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269
ISBN 10:
1138230057
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“A unique and original contribution to the debate about AI now
unfolding across the world. Rather than offering an exercise in
futurology, Elliott provides a detailed and sophisticated analysis of
the impact of AI and the digital revolution in the here and now.”
Professor Lord Anthony Giddens, Department of Sociology,
London School of Economics
“Anthony Elliott’s compelling and accessible book is an impressive survey of the impact of artificial intelligence on almost everything, from global politics to everyday communication. Adopting
his fine theoretical lens, he raises crucial questions particularly
regarding the power of automated technologies to reconfigure
our sense of ourselves, our very identity. The book is essential
reading for understanding the way digital transformations work
in the contemporary moment.”
Judy Wajcman, Anthony Giddens Professor of Sociology,
London School of Economics
“Artificial Intelligence is an overused term which has been the
subject of too many inflated claims. So we are lucky that in
this book, Anthony Elliott expertly guides us through this thicket
of hyperbole and out onto clearer ground. His emphasis on what
software does – what Kaplan has called anthropic computing – and

how it is transforming the mundanities of everyday life through
a grab-bag of software is a welcome antidote to AI as a false idol
which, at the same time, shows us where the opportunities and
worries really are. A measured read which really takes the measure of AI.”
Sir Nigel Thrift, Visiting Professor, Oxford and
Tsinghua Universities
“Hollywood has blinded us to the idea that AI will bring a future
of intelligent robots. But, as Anthony Elliott shows in this important book, the reality is that AI is already here and its impact
encompasses the entirety of our social relations. A very welcome
addition to the debate about the impact of AI on society.”
Toby Walsh, Professor of AI, UNSW and
author of 2062: The World that AI Made
“The book breaks new ground by covering familiar debates
about the impact ; of digital systems – Robotics, AI and Machine
Learning – on jobs; communication, mobility and life-styles;
the transformation of identities and self; embattled democracies
and the global economic order. By focusing on everyday digital experience it provides well-argued insights into the adaptive
interactions between humans and digital machines and into the
digitally mediated connectivity between humans. It presents the
self as information system and thus a timely answer to pervasive
cultural anxieties and techno-hype alike. Anthony Elliott prepares us to better understand the digital world that surrounds us
already.”
Helga Nowotny, Professor Emerita of Science and
Technology Studies, ETH Zurich, and Former President
of the European Research Council (ERC)

THE CULTURE OF AI

In this groundbreaking book, Cambridge-trained sociologist
Anthony Elliott argues that much of what passes for conventional
wisdom about artificial intelligence is either ill-considered or
plain wrong. The reason? The AI revolution is not so much
about cyborgs and super-robots in the future, but rather massive
changes in the here-and-now of everyday life.
In The Culture of AI, Elliott explores how intelligent machines,
advanced robotics, accelerating automation, big data and the Internet
of Everything impact upon day-to-day life and contemporary
societies. With remarkable clarity and insight, Elliott’s examination
of the reordering of everyday life highlights the centrality of AI to
everything we do – from receiving Amazon recommendations to
requesting Uber, and from getting information from virtual personal
assistants to talking with chatbots.
The rise of intelligent machines transforms the global
economy and threatens jobs, but equally there are other major
challenges to contemporary societies – although these challenges
are unfolding in complex and uneven ways across the globe. The
Culture of AI explores technological innovations from industrial
robots to softbots, and from self-driving cars to military drones –
and along the way provides detailed treatments of:
• The history of AI and the advent of the digital universe;
• automated technology, jobs and employment;

• the self and private life in times of accelerating machine
intelligence;
• AI and new forms of social interaction;
• automated vehicles and new warfare;
• and the future of AI.
Written by one of the world’s foremost social theorists, The
Culture of AI is a major contribution to the field and a provocative
reflection on one of the most urgent issues of our time. It will be
essential reading to those working in a wide variety of disciplines
including sociology, science and technology studies, politics, and
cultural studies.
Anthony Elliott is Executive Director of the Hawke EU
Jean Monnet Centre of Excellence at the University of South
Australia, where he is Research Professor of Sociology and
Chancellery Dean of External Engagement. He is Super-Global
Professor of Sociology (Visiting) at Keio University, Japan, and
Visiting Professor of Sociology at UCD, Ireland. Professor
Elliott studied at the Universities of Melbourne and Cambridge,
where he was supervised by Lord Anthony Giddens. He was
previously Professor of Sociology at the University of Kent at
Canterbury, UK and was Associate Deputy Vice-Chancellor
at Flinders University, Australia. Professor Elliott is a Fellow
of the Academy of the Social Sciences in Australia, a Fellow of
the Cambridge Commonwealth Trust, and a member of King’s
College, Cambridge. He is the author and editor of some 40
books, which have been translated into or are forthcoming in
17 languages. His recent books include Identity (4 volumes),
Contemporary Social Theory: An Introduction, The New Individualism
(with Charles Lemert), Mobile Lives (with John Urry), On Society
(with Bryan S. Turner), Reinvention, and Identity Troubles. He is
best known for Concepts of the Self, which has been in continuous
print for 20 years and across three editions.

Also by Anthony Elliott

Social Theory and Psychoanalysis in Transition: Self and Society from
Freud to Kristeva
Psychoanalytic Theory: An Introduction
Psychoanalysis in Contexts: Paths Between Theory and Modern
Culture (Co-editor)
Subject To Ourselves: Social Theory, Psychoanalysis and Postmodernity
Freud 2000 (Editor)
The Blackwell Reader in Contemporary Social Theory (Editor)
The Mourning of John Lennon
Psychoanalysis at its Limits: Navigating the Postmodern Turn
(Co-editor)
Concepts of the Self
Profiles in Contemporary Social Theory (Co-editor)
Key Contemporary Social Theorists (Co-editor)
Critical Visions: New Directions in Social Theory

Social Theory Since Freud: Traversing Social Imaginaries
The New Individualism: The Emotional Costs of Globalization (with
Charles Lemert)
The Contemporary Bauman (Editor)
Making The Cut: How Cosmetic Surgery is Transforming Our Lives
The Routledge Companion to Social Theory (Editor)
Contemporary Social Theory: An Introduction
Identity in Question (Co-editor)
Mobile Lives (with John Urry)
Globalization: A Reader (Co-editor)
The Routledge Handbook of Identity Studies (Editor)
On Society (with Bryan S. Turner)
Reinvention
The Routledge Companion to Contemporary Japanese Social Theory:
From Individualization to Globalization in Japan Today (Co-editor)
Identity: Critical Concepts in Sociology (Editor)
Introduction to Contemporary Social Theory (with Charles Lemert)
The Routledge Handbook of Social and Cultural Theory (Editor)
Identity Troubles
The Routledge Handbook of Psychoanalysis in the Social Sciences and
Humanities (Co-editor)
The Consequences of Global Disasters (Co-editor)
Routledge Handbook of Celebrity Studies (Editor)

THE CULTURE OF AI
Everyday Life and the
Digital Revolution

Anthony Elliott

First published 2019
by Routledge
2 Park Square, Milton Park, Abingdon, Oxon OX14 4RN
and by Routledge
52 Vanderbilt Avenue, New York, NY 10017
Routledge is an imprint of the Taylor & Francis Group, an informa business
© 2019 Anthony Elliott
The right of Anthony Elliott to be identified as author of this work
has been asserted by him in accordance with sections 77 and 78 of the
Copyright, Designs and Patents Act 1988.
All rights reserved. No part of this book may be reprinted or
reproduced or utilised in any form or by any electronic, mechanical,
or other means, now known or hereafter invented, including
photocopying and recording, or in any information storage or retrieval
system, without permission in writing from the publishers.
Trademark notice: Product or corporate names may be trademarks
or registered trademarks, and are used only for identification and
explanation without intent to infringe.
British Library Cataloguing-in-Publication Data
A catalogue record for this book is available from the British Library
Library of Congress Cataloging-in-Publication Data
A catalog record has been requested for this book
ISBN: 978-1-138-23004-0 (hbk)
ISBN: 978-1-138-23005-7 (pbk)
ISBN: 978-1-315-38718-5 (ebk)
Typeset in Janson
by Apex CoVantage, LLC

FOR TONY GIDDENS

CONTENTS

CONTENTSCONTENTS

Acknowledgmentsxiii
Preface 
xvii
Introduction
The Turing test and after 5
From self-driving cars to space robots: disruptive technology
and the digital universe 10
The arguments of this book 15

1

1

The digital universe
Complex digital systems 26
Digital life: theoretical perspectives 40

23

2

The rise of robotics
Technology and automation 54
The fourth industrial revolution: the sceptics and
their critics 55
Globalization and offshoring 66
Robotics and jobs: where we stand 73

52

3

Digital life and the self
The self as information system 80
Turkle: narcissism and the new solitude 84
Critical remarks 86
Containment, storage and digital keys 94

78

xii Contents

4

Digital technologies and social interaction
The institutional organization of social interaction: faceto-face and digitally mediated action frameworks 107
Bots, talk and co-presence 118
Dimensions of the digital revolution: portals,
desynchronization, instantaneity 126
Digital noise: silence is golden? 130

106

5

Modern societies, mobility and artificial intelligence
Automated automobility: the Google car 135
New wars, drones and killer robots 141

133

6

AI and social futures
Robot intimacy 160
Healthcare after AI 170
Democracy beyond AI 180
AI futures and public policy 195

156

Notes202
Index238

ACKNOWLEDGMENTS

ACKNOWLEDGMENTSACKNOWLEDGMENTS

It was partly with the aim of addressing what I have termed today’s
“technological tsunami” that I set out, in 2013, to study systematically the digital revolution and its associated global transformations. At that time, I was Director of the Hawke Research
Institute at the University of South Australia, and I was influenced considerably by the former Prime Minister of Australia,
the Hon. Bob Hawke, who suggested to me the urgency of these
issues for both the social sciences and public policy. I began by
working on an area of the digital revolution which was close to
my own heart, namely the reorganization of identity and the self
as a consequence of large-scale technological change. The results
of that research were published in 2016 in Identity Troubles. Following the publication of that book, I turned to address a related,
but quite distinct, set of developments associated with the digital
revolution – that of artificial intelligence (AI), machine learning,
advanced robotics and accelerating automation. My principal
goal was to study the extensity and intensity of the world of AI
from the standpoint of sociology in general and social theory in
particular. In doing so, I should like to acknowledge that I owe
a large debt of gratitude to Lord Anthony Giddens, who perhaps more than anyone else has influenced my thinking of digital
transformation in our times and our lives in these times. I am
very grateful to him for taking the time to talk through with me

xiv Acknowledgments

in detail his work on the UK Parliament’s House of Lords Select
Committee on Artificial Intelligence. I am similarly grateful for
the time he devoted to reading an earlier draft of my manuscript,
and for his insightful suggestions and recommendations. I should
also like to express my thanks to Sven Kesselring, who provided
remarkably helpful comments on an earlier draft of the book.
I benefited considerably from being appointed by the Chief
Scientist of Australia, Dr Alan Finkel, to the Expert Working
Group on Artificial Intelligence of the Australian Council of
Learned Academies. This inquiry was at the request of the Prime
Minister’s Commonwealth Science Council, and with support
from the Australian Research Council, the Department of Prime
Minister and Cabinet, and the Department of Industry, Innovation and Science. I owe thanks to my colleagues on the Expert
Working Group, and in particular to Dr Angus Henderson of
ACOLA and to Dr John Beaton at the Academy of the Social
Sciences of Australia.
The research for this book was carried out over a period of four
years, from 2015 to 2018. I am grateful to a number of academic
institutions and funding agencies which supported this research
and enabled me to spend extended periods of time working overseas on this project. These include the Australian Research Council (DP 160100979 and DP180101816); the Toyota Foundation,
Japan (D16-R-0242) and the European Commission’s Erasmus+
Jean Monnet Actions (587082-EPP-1-2017-1-AU-EPPJMOPROJECT) for a generous grant. I carried out research in Japan
through the award of a Super-Global (Visiting) Professorship in
the Graduate School of Human Relations at Keio University,
and I am very grateful for the support of colleagues at the School
and University. In Europe, my base was as a Visiting Fellow at
the Long Room Hub at Trinity College Dublin (many thanks
to Juergen Barkhoff), Visiting Professor at the School of Sociology at University College Dublin (with thanks to Iarfhlaith
Watson and Siniša Malešević), and in Paris as Visiting Professor
at the Universite Pantheon Assas, Paris II (with thanks to JeanJacques Roche). I was fortunate to receive detailed and pertinent

Acknowledgments

xv

comments from audiences where I lectured on the sociology of
AI in Brazil, Japan, Germany, France, the UK, Ireland, Finland
and Australia.
I am especially grateful for collaboration with colleagues in
the Hawke EU Jean Monnet Centre of Excellence at the University of South Australia, and in particular thanks to Eric Hsu and
Louis Everuss. Ross Boyd, Senior Research Associate at the Centre, supported the various stages of the book’s gestation with his
highly calibrated research assistance and unstinting meticulous
care. At UniSA, I should also express my thanks to colleagues in
the External Relations and Strategic Projects Portfolio in Chancellery, and in particular to Nigel Relph – with whom it has been
my good fortune to work – for helping to create the conditions
under which I could finish this book.
I am very grateful for discussions with many colleagues on
these various themes, including especially the late John Urry.
Special thanks for comments, suggestions or recent discussions
with Masataka Katagiri, Atsushi Sawai, Ralf Blomqvist, BoMagnus Salenius, Malene Freudendal-Pedersen, Robert J. Holton, Charles Lemert, Nigel Thrift, Nick Stevenson, Anthony
Moran, Thomas Birtchnell, Mikako Suzuki, Takeshi Deguchi,
Mike Innes, Kriss McKie, Bianca Freire-Mederios, Judy Wajcman, David Bissell, John Cash, Rina Yamamoto, Ingrid Biese,
David Radford, Deborah Maxwell, Jean Elliott, Keith Elliott,
Jeffrey Prager, Susan Luckman, Hideki Endo, Carlos Benedito
Martins, Yukari Ishi, Fumi Kato, Pal Ahluwalia and Michael Lai.
Thanks, as ever, to my editor Gerhard Boomgaarden at Routledge. I have greatly appreciated his wise counsel, and he has
shown me over and over what friendship can mean. Also at Routledge, many thanks to Alyson Claffey and Diana Ciobotea. Huge
thanks to Caoimhe Elliott for assisting in getting the cover of the
book right.
There is a final, and most significant, debt to my family.
Throughout working on this book, Nicola Geraghty understood what I was trying to accomplish better than anyone and
gave her full support. Her encouragement and faith has been

xvi Acknowledgments

vital. Caoimhe, Oscar and Niamh have grown up in a world of
intensive AI, and the story of digital transformation has been the
background story of their lives. My work on AI and robotics has
been hugely enriched as a result of their interest in, and fascination for, the digital revolution. They have helped me see that
thinking about AI is also a way of thinking about social relations,
and especially alternative futures for self and society. Thinking
about mobile digital connectivity is a way of thinking about what
we mean to each other, and of how those meanings are transforming across space and time. The book is written, in one sense,
as an extended essay to them about how I see our connections in
the future – mediated significantly, but hopefully not wholly, by
intelligent machines – and of the wider social, cultural, economic
and political consequences of AI.

PREFACE

PREFACEPREFACE

Rachel wakes at 7 AM to the sound of BBC radio, activated by
Amazon’s Alexa device.1 The virtual personal assistant has been
programmed to assist with Rachel’s tight morning schedule, and
completes multiple tasks – turning on the lights and heating system, starting the coffee machine – whilst Rachel gets on with
her usual morning routine. Heading to the bathroom where she
picks up a digital quip toothbrush, which pings every 30 seconds
to remind her to move to a different quadrant of teeth for optimal oral hygiene, Rachel listens to the latest BBC update on the
UK Parliament’s House of Lords Inquiry into Artificial Intelligence which has been hearing evidence from security experts
on AI-enabled cyber-attacks exploiting everyday smart technologies.2 Checking traffic conditions on her tablet over breakfast,
she decides to use the eco-friendly car-sharing app Zipcar. Arriving at the office, Rachel focuses swiftly on work, as she is mindful
that a recent raft of job cuts due to a new round of automation
has generated much anxiety amongst her colleagues. She spends
the day organizing the filling of a vacant company position with a
recently developed and increasingly popular jobs website, which
uses smart algorithms to categorize applicants.3 Whilst working
on this, and throughout the day, Rachel monitors her elderly pet
cat with Petcube, a Wi-Fi enabled device that streams video and
other monitoring functions.4

xviii Preface

After work, Rachel heads to a café, where she logs onto the
app Be My Eyes, which matches sighted people wishing to volunteer their vision to the visually impaired through mobile devices.
She tries to do this a couple of times a week, as it has a strong
emotional connection due to the fact that her father (who passed
away some years earlier) had been blind. Returning home, she
stops at a supermarket to collect some items to fix dinner for
herself and partner. Using her recently purchased smartfridge
app, Rachel is reminded to buy tomatoes, onions and milk, items
on which she is low and which the smartfridge ‘knows’ she uses
frequently.5 After dinner and catching up with her partner, she
picks up her mobile and checks a notification that ticket prices
for flights to Australia have dropped significantly. Rachel wants
to visit her cousin in Sydney, and had requested an alert when
airfares drop to a price she could better afford. Retiring to the
bedroom, Rachel and her partner rest in their new smartbed.
The bed ‘knows’ when she tends to go to sleep, which allows it
to warm her side of the bed to a temperature she finds comfortable; the bed can also gently raise her partner’s head if he starts
snoring.6
What can be gleaned about our lives, and our lives in these
times, from Rachel’s day? What does Rachel’s story tell us about
how AI is changing the ways we live and work in these early
decades of the twenty-first century? To begin with, this vignette
is set in London, but it might just as easily be Copenhagen or
Chicago, Singapore or San Francisco. The unfolding of Rachel’s
day tells us not only about the digital revolution but the rise of
AI and software algorithms in our everyday activities and connections with others. AI is not what you think, but rather what
you do! From virtual personal assistants to voice-based chatbots,
Rachel’s story indicates that AI has become increasingly central to our daily lives – as more and more of us access multiple
AI software programs and virtual assistants simultaneously and
often across multiple platforms. This explosion in AI, machine
learning and big data goes to the core of the daily routine interactions in which people are embedded – from personalized social
media to facial recognition software to gain access to offices.

Preface

xix

AI has become, in a word, mainstream. There are, however,
clearly other changes at work too. If AI impacts lifestyles and
personal life, it also transforms organizations, social systems,
nation-states and the global economy. AI is not an advancement
of technology, but rather the metamorphosis of all technology. The increasingly ubiquitous spread of software algorithms,
deep learning, advanced robotics, accelerating automation and
machine decision-making, when contextualized in terms of the
global digital distribution and use of Internet-connected devices
which generate massive quantities of data, generates complex
new systems and processes with multiple impacts across social,
cultural, political and institutional life. As Rachel’s daily activities
demonstrate, people’s lives and lifestyles today presuppose complex digital systems, as well as specialized forms of technological
expertise, of which they are often only dimly aware. Another way
of putting this point is to say that lifestyles permeated by AI are
intricately interwoven with extensive and highly intensive complex digital systems. In this book I focus at some length on this
interplay of digital systems and lifestyles ushered into existence by
the rise of AI, advanced robotics and accelerating automation.
To live during the advent of the digital revolution is not, to be
sure, an unmixed blessing. We live increasingly in a world of technological innovation riven between extraordinary opportunity and
wholesale risk. As the huge wave of AI breaks across the world, the
possibilities for the reinvention of common public life and successful collaborative social action on a scale unprecedented in human
history has come into focus. AI is being used, for example, to track
fish in the Great Barrier Reef, protect biodiversity in the Amazon and deter animals from entering endangered habitats using
sensors7; research is also at an advanced stage for AI-powered
microscopes to monitor plankton floating in the sea and for robots
powered by AI to clean the oceans.8 The deployment of AI in the
fight against global terrorism, through the international pooling
of information and intelligence from supercomputers, is another
case in point. But there are also massive high-consequence, possibly existential, threats.9 From killer robots to lethal autonomous
weapons technology to AI used by criminal organizations or rogue

xx

Preface

states, AI might potentially spell the end of humanity – a warning
issued by such luminaries as the late Stephen Hawking, Bill Gates
and Elon Musk. At its center, this cultural anxiety concerns what
might happen if AI outstrips human intelligence. One of the most
disturbing trends has to do with the merging of AI, digital technology and the means of waging war. In this book I place a good deal
of emphasis upon the role of AI in the transformation of military
power, and especially the impact of new forms of surveillance –
of which big data and awesome algorithmic power have been the
most momentous features of technological development – upon
the development of world order.
In order to systematically capture an argument that spills out
over large tracts of technological innovation and scientific discovery, I shall summarize here the main claims of this book in the
form of basic observations.
1 The digital universe has a direct connection with AI, but
today’s technological changes are far more encompassing in scope than AI alone. Notwithstanding key terminological differences, digital transformation can be adequately
grasped in social, cultural and political terms only if we see
the interconnections between, amongst other technologies,
AI, advanced robotics, Industry 4.0, accelerated automation,
big data, supercomputers, 3D printing, smart cities, cloud
computing and the Internet of Everything. These technological transformations must also be viewed in the wider context of developments in biotechnology, nanotechnology and
information science. Benjamin Bratton has recently captured
this point with reference to a “planetary-scale computing
megastructure”.10
2 AI is not so much about the future as the here-and-now. Our
lives are already saturated with AI – evidenced in the rise of
chatbots, Google Maps, Uber, Amazon recommendations,
email spam filters, robo-readers, and AI-powered personal
assistants such as Siri, Alexa and Echo. The AI revolution is
thus already well underway, and is unfolding in complex and
uneven ways across the globe.

Preface

xxi

3 AI is not simply an “out-there” phenomenon, such as the
technological field of machine learning algorithms or emotion recognition technologies. AI also pervades personal life,
reorganizing the nature of self-identity and the fabric of
social relations in the broadest sense.
4 Much of what we do in everyday life is organized and mediated
by AI. Yet AI transforms the fabric of everyday life in largely
unnoticed ways. Like electricity, AI is essentially invisible. AI
functions automatically, operating “behind the scenes” – so that
airport doors automatically open (or not!), GPS navigation gets
us home, and virtual personal assistants help in our daily lives.
And just like electricity, AI is fast becoming a general purpose
technology – that is to say, a technology which enables the development of a whole range of further innovative applications.
5 As a consequence of the development and deepening of
Industry 4.0, AI will radically intensify digital disruption in
the labor market and employment. Many jobs will certainly
disappear as a result of AI, but this is not as simple as the “rise
of the robots” thesis. Other jobs will be enhanced by AI, and
many – as yet unknown – jobs will be generated. In all of this,
digital skills – and especially the fostering of digital understanding – will be crucial.
6 To be sure, AI inaugurates an employment revolution. But
perhaps the most significant global transformation will be at
the level of talk and everyday life. AI has major implications for
the ways in which people will communicate and talk with each
other. Not only is over 50% of Internet traffic now generated by machine-to-machine communication, but person-tomachine talk is significantly rising and will continue to escalate.
In particular, chatbots, softbots and virtual personal assistants
will become an integral part of how people live and work.
7 Advanced AI is very different from previous forms of technological automation. Today we witness the spread of new technologies which are mobile, situationally aware, adaptive and
in communication with other intelligent machines. Intelligent machines are now “on the move” as never before – from
self-driving cars to drones – and are making and remaking

xxii

Preface

networked connections and communications at often rapid
speed around the world.
8 Technological innovations and scientific discoveries are
dramatically advancing the scope and intensity of AI across
societies, economies, polities and cultures. This next phase
of development – from edible surgical robots to military
micro-drones – involves very high levels of uncertainty.
The key question for us today is whether our societies can
tolerate the uncertainty of the culture of AI, react creatively
to it and become more open towards constantly evolving
digital transformation.
Some remarks should perhaps be noted about the nature and
scope of these arguments. The central emphasis of this book is
upon providing an interpretation of the culture of AI, both its
embedding in everyday life and transformations of modern institutions. AI has its origins in geopolitics, which at the same time it
has impacted and transformed. AI constantly interlaces with the
nation-state, the contemporary phase of globalization and global
politics. In the sphere of geopolitics, the main narrative for AI
has been about power – the power to shape the worldwide race in
AI-driven economic growth, as well as research and development
initiatives to remain globally competitive. Innovation underpinned by monetary investment and public policy initiatives lies
at the core of the digital revolution. Globally the most important
AI hubs are in Silicon Valley, New York, Boston, London, Beijing
and Shenzhen.11 In terms of national investment in AI, for example, the UK has committed $1.3 billion over 10 years and France
$1.8 billion over five years, and the EU estimates a total public
investment of $20 billion by 2030 and China calculates it will
spend $209 billion by 2030. Small wonder that some estimates
of productivity-driven economic growth conclude that AI could
contribute approximately $16 trillion to the global economy by
2030.12 Throughout this book I try to trace out the direction of
movement of such transformations in AI, but I make no claim
to develop an exhaustive analysis of the geopolitics of AI, nor of
variations among nations in today’s world.13

INTRODUCTION

INTRODUCTIONINTRODUCTION

Like many a supposedly contemporary phenomenon, artificial
intelligence (AI) is in fact an ancient invention.1 As a cultural
ideal, it first emerged during the Hellenistic period – which is
to say, it was an idea that pervaded ancient Greece as an urge (in
the words of one commentator) to “forge the Gods”.2 The idea
of intelligent robots and thinking machines crops up in Greek
myths such as Talos of Crete, and humanoid automatons were
crafted by artificer Yan Shi and presented to King Mu of Zhou.3
The classical epoch saw the appearance of mechanical men and
other automatons as designed by the Greek engineer Hero of
Alexandria, and for a polymath like Ismail al-Jazari only a programmable orchestra of mechanical automatons could sustain
legitimately scientific inquiry as set out in his programmatic The
Book of Knowledge of Ingenious Mechanical Devices.4 Kevin LaGrandeur holds that artificial slaves can be traced as far back as Book
XVIII of Homer’s Iliad, and also underscores Aristotle’s lengthy
treatment of artificial slaves in his Politics as foundational.5
The arrival of the early modern period in Europe ushered in
less eye-catching brands of AI, with Rene Descartes comparing
the bodies of animals to complex machines. For political theorists like Thomas Hobbes, only a mechanical theory of cognition could adequately grasp the contours of human reason. The

2

Introduction

French philosopher Blaise Pascal set about inventing a mechanical calculator, and along the way this remarkable mathematician developed some fifty prototypes and twenty calculating
machines. Gaby Woods, who considers that our anxious fascination with robots can be traced directly to the early modern quest
for mechanical life, discusses Jacques de Vaucanson’s Digesting
Duck (which was a wonderful con) and his mechanical Flute
Player (which actually worked) as symptomatic.6 The wranglings
of the early modern age over mechanical life were, in effect,
dreams of technological promise, which in turn generated the
wish for more technology throughout cultures at large. In the
nineteenth century, artificial beings crop up in various works of
fiction, represented as the nexus of science and society. There is,
say, Victor Frankenstein’s scientific forays into imparting life to
non-living matter in Mary Shelley’s Frankenstein, or the factory
production of robots, cyborgs and androids in Karel Capek’s Rossum’s Universal Robots.
In our own time, artificial intelligence has been largely the
preserve of such disciplines as computer science, mathematics,
information science, linguistics, psychology and neuroscience.
The word “artificial” in this context has come to denote that
machines can be made to replicate or simulate human intelligence, and hence the affinity between artificial intelligence and
digital technologies (including advanced robotics and accelerating automation) which I seek to sketch throughout this book.
The debate over what AI actually is, and what it is not, could
easily merit book-length treatment. Since the mid-1950s when
the American computer scientist John McCarthy, along with
Marvin Minksy, Herbert Simon and Allen Newell, founded the
field of artificial intelligence and organized a legendary academic conference at Dartmouth College in the US, there has
been great controversy over claims that human abilities will be
increasingly replicable by intelligent machines in the future.
Among the central questions have been these. What, specifically,
defines AI? How does AI differ from, say, advanced robotics?
What makes a machine artificially intelligent, as opposed to just

Introduction

3

useful? How might artificial intelligence be disentangled from
organic intelligence? Whilst the debate over what AI actually
is has remained highly contested in the academic discourse of
computer science, information science, semantics, philosophy of
language and mind, and theories of consciousness, the discussion
more broadly in the media and the business community has been
more opportunistic. Here AI has, for the large part, appeared
as a buzzword, a marketing tool to scoop up customer attention and position companies as at the cutting-edge of the newest
technologies. Equally, AI has been conflated with robots, with
the Hollywood dreamscapes of Terminator and Wall-E. “Artificial intelligence”, writes Ian Bogost of the contemporary cultural
debate, “has become meaningless”.7
Although there is a lack of agreement among researchers
about how to characterize the main defining elements of AI and
its related technologies,8 there is some measure of agreement in
the area of public policy and governance. The UK Government’s
2017 “Industrial Strategy White Paper”, for example, defines
AI as “technologies with the ability to perform tasks that would
otherwise require human intelligence, such as visual perception,
speech recognition, and language translation”.9 It is perhaps useful
to begin with such a definition, one geared to state-promoted AI,
if only because such an account is clearly quite narrow, and leaves
unaddressed some of the most important deep drivers of AI. It is
crucially important, for instance, to underscore the intricate interconnections between AI and machine learning. A key condition of
AI, one not captured by the UK Government’s White Paper, is the
capacity to learn from, and adapt to, new information or stimuli.
Among the deep drivers of AI are technological advances in the
networked communications of self-learning and relative autonomy of intelligent machines. These new systems of self-learning,
adaptation and self-governance have helped to reconstitute not
only the debate over what AI actually is, but also impacted the
relationship between artificial and organic intelligence.
While AI generates increasing systems of interconnected selflearning, it does not automatically spawn a common set of human

4

Introduction

reactions or values in terms of those engaging with such technologies. The relation between AI and its technologies, including
particularly people’s experiences or views of AI, is a complicated
one. For the purposes of this study I define AI, and its related
offshoot machine learning, as encompassing any computational
system that can sense its relevant context and react intelligently
to data. Machines might be said to become ‘intelligent’, thus
warranting the badge ‘AI’, when certain degrees of self-learning,
self-awareness and sentience are realized. Intelligent machines
act not only with expertise, but ongoing degrees of reflexivity.
The relation between AI and self-learning can be considered to
operate at a high level when intelligent machines can cope with
the element of surprise. After all, many machine learning algorithms can easily be duped. Broadly speaking, I thus approach AI
in this book as referring to any computational system which can
sense its environment, think, learn and react in response (and
cope with surprises) to such data-sensing.10 AI-related technologies may include both robots and purely digital systems that
employ learning methods such as deep learning, neural networks, pattern recognition (including machine vision and cognition), reinforcement learning and machine decision-making.
Computational learning, adaptation and system improvement
in response to data or stimuli is a common component of artificially intelligent systems. The rise of neural networks, a kind
of machine learning loosely modelled on the structure of the
human brain, consisting of deeply layered processing nodes, has
been especially significant in the spread and efficacy of AI. So
too, deep leaning – a more recent spin-off of neural networks –
which deploys multiple layers of AI to solve complex problems
has underpinned much of the explosion of interest from businesses, media, the finance sector and large-scale corporations.
The essential scientific aspiration, as we will chart throughout
this book, has focused on replicating general intelligence, which
for the most part has been understood largely in terms of reason,
cognition, perception as well as planning, learning and natural language processing. As such, it is not always clear in what
sense the psychological, sexual or private domains might actually

Introduction

5

count for the discourse of artificial intelligence. But one of the
central arguments I develop in this book is that the rise of digital
life (ranging across ubiquitous computing, the Internet of Everything, AI and robotics) is producing a profound transformation
of the relations between the public, political and global on the
one hand and the private, sexual and psychological on the other.
The promises of AI – some fulfilled, others dreams – lie at the
core of this metamorphosis.

The Turing test and after
For most people today, AI denotes chatbots and complex algorithms, not the definitional argumentation of computer scientists. Indeed, some of those who nowadays drop reference to
AI in daily conversation are probably unaware that there exists
a rich scientific and philosophical debate as to whether AI can
replicate human intelligence at all. Computer pioneer Alan
Turing raised the key question “can machines think?” as early
as 1950. Since there was no agreed method or singular test for
determining what constitutes ‘thinking’, Turing instead posed a
thought experiment in which the question of whether scientists
can build a machine that would pass as a human to other humans
was pivotal. Turing called this thought experiment the “imitation game” – an adaptation of a Victorian-style competition – in
which a judge sought to identify the difference between human
and machine contestants. In this game, the judge sits one side of
a computer screen, chatting to mysterious interlocutors on the
other side of the screen. These interlocutors are human beings,
but one of the interlocutors will be a machine, seeking to trick
the judge into thinking that it is a flesh-and-blood person. This
experiment became known as the Turing Test.
The discrepancy between AI as thought experiment and AI
as actuality is one which has played out, sometimes dramatically, over recent decades in assessing the possibility of thinking
machines. As with any test or experiment, there have been various
claims to have passed the Turing Test, as well as many more stories of failure. In 1966, the ELIZA Computer program – which

6

Introduction

replicated the behavior of a psychotherapist – was determined by
some to pass the Turing Test, though this claim was highly contested by others.11 Since that time, AI has been deployed in computer programs which have defeated world champions at chess
and won against contestants on the TV quiz show Jeopardy! AI
has generated software in mobile devices which can converse in
natural language, from Apple’s Siri to Microsoft’s Cortana. There
has also been a dramatic increase in intelligent digital assistants,
especially in-car assistants such as those developed by Toyota,
Hyundai and Tesla. Most recently, Google has released Duplex, a
dazzling AI and voice technology – which not only can reserve a
table at a restaurant or book a haircut, but can chat relatively easily with people on the phone when making such arrangements.
Notwithstanding the significant advances in natural language
processing by data-driven software, the search for machine intelligence remains elusive. The reasons for this are not only technological, but touch on profound issues of what it means to be
human – issues which the social sciences have helped to illuminate. The American philosopher John Searle has provided an
important discussion of this issue. Given the immense complexity of language as experienced in the shifting contexts of everyday
life, Searle argued that it is not possible for computer systems to
think or understand language in the manner that people do. To
demonstrate this, Searle developed what he called the “Chinese
Room Argument”. He sets out this argument as follows:
Imagine a native English speaker who knows no Chinese
locked in a room full of boxes of Chinese symbols (a data
base) together with a book of instructions for manipulating symbols (the program). Imagine that people outside the
room send in other Chinese symbols which, unknown to the
person in the room, are questions in Chinese (the input).
And imagine that by following the instructions in the program the man in the room is able to pass out Chinese symbols which are correct answers to the questions (the output).
The program enables the person in the room to pass the

Introduction

7

Turing Test for understanding Chinese but he does not
understand a word of Chinese.12
The functioning of computer code – and, by implication, any AI
program – is insufficient to achieve an enduring sense of consciousness or intentionality. As Searle summarizes this, “if the
man in the room does not understand Chinese on the basis of
implementing the appropriate program for understanding Chinese then neither does any other digital computer solely on the
basis because no computer, qua computer, has anything the man
does not have”.
Searle developed the Chinese Room Argument to refute functionalist approaches to the mind. Against computational theories of mind which treat understanding as a form of information
processing, Searle was out to show that consciousness or intentionality cannot be ordered independently of our encounters
with external reality. There have been many criticisms levelled
against the Chinese Room Argument, and these have been well
rehearsed in the relevant literatures – so I will not examine them
here.13 The broad conclusion of Searle’s argument – that is, that
understanding is not built up through descriptions of external
reality – is, I think, substantially correct. To know the meaning
of words, as Wittgensteinian philosophy emphasizes, involves
instead being able to use those words as an essential aspect of
the routines of everyday life. Listening to Google’s Duplex chat
on the phone with a waiter whilst booking a restaurant table has
convinced some observers that machine intelligence has finally
arrived. Whether this is so or not, my focus in this book is on a
different, but related issue. This concerns transformations which
AI is ushering into existence around the globe – the AI revolution in talk. Talk ordinarily is produced as conversation between
people. But today talk (and how we produce talk in everyday
life) is changing, and rapidly, thanks to AI. What is talk, viewed
through the lens of AI? Many point to the rise of Siri, Alexa,
Cortana, Ozlo and other chatbots. Rather than focus on AI as a
technological achievement alone, my focus in what follows will

8

Introduction

be on how people use, and react to, these AI systems. Talk is an
increasingly central feature of our daily encounters mediated by
AI – in person-to-machine conversation – though it has been a
neglected aspect of the AI debate.
Throughout this book, I develop a broad interpretation of
AI rather than using narrow methodological definitions which
proliferate within the AI and ML research communities. My
focus is on AI as rooted in everyday life and modern institutions,
and I draw liberally from media reports as well as industry and
business understandings of this phenomenon. I develop this orientation partly in order to scoop up various forms of machine
‘intelligence’ and AI ‘self-learning algorithms’ and to consider
their consequences for social, cultural, economic and political
relations. The book addresses a range of current applications in
AI, robotics and machine learning that already permeate many
aspects of our lives, as well as potential applications that are set to
profoundly transform our personal and professional lives.
What was once a wish has today arguably become a worldwide
reality. The demand for digital technologies to order, reorder and
transform our daily lives seems to know no boundary. Today, AI is
threaded into much of what we do, and increasingly shapes who we
are. Digital technology has been remarkably successful in satisfying
the demands of our high-speed societies. AI creeps more and more
into the fabric of our lives, through technology like check-scanning
machines at ATMs to GPS navigation. What began as philosophical dreaming or experimental science has by now become commonplace, even routine. Today’s technology revolution – from
digitalization 3.0, cloud computing and 3D printing to chatbots,
telerobotics and drones – is one geared to a transformation of the
future. The digital revolution, we are routinely told by technology experts and the media, will change how we live and work in
the decades ahead. Transformed futures are everywhere, and there
is now a large and ever-growing industry of specialists thinking
and anticipating how digital technologies will transform how we
act, see, feel, think and talk in the future.14 Such future-orientated
orientations to possible worlds unlocked by artificial intelligence

Introduction

9

are, again, hardly new. From Isaac Asimov’s I, Robot to Arthur C.
Clarke’s 2001: A Space Odyssey, portraits of the future have strongly
overlapped with the worlds of artificial intelligence and robotics.
But the future, as morphed by new technologies, has most definitely arrived. Technology futures – whilst hugely contested and
saturated with conflicting socio-economic interests – are remolding
the here-and-now of contemporary societies and as never before.
AI is not simply ‘external’, or merely an ‘out there’ technology. AI cuts to the core of our lives, deeply influencing and
restructuring social relations and personal identity. The complex
ways in which people interact with new technologies fundamentally reshapes the further development of those very technologies. One of the central distinguishing features of advanced AI
and associated new digital technologies is that the boundaries
between humans and machines have – to a considerable extent –
dissolved, which in turn promotes ever-growing opportunities
for human-AI interaction in diverse robotic ecosystems. Today’s
proliferation of human-machine interfaces have deep implications for the way we work, how we live, how we socialize and
interact with others, and many other aspects of our personal and
professional lives. For example, it is more and more evident that
we will be unlikely to interact with most intelligent systems in the
future through keyboards and mice – natural language is already
making headlines as a game-changing technology for personal
assistant devices, yet is still very much in its infancy. An increasing number of consumer devices have recently appeared on the
market that dispense altogether with conventional interfaces,
such as Amazon’s Alexa and Google’s Home. Instances of other
novel interfaces include augmented and virtual reality, interactive holograms, consumer-level EEG, RFID implantation,
computational mood analysis and prediction, and wearables.15
Emerging interfaces have been demonstrated in research laboratories, yet remain some years away from widespread commercialization. These include immersive haptics, implantable EEG
or ECG, multi-function implants (the beginnings of cyborgs),
human augmentation and exoskeletons.

10 Introduction

From self-driving cars to space robots: disruptive
technology and the digital universe
Consider these three instances – selected somewhat randomly
from recent media reports – of technological innovations and
scientific breakthroughs transforming social, economic, cultural
and political life. First, consider self-driving cars. Rapid progress
in the autonomization of mobility systems, as well as big data
for the modelling of traffic behavior, has given rise to claims
that driverless vehicles will soon be the future of road transportation. Perhaps nowhere more so have the prospects of future
making been closely tied to cultural expectations on technology
and science than the advent of driverless cars. As it happens and
notwithstanding that many experts predict that full adoption of
autonomous vehicles will not occur until the 2030s,16 the age of
AI has rendered the future already here, with many autonomous
vehicles – from self-driving cars to robot lorries – already on the
world’s roads and highways. Technology giants from Google to
Uber, along with automotive manufacturers such as Tesla, GM,
Volvo, Daimler, Ford, Jaguar, Audi and BMW, have been developing self-driving vehicles. Many self-driving vehicles are small,
compact cars; but other self-driving technologies have involved
innovations in autonomous trucks as well as public transport
shuttles. A self-driving electric shuttle bus, WePod, was successfully trialled on Dutch public roads in early 2016; this was followed in July 2016 by an automated bus capable of carrying up to
12 people, the Easymile EZ-10 electric mini-bus, which carried
commuters alongside rush-hour traffic in Helsinki, Finland. Trialling the future of road transportation has also been conducted
with many other self-driving vehicles, including self-driving cars
on public roads in California, Florida, Nevada and Michigan in
the US since 2012 as well as driverless trucks at the port of Rotterdam and automated lorries on the M6 in the UK.17
As a narrative, the future making of self-driving vehicles
involves not only powerful technologies (from advanced sensors
to computer vision systems) but the controlled management of
mobility. Future making and future transport thus interweave

Introduction

11

through innovations in camera technology, GPS, accelerometers
and gyroscopes when coupled to transportation development
blueprints and the commercialization of driverless technology.18
The roll-out of driverless vehicles for the advancement of public transport in the UK illustrates this well, as reported by New
Scientist:
London [will] become one of the first cities in the world to
have driverless vehicles. The number and exact routes they
will take have still to be decided, but a few months from now
you will be able to jump into an autonomous pod and be ferried to your destination along public roads. . . . This is the
beginning of a revolution in transport, as the cars roll out
slowly in small pilots in urban areas. In the UK, Greenwich,
Milton Keynes, Coventry and Bristol will lead the way. Similar projects are happening in other cities around the world,
including Singapore; Austin, Texas; Mountain View in California; and Ann Arbor in Michigan.19
In 2017, autonomous pods commenced operating from Heathrow Airport and there were associated roll-outs across south-east
London.20 Various personal and cultural benefits were underscored for consumers, from watching movies to getting on with
work on these autonomous passenger-ferrying pods. Engineers
were quick to emphasize the improved safety of autonomous
vehicles,21 and policy planners have stressed the social benefits
of assisting less mobile people to move around the city.22 Most
recently, however, the argument in favor of self-driving vehicles
suffered a massive blow after an autonomous car operated by
Uber – and with an emergency backup driver behind the wheel –
struck and killed a woman in the United States.23 This was a stark
reminder of the new risk parameters stemming from AI, with
some commentators suggesting that such risks are now an unavoidable part of our contemporary experience.
Second, let’s turn to 3D printing. The scientific trajectory of
3D printing and its consolidation has been marked by strong
technological innovation and commercial investment, along

12 Introduction

with surging demand for rapid prototyping. 3D printing has
opened the way for a process of manufacture which is “additive”,
involving the building up of products layer by layer. This contrasts sharply with industrial manufacturing that was “subtractive”, and involved for example the cutting, welding or drilling
of metal or timber or other materials. The worldwide media
attention accorded to 3D printing as a form of “desktop manufacturing”, involving the possible spread of such technologies in
offices, homes, stores and workshops, largely centered on new
innovations in the local design and production of products. But,
in assessing the promises of 3D printing against the risks, a range
of controversies have raged regarding the extent to which the
mass adoption of 3D printing would disrupt existing systems of
industrial and post-industrial manufacture as well as create new
challenges for the global economy.24 Carrying a future making
promise similar to that of self-driving vehicles, such controversy
has been to some large degree undercut by current trends in
global manufacturing and world trade where products are already
3D printed. As Thomas Birtchnell and John Urry point out, 3D
printing is already used in many industrial processes in automotive and aerospace manufacture, luxury product accessories,
medical and health applications (from the printing of prosthetics
to organic transplants), as well as retail and service products.25
A rapidly future-orientated convergence of 3D printing and
traditional construction, backed by evolving desktop manufacturing technologies, created media waves in China in the 2010s
with the printing of houses. One might well have been excused
for thinking that this was science fiction; however, the design
and manufacture of houses in China through software packages
and 3D printers unfolded rapidly and dramatically. As one media
report summarized these developments:
A 3D-printed printed house has been built in just three
hours in one of China’s capital cities. The individual modules
of a dining room, kitchen, bathroom and bedrooms were
assembled by Chinese developer Zhuoda Group on a site in
Xi’an earlier this month.26

Introduction

13

Apart from the speed of construction, these 3D houses were
remarkably inexpensive to build and were made from environmentally friendly materials. Most recently, this type of innovation
has been further developed in China by a company printing 10
houses every day. Such technology, it has been emphasized, ushers
in a whole new world in real estate, where consumers will be able
to update and print new house extensions as and when desired.
Third, one of the most astonishing deployments of ‘disruptive technology’ over recent years has been in space exploration. It is now over 50 years ago that the iconic science-fiction
film 2001: A Space Odyssey portrayed HAL 9000, a sentient AI
computer that killed many of the crew on the Discovery One
spacecraft. 2001: A Space Odyssey is still highly relevant today,
as a commentary on fears about new technologies and anxieties evoked by AI and robotics. Such worries, however, have
not clouded the outlook of many agencies introducing robotics and advanced artificial intelligence into spacecraft exploration. Since 2012, dexterous humanoids such as NASA’s
Robonaut and the University of Tokyo’s Kirobo have been sent
to assist astronauts on board the International Space Station
(ISS). More recently, airbus and IBM have developed CIMON
(Crew Interactive MObile CompanioN), a floating robot with
Watson AI technology. Referred to by researchers as the first
‘flying brain’ in space, CIMON sports an advanced AI neural
network of facial and voice recognition technology, and can
support astronauts in performing routine work as a “genuine
colleague” on board the ISS. Or take Valkyrie, a 6ft 2in, 275
pound humanoid space robot. Developed by NASA’s Johnson
Space Center for future space missions to Mars, Valkyrie will
be sent ahead to establish base camps and life-support systems
until human astronauts arrive.27 To do this, Valkyrie has been
fitted with the most sophisticated sensing, computing and
mobility technology – including two Intel core i7 computers,
lasers, hazard cameras, actuators and a multi-sense camera on
the robot’s head.
So what do these instances of changing digitalization and
advanced AI tell us about our world? With rapid advances in

14 Introduction

technology intersecting with social relations in unpredictable
ways, what about the opportunities of AI, robotics and advanced
automation and also the anxieties evoked by such innovation?
From self-driving vehicles to 3D printing to advanced space
robotics, much will depend on how society reacts to and copes
with the current and future technologies which order and reorder our ways of living and working. As with other AI experiments, it is the social reception of technology and not simply
technology itself which conditions our collective imaginaries and
desirable futures.28 In other words, the outcome of AI innovations cannot be known in advance. What can be said is that the
dream of AI has not only become a worldwide actuality but now
infuses our culture of technological promises. In the software
universe of digital lives, AI has yielded knowledge an informational overlay (with territory now open to virtual intrusion) and
with ever-increasing instrumental-technical dexterity. The fundamental transformation, I argue, is a new protological infrastructure which triggers the contactless contact (communicative, digital,
virtual) operating between people and machines and which converses the machine-to-machine connections which are beginning to dramatically impact on our lives. Nigel Thrift noted as
early as 2014 that “half of internet traffic now comes from nonhuman sources”, underscoring the rise of social bots on computational machines masquerading as flesh-and-blood human
agents.29 Economist Brian Arthur calls this the new “second
economy” of intelligent, automatic machines.30 As Arthur tells
the story of this software-driven automation, the most advanced
technology “is running an awful lot of the economy. It’s helping architects design buildings, it’s tracking sales and inventory,
getting goods from here to there, executing trades and banking operations, controlling manufacturing equipment, making
design calculations, billing clients, navigating aircraft, helping
diagnose patients and guiding laparoscopic surgeries”. This is
undeniably accurate, but the cases described by Arthur only hint
at the watershed-like social, cultural and political changes in the
development of digital technologies and AI. These changes are

Introduction

15

not only economic, but fundamentally impact the human condition and social relations. Digital technologies and AI engender new models of identity and personhood, social relationships,
family and friendship formation, gender and sexuality as well as
power imbalances alongside its lightning-speed delivery of big
data, self-referential calculations, sentient environments, location tagging, complex algorithms, sensors and robots.

The arguments of this book
The social impacts of robotics and AI, its current development
and future institutional forms, have emerged as fundamental
issues for the social sciences in the twenty-first century. The connections between social science and the emergence of technological automation in the workplace and society more broadly have
long been recognized. Indeed, a good deal of nineteenth- and
twentieth-century social science had been devoted to mapping
these connections, especially the intricate ties between technological automation and industrialization (and subsequently postindustrialization). Yet in the present day, we see not only that
new digital technologies are merging the physical, biological and
digital worlds in ways not previously anticipated, but that robotics
and AI are increasingly networked, mobile and global. That is to
say, we are witnessing a new kind of technological transformation
which is unlike anything previously realized – especially when
viewed as converging with developments in biotechnology and
nanotechnology. What is new is not only the speed, breadth and
depth of digital innovation and change, but also the connected
nature of our interactions with others and everyday objects. From
this angle, the Internet of Things – in bringing together people,
processes, data and things – is generative of techno-landscapes
comprising self-aware devices which can sense, interact and analyze data from other devices whilst “on the move”. The consequences of these transformations are extraordinary, and require a
rethinking of the nature of modernity which must go hand in hand
with a reworking of certain basic premises of the social sciences.

16 Introduction

Contemporary life differs from previous forms of social
organization not only in its degree of technological dynamism
(radically transforming both time and space), but also in its
interlacing of the physical, communicative, digital and virtual
spheres. Consider, for example, the globe’s cybersphere. Over
three billion people are today online, which represents almost
half of the world’s population.31 In 2016, the Internet-based
economy reached $US4.2 trillion in the G-20 economies.32 If the
Internet-based economy were a national economy, it would rank
behind only the US, China, Japan and India. Across the G-20,
this new high-tech economy already contributes to over 4% of
gross domestic product. It is the projected growth of the globe’s
cybersphere, however, which is most staggering. By 2030 it is
estimated that there will be 125 billion inter-connected devices
operating worldwide.
No matter how far-reaching these changes may be for our
professional and personal lives, however, this is only the tip of
the iceberg as regards the technological tsunami sweeping the
globe. For whilst people are connecting to the Internet as never
before, so too are machines – and in staggering numbers. Hightech electric cars, TVs, computers, fridges – more and more, the
appliances and devices we use in daily life have the capacity to
communicate autonomously with other machines. Smart homebased devices have in large part attracted the bulk of media attention, yet it is in industry and the public services sector – ranging
across retail, services, smart buildings and smart grid applications – where the large bulk of growth in connected devices will
occur. Contemporary life increasingly consists of a merging of
social and digital networks of interaction – with devices and software systems (operational via the Internet) producing, receiving
and analyzing data. Some government estimates forecast that, by
2020, there may be 50 billion machines connected to the Internet
globally.33 Some other commentators have gone as far as putting
the figure at over 200 billion devices. Clearly, the real revolution
is an explosion in the Internet of Things, which is fast emerging
as the Internet of Everything.

Introduction

17

This book is not intended as an addition to the mounting
number of technical studies of digital technologies, robotics
and AI. Instead, my aim is to trace the contours of these sociotechnological transformations, and to explore some of their
consequences for the world in which we live today. In general,
I try to set the study of digital technologies in what I hope is a
rather more original context, one which is grounded in social
theory. This is a work of theory and sociology, couched in an
appropriately analytical style. In seeking to insert digital technologies, robotics and AI into social theory, I am aiming to challenge the current evasions and displacements of mainstream
social science treatments of the topic, especially in economics,
political science and social policy. For much of the contribution from these disciplines has damagingly neglected certain
developments – of social relations, identity and personal life,
mobility, violence – which have accompanied transformations
in digital technologies. Thus, I try to identify in this book some
structuring features at the core of digital technologies – and
especially in robotics and AI – which are interwoven in complex
ways with a number of other transformations in society, culture
and politics.
The opening chapter sketches the broad parameters of the
digital revolution, and its penetration into daily life through the
impact of big data, supercomputers, robotics and artificial intelligence. Developing a theme which will inform the whole of this
book, I shall be concerned to underscore the gradual expansion
of networks of digital technology, and to try to show how robotics and AI have become pervasive features of social relations and
social organization which are increasingly global in scope. I try
to identify some of the structuring features at the core of the
digital revolution which interact with transformations of the self
and social interaction. I also introduce the reader to notions that
will form the key focus of this book: the rise of digital technologies; the digital transformation of social interaction; the reinvention of processes of self-formation; and, the reshaping of the
boundaries of public and private life.

18 Introduction

Drawing on the theoretical precepts elaborated in the first
chapter, Chapter 2 shifts the analysis to a focus on technological automation in the workplace. There I develop an account
of the main transformations influencing work, employment
and unemployment associated with the rise of technological
automation and digital technologies. I examine the globalizing
tendencies of modernity as deeply interwoven with the spread
of capitalism and technological automation, focusing on Karl
Marx’s classic account of technological automation as serving the development of capitalism and its continual changing,
expanding and transforming of itself. From Marx’s account of
capitalism as substituting machines for human labor, the chapter
shifts to contemporary debates on how today’s world is being
reshaped by automated technology as well as the consequences
of technological innovation for employment and unemployment. New automated technologies spawned by robotics and
artificial intelligence loom large in this connection, and I critically review the recent contributions of – amongst others – Erik
Brynjolfsson and Andrew McAfee, Martin Ford, Jeremy Rifkin,
Martin Ford and Nicholas Carr.34 In conditions of advanced AI
and intensive digitalization, the importance of digital literacy in
order to participate in economy and society becomes more and
more commonplace.
The development of digital technologies, and especially the
rise of robotics and AI, is not (as I stressed earlier) an ‘out-there’
phenomenon, as if technologies operate with straightforward
given properties and causal effects upon institutions, organizations and networks. Technologies, on the contrary, are always
mediated through social relations, entangled in our everyday
ways of doing things and the living of lives. If digital technologies transfigure institutions, they also reach profoundly into
individual identities. The digital is both around us and inside
us. In our age of self-cultivation, where do-it-yourself identity construction and reconstruction is all the rage, this implies
that digital technologies, robotics and AI become raw materials
for the production and performance of the self. Chapter 3 is

Introduction

19

concerned to explore some of the ways in which the development of digital technologies enter into self-actualization and
the daily lives of individuals. Here I focus on the recent work
of Sherry Turkle, particularly her thesis that new technology
produces an enforced solitude, as a foil to develop an alternative standpoint. I argue, pace Turkle, that new technology creates both new opportunities and new burdens for the self. From
the use of iPhones to Fitbit, and from AI-powered predictive
analytics to smart personal assistants, the production of the self
has become increasingly interwoven with digital technologies.
Digital technologies and AI innovations, as I argue at length,
are transforming what self-formation and self-experience actually mean.
A central argument of this book is that the robotics revolution and AI impact upon not only work, employment and unemployment, but also social relationships in the broadest sense. We
can adequately grasp the social impact of robotics and AI only
if we question the general notion that digital technologies leave
relations between people essentially unaltered. On the contrary,
I try to demonstrate in this book that the use of digital technologies, robotics and AI necessarily involves the development of
new forms of social interaction, new kinds of social relationships
and new ways of experiencing and performing our identities. In
conditions of advanced automation, robotics and AI, the influence of digitally mediated materials on social relationships, and
on personal intimacies of the self, become more pronounced.
Social media, cloud computing and digital communication more
broadly plays a central role in this respect. But so too do smart
products, services and devices, 3D printing, intelligent ecosystems, virtual reality, augmented reality, and supercomputer
algorithms. In a fundamental way, this informational overlay of
contemporary societies reorients social life away from face-to-face
interaction which has traditionally characterized social organization and generates new forms of digitally mediated interaction which transforms our basic coordinates of time and space.
With the development of digital technologies, particularly AI, a

20 Introduction

revised interlacing of self-organization and social interaction, up
to and including the global electronic economy, becomes more
and more commonplace.
In Chapter 4 I explore those features of social interaction
which have become increasingly bound up with digital technologies, and of associated technological transformations unfolding
across social relationships and society more generally. From the
use of SMS to social media, and from Internet apps to chatbots, individuals today increasingly navigate daily life and social
interaction through the informational overlays of touchscreens,
virtual landscapes, location tagging, and augmented realities.
Such navigations routinely take individuals away from physical
face-to-face co-presence and into the digital terrain of mediated, online interaction. But as I try to show, it is a mistake to
separate off our online and offline worlds. We must see, instead,
that interactions of communication, whilst flowing across digital
platforms, impact directly upon and restructure existing social
settings – as people are busy texting, emailing or posting status
updates at business meetings, on trains or during regular catchups with friends. In order to best grasp these transformations in
technology and social interaction, I draw in this chapter from
the sociological insights of Erving Goffman. Examining Goffman’s celebrated notion of the “action framework”, I analyze
how digital technologies, robotics and AI are impacting upon
social encounters, framing and co-presence. The interactive
framework spawned by digital technologies brings with it major
transformations in space and time which increasingly frees individuals from the restrictions of traditional social mores and the
physical movement of their bodies. This creates new possibilities for digital social interaction, but there are also significant
burdens impacting upon the professional and personal lives of
women and men.
Robotics and AI are very different from previous forms of
technological automation, partly because recent technologies have heralded robots equipped with self-learning abilities, action initiatives and the capacity for deep learning. That

Introduction

21

is to say, robotics is characterized by data-driven computing
rather than instruction-driven computing. This quantum leap
in machine intelligence has emerged through exponentially
growing quantities of data and processing power together with
the development of complex algorithms, leading to new capacities for self-organization, sense-making, insight extracting,
and problem solving. Advances in cloud computing, machineto-machine communications and the Internet of Things have
simultaneously developed incredibly rapidly, faster than previous technologies and with huge mobility consequences for
how we live increasingly mobile lives as well as for enterprises
and institutions.
These converging digital technologies are transforming many
aspects of economic, social and cultural life that are in some
sense mobilized or “on the move”. Where conventional automated machines were fixed in place and programmed for specific
repetitive tasks, the new technologies are mobile, situationally
aware and can adapt to and communicate with their environment. In a world of intensive digitalization, the rise and rise of
machine-generated data is especially consequential, with the
overall volume of communications increasingly written by automated machines, using data and analytical information which
has been converted into natural language. Travel, transport and
tourism more generally play a fundamental role in the mobilization of digital technologies, and in Chapter 5 I turn to consider
how machine-based tech is increasingly “on the move”, making
and remaking communications, connections and networks at
often rapid speed around the world. From Uber to self-driving
cars, from collaborative robotics in logistics to transport robots,
the emergence of what might be termed “mobility robotics” has
moved center-stage on many industry and policy agendas.
In the final chapter of the book I take a look ahead, focusing on
advances in AI, robotics and machine learning in terms of social
futures. Here I outline some of the main parameters of how new
digital technologies are transforming intimacy, gender and selfactualization; healthcare and AI as a framework for the redesign

22 Introduction

of medicine; and, the transformation of democratic politics in
the wake of the digital revolution. Thinking social futures in the
light of advanced artificial intelligence demands fresh thinking,
and forces us to confront how the globalizing tendencies of AI
are transforming day-to-day social life and the fabric of our personal lives.

1
THE DIGITAL UNIVERSE

THE DIGITAL UNIVERSETHE DIGITAL UNIVERSE

Zoe Flood, a well-known journalist writing in The Guardian,
recently summed up advances in unmanned aerial vehicles
(UAVs) thus: “Some are killing machines. Others are pesky passions of the weekend hobbyist. As such, drones have not always
been welcomed in our skies”.1 A critical observer might say that
drones are all this and much more, especially since many people
are increasingly held in thrall to those UAVs deployed in the service of the retail and service sectors.2 All sorts of contradictions
and ambiguities can be at identified in this respect. The very
same people who protest about the militarization of drones may
also want to order books through Amazon, which plans future
dispatches by UAVs. Drones not only have noxious uses but promote the dehumanization of bodies into targets – for identification in service delivery, for remote monitoring in surveillance,
and for destruction in war. There has also been growing public
concern where drones have flown near commercial planes at airports worldwide, and in 2017 a Canadian charter skyjet was hit
by a drone (without incident) as it prepared to land at Quebec
City’s Jean Lesage International Airport.3
The social impact of drones has to be understood against a
wide institutional backdrop. UAVs, for example, have the potential to radically diminish barriers to access for countless medical

24 The digital universe

services and critical medicines to save lives, and on a scale not
previously realizable.4 This is a socio-technological development with major global significance, and one that is radically
transforming underdeveloped countries too. Consider the following example. In Rwanda, where travel between towns and
villages in the rainy season is particularly fraught with danger,
drones are now in use to deliver blood, vaccines and other urgent
supplies to provide nationwide delivery of medical services.5
The Rwandan government signed a contract with Zipline, a
California-based robotics company, for fixed-wing drones to
deliver medical essentials to rural health facilities across its landlocked state. In 2016, the Rwandan government also announced
the location for the world’s first droneport, designed by celebrated British architect Norman Foster.6 It is envisioned that
various robotics start-up companies will develop services operating across a national network of droneports in Rwanda. Most
significantly, the Rwandan droneport is not an isolated development. Drones are increasingly in use, both commercial and
otherwise, in many other countries. In South Africa, Peru, Guyana, Papua New Guinea and the Dominican Republic, UAVs are
being used for health deliveries and other humanitarian emergencies. In the Democratic Republic of the Congo, the UN has
deployed drones as part of their general peacekeeping program.
And in the rich North, UAV advocates argue that drones will
soon become mainstream in potential commercial uses from
retail delivery to medical supplies, and from building construction analysis to infrastructure inspection.
But there are other consequences too, and many involve huge
risks. Advances in machine-learning algorithms for the guiding
of military drone programs is one powerful indication of how
new technology contributes to the perpetration of violence
and war. The United States, for example, has used unmanned
drones to attack militants in Pakistan and Afghanistan; however, the very same U.S. drone program has killed thousands of
innocent people, having wrongly targeted numerous innocent
civilians, according to some reports.7 And then there is the case

The digital universe

25

of a new drone which French and British military contractors
have developed for use by the Royal Air Force, with autonomous
capabilities for selecting and engaging targets using AI. This is
the Taranis drone, named after the Celtic god of thunder. The
financial investment in the development of this unmanned combat system, which aims to provide autonomous drones by 2030,
is estimated at over $US2 billion. Under current international
law, autonomous combat systems such as military drones require
human operators to fire on targets.8 But whether military violence or war could be conducted entirely by machines remains
an open possibility, and the production of drones such as Taranis
suggests that autonomous military drones might become a reality in the future. Certainly, the possibility of fully autonomous
weapons systems is a topic of great debate, and with huge implications for global politics, military defence and humanitarian
issues.
On the face of it, AI-based drones are contested and saturated with different socio-economic interests, and this is perhaps nowhere more evident than in relation to military drones.
There are serious concerns about the kinds of threats autonomous combat systems might pose to the future of humanity. But
at this point we need to recognize that the rise of AI in society
is double-edged. There is no easy way in advance of identifying
how new technologies based on autonomous systems and adaptation to the environment will play out. There are certainly some
stunning opportunities, with the potential to drastically reduce
poverty, disease and war. But so too the risks are enormous, and
this can be clearly discerned from the IT arms race, the development of autonomous weapons systems and other fundamental
threats. Moreover, the assessment of risk here must involve not
only direct but also indirect threats. An example of the latter
kind of high-consequence risk is that of insurgent groups tapping into communication satellites and aerial drone camera feeds
in order to hack into military drones.
In this opening chapter, I shall not offer an analysis of
the opportunities and risks arising in relation to social and

26 The digital universe

technological systems. Instead, I focus on the complex systems
which power and sustain digital life itself. I begin with the complexity debate and consider how new technologies are folded
into social relations, ranging from smart grids and cloud infrastructures to the legions of algorithms, sensors and robots that
infuse everyday life. I shall concentrate my attention on trying to
define the distinctive characteristics of complex digital systems,
both as key to the production of our professional and personal
lives and as integral to the world’s future as a whole. I shall then
look at some innovative attempts to conceptualize emergent
intersections between technology and society – not only computational forms, but also developments in AI and robotics. I argue
that the development of digital life creates new forms of action,
interaction and social structure which depend upon the performance of digital identities on the one hand and the reproduction
and transformation of digital systems on the other. In outlining
and drawing upon various traditions of contemporary social and
cultural theory, I contend that transformations in complex digital systems (mobile apps, bots, technological automation, smart
cities, the Internet of Things) occur at the intersection where
ways of life and digital skills become deeply layered as everyday
occurrences.

Complex digital systems
The flow of human action and the production of cultural practices takes place today in the context of complex, powerful technological and social systems that stretch across time and space.
In speaking of the systematic properties of technology and society, I mean their ordering features, giving a certain degree of
‘solidity’ to social practices which are self-organizing, adaptive
and evolving. From this angle, technical and social systems are
by definition emergent, dynamic and open. Yet such systems
are never ‘solid’ in the sense that they are stable or unchanging.
Complex technological and social systems, including the conditions of systems reproduction, are characterized by unpredictability, non-linearity and reversal. The ordering and reordering

The digital universe

27

of systems, structures and networks, as developed in complexity theory, is highly dynamic, processual and unpredictable; the
impact of positive and negative feedback loops shift systems away
from states of equilibrium.9 Drawing from advances in complexity theory, historical sociology and social theory, I shall argue
that a grounded, theoretically informed account of the digitization of technological and social systems must be based on seven
sets of considerations. These complex, overlapping connections
between technological systems and digital life can be analyzed
and critiqued from the sociological considerations I now detail.
First, there is the sheer scale of systems of digitization, of technological automation and of social relations threaded through
artificial intelligence – all being key global enablers of the digital
data economy. Over 3 billion people – almost half the world’s
population – are online, and digital interactions increasingly
impact upon even those who find themselves with limited digital
resources.10 Complex computerized systems of digitization make
possible (and are increasingly interwoven with) the production
and performance of social life – of business, leisure, consumerism, travel, governance and so on. These systems – of computing databases, codes of software, Wi-Fi, Bluetooth, RFID, GPS
and other technologies – make possible our everyday networked
interactions, from search engine enquiries to online shopping to
social media. These systems facilitate predictable and relatively
routine pathways of digitization which underpin smartphone
social interactions, online banking, music streaming, status
updates, blogs, vlogs and related actions of searching, retrieval
and tagging spawned by the Internet. Systems of digitization
enable repetition. In the contemporary world of digital life, these
systems include social media, CCTV, credit cards, laptops, tablets, wearable computers, URLs (Uniform Resource Locators),
smartphones, email, SMS, satellites, computer algorithms, location tagging and so on. The complex, interdependent systems of
digitization flourishing today are the “flow architectures” that
increasingly order and reorder social relations, production, consumption, communications, travel and transport, and surveillance around the world.11

28 The digital universe

In addition to the rapid spread of systems of digitalization, the
scaling up of robotics is hugely significant throughout much of
the world. Industrial robots transforming manufacturing – from
packaging and testing to assembling minute electronics – are the
fastest growing source of robotic technologies. From the early
1960s when one of the first industrial robots was operationalized in a candy factory in Ontario through to the 2010s where
new technologies facilitated robots working hand-in-hand with
workers, there has been a growing expansion in robotics and the
number of published patents on robotics technology. The number of industrial robots in the USA jumped from 200 in 1970
to 5,500 in 1981 to 90,000 in 2001.12 In 2015, the number of
industrial robots sold worldwide was nearly 250,000; industrial
robotics is an industry which annually enjoys global growth of
approximately 10%. Automotive and electronics have been the
major industry sectors for robotics use, but many other sectors
are increasingly adopting robotics and technological automation.
Robotics coupled with converging mobile technologies are especially transforming industry in Asia, which has dominated the
ramp-up of robotics use, with China being the primary contributor. But demand for greater productivity, mass customization,
miniaturization and shorter product life cycles has also driven
growth for robotics worldwide, especially in Japan, Germany,
Korea and the USA.
Second, digital systems should not be viewed as simply products of the contemporary but in part depend upon technological systems which have developed at earlier historical periods.
“Many old technologies”, writes John Urry, “do not simply disappear but survive through path-dependent relationships, combining with the ‘new’ in a reconfigured and unpredicted cluster.
An interesting example of this has been the enduring importance
of the ‘technology’ of paper even within ‘high-tech’ offices”.13
Thus, the development and exploitation of digital technologies
are interwoven in complex ways with multiple pre-digital technological systems. Another way of putting this point is to say
that our wireless world is interdependent with a range of wired

The digital universe

29

technologies. Many of the wired technologies – the wires, cables
and connections of pre-digital systems – which intersect with
digital technologies of Wi-Fi, Bluetooth and RFID date from the
1830s, 1840s and 1850s. There occurred in this historical period
an astonishing range of experiments with systems of electrical
energy for the purposes of communication. Systems dating from
that period based upon the communication potential of electricity include electromagnetic telegraphy (which was trialled in
England, Germany and the United States in the 1830s), the first
viable telegraph line between Washington and Baltimore (constructed by Morse in 1843 with funds from the US Congress),
the successful laying of early submarine cables across the English
Channel and between England and Ireland in 1851–2 (with a
transatlantic cable successfully laid the following decade), and
the discovery of the electric voice-operated telephone (demonstrated in 1854 by Antonio Mecucci in New York), although it
was some decades later that Alexander Graham Bell conceived
the idea for the telephone as a communication system.14
Subsequent to this period, the twentieth century witnessed a
vast array of technological systems emerge and develop. Broadcasting systems – radio from the 1920s, television from the
1940s – were pervasive and hugely consequential for social transformations associated with mass communications. In the 1960s,
the launching of the world’s first geo-stationary communications
satellites spelt the arrival of near-instantaneous communication
on a global level. Around this time, other technological systems –
from personal computing to mobile telephony – underwent early
development too. The interlinked, tangled dynamics of these
‘systems’, of which most people are largely unaware as they go
about their everyday social activities, is of key importance. Individuals will not necessarily know, or entertain awareness of, the
conditions, scale or impact of such complex systems since these
different technologies fuse and enrich each other.
Third, whilst the emergence of complex communication networks coincided with the advent of industrialization, it was only
in the late twentieth century and early twenty-first century that

30 The digital universe

digital communication technologies and networks were systematically established on a global scale. In this connection, the
exceptional significance of various technological transitions that
occurred between 1989 and 2007 should be underscored. While
digital technologies have progressively developed across time,
1989 is a key moment in the constitution of digital life. For this
was the year that Tim Berners-Lee invented the World Wide
Web through the technological innovations of URL, HTML
and HTTP. (The Web did not become readily accessible to
people, however, until 1994). 1989 is also significant because
Soviet Communism collapsed. According to Manuel Castells,
this occurred because of Russia’s failure to develop new information technologies.15 Also, in this year, global financial markets
were increasingly integrated through instantaneous communications and online real-time trading. Also, mobile telephony was
launched, initially through Nokia and Vodafone, through the
breakthroughs of GSM (global system for mobile communications). In 1991, the first GSM phone call was made with a Nokia
device through the Finnish network Radilinja.
As the computing technology–inspired 1990s turned into the
social media–driven 2000s, the sheer technological brilliance of
digitization seemed all the more striking. For this next decade
ushered in a range of platforms, apps and devices, along with the
digital transformation of society. In 2001, iTunes and Wikipedia commenced operation. There were also new commercialized
forms of social media. LinkedIn was rolled out in 2003, Facebook in 2004, YouTube and Flickr in 2005, and Twitter in 2006.
The point, seemingly, was less to apply the digital to everyday
life, and instead to secure one’s social niche within the field of
the digital. In 2007, smartphones arrived on the market. This
was followed by the introduction of tablets in 2010. With the
arrival of the 2010s, and such additional platforms as Instagram,
Spotify, Google+ and Uber, culture and society was coming to
mean status updates, SMS, posts, blogs, tagging, GPS and virtual
reality. Digital technologies were transforming social life.
Fourth, these various interdependent systems are today everywhere transferring, coding, sorting and resorting digital

The digital universe

31

information (more or less) instantaneously across global networks. With systems of digitization and technological automation, information processing becomes the pervasive architecture
of our densely networked environments. As society becomes
informationalized as never before, digitization emerges as the
operating backcloth against which everything is coded, tagged,
scanned and located. Complex automated systems of digital technology emerge as the ‘surround’ to both everyday life and modern institutions. These technological systems seem to usher in
worlds – informational, digital, and virtual – that are generalized;
that is, these technologies are increasingly diffused throughout
contemporary systems of activity and take on the appearance
of a functionality which is “wall-to-wall”. Today’s independent, informational systems of digitization are, to invoke Adam
Greenfield, both “everywhere and everyware”.16 From GPS to
RFID tagging, and from augmented reality to the Internet of
Things, these various interdependent systems are the architectural surround or operational backcloth through which airport
doors automatically open, credit card transactions are enabled,
SMS is enacted, and big data is accessed. As Greenfield contends,
this increasingly pervasive digital surround scoops up “all of the
power of a densely networked environment, but refining its perceptible signs until they disappear into the things we do every
day”.17
To invoke the possibility of disappearance in this context, as
Greenfield does, is to raise the question of the hidden and the
invisible as concerns systems of digitalization. Digital life inaugurates a transformation in the nature of invisibility – operationalized through supercomputers, big data, and artificial
intelligence – and the changing relation between the visible, the
hidden and power. My argument is that the rise of systems of
digital technology in the late twentieth and early twenty-first
centuries has created a new form of invisibility which is linked
to the characteristics of software code, computer algorithms
and AI protocols and to its modes of information processing.
The invisibility created by digital technologies is that of a protocological infrastructure which orders and reorders the many

32 The digital universe

connectivities, calculations, authorizations, registrations, taggings, uploads, downloads and transmissions infusing everyday
life. Codes, algorithms and protocols are the invisible surround
which facilitates our communications with others and our sharing with others of personal data through the array of devices
and apps and wearable technologies and self-tracking tools
which monitor, measure and record people’s personal data. The
development of Wi-Fi, Bluetooth, RFID, and other novel technologies of artificial intelligence has thus created a new form of
sociality, based on a distinctive kind of invisibility, which touches
on and tracks identities and bodies and constitutes and reorders
our social interactions through ubiquitous contactless technologies. But the digital field is, of course, much more extensive in
scope, enabling also smart objects (or, anti-wearables) and other
digital data-gathering technologies. Many objects and environments have been rendered ‘smart’ through embedded sensors,
interactive visualizations and digital dashboards – again, with an
invisible protological infrastructure and the kinds of social relations spawned by it, touching upon the operations of shopping
centers, airports, road toll systems, schools and many more.
Fifth, these systems which are ordering and reordering digital
life are becoming more complex, and increasingly complicated.
This growing complexity has powered the rise of ubiquitous
computing and AI, and has been underpinned by exponential
rates of technological and associated social transformations.
‘Moore’s Law’ has been the guiding maxim of innovation since
the mid-1960s, and refers to the so-called doubling of computing
power every two years. Computing power is based on the number of transistors in an integrated circuit; and against the backdrop of ever-shrinking computer circuits, engineers have been
able to fit exponentially more onto microchips. This has made
computers more complex, powerful and cheaper: it is estimated
that a smartphone, for example, possesses the computer power
previously available only in large mainframe computers. More
recently, reports from various technology companies – such as
Samsung and Intel – have suggested that beyond 2021 it may not

The digital universe

33

be feasible to shrink transistors any smaller.18 The limits to technological miniaturization has thus propelled a debate on whether
Moore’s Law has reached an end point;19 some analysts argue
that quantum computing will provide the new route forward for
the continued expansion of computing processing power. And
many people believe that ubiquitous computing and AI, when
viewed in the context of convergence with nanotechnology,
biotechnology and information science, will continue to propel
exponential rates of technological complexity, socio-economic
innovation and social transformation. Certainly the ubiquity of
digital technology, and especially complexity in AI and robotics,
involves multimodal informational traffic flows, which in turn
substantially depends on technical specialization and complex
expert systems.
Sixth, complex systems and technological infrastructures are
not just ‘out there’ processes or happenings, but are condensed
in social relationships and the fabric of peoples’ lives. That is to
say, complex digital systems generate new forms of social relations as well as reshape processes of self-formation and personal
identity. Complex computerized systems, for example, ‘bend’
social relations towards the short-term, the fragmentary and the
episodic – based upon computational interplays of connection
and disconnection. ‘Life on the screen’ (to invoke Sherry Turkle)
appears to unfold faster and faster in the early decades of the
twenty-first century, as people ‘life-splice’ the threads of professional, business, family and leisure zones together – using multiple devices across diverse digital platforms. As I try to show in
Chapter 4, digital technologies are intricately interwoven with
the trend towards DIY, individualized life-strategies, where people are busy using devices, apps and bots to schedule and reschedule their everyday lives and experiments with digital life. Systems
of digital technology increasingly wrap the self in experiences of
“instantaneous time”, and the individualized work of constituting and reinventing digital identities is built out of instantaneous
computer clicks of ‘search’, ‘cut-and-paste’, ‘erase’, ‘delete’ and
‘cancel’.

34 The digital universe

Web-based digital technologies play a constitutive role in
social relations today, facilitating digitally downloadable and
transferable files containing apps and bots which power the
smart-devices that people use “on the move”. Over 100 billion
apps have been downloaded from the Apple App Store alone
since 2008,20 and over 75% of all smartphone users deploy some
kind of messaging app – from Facebook Messenger to WeChat to
Viber. The instantaneous, just-in-time culture of Apps has been
a primary conduit through which the great bulk of people in the
rich North now communicate, work and socialize. The arrival of
the 2020s, however, promises a wholesale shift of social relations
into even more accelerated web-based digital technologies, and
specifically the rise of mobile chatbots. This is part of a growing
shift to conversational computing, where language is the new
user interface which people use for calling upon their digital
assistants for booking a hotel room or ordering a pizza. There is
already a large online source network of efficient and intelligent
bots available for download, and in Chapter 4 I examine how the
spread of mobile chatbots is reshaping social relationships both
now and into the future.
Seventh, the technological changes stimulated by the advent
of complex digital systems involve processes of transformation
of surveillance and power quite distinct from anything occurring
previously. The expansion of surveillance capabilities is a central
medium of the control of social activities – especially the control
over the spacing and timing of human activities – arising from
the deployment of digital technologies to watch, observe, record,
track and trace human subjects. From one angle, complex digital
systems might be said to have ushered into existence a digital
observatory of greatly increased surveillance, somewhat akin to
George Orwell’s account of Big Brother and Newspeak. Ubiquitous CCTV in public spaces, data mining software, RFID chips
in passports and identity cards, automated software systems governing transport and the speed of vehicles, and the migration of
biometric security into various organizational settings: a whole
variety of convergent developments has unfolded dramatically

The digital universe

35

extending the scope of digital surveillance. It is evident that digital monitoring of the activities of citizens and the observing of
the online and smartphone interactions of individuals has been
undertaken by a gr