interventions, that is, when educational policy interacts with political, geographical and socio-cultural values. No matter how successful a RCT might be in one or twenty schools, its success is difficult to replicate in other schools because it is difficult to keep high intervention fidelity over time (i.e., ensure that all teachers carry out the new approach in exactly the way they are told by the intervention advocates). Then there are significant ethical concerns regarding the ways RCTs are carried out in education and the amount of public funding that is spent on RCTs in disproportion with other methods available for evaluation. More on this in R. Brooks, Te Riele, and Maguire (2014). CHAPTER 7 7.1. A story is a sequence of actions or events while a discourse is the form in which these actions are portrayed or told. Although discourse and story work together, they both have their own formats. Narratives are not neutral, they always contain the psychological perspective of those who developed them. Therefore, to turn

Notes

235

a narrative into a different medium (e.g., a story that first appeared in a published book into a virtual game), requires a translation of both the discourse (the way it’s told) and the story (the sequence of events). It follows that digital stories that merely take the text from a printed book without adjusting its discourse are failed projects (think of an e-book that is nothing more than a digitized text). 7.2. Son and Goldstone’s study raised a lot of interest in the psychology community with some follow-up interpretations by other psychologists. Greeno (2009) argued that rather than framing context as either present or absent it would be more accurate to agree that a context is always there, and that what matters is how personalized the context is and how it relates to a particular activity. Psychologists moor themselves to the fact that contextualization is a condition (a stable variable) but in reality, it changes depending on each individual. 7.3. A meta-analysis of the conversational style effects by Ginns, Martin, and Marsh. (2013) concluded that the conversational style has a significantly positive learning effect. So far, researchers have not established why the effect occurs but they found some interesting moderating factors: across studies, positive learning effects occurred only if the learning was confined to half an hour or less. If the learning was for more than 30 minutes, the positive effects dropped sharply to almost zero. The researchers speculated that perhaps given this time boundary and its dramatic impact on whether personalized learning is actually positive or not, the effect occurs because of novelty. Since most learning materials are not written in conversational style, it could be that encountering materials that address students directly increases their attention levels because it is something they have not seen before. Once they get used to the fact that the materials are personalized, their attention dwindles and their processing of the learning material is less focused. This explanation has not been supported elsewhere and is not confirmed by Meyer’s current work. What is emerging from the latest research is a differential preference for personalized information presented in different modes (texts vs pictures) and content that is aversive or positive. So far, the experiments have been conducted with adult users and c­ omputer-based

236

The Future of the Self

learning materials (e.g., Zander, Wetzel, Kuhl, & Bertel, 2017), but with the growing interest in personalized learning we might expect studies in other areas too. 7.4. See the following studies by Janes and Kermani (2001), Bernhard, Winsler, Bleiker, Ginieniewicz, and Madigan (2008) and González et al. (2006). 7.5. Relevant publications are O’Sullivan and McGonigle (2010) and Cremin, Mottram, Collins, Powell, and Safford (2014). 7.6. As asserted decades ago by Margaret Meek, one of the most inspirational writers and reading teachers in Britain, the digital text with hyperlinks and animated pop-ups, distracts children from deeply processing the text. But while there has been a lot of research and public interest in the difference between digital and print books, less is known about the underlying reasons for the differences. Eliza Dresang (1999) describes the concomitant changes in the printed and digital books produced for youth as a radical change that came about as a result of increased interactivity, connectivity and digital access. 7.7. Personalized books challenge what children don’t know to a lesser extent than non-personalized books because they provide familiar clues and evolve around familiar scenarios, or at least scenarios that involve story characters and settings the child is familiar with. This lowers the threshold for participation and invites the children to see themselves in a world they are already part of. This might be engaging but not instructive for children’s theory of mind development, because, as psychologists assert, there is a very close link and a functional overlap between autobiographical memory and theory of mind (Spreng, Mar, & Kim, 2009).

REFERENCES Aarseth, E. J. (1997). Cybertext: Perspectives on ergodic literature. Baltimore, MD: Johns Hopkins University Press. Abeles, V. (2015). Beyond measure: Rescuing an overscheduled, overtested, underestimated generation. New York, NY: Simon & Schuster. Adams, D. M., McLaren, B. M., Mayer, R. E., Goguadze, G., & Isotani, S. (2013). Erroneous examples as desirable difficulty. In H. C. Lane, K. Yacef, J. Mostow, & P. Pavlik (Eds.), Artificial intelligence in education. AIED 2013. Lecture Notes in Computer Science, vol 7926. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-39112-5_117 Agalianos, A., Whitty, G., & Noss, R. (2006). The social shaping of logo. Social Studies of Science, 36(2), 241–267. Aguirre, E., Roggeveen, A. L., Grewal, D., & Wetzels, M. (2016). The personalization–privacy paradox: Implications for new media. Journal of Consumer Marketing, 33(2), 98–110. doi:10.1108/Jcm-06-2015-1458 Ainsworth, S. (1999). The functions of multiple representations. Computers & Education, 33(2–3), 131–152. doi:10.1016/ S0360-1315(99)00029-9 Albright, M. K. (2003). Bridges, bombs, or bluster? Foreign Affairs, 82(5), 2. doi:10.2307/20033679 Alexander, J. J., & Sandahl, I. (2016). The Danish way of parenting: What the happiest people in the world know about raising confident, capable kids. London: Penguin. Alfaro, M. J. M. (1996). Intertextuality: Origins and development of the concept. Atlantis, 18, 268–285.

237

238

The Future of the Self

Amnesty International. (2019). Surveillance giants: How the business model of Google and Facebook threatens human rights. Report. Retrieved from https://www.amnesty.org/download/Documents/ POL3014042019ENGLISH.PDF Andersen, S. M., & Chen, S. (2002). The relational self: An interpersonal social-cognitive theory. Psychological Review, 109(4), 619–645. Retrieved from https://www.ncbi.nlm.nih.gov/pubmed/12374322 Andrejevic, M. (2003). Monitored mobility in the era of mass customization. Space and Culture, 6(2), 132–150. Antonelli, P., Hunt, J., & Fisher, M. M. (2015). Design and violence. New York, NY: The Museum of Modern Art. Araujo, H. F., Kaplan, J., & Damasio, A. (2013). Cortical midline structures and autobiographical-self processes: An activation-likelihood estimation meta-analysis. Frontiers in Human Neuroscience, 7, 548. doi:10.3389/fnhum.2013.00548 Asadoorian, M. N. (2007). Where did all these books come from? The publishing industry and American intellectual life. Honors Theses Paper 282. Retrieved from https://digitalcommons.colby.edu/ honorstheses/282 Bahl, S., & Milne, G. R. (2009). Talking to ourselves: A dialogical exploration of consumption experiences. Journal of Consumer Research, 37(1), 176–195. Bahrami, B., Olsen, K., Latham, P. E., Roepstorff, A., Rees, G., & Frith, C. D. (2010). Optimally interacting minds. Science, 329(5995), 1081–1085. doi:10.1126/science.1185718 Bailey, B. (2007). Heteroglossia and boundaries. In M. Heller (Ed.), Bilingualism: Social and political approaches (pp. 257–274). New York, NY: Palgrave MacMillan. Bailey, R., Wise, K., & Bolls, P. (2009). How avatar customizability affects children’s arousal and subjective presence during junk food-sponsored online video games. CyberPsychology & Behavior, 12(3), 277–283. doi:10.1089/cpb.2008.0292

References

239

Baishya, A. (2015). Selfies|# NaMo: The political work of the selfie in the 2014 Indian general elections. International Journal of Communication, 9, 15. Bakhtin, M. M. (1986). The Bildungsroman and its significance in the history of realism. Speech Genres and Other Late Essays, 10, 21. Baldwin, M. W. (1992). Relational schemas and the processing of social information. Psychological Bulletin, 112(3), 461. Banaji, M. R., & Greenwald, A. G. (2016). Blindspot: Hidden biases of good people. London: Bantam. Bandura, A. (1977). Self-efficacy: Toward a unifying theory of behavioral change. Psychological Review, 84(2), 191–215. Retrieved from https:// www.ncbi.nlm.nih.gov/pubmed/847061 Bandura, A., & Schunk, D. H. (1981). Cultivating competence, selfefficacy, and intrinsic interest through proximal self-motivation. Journal of Personality and Social Psychology, 41(3), 586–598. doi:10.1037/0022-3514.41.3.586 Bar, M., Aminoff, E., & Schacter, D. L. (2008). Scenes unseen: The parahippocampal cortex intrinsically subserves contextual associations, not scenes or places per se. Journal of Neuroscience, 28(34), 8539–8544. Barber, J. (2007). Consumed: How capitalism corrupts children, infantilizes adults, and swallows citizens whole. New York, NY: Norton. Baron-Cohen, S. (2017). Editorial perspective: Neurodiversity – A revolutionary concept for autism and psychiatry. Journal of Child Psychology and Psychiatry, 58(6), 744–747. Barry, B. (2005). Why social justice matters. Cambridge: Polity. Baumeister, R. F. (1982). A self-presentational view of social phenomena. Psychological Bulletin, 91(1), 3–26. doi:10.1037/0033-2909.91.1.3 BBC. (2015). The decline of religion in the West. Retrieved from https://www.bbc.com/news/world-33256561

240

The Future of the Self

Beavers, A. F. (2012). In the beginning was the word and then four revolutions in the history of information. In H. Demir (Ed.), Luciano Floridi’s philosophy of technology (pp. 85–103). New York, NY: Springer. Beggan, J. K. (1992). On the social nature of nonsocial perception – The mere ownership effect. Journal of Personality and Social Psychology, 62(2), 229–237. doi:10.1037/0022-3514.62.2.229 Belfield, C. R., & Levin, H. M. (2015). Privatizing educational choice: Consequences for parents, schools, and public policy. New York, NY: Routledge. Belk, R. W. (1988). Possessions and the extended self. Journal of Consumer Research, 15(2), 139–168. doi:10.1086/209154 Belk, R. W. (2014). The extended self unbound. Journal of Marketing Theory and Practice, 22(2), 133–134. Bellah, R. N., Madsen, R., Sullivan, W. M., Swidler, A., & Tipton, S. M. (2007). Habits of the heart: Individualism and commitment in American life. Berkeley, CA: University of California Press. Berkling, K. K., & Gilabert, R. (2019). Transfer of educational skills from games to classroom tasks: A case study using iRead to improve reading and writing. Workshop paper presentation at GamiLearn conference, October 22, Barcelona. Bernhard, J. K., Winsler, A., Bleiker, C., Ginieniewicz, J., & Madigan, A. L. (2008). “Read my story!” using the early authors program to promote early literacy among diverse, urban preschool children in poverty. Journal of Education for Students Placed at Risk, 13(1), 76–105. Bernstein, B. (2000). Pedagogy, symbolic control and identity: Theory, research, critique. London: Rowman and Littlefield (Original work published in 1996). Bernstein, B. (2003). Class, codes and control: Towards a theory of educational transmission (Vol. 3). London: Psychology Press. Best, S. (1991). Postmodern theory: Critical interrogations. London: Macmillan International Higher Education. Biesta, G. (2013). Responsive or responsible? Democratic education for the global networked society. Policy Futures for Education, 11(6), 733–744.

References

241

Bloom, P. (2017). Against empathy: The case for rational compassion. London: Random House. Boakes, E., & Redding, D. (2018). Extinction is natural, but it’s happening at 1,000 times the normal speed. The Conversation. Retrieved from https:// theconversation.com/extinction-is-a-natural-process-but-its-happening-at-1000-times-the-normal-speed-99191. Accessed on January 4, 2019. Bolter, J. D., Grusin, R., & Grusin, R. A. (2000). Remediation: Understanding new media. Cambridge, MA: MIT Press. Boudet, J., Gregg, B., Rathje, K., Stein, E., & Vollhardt, K. (2019, June). The future of personalization – And how to get ready for it. McKinsey Report. Retrieved from https://www.mckinsey.com/business-functions/ marketing-and-sales/our-insights/the-future-of-personalization-and-howto-get-ready-for-it Bourdieu, P. (1986). The forms of capital. In J. G. Richardson (Ed.), Handbook of theory and research for the sociology of education (pp. 241–258). Westport, CT: Greenwood Press. Bradbury, A. (2019). Datafied at four: The role of data in the ‘schoolification’ of early childhood education in England. Learning, Media and Technology, 44(1), 7–21. Brandist, C., & Tihanov, G. (Ed.). (2000). Materializing Bakhtin. London: Palgrave Macmillan. Brasel, S. A., & Gips, J. (2014). Tablets, touchscreens, and touchpads: How varying touch interfaces trigger psychological ownership and endowment. Journal of Consumer Psychology, 24(2), 226–233. doi:10.1016/j.jcps.2013.10.003 Brod, G., Hasselhorn, M., & Bunge, S. A. (2018). When generating a prediction boosts learning: The element of surprise. Learning and Instruction, 55, 22–31. doi:10.1016/j.learninstruc.2018.01.013 Brooks, R., Te Riele, K., & Maguire, M. (2014). Ethics and education research. London: Sage. Brooks, R. A. (1991). Intelligence without representation. Artificial Intelligence, 47(1–3), 139–159.

242

The Future of the Self

Brown, B. (2015). Daring greatly: How the courage to be vulnerable transforms the way we live, love, parent, and lead. London: Penguin. Brown, P. C., Roediger III, H. L. & McDaniel, M. A. (2014). Make it stick. Cambridge, MA: Harvard University Press. Bruneau, E. G., Cikara, M., & Saxe, R. (2017). Parochial empathy predicts reduced altruism and the endorsement of passive harm. Social Psychological and Personality Science, 8(8), 934–942. Bruner, J. (1991). The narrative construction of reality. Critical Inquiry, 18(1), 1–21. Buckner, R. L., Andrews-Hanna, J. R., & Schacter, D. L. (2008). The brain’s default network: Anatomy, function, and relevance to disease. Annals of the New York Academy of Sciences, 1124(1), 1–38. doi:10.1196/annals.1440.011 Bull, B. L., & Wittrock, M. C. (1973). Imagery in the learning of verbal definitions. British Journal of Educational Psychology, 43(3), 289–293. Bullock, M., & Lütkenhaus, P. (1988). The development of volitional behavior in the toddler years. Child Development, 59, 664–674. Burston, D. (2019). It’s hip to be square! The myths of Jordan Peterson. Psychotherapy and Politics International, 17(1), e1475. Bus, A. G., Sarı, B., & Takacs, Z. K. (2019). The promise of multimedia enhancement in children’s digital storybooks. In J. E. Kim & B. HassingerDas (Eds.), Reading in the digital age: Young children’s experiences with e-books (pp. 45–57). Cham: Springer. Cabibihan, J.-J., Javed, H., Ang, M., & Aljunied, S. M. (2013). Why robots? A survey on the roles and benefits of social robots in the therapy of children with autism. International Journal of Social Robotics, 5(4), 593–618. Carr, N. (2011). The shallows: What the Internet is doing to our brains. New York, NY: W.W. Norton & Company. Caruso, V. C., Mohl, J. T., Glynn, C., Lee, J., Willett, S. M., Zaman, A., … Groh, J. M. (2018). Single neurons may encode simultaneous stimuli by switching between activity patterns. Nature Communications, 9(1), 2715. doi:10.1038/s41467-018-05121-8

References

243

Celan, P. (1963). Zum Storchen. The no-one’s-rose. Frankfurt, Germany: S. Fischer Verlag. Cerf, V. (2018). We will tackle the internet’s dark side. Wired World, January 6, pp. 24–25. Chao, R. K. (1996). Chinese and European American mothers’ beliefs about the role of parenting in children’s school success. Journal of CrossCultural Psychology, 27(4), 403–423. doi:10.1177/0022022196274002 Chaudron, S., Beutel, M. E., Donoso Navarrete, V., Dreier, M., FletcherWatson, B., Heikkilä, A. S., & Mascheroni, G. (2015). Young children (0–8) and digital technology: A qualitative exploratory study across seven countries. EU Report. Chaudron, S., & Eichinger, H. (2018). Eagle-eye on identities in the digital world, EUR 29044 EN, Publications Office of the European Union, Luxembourg, ISBN 978-92-79-77689-2. doi:10.2760/48837 Chetty, R., Henderson, N., Kline, P., & Saez, E. (2013). Summary of project findings: Executive summary. Equality of Opportunity Project. Retrieved from https://www.scribd.com/document/157408091/ Harvard-Berkeley-study Chetty, R., Hendren, N., Kline, P., & Saez, E. (2014). Where is the land of opportunity? The geography of intergenerational mobility in the United States. The Quarterly Journal of Economics, 129(4), 1553–1623. Cleveland, M., Laroche, M., & Papadopoulos, N. (2016). Global consumer culture and local identity as drivers of materialism: An international study of convergence and divergence. In C. Campbell & J. Ma (Eds.), Looking forward, looking back: Drawing on the past to shape the future of marketing (pp. 479–479). New York, NY: Springer. Comfort, N. (2019). How science has shifted our sense of identity. Nature, 574(7777), 167. Connidis, I. A., & Barnett, A. E. (2018). Family ties and aging. London: Sage Publications. Cordova, D. I., & Lepper, M. R. (1996). Intrinsic motivation and the process of learning: Beneficial effects of contextualization, personalization, and choice. Journal of Educational Psychology, 88(4), 715.

244

The Future of the Self

Coutinho, F., Bosisio, M. E., Brown, E., Rishikof, S., Skaf, E., Zhang, X., & Dahan-Oliel, N. (2017). Effectiveness of iPad apps on visualmotor skills among children with special needs between 4y0m–7y11m. Disability and Rehabilitation-Assistive Technology, 12(4), 402–410. doi:10.1080/17483107.2016.1185648 Cowie, D., McKenna, A., Bremner, A. J., & Aspell, J. E. (2018). The development of bodily self-consciousness: Changing responses to the full body illusion in childhood. Developmental Science, 21(3), e12557. doi:10.1111/desc.12557 Craft, A. (2012). Childhood in a digital age: Creative challenges for educational futures. London Review of Education, 10(2), 173–190. Cremin, T., Mottram, M., Collins, F. M., Powell, S., & Safford, K. (2014). Building communities of engaged readers: Reading for pleasure. New York, NY: Routledge. Creswell, H. (1973). The Bongleweed. London: Puffin. Cunningham, S. J., & Turk, D. J. (2017). A review of self-processing biases in cognition. Quarterly Journal of Experimental Psychology, 70(6), 987–995. https://doi.org/10.1080/17470218.2016.1276609 Curran, F. C. (2020). A matter of measurement: How different ways of measuring racial gaps in school discipline can yield drastically different conclusions about racial disparities in discipline. Educational Researcher, 49(5), 382–387. https://doi.org/10.3102/0013189X20923348 da Cruz, N. F., Rode, P., & McQuarrie, M. (2019). New urban governance: A review of current themes and future priorities. Journal of Urban Affairs, 41(1), 1–19. Dawkins, R. (2006). The selfish gene: With a new introduction by the author. Oxford: Oxford University Press (Original work published in 1976). Day, C., Kington, A., Stobart, G., & Sammons, P. (2006). The personal and professional selves of teachers: Stable and unstable identities. British Educational Research Journal, 32(4), 601–616. Debord, G. (1994). The society of the spectacle (D. Nicholson-Smith, Trans.). New York, NY: Zone Books (Original work published in 1967). De Botton, A. (2008). Status anxiety. New York, NY: Vintage.

References

245

De Botton, A. (2012a). How Proust can change your life. London: Pan Macmillan. De Botton, A. (2012b). Religion for atheists: A non-believer’s guide to the uses of religion. New York, NY: Vintage. Deleuze, G., & Guattari, F. (1987). A thousand plateaus (B. Massumi, Trans.). Minneapolis, MN: University of Minnesota Press (Original work published in 1980). Deloitte. (2016). Leisure sector grows to £117 billion as UK consumers prefer pleasure to shopping. Retrieved from https://www2.deloitte.com/ uk/en/pages/press-releases/articles/leisure-sector-grows-to-117-billion.html. Dennett, D. C. (1978). Brainstorms. Montgomery, VT: Bradford Books. Denny, B. T., Kober, H., Wager, T. D., & Ochsner, K. N. (2012). A metaanalysis of functional neuroimaging studies of self- and other judgments reveals a spatial gradient for mentalizing in medial prefrontal cortex. Journal of Cognitive Neuroscience, 24(8), 1742–1752. doi:10.1162/jocn_a_00233 Derudder, B., & Witlox, F. (2016). International business travel in the global economy. New York, NY: Routledge. Diemand-Yauman, C., Oppenheimer, D. M., & Vaughan, E. B. (2011). Fortune favors the bold (and the Italicized): Effects of disfluency on educational outcomes. Cognition, 118(1), 111–115. doi:10.1016/ j.cognition.2010.09.012 Diener, E. (2009). The science of well-being: The collected works of Ed Diener (Vol. 37, pp. 11–58). New York, NY: Springer. Dobbin, R. (2008). Discourses and selected writings. London: Penguin UK. Dockterman, D. (2018). Insights from 200+ years of personalized learning. NPJ Science of Learning, 3(1), 1–6. Donati, P. (2014). We need a relational reason for different cultures to meet and build a common world. In A. López & J. Prades (Eds.), Retrieving origins and the claim of multiculturalism (pp. 31–44). Cambridge: Wiliam B Eerdmans Publishing Company. Doudna, J. A., & Sternberg, S. H. (2017). A crack in creation: Gene editing and the unthinkable power to control evolution. London: Houghton Mifflin Harcourt.

246

The Future of the Self

Dowdall, C. (2009). Impressions, improvisations and compositions: Reframing children’s text production in social network sites. Literacy, 43(2), 91–99. doi:10.1111/j.1741-4369.2009.00521.x Dresang, E. T. (1999). Radical change: Books for youth in a digital age. London: HW Wilson. Druin, A. (2005). What children can teach us: Developing digital libraries for children with children. The Library Quarterly, 75(1), 20–41. Dummett, M. (2002). On immigration and refugees. New York, NY: Routledge. Dusenbery, M. (2018). Doing harm: The truth about how bad medicine and lazy science leave women dismissed, misdiagnosed, and sick. New York, NY: HarperCollins. Dyson, A. H. (1997). Writing superheroes: Contemporary childhood, popular culture, and classroom literacy. New York, NY: Teachers College Press. Eccles, J. S., Wigfield, A., & Schiefele, U. (1998). Motivation to succeed. In W. Damon & N. Eisenberg (Ed.), Handbook of child psychology: Social, emotional, and personality development (pp. 1017–1095). London: John Wiley & Sons. Edtech Europe. (2019). Global Report predicts EdTech Spend to reach $252bn by 2020. Finance Digest. Retrieved from https://www. financedigest.com/global-report-predicts-edtech-spend-to-reach-252bnby-2020.html. Accessed on August 1, 2019. Eliot, G. (2018). Middlemarch (chapter XV). New York, NY: Start Publishing, LLC. Emerson, C. (1983). The outer word and inner speech: Bakhtin, Vygotsky, and the internalization of language. Critical Inquiry, 10(2), 245–264. Engel, S. (2015). The hungry mind: The origins of curiosity in childhood. Cambridge, MA: Harvard University Press. Epley, N., Waytz, A., & Cacioppo, J. T. (2007). On seeing human: A three-factor theory of anthropomorphism. Psychological Review, 114(4), 864–886. doi:10.1037/0033-295X.114.4.864 Falconer, C. J., Slater, M., Rovira, A., King, J. A., Gilbert, P., Antley, A., & Brewin, C. R. (2014). Embodying compassion: A virtual reality paradigm for overcoming excessive self-criticism. PLoS One, 9(11), e111933. doi:10.1371/journal.pone.0111933

References

247

Fein, G. G. (1981). Pretend play in childhood – An integrative review. Child Development, 52(4), 1095–1118. doi:10.2307/1129497 Ferreira, V. S. (2009). Youth scenes, body marks and bio-sociabilities. Young. Nordic Journal of Youth Research, 17(3), 285–306. Fleer, M. (2009). A cultural-historical perspective on play: Play as a leading activity across cultural communities. In I. Pramling-Samuelsson & M. Fleer (Eds.), Play and learning in early childhood settings (pp. 1–17). Dordrecht: Springer. Fletcher, G. J., Simpson, J. A., Thomas, G., & Giles, L. (1999). Ideals in intimate relationships. Journal of Personality and Social Psychology, 76(1), 72–89. Retrieved from https://www.ncbi.nlm.nih.gov/pubmed/9972554 Floridi, L. (2014). The fourth revolution: How the infosphere is reshaping human reality. Oxford: Oxford University Press. Frede, E. C., Gilliam, W. S., & Schweinhart, L. J. (2011). Assessing accountability and ensuring continuous program improvement: Why, how, and who. In E. Zigler, W. S. Gilliam, & W. S. Barnett (Eds.), The pre-k debates: Current controversies and issues (pp. 152–159). Baltimore, MD: Paul H. Brookes Publishing Co. Friedman, T. L. (2017). Thank you for being late: An optimist’s guide to thriving in the age of accelerations (Version 2.0, with a new Afterword). New York, NY: Picador USA. Fukuyama, F. (2003). Our posthuman future: Consequences of the biotechnology revolution. New York, NY: Farrar, Straus and Giroux. Fukuyama, F. (2006). The end of history and the last man. New York, NY: Simon and Schuster. Galinsky, E. (1999). Ask the children: What America’s children really think about working parents. New York, NY: William Morrow and Company, Inc. Retrieved from http://www.familiesandwork.org Ganea, P. A., Canfield, C. F., Simons-Ghafari, K., & Chou, T. (2014). Do cavies talk? The effect of anthropomorphic picture books on children’s knowledge about animals. Frontiers in Psychology, 5, 283. Gardner, H. E. (2008). Multiple intelligences: New horizons in theory and practice. New York, NY: Basic Books. Gardner, H. E. (2011). Frames of mind: The theory of multiple intelligences. London: Hachette UK (Original work published in 1983).

248

The Future of the Self

Garner, R. (2005). Post-it (R) note persuasion: A sticky influence. Journal of Consumer Psychology, 15(3), 230–237. doi:10.1207/ s15327663jcp1503_8 Garvey, C., & Kramer, T. L. (1989). The language of social pretend play. Developmental Review, 9(4), 364–382. Gee, E., Takeuchi, L., & Wartella, E. (2017). Children and families in the digital age: Learning together in a media saturated culture. New York, NY: Routledge. Gee, J. P. (2005). Learning by design: Good video games as learning machines. E-learning and Digital Media, 2(1), 5–16. Geerdts, M. S., Van de Walle, G. A., & LoBue, V. (2016). Learning about real animals from anthropomorphic media. Imagination, Cognition and Personality, 36(1), 5–26. Giddens, A. (1989). A constituição da sociedade (Vol. 458). São Paulo, Brazil: Martins Fontes. Gilmore, J. N. (2016). Everywear: The quantified self and wearable fitness technologies. New Media & Society, 18(11), 2524–2539. doi:10.1177/1461444815588768 Gilovich, T., Kumar, A., & Jampol, L. (2015). A wonderful life: Experiential consumption and the pursuit of happiness. Journal of Consumer Psychology, 25(1), 152–165. Ginns, P., Martin, A. J., & Marsh, H. W. (2013). Designing instructional text in a conversational style: A meta-analysis. Educational Psychology Review, 25(4), 445–472. doi:10.1007/s10648-013-9228-0 Gjersoe, N. L., Hall, E. L., & Hood, B. (2015). Children attribute mental lives to toys when they are emotionally attached to them. Cognitive Development, 34, 28–38. doi:10.1016/j.cogdev.2014.12.002 Gladwell, M. (2006). The tipping point: How little things can make a big difference. Boston, MA: Little, Brown and Company. Golec de Zavala, A., Peker, M., Guerra, R., & Baran, T. (2016). Collective narcissism predicts hypersensitivity to in-group insult and direct and indirect retaliatory intergroup hostility. European Journal of Personality, 30(6), 532–551.

References

249

Golinkoff, R. M., & Hirsh-Pasek, K. (2016). Becoming brilliant: What science tells us about raising successful children. Washington, DC: American Psychological Association. Gommans, M., Krishman, K. S., & Scheffold, K. B. (2001). From brand loyalty to e-loyalty: A conceptual framework. Journal of Economic & Social Research, 3(1), 43–58. González, N., Moll, L. C., & Amanti, C. (2006). Funds of knowledge: Theorizing practices in households, communities, and classrooms. New York, NY: Routledge. Goodenow, C., & Grady, K. E. (1993). The relationship of school belonging and friends’ values to academic motivation among urban adolescent students. The Journal of Experimental Education, 62(1), 60–71. Gramsci, A., & Hoare, Q. (1971). Selections from the prison notebooks (Vol. 294). London: Lawrence and Wishart. Greene, B. (2007). The fabric of the cosmos: Space, time, and the texture of reality. New York, NY: Vintage. Greenfield, P., & Beaglesroos, J. (1988). Radio vs television – Their cognitive impact on children of different socioeconomic and ethnic-groups. Journal of Communication, 38(2), 71–92. doi:10.1111/j.1460-2466.1988.tb02048.x Greenfield, P. M. (2014). Mind and media: The effects of television, video games, and computers. Hove: Psychology Press. Greenfield, S. (2002). The private life of the brain. London: Penguin UK. Greeno, J. G. (2009). A theory bite on contextualizing, framing, and positioning: A companion to Son and Goldstone. Cognition and Instruction, 27(3), 269–275. doi:10.1080/07370000903014386 Guernsey, L., & Levine, M. (2015). Tap click read. New York, NY: Wiley Jossey-Bass. Haidt, J. (2012). The righteous mind: Why good people are divided by politics and religion. New York, NY: Vintage. Hale, L., & Guan, S. (2015). Screen time and sleep among school-aged children and adolescents: A systematic literature review. Sleep Medicine Reviews, 21, 50–58.

250

The Future of the Self

Harari, Y. N. (2018). 21 lessons for the 21st century. New York, NY: Random House. Harris, A. (2015). Weatherland: Writers & artists under English skies. London: Thames & Hudson. Hartley, D. (2007). Personalisation: The emerging ‘revised’ code of education? Oxford Review of Education, 33(5), 629–642. Hartley, D. (2008). Education, markets and the pedagogy of personalisation. British Journal of Educational Studies, 56(4), 365–381. doi:10.1111/j.1467-8527.2008.00411.x Harvey, A. (2012). Opinion leaders’ views on issues in personalized medicine. Personalized Medicine, 9(2), 127–131. Haste, H. (2013). Deconstructing the elephant and the flag in the lavatory: Promises and problems of moral foundations research. Journal of Moral Education, 42(3), 316–329. doi:10.1080/03057240.2013.818529 Hattie, J. (2012). Visible learning for teachers: Maximizing impact on learning. New York, NY: Routledge. Haven, K. (2007). Story proof: The science behind the startling power of story. Westport, CT: Greenwood Publishing Group. Hay, I., & Beaverstock, J. V. (2016). Handbook on wealth and the superrich. Cheltenham: Edward Elgar Publishing. Herrera, F., Bailenson, J., Weisz, E., Ogle, E., & Zaki, J. (2018). Building long-term empathy: A large-scale comparison of traditional and virtual reality perspective-taking. PLoS One, 13(10), e0204494. Heydon, R. M. (2012). Multimodal communication and identities options in an intergenerational art class. Journal of Early Childhood Research, 10(1), 51–69. Hibbard, K. A., Crutzen, P. J., Lambin, E. F., Liverman, D., Mantua, N. J., McNeill, J., … Steffen, W. (2006). Decadal interactions of humans and the environment. In R. Costanza, L. Graumlich, & W. Steffen (Eds.), Integrated history and future of people on Earth (pp. 341–375). Dahlem Workshop Report 96. Cambridge, MA: MIT Press. Hobbs, R. (2018). Expanding the concept of literacy. R. W. Kubey (Ed.), In Media literacy around the world (pp. 163–183). London: Routledge.

References

251

Hodgson, D. (2012). Rationality+consciousness= free will. Oxford: Oxford University Press. Hogan, P. C. (2003). The mind and its stories: Narrative universals and human emotion. Cambridge: Cambridge University Press. Hogarth, R. M. (1987). Judgement and choice: The psychology of decision. London: John Wiley & Sons. Hollands, F., Pan, Y., & Escueta, M. (2019). What is the potential for applying cost-utility analysis to facilitate evidence-based decision making in schools? Educational Researcher, 48(5), 287–295. doi:10.3102/0013189x19852101 Hood, B. M., & Bloom, P. (2008). Children prefer certain individuals over perfect duplicates. Cognition, 106(1), 455–462. Hood, B. M., Gjersoe, N. L., & Bloom, P. (2012). Do children think that duplicating the body also duplicates the mind? Cognition, 125(3), 466–474. Human Progress Institute. (2015, November 10). Putting income inequality in perspective. Retrieved from https://humanprogress.org/article.php?p=100 Hunt, C. (1998). The self on the page: Theory and practice of creative writing in personal development: London: Jessica Kingsley Publishers. Hutton, J., DeWitt, T., Horowitz-Kraus, T., & Ittenbach, R. (2018). Goldilocks effect? Illustrated story format seems “just right” and animation “too hot” for integration of functional brain networks in preschool-age children. Paper presented at the Pediatric Academic Societies (PAS) Meeting, Toronto, Canada. James, W. (2018). Democracy distracted. RSA Journal, 163(4), 26–31. Janes, H., & Kermani, H. (2001). Caregivers’ story reading to young children in family literacy programs: Pleasure or punishment? Journal of Adolescent & Adult Literacy, 44(5), 458–466. Retrieved from ://WOS:000166573500008 Janis, I. L. (1972). Victims of groupthink: A psychological study of foreignpolicy decisions and fiascoes. New York, NY: Houghton Mifflin Company. Janssen, C. P., Donker, S. F., Brumby, D. P., & Kun, A. L. (2019). History and future of human-automation interaction. International Journal of Human–Computer Studies, 131, 99–107. Retrieved from https://www. sciencedirect.com/science/article/pii/S1071581919300552

252

The Future of the Self

Jensen, H. S. (2017). From superman to social realism: Children’s media and Scandinavian childhood (Vol. 6). Amsterdam, The Netherlands: John Benjamins Publishing Company. Jewitt, C., & Kress, G. (2003). Multimodal literacy. London: Peter Lang. John-Steiner, V. (1999). Sociocultural and feminist theory: Mutuality and relevance. In S. Chaiklin, M. Hedegaard, & U. J. Jensen (Eds.), Activity theory and social practice (pp. 201–244). Aarhus, Denmark: Aarhus University Press. Jones, J. T., Pelham, B. W., Mirenberg, M. C., & Hetts, J. J. (2002). Name letter preferences are not merely mere exposure: Implicit egotism as selfregulation. Journal of Experimental Social Psychology, 38(2), 170–177. Kahneman, D., & Frederick, S. (2002). Representativeness revisited: Attribute substitution in intuitive judgment. In T. Gilovich, D. Griffin, & D. Kahneman (Eds.), Heuristics and biases: The psychology of intuitive judgment (pp. 49–81). Cambridge: Cambridge University Press. Kamenetz, A. (2018). The art of screen time. New York, NY: Hachette. Kanoh, H. (2012). Influence of human beings on virtual pets. Paper presented at the e-society: IADIS International Conference, Berlin, Germany. Keating, G. (2012). Netflixed: The epic battle for America’s eyeballs. London: Penguin. Kegan, R. (1982). The evolving self: Problem and process in human development. Cambridge, MA: Harvard University Press. Kelley, W. M., Macrae, C. N., Wyland, C. L., Caglar, S., Inati, S., & Heatherton, T. F. (2002). Finding the self? An event-related fMRI study. Journal of Cognitive Neuroscience, 14(5), 785–794. Kelly, D., & Tangney, B. (2006). Adapting to intelligence profile in an adaptive educational system. Interacting with Computers, 18(3), 385–409. Kennefick, V. (2015). The preacher’s daughter (White Whale Collection). Cork, Ireland: Southword Editions. Kerner, C., & Goodyear, V. A. (2017). The motivational impact of wearable healthy lifestyle technologies: A self-determination perspective on Fitbits with adolescents. American Journal of Health Education, 48(5), 287–297.

References

253

Khan, A. (2009, June 9). Graduation ceremony of the University of Alberta. Retrieved from http://www.akdn.org/speech/ his-highness-aga-khan/graduation-ceremony-university-alberta Kim, T. E. (2019). The messy reality of personalized learning, The New Yorker. Retrieved from https://www.newyorker.com/news/dispatch/ the-messy-reality-of-personalized-learning Kirschner, P. A., Sweller, J., & Clark, R. E. (2006). Why minimal guidance during instruction does not work: An analysis of the failure of constructivist, discovery, problem-based, experiential, and inquiry-based teaching. Educational Psychologist, 41(2), 75–86. Kleeman, J. (2020). Sex robots and vegan meat: Adventures at the frontier of birth, food, sex and death. London: Picador. Komatsu, K. (2016). On the dialectic nature of human mind: The dynamic tension between sameness and non-sameness. Integrative Psychological and Behavioral Science, 50(1), 174–183. doi:10.1007/s12124-015-9325-3 Koopman, E. M. (2015). Empathic reactions after reading: The role of genre, personal factors and affective responses. Poetics, 50, 62–79. doi:10.1016/j.poetic.2015.02.008 Korat, O., Graister, T., & Altman, C. (2019). Contribution of reading an e-book with a dictionary to word learning: Comparison between kindergarteners with and without SLI. Journal of Communication Disorders, 79, 90–102. https://doi.org/10.1016/j.jcomdis.2019.03.004 Korat, O., Shamir, A., & Heibal, S. (2013). Expanding the boundaries of shared book reading: E-books and printed books in parent–child reading as support for children’s language. First Language, 33(5), 504–523. Koretz, D. (2017). The testing charade: Pretending to make schools better. Chicago, IL: University of Chicago Press. Kotaman, H., & Balcı, A. (2017). Impact of storybook type on kindergarteners’ storybook comprehension. Early Child Development and Care, 187(11), 1771–1781. Kraemer, K. L., Dedrick, J., & Sharma, P. (2009). One laptop per child: Vision vs. reality. Communications of the ACM, 52(6), 66–73. doi:10.1145/1516046.1516063

254

The Future of the Self

Kremer, P., Elshaug, C., Leslie, E., Toumbourou, J. W., Patton, G. C., & Williams, J. (2014). Physical activity, leisure-time screen use and depression among children and young adolescents. Journal of Science and Medicine in Sport, 17(2), 183–187. Kress, G. R. (2009). Multimodality: A social semiotic approach to contemporary communication. New York, NY: Routledge. Kress, G. R., & Van Leeuwen, T. (1996). Reading images: The grammar of visual design. New York, NY: Psychology Press. Krienen, F. M., Tu, P. C., & Buckner, R. L. (2010). Clan mentality: Evidence that the medial prefrontal cortex responds to close others. Journal of Neuroscience, 30(41), 13906–13915. doi:10.1523/Jneurosci.2180-10.2010 Kross, E., & Ayduk, O. (2017). Self-distancing: Theory, research, and current directions. In P. Devine & A. Plant (Eds.), Advances in experimental social psychology (Vol. 55, pp. 81–136). New York, NY: Elsevier. Kross, E., & Grossmann, I. (2012). Boosting wisdom: Distance from the self enhances wise reasoning, attitudes, and behavior. Journal of Experimental Psychology, 141(1), 43–48. doi:10.1037/a0024158 Krotoski, A. (2018). Regret, BBC Radio 4 show, The digital human. Retrieved from www.bbc.co.uk Kuby, C. R., Rucker, T. G., & Kirchhofer, J. M. (2015). ‘Go be a writer’: Intra-activity with materials, time and space in literacy learning. Journal of Early Childhood Literacy, 15(3), 394–419. Kucirkova, N. (2016). Personalisation: A theoretical possibility to reinvigorate children’s interest in storybook reading and facilitate greater book diversity. Contemporary Issues in Early Childhood, 17(3), 304–316. Kucirkova, N. (2017). Digital personalization in early childhood: Impact on childhood. London: Bloomsbury Publishing. Kucirkova, N. (2018). Is Silicon Valley standardizing ‘personalized’ learning?. Education Week. Retrieved from https://www.edweek.org/ew/ articles/2018/05/30/is-silicon-valley-standardizing-personalized-learning.html Kucirkova, N. (2019a). The learning value of personalization in children’s reading recommendation systems: What can we learn from

References

255

constructionism?. International Journal of Mobile and Blended Learning (IJMBL), 11(4), 1–16. Kucirkova, N. (2019b). How could children’s storybooks promote empathy? A conceptual framework based on developmental psychology and literary theory. Frontiers in Psychology, 10, 121. Kucirkova, N. (2019c). Forget swiping. Your next date will be based on your genes. Wired. Retrieved from https://www.wired.co.uk/article/ dating-apps-gene-testing Kucirkova, N. (2019d). Book review of Wolf, M.: Reader, come home. Journal of Children and Media, 13(1), 231–234. doi:10.1080/17482798.2 019.1574280. Published online: February 1, 2019. Kucirkova, N., & Flewitt, R. (2020). The future-gazing potential of digital personalization in young children’s reading: Views from education professionals and app designers. Early Child Development and Care, 190(2), 135–149. Kucirkova, N., & Leaton Gray, S. (forthcoming). If personalised education and artificial intelligence are a democratic problem, could pluralisation be the democratic solution? British Journal of Educational Studies. Kucirkova, N., & Littleton, K. (2017). Developing personalised education for personal mobile technologies with the pluralisation agenda. Oxford Review of Education, 43(3), 276–288. doi:10.1080/03054985.2017.1305046 Kucirkova, N., & Livingstone, S. (2017). Why the very idea of ‘screen time’ is muddled and misguided. The Conversation. Retrieved from https://theconversation.com/ why-the-very-idea-of-screen-time-is-muddled-and-misguided-82347 Kucirkova, N., & Mackey, M. (2020). Digital literacies and children’s personalized books: Locating the ‘self’. London Review of Education, 18(2), 151–162. Kucirkova, N., Messer, D., & Sheehy, K. (2014). The effects of personalisation on young children’s spontaneous speech during shared book reading. Journal of Pragmatics, 71, 45–55. Kucirkova, N., Messer, D., Sheehy, K., & Fernandez-Panadero, C. (2014). Children’s engagement with educational iPad apps: Insights from a

256

The Future of the Self

Spanish classroom. Computers & Education, 71, 175–184. doi:10.1016/ j.compedu.2013.10.003 Kucirkova, N., Messer, D., Sheehy, K., & Flewitt, R. (2013). Sharing personalised stories on iPads: A close look at one parent–child interaction. Literacy, 47(3), 115–122. Kucirkova, N., Messer, D., & Whitelock, D. (2013). Parents reading with their toddlers: The role of personalization in book engagement. Journal of Early Childhood Literacy, 13(4), 445–470. Kucirkova, N., Toda, Y., & Flewitt, R. (2020, August). Young children’s use of personalized technologies: Insights from teachers and digital software designers in Japan. Technology, Knowledge and Learning, 1–20. Kuijpers, M. M., Hakemulder, F., Tan, E. S., & Doicaru, M. M. (2014). Exploring absorbing reading experiences. Scientific Study of Literature, 4(1), 89–122. Kuperman, A., & Mioduser, D. (2012). [Chais] Kindergarten children’s perceptions of “anthropomorphic artifacts” with adaptive behavior. Interdisciplinary Journal of E-Learning and Learning Objects, 8(1), 137–147. Langford, P. E. (2004). Vygotsky’s developmental and educational psychology. Hove: Psychology Press. Lanningham-Foster, L., Jensen, T. B., Foster, R. C., Redmond, A. B., Walker, B. A., Heinz, D., & Levine, J. A. (2006). Energy expenditure of sedentary screen time compared with active screen time for children. Pediatrics, 118(6), e1831–e1835. Lapid, Y. (1989). The third debate: On the prospects of international theory in a post-positivist era. International Studies Quarterly, 33(3), 235–254. László, J., & Larsen, S. F. (1991). Cultural and text variables in processing personal experiences while reading literature. Empirical Studies of the Arts, 9(1), 23–34. Latour, B. (2005). Reassembling the social: An introduction to actornetwork-theory. Oxford: Oxford University Press. Laurillard, D. (2002). Rethinking university teaching: A conversational framework for the effective use of learning technologies. London: Routledge.

References

257

Leaton Gray, S. H. (2017). The social construction of time in contemporary education: Implications for technology, equality and Bernstein’s ‘conditions for democracy’. British Journal of Sociology of Education, 38(1), 60–71. Leaton Gray, S. H., & Kucirkova, N. (2018, September). A united and thriving Europe? A sociology of the European schools and If personalised education and artificial intelligence are a democratic problem, could pluralisation be the democratic solution? British Educational Research Association Conference. Leaton Gray, S. H., & Phippen, A. (2017). Invisibly blighted: The digital erosion of childhood. London: Bloomsbury. Lecci, L., Okun, M. A., & Karoly, P. (1994). Life regrets and current goals as predictors of psychological adjustment. Journal of Personality and Social Psychology, 66(4), 731–741. Leiner, B. M., Cerf, V. G., Clark, D. D., Kahn, R. E., Kleinrock, L., Lynch, D. C., & Wolff, S. (2009). A brief history of the internet. ACM SIGCOMM Computer Communication Review, 39(5), 22–31. doi:10.1145/1629607.1629613 Levie, W. H., & Lentz, R. (1982). Effects of text illustrations: A review of research. Educational Communication and Technology, 30(4), 195–232. Levinson, A. M., & Barron, B. (2018). Latino immigrant families learning with digital media across settings and generations. Digital Education Review, 33, 150–169. Retrieved from :// WOS:000437493300011 Leyens, J. P., Paladino, P. M., Rodriguez-Torres, R., Vaes, J., Demoulin, S., … Gaunt, R. (2000). The emotional side of prejudice: The attribution of secondary emotions to ingroups and outgroups. Personality and Social Psychology Review, 4(2), 186–197. Linn, M. C., Clark, D., & Slotta, J. D. (2003). WISE design for knowledge integration. Science Education, 87(4), 517–538. Litowitz, B. E. (1993). Deconstruction in the zone of proximal development. In E. Forman, N. Minick, & C. A. Stone (Eds.), Contexts for learning: Sociocultural dynamics in children’s development (pp. 184–196). New York, NY: Oxford University Press. Littler, J. (2017). Against meritocracy: Culture, power and myths of mobility. London: Routledge.

258

The Future of the Self

Littleton, K., & Mercer, N. (2013). Interthinking: Putting talk to work. New York, NY: Routledge. Livingstone, S. (2018). iGen: Why today’s super-connected kids are growing up less rebellious, more tolerant, less happy – and completely unprepared for adulthood. New York, NY: Taylor & Francis. Locke, J. (1690/1975). Essay concerning human understanding. In P. Niddich (Ed.), Clarendon edition of the works of John Locke. Oxford: Oxford University Press. Retrieved from https://oll.libertyfund.org/titles/ locke-the-works-vol-1-an-essay-concerning-human-understanding-part-1 Lodge, J. M., Kennedy, G., Lockyer, L., Arguel, A., & Pachman, M. (2018, June). Understanding difficulties and resulting confusion in learning: An integrative review. Frontiers in Education (Vol. 3, p. 49). Lausanne, Switzerland: Frontiers. Louwerse, M. M., & Jeuniaux, P. (2010). The linguistic and embodied nature of conceptual processing. Cognition, 114, 96–104. Luckin, R. (2018). Machine learning and human intelligence. London: UCL IOE Press. Lupton, D. (2016). The quantified self. London: John Wiley & Sons. Lupton, D., & Williamson, B. (2017). The datafied child: The dataveillance of children and implications for their rights. New Media & Society, 19(5), 780–794. Mabbott, C. (2017). The We Need Diverse Books campaign and critical race theory: Charlemae Rollins and the call for diverse children’s books. Library Trends, 65(4), 508–522. Macrae, C. N., Visokomogilski, A., Golubickis, M., & Sahraie, A. (2018). Self-relevance enhances the benefits of attention on perception. Visual Cognition, 26(7), 475–481. doi:10.1080/13506285.2018.1498421 Maddox, J. (2017). “Guns don’t kill people … selfies do”: Rethinking narcissism as exhibitionism in selfie-related deaths. Critical Studies in Media Communication, 34(3), 193–205. Maher, F. A., & Tetreault, M. K. (1993). Frames of positionality: Constructing meaningful dialogues about gender and race. Anthropological Quarterly, 66(3), 118–126.

References

259

Malhotra, N. K., Ulgado, F. M., Agarwal, J., Shainesh, G., & Wu, L. (2005). Dimensions of service quality in developed and developing economies: Multi-country cross-cultural comparisons. International Marketing Review, 22(3), 256–278. Mallett, S., Rosenthal, D., & Keys, D. (2005). Young people, drug use and family conflict: Pathways into homelessness. Journal of Adolescence, 28(2), 185–199. doi:10.1016/j.adolescence.2005.02.002 Marchenkova, L. (2005). Language, culture, and self: The Bakhtin– Vygotsky encounter. In J. K. Hall, G. Vitanova, & L. A. Marchenkova (Eds.). Dialogue with Bakhtin on second and foreign language learning: New perspectives (pp. 171–188). London: Lawrence Erlbaum Associates. Mardell, B., & Kucirkova, N. (2016). Promoting democratic classroom communities through storytelling and story acting. In T. Cremin, R. Flewitt, B. Mardell, & J. Swann (Eds.), Storytelling in early childhood: Enriching language, literacy and classroom culture (p. 169). London: Routledge. Markus, H. R., & Kitayama, S. (1991). Culture and the self-implications for cognition, emotion, and motivation. Psychological Review, 98(2), 224–253. doi10.1037/0033-295x.98.2.224 Martin, E. (1968). Stimulus meaningfulness and paired-associate transfer: An encoding variability hypothesis. Psychological Review, 75(5), 421– 441. Retrieved from https://www.ncbi.nlm.nih.gov/pubmed/4879426 Maslow, A. H. (1987). Motivation and personality (3rd ed.). New York, NY: Harper Row. Masterson, J. F. (1990). Psychotherapy of borderline and narcissistic disorders: Establishing a therapeutic alliance (a developmental, self, and object relations approach). Journal of Personality Disorders, 4(2), 182–191. Matusov, E. (2011). Irreconcilable differences in Vygotsky’s and Bakhtin’s approaches to the social and the individual: An educational perspective. Culture & Psychology, 17(1), 99–119. Mayer, R. E. (2005). Cognitive theory of multimedia learning. In R. E. Mayer (Ed.), The Cambridge handbook of multimedia learning (pp. 31–48). New York, NY: Cambridge University Press. Mazza, N. (2016). Poetry therapy: Theory and practice. New York, NY: Routledge.

260

The Future of the Self

McCarthy, M. (2015). The moth snowstorm: Nature and joy. New York, NY: John Murray. McCloud, S. (2006). Making comics: Storytelling secrets of comics, manga and graphic novels. New York, NY: William Morrow Paperbacks. McGurk, L. Å. (2018). There’s no such thing as bad weather: A Scandinavian mom’s secrets for raising healthy, resilient, and confident kids (from Friluftsliv to Hygge). New York, NY: Touchstone. McKenna, K. Y., Green, A. S., & Gleason, M. E. (2002). Relationship formation on the Internet: What’s the big attraction? Journal of Social Issues, 58(1), 9–31. McLuhan, M. (1960). Effects of the improvements of communication media. Journal of Economic History, 20, 566–575. McLuhan, M. (1962). The Gutenberg galaxy. Toronto, Canada: University of Toronto Press. McLuhan, M. (1994). Understanding media: The extensions of man. Cambridge, MA: MIT Press. Mcmillan, D. W., & Chavis, D. M. (1986). Sense of community – A definition and theory. Journal of Community Psychology, 14(1), 6–23. doi:10.1002/1520-6629(198601)14:13.0.Co;2-I McNamara, D. S., Kintsch, E., Songer, N. B., & Kintsch, W. (1996). Are good texts always better? Interactions of text coherence, background knowledge, and levels of understanding in learning from text. Cognition and Instruction, 14(1), 1–43. Mehrabian, A. (1996). Pleasure arousal dominance: A general framework for describing and measuring individual differences in temperament. Current Psychology, 14(4), 261–292. doi:10.1007/Bf02686918 Mehta, J. (2019). In search of deeper learning: Inside the effort to remake the American high school. Cambridge, MA: Harvard University Press. Mercer, N. (1994). Neo-Vygotskian theory and classroom education. In J. Maybin & B. Stierer (Eds.), Language, literacy and learning in educational practice (pp. 92–110). Philadelphia, PA: Multilingual Matters Ltd.

References

261

Mesthene, E. G. (1997). The role of technology in society. In K. Sharon Shrader-Frechette & L. Westra (Eds.), Technology and values (pp. 71–85). New York, NY: Rowman Publishers. Meyer, J., & Land, R. (2003). Threshold concepts and troublesome knowledge: Linkages to ways of thinking and practising within the disciplines. In C. Rust (Ed.), Improving student learning: Ten years on. Oxford: OCSLD. Michotte, A. (1945/2017). The perception of causality. London: Routledge. Milardo, R. M., & Wellman, B. (1992). The personal is social. Journal of Social and Personal Relationships, 9(3), 339–342. Miliband, D. (2004). Personalised learning: Building a new relationship with schools. Paper presented at the Speech by the Minister of State for School Standards to the North of England Education Conference. Miller, C. (2018). The death of the gods. London: Penguin Random House. Mischel, W. (2004). Toward an integrative science of the person. Annual Review of Psychology, 55, 1–22. Mishra, P. (2017). Age of anger: A history of the present. London: Macmillan. Moreno, R., & Mayer, R. (2007). Interactive multimodal learning environments. Educational Psychology Review, 19(3), 309–326. Morozov, E. (2012). The net delusion: The dark side of Internet freedom. New York, NY: PublicAffairs. Morris, M. E. (2018). Left to our own devices: Hacking technology to reclaim our relationships, health, and focus. Cambridge, MA: MIT Press. Moss, P. (2015). There are alternatives! Contestation and hope in early childhood education. Global Studies of Childhood, 5(3), 226–238. Munslow, A. (2018). Narrative and history. London: Macmillan International Higher Education. Nagy, E. (2001). Winners and losers in the transformation of city centre retailing in East Central Europe. European Urban and Regional Studies, 8(4), 340–348. doi:10.1177/096977640100800406 Nehring, K., & Puppe, C. (2002). A theory of diversity. Econometrica, 70(3), 1155–1198. doi:10.1111/1468-0262.00321

262

The Future of the Self

Neisser, U., & Fivush, R. (Eds.). (1994). The remembering self: Construction and accuracy in the self-narrative (Vol. 6). Cambridge, MA: Cambridge University Press. Nelson, K. (1989). Narratives from the crib. Cambridge, MA: Harvard University Press. Nelson, K., & Fivush, R. (2004). The emergence of autobiographical memory: A social cultural developmental theory. Psychological Review, 111(2), 486. Ng, I. (2018). Personal data as currency. Medium Blog. Retrieved from https://medium.com/hub-of-all-things/personal-data-as-currencyab1590163ad6 Nicholson, L. (2013). Feminism/postmodernism. New York, NY: Routledge. Nikolajeva, M. (2015). Children’s literature comes of age: Toward a new aesthetic. New York, NY: Routledge. Noble, S. U. (2018). Algorithms of oppression: How search engines reinforce racism. New York, NY: NYU Press. NPfE (2017). Re-energising Europe. A package deal for the EU27, New pact for Europe. Report. Retrieved from https://www.newpactforeurope. eu/documents/ Nuttin, J. M. (1985). Narcissism beyond gestalt and awareness – The name letter effect. European Journal of Social Psychology, 15(3), 353–361. doi:10.1002/ejsp.2420150309 Oatley, K. (1999). Meetings of minds: Dialogue, sympathy, and identification, in reading fiction. Poetics, 26(5–6), 439–454. doi:10.1016/ S0304-422x(99)00011-X OECD. (2015). OECD report, students, computers and learning: Making the connections. Paris, France: OECD. Ofcom. (2018). UK home broadband performance. Retrieved from https://www.ofcom.org.uk/research-and-data/telecoms-research/ broadband-research/home-broadband-performance-2018 Ofcom. (2019). Communications market report 2019 – Summary of key findings. Retrieved from https://www.ofcom.org.uk/research-and-data/ multi-sector-research/cmr/cmr-2019

References

263

O’Hara, K., & Shadbolt, N. (2014). The spy in the coffee machine: The end of privacy as we know it. New York, NY: Simon and Schuster. O’Keeffe, G. S., Clarke-Pearson, K., & Council on Communications and Media. (2011). The impact of social media on children, adolescents, and families. Pediatrics, 127(4), 800–804. doi:10.1542/ peds.2011-0054 Oliver, M. (1986). Wild geese. New York, NY: Dream Work. Ortner, S. B. (2006). Anthropology and social theory: Culture, power, and the acting subject. Durham, NC: Duke University Press. Orvell, A., Kross, E., & Gelman, S. A. (2019). Lessons learned: Young children’s use of generic-you to make meaning from negative experiences. Journal of Experimental Psychology: General, 148(1), 184. O’Sullivan, O., & McGonigle, S. (2010). Transforming readers: Teachers and children in the Centre for Literacy in Primary Education Power of Reading project. Literacy, 44(2), 51–59. Oswell, D. (2013). The agency of children: From family to global human rights. Cambridge, MA: Cambridge University Press. Ott, B. L. (2017). The age of Twitter: Donald J. Trump and the politics of debasement. Critical Studies in Media Communication, 34(1), 59–68. doi:10.1080/15295036.2016.1266686 Outhwaite, L. A., Faulder, M., Gulliford, A., & Pitchford, N. J. (2019). Raising early achievement in math with interactive apps: A randomized control trial. Journal of Educational Psychology, 111(2), 284. Owens, J., & Cribb, A. (2019). ‘My fitbit thinks i can do better!’ Do health promoting wearable technologies support personal autonomy? Philosophy & Technology, 32(1), 23–38. Pagels, H. R. (1982). The cosmic code: Quantum physics as the language of nature. New York, NY: Simon & Schuster. Pahl, K., & Rowsell, J. (2020). Living literacies: Literacy for social change. Boston, MA: MiT Press. Paley, V. G. (1991). The boy who would be a helicopter. Cambridge, MA: Harvard University Press.

264

The Future of the Self

Pane, J. F. (2017). Informing progress: Insights on personalized learning implementation and effects. New York, NY: RAND. Papacharissi, Z. (2010). A networked self: Identity, community, and culture on social network sites. New York, NY: Routledge. Papert, S. (1995). The parent trap. Time Magazine. Retrieved from http://content.time.com/time/magazine/article/0,9171,1626727,00.html. Accessed on March 15, 2019. Parkinson, R. (2010). Storytelling and imagination: Beyond basic literacy (pp. 8–14). New York, NY: Routledge. Parsons, D. (2014). The future of mobile learning and implications for education and training. In M. Ally & A. Tsinakos (Eds.), Increasing access through mobile learning (chap. 16, pp. 217–229). Vancouver, Canada: Commonwealth of Learning and Athabasca University. Retrieved from http://oasis.col.org/bitstream/handle/11599/558/pub_Mobile%20 Learning_web.pdf#page=234. Partanen, A. (2017). The Nordic theory of everything: In search of a better life. London: Gerald Duckworth & Co. Pearce, J., & Moscardo, G. (2015, June 17–21). Social representations of tourist selfies: New challenges for sustainable tourism. Conference proceedings of BEST EN think tank XV, Skukuza, Mpumalanga, South Africa (pp. 59–73). Perrotta, C., & Williamson, B. (2018). The social life of learning analytics: Cluster analysis and the “performance” of algorithmic education. Learning Media and Technology, 43(1), 3–16. doi:10.1080/17439884. 2016.1182927 Peskin, J., & Astington, J. W. (2004). The effects of adding metacognitive language to story texts. Cognitive Development, 19(2), 253–273. doi:10.1016/j.cogdev.2004.01.003 Peterson, J. B. (2018). 12 rules for life: An antidote to chaos. Toronto, Canada: Random House. Picton, I., & Clark, C. (2015). The impact of ebooks on the reading motivation and reading skills of children and young people: A study of schools using RM books. Final Report, National Literacy Trust. Piketty, T. (2013). Capital in the twenty-first century. Boston, MA: Harvard University Press.

References

265

Pinker, S. (2012). The better angels of our nature: Why violence has declined. New York, NY: Penguin Group USA. Pinker, S. (2018). Enlightenment now: The case for reason, science, humanism, and progress. New York, NY: Penguin. Porter, S. D., Reay, D. S., Bomberg, E., & Higgins, P. (2018). Avoidable food losses and associated production-phase greenhouse gas emissions arising from application of cosmetic standards to fresh fruit and vegetables in Europe and the UK. Journal of Cleaner Production, 201, 869–878. doi:10.1016/j.jclepro.2018.08.079 Porter, T. M. (1996). Trust in numbers: The pursuit of objectivity in science and public life. Princeton, NJ: Princeton University Press. Preston, S. D., & Hofelich, A. J. (2012). The many faces of empathy: Parsing empathic phenomena through a proximate, dynamic-systems view of representing the other in the self. Emotion Review, 4(1), 24–33. doi:10.1177/1754073911421378 Prout, A. (2000). Childhood bodies: Construction, agency and hybridity. In A. Prout (Ed.), The body, childhood and society (pp. 1–18). New York, NY: Springer. Przybylski, A. K., & Weinstein, N. (2017). A large-scale test of the goldilocks hypothesis: Quantifying the relations between digital-screen use and the mental well-being of adolescents. Psychological Science, 28(2), 204–215. doi:10.1177/0956797616678438 Przybylski, A. K., Weinstein, N., Murayama, K., Lynch, M. F., & Ryan, R. M. (2012). The ideal self at play: The appeal of video games that let you be all you can be. Psychological Science, 23(1), 69–76. doi:10.1177/0956797611418676 Puwar, N. (2004). Space invaders: Race, gender and bodies out of place. New York, NY: Berg. Querstret, D., & Robinson, O. C. (2013). Person, persona, and personality modification: An in-depth qualitative exploration of quantitative findings. Qualitative Research in Psychology, 10(2), 140–159. doi:10.1080/14780 887.2011.586450 Reeves, R. V., & Howard, K. (2013). The glass floor: Education, downward mobility, and opportunity hoarding. New York, NY: Center on Children and Families at Brookings.

266

The Future of the Self

Rice, J. J., & Prince, M. J. (2013). Changing politics of Canadian social policy. Toronto: University of Toronto Press. Richards, G. (2015). The new global nomads: Youth travel in a globalizing world. Tourism Recreation Research, 40(3), 340–352. doi:10.1080/02508281.2015.1075724 Richter, A., & Courage, M. L. (2017). Comparing electronic and paper storybooks for preschoolers: Attention, engagement, and recall. Journal of Applied Developmental Psychology, 48, 92–102. Ridgway, J. L., & Clayton, R. B. (2016). Instagram unfiltered: Exploring associations of body image satisfaction, Instagram #selfie posting, and negative romantic relationship outcomes. Cyberpsychology, Behavior, and Social Networking, 19(1), 2–7. doi:10.1089/ cyber.2015.0433 Riley-Ayers, S., Frede, E., Barnett, W. S., & Brenneman, K. (2011). Improving early education programs through data-based decision making. New Brunswick, NJ: NIEER. Rilke, M. (1922). X (ZEITER TEIL) Alles Erworbene bedroht die Maschine, solange sie auch erdreistet, im Geist, statt im Gehorchen, zu sein. X [SECOND PART] Selected poems from the Sonnets to Orpheus (1922) by Rainer Maria Rilke (C. Crego, Trans.). Retrieved from http://cs-music.com/features/sonnets-to-orpheus.html Roberts-Holmes, G., & Bradbury, A. (2016). The datafication of early years education and its impact upon pedagogy. Improving Schools, 19(2), 119–128. doi:10.1177/1365480216651519 Rodrigues-Leon, L. (2020). Literacy experiences: An exploration of young children’s orientations, identities, and affective relations with text. Ph.D. thesis, The Open University. Romeo, R. R., Leonard, J. A., Robinson, S. T., West, M. R., Mackey, A. P., Rowe, M. L., & Gabrieli, J. D. E. (2018). Beyond the 30-millionword gap: Children’s conversational exposure is associated with language-related brain function. Psychological Science, 29(5), 700–710. doi:10.1177/0956797617742725 Rose, T. (2016). The end of average: How to succeed in a world that values sameness. London: Penguin UK.

References

267

Rosenblatt, L. M. (1994). The transactional theory of reading and writing. London: Routledge. Rushkoff, D. (2019). Team human. New York, NY: W. W. Norton & Company. Russell, H. (2018). The atlas of happiness. New York, NY: Two Roads. Ryan, R. M., & Deci, E. L. (2000). Self-determination theory and the facilitation of intrinsic motivation, social development, and well-being. American Psychologist, 55(1), 68–78. Retrieved from https://www.ncbi. nlm.nih.gov/pubmed/11392867 Saltman, K. J. (2016). Corporate schooling meets corporate media: Standards, testing, and technophilia. Review of Education Pedagogy and Cultural Studies, 38(2), 105–123. doi:10.1080/10714413.2016.1155953 Sameroff, A. (2009). The transactional model. New York, NY: American Psychological Association. Sammons, P., Elliot, K., Sylva, K., Melhuish, E., Siraj-Blatchford, I., & Taggart, B. (2004). The impact of pre-school on young children’s cognitive attainments at entry to reception. British Educational Research Journal, 30(5), 691–712. doi:10.1080/0141192042000234656 Sammons, P., Sylva, K., Melhuish, E., Siraj-Blatchford, I., Taggart, B., Smees, R., & Toth, K. (2012). Influences on students’ dispositions in key stage 3: Exploring enjoyment of school, popularity, anxiety, citizenship values and academic self-concepts in Year 9. Project Report. Institute of Education, London. Sandel, M. J. (2012). What money can’t buy: The moral limits of markets. London: Macmillan. Sari, B., Takacs, Z. K., & Bus, A. G. (2017). What are we downloading for our children? Best-selling children’s apps in four European countries. Journal of Early Childhood Literacy, 19(4), 515–532. doi:10.1177/1468798417744057 Sari, B., Takacs, Z. K., & Bus, A. G. (2019). What are we downloading for our children? Best-selling children’s apps in four European countries. Journal of Early Childhood Literacy, 19(4), 515–532.

268

The Future of the Self

Scardamalia, M., & Bereiter, C. (2016). Creating, crisscrossing, and rising above idea landscapes. In R. Huang, Kinshuk, & J. K. Price (Eds.), ICT in education in global context (pp. 3–16). London: Springer. Schacter, D. L. (2002). The seven sins of memory: How the mind forgets and remembers. Boston, MA: Houghton Mifflin Harcourt. Scheidel, W. (2017). The great leveler: Violence and the history of inequality from the stone age to the twenty-first century (Vol. 67). Princeton, NJ: Princeton University Press. Schmidt, R. A., & Bjork, R. A. (1992). New conceptualizations of practice: Common principles in three paradigms suggest new concepts for training. Psychological Science, 3(4), 207–218. Schoar, A. (2012). The personal side of relationship banking. Semantic Scholar. Corpus ID: 54686125. doi:10.2139/SSRN.2024653Corpus Schreier, S. S., Heinrichs, N., Alden, L., Rapee, R. M., Hofmann, S. G., Chen, J., … Bögels, S. (2010). Social anxiety and social norms in individualistic and collectivistic countries. Depression and Anxiety, 27(12), 1128–1134. Schüll, N. D. (2012). Addiction by design: Machine gambling in Las Vegas. Princeton, NJ: Princeton University Press. Schwab, K. (2017). The fourth industrial revolution. New York, NY: Crown Business. Schwartz, B. (2004). The paradox of choice: Why more is less. New York, NY: Ecco. Schwartz, J. (2004). Air pollution and children’s health. Pediatrics, 113(4), 1037–1043. Retrieved from https://www.ncbi.nlm.nih.gov/ pubmed/15060197 Schwartz, S. H. (1992). Universals in the content and structure of values: Theoretical advances and empirical tests in 20 countries. In P. Devine & A. Plant (Eds.), Advances in experimental social psychology (Vol. 25, pp. 1–65). New York, NY: Elsevier. Scruton, R. (2011). Beauty: A very short introduction (Vol. 262). Oxford: Oxford University Press.

References

269

Seilman, U., & Larsen, S. F. (1989). Personal resonance to literature – A study of remindings while reading. Poetics, 18(1–2), 165–177. doi:10.1016/0304-422x(89)90027-2 Selwyn, N. (2016). Education and technology: Key issues and debates. London: Bloomsbury Publishing. Shamir, A., Korat, O., & Fellah, R. (2012). Promoting vocabulary, phonological awareness and concept about print among children at risk for learning disability: Can e-books help? Reading and Writing, 25(1), 45–69. Shapiro, J., Anderson, J., & Anderson, A. (1997). Diversity in parental storybook reading. Early Child Development and Care, 127(1), 47–58. Shavlik, M., Bauer, J. R., & Booth, A. E. (2020). Children’s preference for causal information in storybooks. Frontiers in Psychology, 11, 666. Sheehy, K. (2002). The effective use of symbols in teaching word recognition to children with severe learning difficulties: A comparison of word alone, integrated picture cueing and the handle technique. International Journal of Disability, Development and Education, 49(1), 47–59. Sheehy, K., Ferguson, R., & Clough, G. (2014). Augmented education: bringing real and virtual learning together. New York, NY: Springer. Shotter, J. (1993). Bakhtin and Vygotsky: Internalization as a boundary phenomenon. New Ideas in Psychology, 11, 379. Sikora, S., Kuiken, D., & Miall, D. S. (2010). An uncommon resonance: The influence of loss on expressive reading. Empirical Studies of the Arts, 28(2), 135–153. Singelis, T. M., Triandis, H. C., Bhawuk, D. P., & Gelfand, M. J. (1995). Horizontal and vertical dimensions of individualism and collectivism: A theoretical and measurement refinement. Cross-cultural Research, 29(3), 240–275. Siraj, I., Taggart, B., Sammons, P., Melhuish, E. C., Sylva, K., & Shepherd, D. L. (2019). Teaching in effective primary schools: Research into pedagogy and children’s learning. London: IOE Press. Skeggs, B. (1997). Formations of class and gender: Becoming respectable (Vol. 51). London: Sage.

270

The Future of the Self

Slater, M., Usoh, M., & Steed, A. (1994). Depth of presence in virtual environments. Presence: Teleoperators and Virtual Environments, 3(2), 130–144. Smeets, D. J., & Bus, A. G. (2012). Interactive electronic storybooks for kindergartners to promote vocabulary growth. Journal of Experimental Child Psychology, 112(1), 36–55. Smeets, E., & Roeleveld, J. (2016). The identification by teachers of special educational needs in primary school pupils and factors associated with referral to special education. European Journal of Special Needs Education, 31(4), 423–439. doi:10.1080/08856257.2016.1187879 Snow, C. E. (1991). The theoretical basis for relationships between language and literacy in development. Journal of Research in Childhood Education, 6(1), 5–10. Snow, C. E., & Biancarosa, G. (2003). Adolescent literacy and the achievement gap: What do we know and where do we go from here?. New York, NY: Carnegie Corporation. Son, J. Y., & Goldstone, R. L. (2009). Contextualization in perspective. Paper presented at the Cognition and Instruction. Sparrow, B., Liu, J., & Wegner, D. M. (2011). Google effects on memory: Cognitive consequences of having information at our fingertips. Science, 333(6043), 776–778. doi:10.1126/science.1207745 Spaulding, E., & Perry, C. (2013). Making it personal: Rules for success in product customization. Boston, MA: Bain & Company Publication. Spivack, N. (2013). Web 3.0: The third generation web is coming. Reno, NV: Lifeboat Foundation. Spreng, R. N., Mar, R. A., & Kim, A. S. (2009). The common neural basis of autobiographical memory, prospection, navigation, theory of mind, and the default mode: A quantitative meta-analysis. Journal of Cognitive Neuroscience, 21(3), 489–510. doi:10.1162/jocn.2008.21029 Stallard, P., Skryabina, E., Taylor, G., Phillips, R., Daniels, H., Anderson, R., & Simpson, N. (2014). Classroom-based cognitive behaviour therapy (FRIENDS): A cluster randomised controlled trial to prevent anxiety in children through education in schools (PACES). Lancet Psychiatry, 1(3), 185–192. doi:10.1016/S2215-0366(14)70244-5

References

271

Standage, M., Duda, J. L., & Ntoumanis, N. (2006). Students’ motivational processes and their relationship to teacher ratings in school physical education: A self-determination theory approach. Research Quarterly for Exercise and Sport, 77(1), 100–110. Steffen, W., Grinevald, J., Crutzen, P., & McNeill, J. (2011). The anthropocene: Conceptual and historical perspectives. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 369(1938), 842–867. Stevenson, H. W., & Lee, S. Y. (1990). Contexts of achievement: A study of American, Chinese, and Japanese children. Monographs of the Society for Research in Child Development, 55(1–2), 1–123. Retrieved from https://www.ncbi.nlm.nih.gov/pubmed/2342493 Stoodt, B. (1996). Children’s literature. London: Macmillan Education AU. Street, B. (2003). What’s “new” in new literacy studies? Critical approaches to literacy in theory and practice. Current Issues in Comparative Education, 5(2), 77–91. Sui, J., & Zhu, Y. (2005). Five-year-olds can show the self-reference advantage. International Journal of Behavioral Development, 29(5), 382–387. doi:10.1080/01650250500172673 Sung, Y. T., Wu, M. D., Chen, C. K., & Chang, K. E. (2015). Examining the online reading behavior and performance of fifth-graders: Evidence from eye-movement data. Frontiers in Psychology, 6, 665. Surrey, J. L. (1985). The “self-in-relation”: A theory of women’s development. Wellesley, MA: Wellesley College, Stone Center for Developmental Services and Studies. Symons, C. S., & Johnson, B. T. (1997). The self-reference effect in memory: A meta-analysis. Psychological Bulletin, 121(3), 371–394. Retrieved from https://www.ncbi.nlm.nih.gov/pubmed/9136641 Tajfel, H. (1974). Social identity and intergroup behaviour. Social Science Information Sur Les Sciences Sociales, 13(2), 65–93. doi:10.1177/053901847401300204 Takacs, Z. K., Swart, E. K., & Bus, A. G. (2014). Can the computer replace the adult for storybook reading? A meta-analysis on the effects

272

The Future of the Self

of multimedia stories as compared to sharing print stories with an adult. Frontiers in Psychology, 5, 1366. Takacs, Z. K., Swart, E. K., & Bus, A. G. (2015). Benefits and pitfalls of multimedia and interactive features in technology-enhanced storybooks: A meta-analysis. Review of Educational Research, 85(4), 698–739. doi:10.3102/0034654314566989 Tamis-LeMonda, C. S., Way, N., Hughes, D., Yoshikawa, H., Kalman, R. K., & Niwa, E. Y. (2008). Parents’ goals for children: The dynamic coexistence of individualism and collectivism in cultures and individuals. Social Development, 17(1), 183–209. Teepe, R. C., Molenaar, I., & Verhoeven, L. (2017). Technology-enhanced storytelling stimulating parent–child interaction and preschool children’s vocabulary knowledge. Journal of Computer Assisted Learning, 33(2), 123–136. doi:10.1111/jcal.12169 Tegmark, M. (2017). Life 3.0: Being human in the age of artificial intelligence. New York, NY: Knopf. The Week. (2012). America’s booming tattoo economy: By the numbers. The Week. Retrieved from http://theweek.com/articles/472165/americasbooming-tattoo-economy-by-numbers Tippett, K. (2016). Becoming wise: An inquiry into the mystery and the art of living. London: Hachette UK. Tippett, K. (2018). Interview with Robin Wall Kimmerer, On Being Show. Retrieved from https://onbeing.org/programs/ robin-wall-kimmerer-the-intelligence-in-all-kinds-of-life-jul2018/ Tomlinson, C. A. (2014). The differentiated classroom: Responding to the needs of all learners. Alexandria, VA: ASCD. Tomopoulos, S., Klass, P., & Mendelsohn, A. L. (2019). Electronic children’s books: Promises not yet fulfilled. Pediatrics, 143(4), e20190191. Triandis, H. C. (1990). Cross-cultural studies of individualism and collectivism. In J. Berman (Ed.), Nebraska symposium on motivation (pp. 41–133). Lincoln, NE: University of Nebraska Press. Troseth, G. L., Flores, I., & Stuckelman, Z. D. (2019). When representation becomes reality: Interactive digital media and symbolic development. Advances in Child Development and Behavior, 56, 65–108.

References

273

Trotter, D. (1983). The making of the reader: Language and subjectivity in modern American, English and Irish poetry. New York, NY: Springer. Tsai, Y., Perrotta, C., & Gašević, D. (2019). Empowering learners with personalised learning approaches? Agency, equity and transparency in the context of learning analytics. Assessment & Evaluation in Higher Education, 45(4), 554–567. doi:10.1080/02602938.2019.1676396 Tseng, P., Bridgeman, B., & Juan, C. H. (2012). Take the matter into your own hands: A brief review of the effect of nearby-hands on visual processing. Vision Research, 72, 74–77. doi:10.1016/ j.visres.2012.09.005 Turk, D. J., Gillespie-Smith, K., Krigolson, O. E., Havard, C., Conway, M. A., & Cunningham, S. J. (2015). Selfish learning: The impact of self-referential encoding on children’s literacy attainment. Learning and Instruction, 40, 54–60. doi:10.1016/j.learninstruc.2015.08.001 Turkle, S. (2017). Alone together: Why we expect more from technology and less from each other. New York, NY: Hachette UK. Twenge, J. M., & Campbell, W. K. (2009). The narcissism epidemic: Living in the age of entitlement. New York, NY: Simon and Schuster. Tyler, D. I. (2013). Revolting subjects: Social abjection and resistance in neoliberal Britain. London: Zed Books Ltd. UNG Assembly. (1948). Universal declaration of human rights. New York, NY: UN General Assembly. UNICEF. (2016). Uprooted: The growing crisis for refugee and migrant children. London: UN. UNICEF. (2018). The children’s report, Australian Committee for UNICEF Limited. Pyrmont, Australia: UNICEF. U.S. Department of Education (2018). Competency-based learning or personalized learning. Retrieved from https://innovation.ed.gov/ competency-based-learning-or-personalized-learning/ Van der Kolk, B. A. (2003). Psychological trauma. New York, NY: American Psychiatric Pub. Van der Kolk, B. A., & McFarlane, A. C. (1996). Traumatic stress: The effects of overwhelming experience on mind, body, and society. New York, NY: Guilford Press.

274

The Future of the Self

Vertovec, S. (2007). Super-diversity and its implications. Ethnic and Racial Studies, 30(6), 1024–1054. https://doi.org/10.1080/01419870701599465 Vezzoli, Y., Kalantari, S., Kucirkova, N., & Vasalou, A. (2020, April). Exploring the design space for parent–child reading. Proceedings of the 2020 conference on human factors in computing systems (pp. 1–12). Vygotsky, L. S. (1978). Mind in society: The development of higher mental processes. Cambridge, MA: Harvard University Press. Waldman, A. E. (2020). Cognitive biases, dark patterns, and the ‘privacy paradox’. Current Opinion in Psychology, 31, 105–109. Walton, G. M., & Cohen, G. L. (2011). A brief social-belonging intervention improves academic and health outcomes of minority students. Science, 331(6023), 1447–1451. doi:10.1126/science.1198364 Ward, A. F. (2013). Supernormal: How the internet is changing our memories and our minds. Psychological Inquiry, 24(4), 341–348, doi:10.1080/1047840X.2013.850148 Wegerif, R. (2008). Dialogic or dialectic? The significance of ontological assumptions in research on educational dialogue. British Educational Research Journal, 34(3), 347–361. White, R. E., Prager, E. O., Schaefer, C., Kross, E., Duckworth, A. L., & Carlson, S. M. (2017). The “Batman effect”: Improving perseverance in young children. Child Development, 88(5), 1563–1571. doi:10.1111/ cdev.12695 Wiener, N. (1961). Cybernetics or control and communication in the animal and the machine (Vol. 25). Cambridge, MA: MIT Press. Williamson, B. (2017). Decoding ClassDojo: Psycho-policy, socialemotional learning and persuasive educational technologies. Learning, Media and Technology, 42(4), 440–453. Williamson, B., Bayne, S., & Shay, S. (2020). The datafication of teaching in Higher Education: critical issues and perspectives, Teaching in Higher Education, 25(4), 351–365, DOI: 10.1080/13562517.2020.1748811. Winnicott, D. W. (1951). Transitional objects and transitional phenomena. In D. W. Winnicott (Ed.), Collected papers: Through paediatrics to psycho-analysis (pp. 220–229). New York, NY: Basic Books.

References

275

Witkin, H. A., Moore, C. A., Goodenough, D. R., & Cox, P. W. (1977). Field-Dependent and field-independent cognitive styles and their educational implications. Review of Educational Research, 47(1), 1–64. Retrieved from ://WOS:A1977DB28400001 Wohlwend, K. E. (2015). Playing their way into literacies: Reading, writing, and belonging in the early childhood classroom. New York, NY: Teachers College Press. Wolf, M. (2008). Proust and the squid: The story and science of the reading brain. New York, NY: Harper Perennial New York. Wolf, M. (2018). Reader, come home: The reading brain in a digital world. New York, NY: Harper. Wolters, M., Georgila, K., Moore, J. D., & MacPherson, S. E. (2009). Being old doesn’t mean acting old: How older users interact with spoken dialog systems. ACM Transactions on Accessible Computing (TACCESS), 2(1), 2. Wong, Q., & Morse, A. (2019). Whopping $5 billion FTC settlement still a bargain for Facebook, critics say. Cnet. Retrieved from https://www.cnet.com/news/ whopping-5-billion-ftc-settlement-still-a-bargain-for-facebook-critics-say/ Wynn, K., Bloom, P., Jordan, A., Marshall, J., & Sheskin, M. (2018). Not noble savages after all: Limits to early altruism. Current Directions in Psychological Science, 27(1), 3–8. Yalom, I. D. (1980). Existential psychotherapy (Vol. 1). New York, NY: Basic Books. Yoon, J., Alaa, A. M., Cadeiras, M., & van der Schaar, M. (2017). Personalized donor–recipient matching for organ transplantation. Paper presented at the AAAI. Young, M. (1958). The rise of the meritocracy. New York, NY: Routledge. Zahavi, D. (2008). Subjectivity and selfhood: Investigating the first-person perspective. Cambridge, MA: MIT Press. Zander, S., Wetzel, S., Kuhl, T., & Bertel, S. (2017). Underlying processes of an inverted personalization effect in multimedia learning – An eye-tracking study. Frontiers in Psychology, 8, 2202. doi:10.3389/ fpsyg.2017.02202

276

The Future of the Self

Zappavigna, M., & Zhao, S. M. (2017). Selfies in ‘mommyblogging’: An emerging visual genre. Discourse Context & Media, 20, 239–247. doi:10.1016/j.dcm.2017.05.005 Zenner, C., Herrnleben-Kurz, S., & Walach, H. (2014). Mindfulnessbased interventions in schools – A systematic review and meta-analysis. Frontiers in Psychology, 5, 603. doi:10.3389/fpsyg.2014.00603 Zhao, S. M., & Zappavigna, M. (2018). Beyond the self: Intersubjectivity and the social semiotic interpretation of the selfie. New Media and Society, 20(5), 1735–1754. doi:10.1177/1461444817706074 Zhao, S. Y., Grasmuck, S., & Martin, J. (2008). Identity construction on Facebook: Digital empowerment in anchored relationships. Computers in Human Behavior, 24(5), 1816–1836. doi:10.1016/j.chb.2008.02.012 Zhao, Y. (2018). Reach for greatness: Personalizable education for all children. Thousand Oaks, CA: Corwin Press. Zittrain, J. (2008). The future of the internet – And how to stop it. New Haven, CT: Yale University Press. Zuboff, S. (2019). The age of surveillance capitalism: The fight for a human future at the new frontier of power. London: Profile Books.

INDEX Abstraction, 134–137 Accelerated migration, 108 Acceleration, 212–213 of change, 114–116 correlates of personalization, 91–97 mediators, 108–116 moderators of extreme personalization, 97–108 personalization and power, 89–91 symptoms of extreme personalization, 116–121 Accommodation, 231 Actor–network theories, 177–178 Adaptation, 32–33 Adaptive learning, 141–142, 221 Adaptive personalization, 2–3, 141–142 Agency, 12, 65–68, 166, 211–212 5As of agentic personalization, 86–88 agentic and automated choices, 72–77 agentic and automatic personalization, 68–72 bi-composition, 67 hypothesis, 77–88 optimal levels, 81–84 paradox, 63, 78 privacy paradox, 84–86 Agentic choices, 72–77 Agentic personalization, 68–72 Alexa, 21, 41 Alternative metaphors, 154–155 Alternative selves, 217

Always Be Charging (ABC), 41 Amazon, 75 American Academy of Pediatrics (AAP), 187 American culture, 18 Answer–response model, 136 Anthropocene, 215–216 Anthropomorphism, 20–22 Apple Watch, 125 Argonauts, The, 112 Arkangel, 43 Art curators, 200 Assessments, 56–58 Assimilation, 231 Attention Merchants, The, 47 Austerity, 109 Authentic instruction, 27–28 Authenticity, 111 Autobiographical selves, 217 Automated choices, 72–77 Automated personalization, 2–3 Automated technology, 58 Automatic personalization, 68–72 Autonomy, attachment, authenticity, aesthetics and authorship of agentic personalization (5As of agentic personalization), 12, 86–88 Avatars, 71–72 Behavioral genetics, 36 Belonging, 166 Bioconservatist perspectives, 37 Bitmojis, 147 Black Mirror, 43

277

278

Bloggers, 225 Body-related personalization, 124–127 Brain cells, 143 Bring your own device (BYOD), 163 Bubble tests, 55 Cambridge Analytica Scandal, 25 Capital, 104–105 Capitalism, 97–98 “Capitalism Without Capital”, 100 Capitalist corporations, 47 “Caring and sharing” scheme, 120 Catharsis, 198–199 Child(ren) abilities, 222–223 assessments and personalized education, 56–58 child-centered education, 27, 78 child-centered media production, 70 child-oriented instruction, 28 childhood poverty, 110 complexity of personal data, 59–61 data-driven education, 54–56 extreme amplification, 46–49 internet for children, 49–50 making, 29, 32 optimal quantities of personal data, 61–63 persuasive design of technologies, 44–45 psychology theories, 8 quantities of personal data, 50–54 TV programs, 226 use of technologies, 41 Children’s Digital Story Books, 186–188 Children’s Story Books, 185 Choices, 2, 72, 96 “Clan-like” philosophy, 101 Coding movement, 71 Cognitive load, 80 Cognitive psychology research, 167 Collective migrations, 108–116

Index

Collective narcissism, 118 “Comic about comics”, 76 Comics, 15 Commercial models of personalization, 150 Commercial personalization, beginnings of, 94–97 Commercialization, 48 Commercially produced personalized books, 191–192 Common Sense Media, 43 Computer as human brain metaphor, 151–154 Computers act As Persuasive Technologies (CAPTology), 225 Congruence between ideal and actual “self”, 131–134 Constructionism, 138 Context of use, content of activity, children’s individual characteristics and traditions of community (4Cs), 211 Contextualization, 200–202 Contextualized talk, 189–190 Contrast-driven elections, 110 Conversations, 190, 202–204 Coronavirus apps, 84 Covid-19 pandemic, 117 Creative making, 71 Creative writing, 201 Creativity, 70 Customer choice, 73 persona, 21 Customization, 31–33 Customized products, 3–4 Customized shirt, 30 Cybernetics, 151 Data, 5 (see also Personal data) colonialism, 11 data-based instruction, 55 data-driven education, 54–56 data-free zones, 20 future, 62

Index

Datafication, scale of, 39–41 Datafied selves, 217 Dating apps, 106 Decentralized data servers, 226 Decontextualized talk, 189–190 Deep personalization, 19 “Deep reading” processes, 188 Default network, 143 Density, 123, 213–214 abstraction, 134–137 adaptive personalization and adaptive learning, 141–142 body-related personalization, 124–127 congruence between ideal and actual “self”, 131–134 desired difficulties, 137–141 extended self theory, 128–129 networked self, 130 optimal personalization density, 150–155 personalized brain, 143–146 relational self, 146–150 replicating instead of extending our bodies, 127–128 Designer babies, 113 Desired difficulties, 137–141 Determinism, 8 Dialecticism, 204 Dialogic learning functions, 173 Dialogical approaches to education, 14 Dialogue, 171 in education, 171–177 Differentiated education, 27 Differentiated learning, 3–4 Difficult transaction model, 73 Digital amnesia, 57 books, 186 detox, 99 information, 39 library, 26 personalization, 3, 5 self, 147–149 Digitized personal data, 24–25

279

Disaster selfies, 229–230 Discernment, 178 Disequilibrium state, 231 Disinterested interest, 215 Distance, 183, 214–217 distancing techniques, 15 personal resonance, 204–207 personalized story books, 188–192 stories and narratives, 183–188 Distancing hypothesis, 192 contextualization, 200–202 conversation, 202–204 empathy options in relation to stories, 197 immersion/identification options in stories, 196 quadrants of social cognition, 196 techniques, 199–200 Drag nets, 26 E-books (see Digital—books) Early childhood, 26–30 Ebay, 75 Edtech market, 164 Education Endowment Foundation, 231 Education(al), 214 approaches, 27–28 futures, 177 geneism, 179 genomics, 179 meteorological metaphor personalization, 180–182 myths, 167–168 technology, 162–165 EDUCE adaptive educational system, 138–139 Edwardian model of education, 55 Effective Pre-school, Primary and Secondary Education Project, 228–229 Enantiodromia, 34 Encoding variability, 59 Endowment effect, 75

280

Engaged pluralization, 224 Engagement, 169–170 Equilibration, 231 Ergodic literature, 199 European General Data Protection regulation, 25 Everywear, 125 Expanded selves, 217 Expectancy-value theory, 193 Extended self theories, 13–14, 128–129 External body extensions, 126 Extreme personalization (see also Optimal personalization) moderators of, 97–108 symptoms of, 116–121 Face-based personalization, 49 FANG firms, 51 Fear of failure, 119 Fear of missing out (FOMO), 119 Fear of other, 109 Fictional stories, 200 Films, 15 Finger-Reader™, 126 Fitbit apps, 125 Forced migration, 108 Fourth Industrial Revolution, 39 Fragmentation–amplification process, 209 “Free dating” apps, 106 Free play, 27 Free will, 224 FRIENDS program, 229 Future personalized books, 206–207 Game of power, 91 Generation Alpha, 1 “Generation Me”, 18 “Generation Wealth” (documentary), 99 Gig economy, 52, 102, 105–106 Global business travel, 110 Google, Apple, Facebook and Amazon firm (GAFA firm), 51

Index

Government regulation, 25–26 Great Acceleration, 114 Gross domestic product (GDP), 96 GSM telephone system, 143 Handbook on Wealth and the Super-Rich, 105 Handle technique, 149 Happiness, 69 Hawthorne effect, 85 Historic biases, 54 Hook Model, 44 Hoped-for possible selves, 132 Human brain–computer analogy, 152 Human teaching, 162–165 Human–computer interaction (HCI), 219 studies, 76 Humankind, 39 ‘Hungry Caterpillar’ (Carles), 31 Ideal self, 132–133, 217 Identity, 132, 146, 209 chameleons, 113 IKEA effect, 74 Image-based method of word learning, 149 Imagination Library, 24 In-group empathy (see Parochial empathy) Individualism–collectivism, 222 dualism, 17–18 Individualization, 32–33 Individualized education, 27 Inequality, 91–97 Influencers, 47 Infosphere, 11, 39, 130 Innovative edtech, 161 “Inspirational” campaigns, 119 Instagram stars, 47–48 Intellectual humility, 204 Inter-textuality, 200 Internal body extensions, 126 Internet, 49 for children, 49–50 internet of Things, 130 Intuitive system, 205

Index

iPads, 41–42 iPhone, 21 IQ test, 221–222 iRead system, 221 Jacob’s ladder of motivation, 167 Jellies App, 29 Juxtaposed learning, 175 Kidfluencers, 48 Kloneworld™, 127 Knowledge building community systems, 174 Knowledge Forum, 175 “Labor-saving” technologies, 90 Layers, The, 130 Learning, 134, 138–139 Lego, 74 Literary novels, 15 Live literacies, 73 Localization, 31 LOGO robot, 160 Maker Movement, 29 Market economy, 98 Market society, 98 Martin’s hypothesis, 59 Mastery learning, 163 Match. com, 228 Me Books™ app, 192 “Me Generation”, 9 “Me Mobiles”, 9 Me Too movement, 100 Mediators, 108–116 Medicine, 142 “Mere ownership” effect, 75 Meritocracy, 97–108 Meteorological metaphor personalization, 180–182 Meteorology measurements, 181 Migration, 108 Millennials, 11 Mind-wandering, 143 Minecraft, 28, 74 Mister Rogers’ Neighborhood, 229 Mobility, 107, 115

281

Moderators of extreme personalization, 97–108 Montessori Method, 28 “More is better” model, 51, 53, 58, 61–63, 96, 210 Multi-dimensionality of personalization, 17 Multimedia, 39 multimedia/literacy choices, 73 stories, 71–72 Name Jar, The (Choi), 23 Name-based personalization, 22–24, 49 Name-effect, 22 Narratives, 183–188 Nature and nurture in “self”, 36–38 Nearby-hand hypothesis, 170 Neoliberal capitalism, 97–108 Netflix for films, 102 netflix-inspired commercial model, 11 netflix-inspired personalized education, 54 Networked self, 13–14, 130, 217 Neurodiversity movement in education, 77 Neuroimaging studies, 143 New global nomads, 111 New literacy studies, 177–178 New media humanism, 11–12 Newtonian determinism, 9 “No means no” messages, 61 Non-digital personalization, 3 Non-personalization, 30–33 Non-transparent algorithm, 100 Novelty, 170 Observational studies, 42 Online platforms, 132–133 Open-ended apps, 176 Open-ended design, 74–77 Optimal personalization (see also Extreme personalization)

282

alternative metaphors, 154–155 for children, 20 computer as human brain metaphor, 151–154 density, 150 Oral story-telling, 15 ‘Others’, 171 Out-group empathy, 194 Ownership, 23 PAD emotions, 225 Paradox of choice, 72 Parochial empathy, 193–195 Peer review of information, 46 Personal confusion, 116 Personal data, 7, 11 complexity, 59–61 economy, 1 optimal quantities, 61–63 quantities of, 50–54 Personal knowledge, 220 Personal migrations, 108–116, 111–114 Personal possession, 220 Personal resonance, 204–207 Personalization, 2, 4, 9, 17, 30–31, 44, 89–91, 146, 166–170, 188 applications, 10 based on diverse personal data, 24–26 commercial and educational use of, 19–20 correlates, 91–97 and early childhood, 26–30 educational approaches to, 2 effects on consumer behavior, 7 name-based personalization, 22–24 nature and nurture in “self”, 36–38 personalization–inequality relationship, 96 revolution, 114 revolution, 13 revolution, 94 techniques, 3 theory of, 1–2

Index

Personalization and pluralization (P–P), 14, 227 balance, 34–36, 38, 81–82, 209, 216–217 curriculum, 170–171 design solutions, 50, 140 Personalized algorithms, 50 Personalized anonymity models, 220–221 Personalized assessments, 159–162 Personalized books, 9, 191–192 Personalized brain, 142–146 Personalized design, 28–30 Personalized donor–recipient matching, 124 Personalized education, 2, 10, 27–28, 56–58, 69, 158–159 Personalized figurines, 127–128 Personalized gifts, 2 Personalized healthcare, 95 Personalized learning, 3, 27, 230 Personalized life hacks, 71 Personalized medicine, 2, 7 Personalized mnemonics, 149–150 Personalized news, 2 Personalized online world, 150 Personalized shirt, 30 Personalized space, 104–108 Personalized story books, 188 commercially produced personalized books, 191–192 shared book reading, 189–191 Personalized time, 100–103 Personalized treatment, 126 Personification, 20–22 Persuasive design of technologies, 44–45 Physics analogy, 9 Pinwheel self, 216 Play, 135 Playful curriculum, 28 Pluralism, 34 Pluralization, 10, 33–34, 166–168 Plutocratic capitalism, 98 Polyphony, 35–36 Pop-up selfie museums, 148

Index

PopJam, 28 Population, 46 Portable self, 111 Positionality, 100 Post-Millennials, 11 Power, 89–91 Precise personalized medicine model, 179 Pretend play, 135 Printing, 39 Privacy paradox, 84–86 Private Life of the Brain, The, 143 Programmatic pluralization, 139–140 Psychographics, 124 Psychometrics, 124 Public education system, 233 Quantities of personal data, 50–54 Quantity of digital data, 39 children’s use of technologies, 41–63 scale of datafication, 39–41 Quantum physics, 8–9 Randomized controlled trials (RCTs), 233 Rasas, 206 Reactive design, 29–30 Reading stories, 15, 183 Real self, 132 Reality, 21, 100 Reciprocity, 166 Reflective cognitive system, 205 Relational self, 146, 217 personalized mnemonics, 149–150 selfies, 147–149 theories, 13–14 Relativism, 8 Remediation, 222 Remembered self, 154 Responsive design, 29–30 Ressentiment, 118 Ruling capitalist class, 90 Satellites, 180 Screen time, 103–104

283

Screen-space, 104 Scribblitt, 185 Scribd, 102 Self, 1, 10, 18, 26, 61, 123, 129, 172 (see also Relational self) Self-actualization, 37 Self-determination, 71, 166 Self-distanced talk, 203–204 Self-efficacy, 66 Self-esteem, 66 Self-image, 66 Self-presentation theory, 131 Self-reference effect, 7, 131 Self-referential information, 131 speech, 7 talk, 203–204 Self-regulation, 66 Self-relevance, 205 Self-representation, 71 Self-talk, 135 Self-worth, 66 Selfies, 147–149 generation, 18 Self–other distance in texts, 15 Sequence, 157, 214 dialogue in education, 171–177 educational futures, 177–182 educational technology vs. human teaching, 162–165 myth, 14, 168–170 personalization vs. pluralization, 166–168 personalized and standardized assessments, 159–162 personalized vs. standardized education, 158–159 P–P curriculum, 170–171 Shared book reading, 189–191 Sharing economy, 102, 228 Shelfies, 147 Skylanders, 28 “Slow down” movement, 120 Slow TV, 229 Small Basket of Happiness, 154 Smart toys, 136–137

Index

284

Snapchat, 28 Social cues, 69 Social cultural developmental theory, 154 Social proof, 46 Social robots, 69 Society of The Spectacle, The, 99 Socio-cultural education, 219 Socio-cultural learning theory, 172 Spotify for music, 102 Standardization, 96 Standardized assessments, 159–162 Standardized education, 158–159 Sterile practices, 53 Stories, 15, 183–188, 234 Story-telling curriculum (Paley), 68 StoryBird, 185 StoryJumper, 185 Student-focused instruction, 28 Targeted online services, 223 Tattoos, 126–127 Technology, 223 in children’s lives, 41 determinism, 168 developers, 29 technology-driven personalized education, 164–165 technology-free kindergartens, 41 technology-free zones, 20 Template-based apps, 176 Test-oriented education, 159 Testing Charade, The, 158–159 Theory of diversity, 59 Three-dimensional space, 11 ToyTalk Ltd., 224 Traditional institutions, 110 Transactional model, 36 Transhumanist perspectives, 37 Transitional objects, 20 Transparency, 83 True selves, 132, 217 Twitch, 29

Uber economy, 102 Ultra-personalization, 19 “Ultra-personalized” body extensions, 127 Unbound selves, 217 Unboundedness of online self, 129 Uncanny Valley Theory, 79–80 Uncertainty (see Personal confusion) Unfair algorithm, 100 Universal design, 77 US tattoo industry, 127 User profiling, 70 Usie, 147 Utility value interventions, 193 Video production, 71 Violence, 109–110 Virtual reality (VR), 16, 133 researchers, 134 Visual communication, theory of, 224–225 Volition, 71 Voter nostalgia, 120 Weather radars, 180 Web 2. 0, 2, 132, 152 Web 3. 0, 152 WeNeedDiverseBooks, 185 Western acceptance of individualistic values, 99 Western democracies, 110 Western education ideals, 162 Wiki walking, 188 Word-learning technique, 149 Wordpress blogging site, 225 Writing, 39 You-Tube algorithm, 41 entrepreneurs, 47–48 Zone of proximal development, 172