How to Run a City Like Amazon, and Other Fables

Full text

Edited by Mark Graham, Rob Kitchin,
Shannon Mattern and Joe Shaw
Meatspace Press
HOW TO
RUN A
CITY LIKE
AMAZON,
AND
OTHER
FABLES

HOW TO RUN
A CITY LIKE
AMAZON, AND
OTHER FABLES
Edited by
Mark Graham, Rob Kitchin,
Shannon Mattern and Joe Shaw
Meatspace Press

How to Run a City Like Amazon, and Other Fables
Edited by Mark Graham, Rob Kitchin,
Shannon Mat tern and Joe Shaw
Publisher: Meatspace Press (2019)
Weblink: meatspacepress.com
Design: Carlos Romo-Melgar and John Philip Sage
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Length: 350 pages
Language: English
ISBN (paperback): 978-0-9955776-7-1
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License: Creative Commons BY-NC-SA
Contributors (alphabetically): Manuel B. Aalbers, Tooran Alizadeh,
James Ash, Sarah Barns, Gavin Brown, Ryan Burns, Matthew Claudel,
Jeremy W. Crampton, Ayona Datta, Martin Dodge, Leighton Evans,
Jessica Foley, Jennifer Gabrys, Mark Graham, Tony H. Grubesic,
Edward Helderop, Kara C. Hoover, Andrew Iliadis, Kurt Iveson,
Glenn Kaufmann, Rob Kitchin, Agnieszka Leszczynski, Sophia Maalsen,
Shannon Mat tern, Harvey J. Miller, Cian O'Callaghan, Nancy Odendaal,
Dietmar Offenhuber, Alison Powell, Lizzie Richardson, Gillian Rose,
Jathan Sadowski, Kalpana Shankar, Joe Shaw, Harrison Smith,
Monica Stephens, Linnet Taylor, Jim Thatcher, Pip Thornton,
Anthony Vanky, Alberto Vanolo, Alan Wiig, Katharine Willis, Matthew Zook.
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AMA ZON
How to Run a City Like Amazon
Mark Graham, Rob Kitchin, Shannon Mattern and Joe Shaw
ACXIOM
You’re Entitled to What the Data
Says You Deserve
Rob Kitchin
ALPHABET
City of Loops
Mark Graham
ANT FINANCIAL
I_am_the_score_machine
Jathan Sadowski
APPLE
Welcome to Jobstown
Sophia Maalsen and Kurt Iveson
BITCOIN
Cryps, Chains and Cranks
Matthew Zook
CAMBRIDGE ANALYTICA
The Unseen
Jeremy Crampton and Kara C. Hoover
DELIVEROO
Too Much Fulfilment
Lizzie Richardson
DISNEY
The Most Magical Place on Earth
Anthony Vanky
EAS YJET
EasyCity
Manuel Aalbers
1
13
101
145
177
205
234
266
289
330

ELSEVIER
The Civic Method
Matthew Claudel
ETHEREUM
Registering Eve
Alison Powell
GOOGLE ADWORDS
Subprime Language and the Crash
Pip Thornton
GOOGLE ARLens
Seeing the City through Google’s Eyes
Leighton Evans
GOOGLE FIBER
There Is No Such a Thing
as Free infrastructure
Tooran Alizadeh, Edward Helderop and Tony Grubesic
GRINDR
Being Xtra in Grindr City
Gavin Brown
GROUNDTRUTH
Monetizing Movement
Harrison Smith
IKEA
Flat-pack Smart Urbanism
Martin Dodge
IN STAGRAM
A City of Digital Engagement
Ryan Burns
PALINTIR
Save the Shire™
Jennifer Gabyrs
446
475
504
529
539
553
570
606
622
654

PINTEREST
Curating a City
Gillian Rose
PORNHUB
Premium Places
Dietmar Offenhuber
SHOTSPOTTER
Safe andSecure Living in Camden
Alan Wiig
SIDEWALK LABS
So You Want to Live in a Pivot City?
Sarah Barns
SIRI
The Semantic City
Andrew Iliadis
SNAPCHAT
Youthful Indiscretions
Monica Stephens
SONY PLAYSTATION
Playmentalities
Alberto Vanolo
SPOTIFY
Streamers
Cian O’Callaghan
STA RBU C KS
Potholes and Pumpkin Spice
Kalpana Shankar and Glenn Kaufmann
STR AVA
The Strive City of Tomorrow
Katharine Willis
676
706
725
749
787
872
941
955
1035
110 0

TAKEALOT
The Allure of the Frictionless City
Nancy Odendaal
TESLA
Cities Need Mass Transit
Harvey Miller
TINDER
Swipe Right to Welcome,
Left to Reject
Linnet Taylor
TWITTER
Seeking Follows
James Ash
UBER
The Seduction of UberCity
Agnieszka Leszczynski and Rob Kitchin
VODAFONE
The Col and the Black-Outs
Jessica Foley
WHAT3WORDS
Address.Error.503
Jim Thatcher
WH AT SAP P
A City of the People, for the People,
by the People
Ayona D atta
YCOM B I NATO R
Let’s Make this City an Urban
Product Everybody Wants
Shannon Mattern
1114
112 3
113 9
1161
1179
119 6
1245
1295
1337

HOW TO RUN
A CITY LIKE
AMAZON
Mark Graham, University of Oxford
Rob Kitchin, Maynooth University
Shannon Mattern, The New School
Joe Shaw, University of Oxford
In an article to promote their new book—
‘A New City O/S’—Stephen Goldsmith (a for-
mer Mayor of Indianapolis and Deputy May-
or of New York) and Neil Kleiman (Director of
the NYU/Wagner Innovation Labs) contend
that cities should act more like Amazon to
better serve their citizens.
1
They argue that
cities will be more efficient and productive
if they become data-driven, using analytics
and machine learning to parse data about
citizens and city services/infrastructure into
insights that provide a responsive, tailored ex-
perience. Just as Amazon’s online shopping
platform provides a means to order everything
1 Link: https://nextcity.org/daily/entry/cities-should-act-more-
like-amazon-to- better-serve-their-citizens
1

a household might need and deliver individ-
ually-specific recommendations, a city ad-
ministration can function as a marketplace
for services and be accessed through a single
point of entry. The complex systems archi-
tecture that would enable this ‘friction-free
experience’ would also provide a means for
the administration to manage itself.
At first sight, Goldsmith and Klei-
man’s argument seems appealing—who
doesn’t want to live in a more efficient and re-
sponsive city? On reflection, however, the arti-
cle prompts some critical questions. Goldsmith
and Kleiman are not simply using Amazon’s
systems architecture and business model as
a metaphor for how cities might be run. Rather
they are promoting the twin ideas that cities
should be run like businesses and city services
and infrastructure should be run by business-
es. In a city ‘run like a business’, the ethos and
logic of city government shifts from a bureau-
cracy serving citizens for the common good,
to a technocracy that adopts business models
and practices to serve individual consumers.
In a city ‘run by businesses’ the provision of
services and essential infrastructure transfers
from public to private delivery.
2

Both ideas have gained much trac-
tion over the last half century and form key te-
nets of urban neoliberalism, in which there is
a transformation from the practices of urban
managerialism to urban entrepreneurialism.
That is, there is a shift from city administrations
that manage an urban commons and seek
to deliver services and infrastructure largely
through their own endeavours, to cities that
compete with one another for resources and
investment, and services and infrastructure are
opened up to market forces through deregula-
tion, outsourcing, public-private partnerships,
and privatisation. Here, the city is no longer the
place that enables markets to function, but the
city itself—its components and its administra-
tion—become a collection of markets.
This translation from public to pri-
vate, from managerialism to entrepreneurial-
ism, has been driven by arguments from the
Right that city administrations are inefficient,
wasteful, and lack sufficient knowledge and
expertise for managing systems in an increas-
ingly complex world, and competition between
private suppliers produces value for money, in-
novation and choice. In turn, the move towards
entrepreneurial approaches alters the mode of
3
4

urban governmentality (the rationality, practic-
es and techniques through which people are
governed) and the nature of citizenship. Here,
there is a shift from citizens having defined civ-
il, social and political rights and entitlements,
who are disciplined to act in prescribed ways,
to consumers with autonomy to choose from
a suite of public service options dependent on
desire and budget, who gain rights through act-
ing responsibly, and are nudged to act in the in-
terests of state and capital. What little changes
are the underlying notions of stewardship (for
citizens) and civic paternalism (deciding what’s
best for citizens) in how states and companies
view their relationship with residents with re-
spect to how cities are run.
The latest phase of urban entre-
preneurialism is the attempt to produce smart
cities; that is, to use digital, networked tech-
nology to manage cities and deliver urban ser-
vices and utilities. Technologies such as urban
control rooms, city operating systems, urban
dashboards and performance management
systems, sensor networks, smart grids, and
intelligent transport systems, it is argued, will
break-down internal administrative silos, pro-
duce better coordination, and leverage insight
5

and value from data to produce more effective
and efficient delivery of services. They will
also improve security, safety and quality of
life, and create improved resilience and en-
vironmental sustainability. The new markets
created will foster local innovation, economic
development and entrepreneurship. Further,
shared economy platforms and thousands of
urban-living apps are already transforming
services such as taxis, tourist accommoda-
tion, housing, food distribution, work space,
and indeed how work is organized and un-
dertaken. Smart technologies are explicitly
designed to be disruptive innovations; that
is, to radically transform how established ac-
tivities are organised and performed. For the
corporations who develop them, the aim is to
disrupt how the state operates and to create
a new market for their products and services,
or to disrupt existing market actors.
As many critics have argued, the
neoliberalisation of city governance and the
creation of smart cities raises a whole series
of social, political and ethical questions. These
include concerns about profit being placed
before people and the environment, widening
inequalities between citizens, a loss of rights,
6

and the erosion of democracy, fairness, jus-
tice and accountability, the privatisation of
public assets and corporatization of surveil-
lance, the application of predictive profiling
and social sorting to deliver differentiated ser-
vices, and a transfer of risk and liability from
the private to public sector. In turn this raises
normative questions about what kind of city do
we want to live in? Do we really want to reside
in cities run like or by businesses?
It is these questions that this book
explores. Our challenge to the contributing
authors was to imagine what cities might be
like if they were run using the technologies,
business models, and ethos of specific com-
panies. In other words, we asked them to ex-
tend Goldsmith and Kleiman’s thesis beyond
Amazon to consider how the city might be
governed and experienced, the consequenc-
es to citizens if the city was run by or in con-
junction with Uber, Disney, Twitter, Tinder,
Ikea, and so on. We gave authors free-rein
to select any company they wished as long
as we avoided duplicates, with most select-
ing tech companies, many of which produce
smart city technologies.
7

Many companies are actively in-
volved in partnering with cities or are deliv-
ering urban services, though others simply
serve urban consumers. In every case, other
similar companies could have been chosen,
and the selections are designed to provide a
thought experiment or grounded discussion of
urban entrepreneurship. In the cases where
product or corporate names may be trade-
marks they are only used for the purpose of
conducting a thought experiment or identifica-
tion and explanation without intent to infringe.
We also gave authors the choice
of writing a short piece of speculative fiction
or a more conventional academic-style pa-
per, or a combination of the two, to illuminate
their thoughts. The majority of authors chose
the speculative fiction approach, most adopt
-
ing a science fiction framing, with the story
set in the near future.
As scholars of science fiction have
long noted, the genre is a powerful and engag-
ing medium because it uses extrapolation and
speculation to explore possible worlds and to
encourage the reader to reflect on how those
worlds came into being, how they operate, and
8
9
10

how they differ from and reflect our present
world. As such, they use the tactics of es-
trangement (pushing a reader outside of what
they comfortably know) and defamiliarisation
(making the familiar strange) as a way of creat-
ing a distancing mirror on society and to offer
cognitive spaces to reconsider assumptions,
rationales and viewpoints. In our cases, the
stories seek to be plausible and consistent
given existing technologies, business mod-
els, trends, news coverage and academic cri-
tique, though sometimes they push the logic,
ethos, and the form and use of technology
to an extreme to emphasize a point; they are
sometimes satirical, sardonic and playful. They
are designed to prompt critical thought about
contemporary neoliberal urbanism and digital,
networked technologies.
The result is a set of 38 stories
and essays that explore how a city might look,
feel and function, and the effects on society,
economy and politics if different business
models, practices and technologies are ap-
plied to the running of cities. Collectively, the
essays suggest there are good reasons to be
cautious about transforming public assets
and services run for the common good into
11

markets that are run for profit, and in applying
a range of disruptive innovations to civic ad-
ministration and infrastructure that ideally are
stable, reliable and risk adverse. Ultimately,
they ask us to question whether we really do
want cities to be run like or by businesses, and
thus what kinds of cities we want to create
and occupy. And that is the challenge we set
for readers: to use the stories and essays to
answer these questions for themselves.
Acknowledgements
Rob’s contribution to this ch apter and to editing the book as a w hole was un-
dertaken as part of The Programmable City project funded by the European
Research C ouncil (ERC-2012-AdG 3236 36-SOFTCI TY). Funding towards
the publication of the book was provided by Maynooth University. Mark
wishes to acknowledge the Leverhulme Prize (PLP-2016-155), ESRC (ES/
S00081X/1), and European Research Council (ERC-2013-StG335716-
GeoNet) for sup porting his work. Bot h Joe and Mark are grateful for a ddition-
al support received towards this publication from the Alan Turing Institute,
Oxford Internet Institute and the University of Ox ford.
12

YOU’RE
ENTITLED TO
WHAT THE
DATA SAYS YOU
DESERVE
ACXIOM1
Rob Kitchin, Maynooth University
‘Mr Connors? My name is Ms Smith,
I’m a data officer for the city. Please
take a seat. Normally we conduct all
citizen interaction via internet channels
or our premium number service.’
Connors slumped into a plastic
chair. ‘I’ve tried that and I didn’t get
anywhere.’
‘Yes, fourteen times, for a total of four
hours, thirty two minutes and twenty
three seconds. You became quite
abusive on five of those occasions.’
1 The followin g speculative fiction i s a thought experiment
that imagine s a future where a city admini stration uses a
data broker an d their services to ma ke decisions regardin g
the provisio n of services. Suc h a thought experiment cou ld
equally app ly for other data brokers su ch as ChoicePoint,
Experi an and Equifax, many of whom al ready provide
servic es to state bodies. Prod uct or corporate name s may
be trademarks or registered trademarks, and are used only
for the purpo se of conducting a thoug ht experiment without
intent to infringe.
13
15

‘Have you any idea how frustrating
your customer service system is?’
‘We deal in facts, Mr Connors, not
sentiment. Your behaviour has been
flagged in your citizen profile. Now, you
seem to think that you are not receiving
the services due to you?’
‘And what do those flags mean
exactly?’ Connors asked, ignoring
the question.
‘Think of them as like penalty points
on your driver’s license. Once you
get to ten, your service choices are
constrained for three years.’
‘Constrained to what exactly?’
‘To a more limited service pack and in
some cases you’re denied services,
for example being able to meet a city
representative or to apply for city-
supported housing.’
‘But that’s not ethical or democratic.
It’s your job to serve citizens.’
‘It’s our job to help run the city as
efficiently and effectively as possible.
And how else are we expected to
make citizens act responsibly? Good
behaviour is rewarded, poor behaviour
penalised. Now, your complaint?’
20

‘So I continue to pay my taxes, but
I receive no or limited service?’
Connors persisted.
‘Those taxes are an investment in
the city as whole, Mr Connors, not
simply yourself. And your contributions
are quite modest. Indeed, a large
proportion of your sales tax leaves the
state through internet shopping.’
‘How do you know that?’
‘From your citizen profile. It contains
all your data. All your interactions with
public administration offices, your
social media use, your movements,
your work performance, your
purchases, and so on. Our data
partner is very thorough in this regard.
It amalgams our data with those it
acquires through its other partners and
uses them to evaluate each citizen and
guide our services and relationships
with them. I assume you’re aware that
you’re going to be deducted $500 for
failing to meet your fitness quota?’
‘That’s one of the things I wanted to talk
to you about.’
‘The use of a fitness tracker is part of
your work contract as a teacher, Mr
Connors. It’s designed to help you
become more responsible for your
personal health.’
25

‘But it has no bearing on my
performance as a teacher. If I teach the
hours, I should be paid the wage.’
‘Your teaching metrics are pretty
average, to be honest Mr Connors, and
the prediction analytics show they’re
unlikely to improve. That’ll mean a
performance related salary deduction,
plus two points on your citizen profile.’
‘This is a farce! What kind of a hair-
brained system is this?’
‘It’s not a farce. It’s a meritocracy
based on facts and analytics. Citizens
wanted a fairer way to proportion
services and we have delivered it using
tried and tested techniques within the
data broker industry.’
‘You call this ... this data system fairer?
It actively discriminates!’
‘But on the basis of merit. And there are
a range of service choices available to
you. What can be fairer than that?’
‘Choices? Is there any real difference
between utility providers, or schools,
or waste management companies, or
hospital services?’
‘Is that a rhetorical question, Mr
Connors? Your school competes for
students based on its objective ranking
35
30

of reputation and selects students
based on their grades and predicted
future profile.’
‘Yes, and it’s madness! All kids should
be entitled to a good education at a
school within cycling distance.’
‘That’s out-dated idealism, Mr
Connors. People are entitled to what
the data says they deserve.’
40
45
.:;
The two men glanced at the street nervously. Crime
in the area had been on an upward tick for a couple
of years. The installation of a real-time crime center
with an array of high definition cameras and military-
style response units had made little difference.
‘Are you ready?’ the middle-aged man
in a suit asked.
‘Yes, Sir,’ the young man replied,
twisting his shoulders inside the body
armour, his hand already on his gun.
‘Okay, let’s go meet Bryan Jenkins.’
The two men entered the apartment block, climbing to
the second floor and stopping outside a door in need
of a fresh coat of paint. The elder man knocked and
stepped back.
A few seconds later it was opened by a skinny man
in his early thirties. ‘Yeh?’

‘Are you Bryan Jenkins?’
‘Yeh, who’s asking?’
‘I’m Mr Jones. This is Mr Popowski.
We’re from the City Authority.’
‘You’ve come about my re-housing
application?’
‘In a manner of speaking, yes.
Can we come in?’
‘Not really, man. It’s crowded in here.
No privacy.’
‘Well, Mr Jenkins, our system is
flagging up that you’re a housing risk
and this is likely to be realised in the
next 12 to 24 months.’
‘I’m a housing risk?’
‘Yes, you’re consistently late with
payments. You make little contribution
to the local community and you’re
flagged as a credit and tenancy risk
in your citizen profile. Which is why
your re-housing application has been
refused. We’re also serving notice on
your present tenancy.’
‘What? What you talking about man?
We pay our rent!’
50
55

‘Yes, but you’re often late and our
analytics predict that you’re going to
start missing payments shortly. The
city needs this apartment for more
deserving citizens.’
‘More deserving citizens?’
‘The data shows that you are a low net
contributor to the city in terms of work,
taxes and legal consumption. You live
precariously. Your credit rating is very
poor. You have had several brushes with
the law and you’ve a number of active
flags in your citizen profile. There are
people who contribute more, who have
better metrics. And our analytics tell us
yours are only likely to fall.’
‘This is bullshit, man! What, you have a
crystal ball now in City Hall?’
‘Please, Mr Jenkins, there’s no need to
lose your temper. But yes, we have a
crystal ball. Or rather our data partners
can produce an accurate assessment
of your current status and a prediction
of your future circumstances based on
all the data they hold about you from
different sources. We’re not the only
organisation to use their services; they
also calculate insurance premiums,
decide who gets what targeted ads,
help private landlords assess potential
tenants, and help companies vet who
should get offered a job.’
60

‘But I’m not actually behind with my
rent right now, am I?’
‘I’m afraid you’re three days late. This
is the third month in a row you’ve
been late. In that sense you’re a risk
to the City and there are others on the
housing waiting list who deserve city-
supported housing.’
‘So, you’re going to evict us because
of what some bullshit algorithm thinks
might happen?’
‘That’s one way of looking at it.’
‘One way! It’s the only way. I’ve a wife
and three kids. Where are we meant
to go?’
‘That is your issue, Mr Jenkins. There
are a wide variety of other housing
options in the city from short term and
long-term private rental through to
home ownership.’
‘And homelessness!’
‘We don’t tolerate homelessness,
Mr Jenkins.’
‘Well, I don’t want to tolerate it either,
you Jackass!’
‘Please, Mr Jenkins ...’
65
70

‘How do I see how you’ve calculated my
future?’ Jenkins asked, reining in his fury.
‘Your citizen profile is free to examine.
You just need to register on the City
website. However, the underlying
databases and algorithms are not open
to scrutiny.’
‘What? So they can make decisions
about me and my family but I can’t see
on what basis?’
‘The service is provided by a private
contractor using proprietary data
systems and software. We just receive
updates to the citizen profiles and the
suggested courses of action.’
‘So, how do I challenge the decision?’
‘Well, you can appeal to the City’s data
office, and they’ll refer it to our data
partner for assessment.’
‘So, it’s just one giant black box then?
Pay the organ grinder and you get
what you get?’
‘I don’t make the rules, Mr Jenkins. I’m
just asked to enforce them.’
.;:
‘The Mayor’s Citizen Relationship
team, my name is Joanna; how may I
help you, Mr Fitzgerald?’
75
80

‘Well ... how did you know who
was calling?’
‘Our system is configured to show us
the name of all our mostly highly valued
citizens, Sir.’
‘Oh! Right. Very good. I was calling
about McCarthy Avenue. Several
potholes have developed over the
winter and I was wondering if they
could be filled?’
‘Let me see.’ Joanna tapped away at
her keyboard. ‘Yes, Mr Fitzgerald, I
can schedule that work as your area
exceeds the investment quota criteria.
It should be completed within 24 hours.’
‘Wonderful, but if you don’t mind me
asking what’s an investment quota?’
‘Not at all, Sir. Based on the citizen
profiles of people living in an area,
and the net contributions to the city in
terms of taxes, job and wealth creation,
and community development, the
city allocates an investment fund to
conduct repairs and to improve the
area’s amenities, and to also set the
scheduling.’
‘So poorer neighbours get less
investment?’
‘Yes, in line with their net contribution
and profile.’
85

‘And what they do get is less timely
in delivery?’
‘Exactly! We reward our most valued
citizens first.’
‘But it’s the poorer neighbourhoods that
need proportionally more investment to
help them address their problems and
to improve the area.’
‘But they’re also more of a long-term
risk with respect to dollars invested
being wasted. As a city we’ve
adopted the practices of the data
broker industry, seeking to identify
and preferentially target higher value
citizens as they contribute the most
to making our great city even greater!
By investing in them, opportunities will
trickle down to everyone else.’
‘I guess that makes sense. I think.’
‘In fact, Mr Fitzgerald, I see from your
profile that you and your company have
been partners in property development
in the regeneration zone. The city will
shortly be seeking tenders for work in
the next phase of the project. Our data
partners are confident that there will be
a very healthy return on investment. I
could send you an advance pack about
the opportunities.’
‘That sounds interesting, thanks.
Where’s the next phase located?’
90
95

Rob Kitchin i s a Professor in the Depar tment of
Geography and Maynooth University Social Sciences
Institute. Hi s research focuses o n the relationship
between te chnology and socie ty, espe cially related
to the creatio n of smart cities, and he i s the principle
investigator for the Programmable City project and the
Building City Dashboards project.
‘Next to the old barracks on Cable
Street.’
‘But isn’t that the site of the small
trader’s market?’
‘The city is in the process of
addressing that issue, Mr Fitzgerald.
The traders have been offered a new
site off of Union Street.’
‘Hardly as good a spot.’
‘No, but our data partners predict that
most will survive the move and the
city will get much more value from the
regeneration of the old barracks site.
We can’t stop progress, Mr Fitzgerald,
can we?’
100
Acknowledgement
This chapter is an output of The Programmable City project funded by the
European Research Council (ERC-2012-AdG 323636-SOFTCITY).

CITY OF LOOPS
ALPHABET1
Mark Graham, University of Oxford
May 25, 2024. Augmented Berlin. Sixth loop from the Datum.
First meeting of the Un⍴latform S



ociet y.
GregoꞂ shielded his screen from the fierce pink midday
sunlight with his webbed hands, creating a temporary
shadow on his device. It was time to start the meeting.
Bodily transformations, like webbed hands,
were one of the many advantages of life in Alphabet
Corporation’s Looped Web (LW). The LW was a mix
of immersive, geo-sensitive, virtual augmented city
layers that could be accessed through full-body tanks
in which people would be hooked up to all manner of
neuro-nodes and sensors, nutro powder to keep the
meatspace body sustained for a few days, and the
newly-discovered long-lasting dissociative hallucino-
genic 2CQ. The first few prototypes were created by
advanced autonomous AI systems communicating
with each other in a language only they understood.
Nobody fully comprehended how they worked—not
even the original engineers themselves. In the initial
months, people were in awe of the first loop. A whole
new augmented society was created: cities and towns
that existed over-layered on top of the old ones. It was
1 The followin g speculative fiction im agines a future where
a large, diver se platform has thoro ughly permeated
everyday life . Such a thought experime nt applies for other
large intern et platforms such as Fac ebook, Yandex or
Weibo. Produc t or corporate names may b e trademarks
or register ed trademarks, and are u sed only for for the
purpose of c onducting a thought exp eriment without intent
to infringe.
101
102

virtual reality, but somehow very real. People started
living dual existences in meatspace and the LW.
But then someone had the idea to access the
LW from within the LW. That’s when the consensual
hallucinations started getting weird. Each loop was a
shared experience amongst each of its participants,
and each loop was mostly a replica of the augmentation
before it.
2
In other words, each loop was simply a world
built on top of the world beneath it. London’s Trafalgar
Square was full of tourists taking photos of Nelson’s
Column in every loop. But, every loop further away from
the datum also contained glitches that were amplifi-
cations and exaggerations of elements from the inner
loops. The deeper dreams were worlds full of odd phe-
nomena. Transparent skin, music that could be tasted,
liquid buildings, insects made of fur and circuit-boards,
a background hum
3
that got more noticeable in the outer
loops, and all manner of other oddities.
Scholars speculated that even Alphabet’s enor-
mous computing infrastructures couldn’t keep up with
the multitude of minds and spaces that were connect-
ed (not to mention the fact that it needed to create AIs
within AIs within AIs and so on). It therefore had to use
sophisticated modelling techniques to fill in some of
the blanks: techniques that were clearly imperfect,
judging by the ripple effects of some of its glitches by
the time you got to the outer loops.
‘W



elcome Everyone Ꞃ.
The hundreds of glitches, and gabbers present
all shouted greetings back. The background humming
intensified, a pleasant neon pink smell scrambled up
a nearby tree, and everyone quieted down. Speaking
could be a sensory overload out in the sixth loop, and
2 Every trip to th e first loop could last
up to about two d ays in meatspace,
but that same t ime was experienced
as four days in the LW. The ne sted
nature of each l oop meant that each
loop deeper was experienced for an
exponentia lly-longer amount of ti me.
The second loop wou ld take you away
for four days, th e third for 16 days, the
fourth 256 days, the fif th for 65,53 6 days
(179 years), and you are gone for 11
million year s if you venture into the
sixth loop. Physicists theorise that
loops exist b eyond the sixth, but little is
known about them.
3 Scholars r eferred to the hum as sor t
of psychic fee dback loop similar to
the feedba ck that arises when live
microphones are placed near active
speakers. I n the early days, people
used the hum to re mind themselves
where they wer e.
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105

therefore quite distracting—so GregoꞂ went back to
typing in order to communicate with the group.
‘We’ve gathered here to build
a new future!’
He typed as he pumped one of his webbed hands
in the air.
‘

’ rumbled the crowd.
‘I need you all to remember the past so
that we can build our shared future.’
Many in the crowd had been absent from the datum
for tens or even hundreds of thousands of years. But
the Un⍴latform Society hadn’t let this stop it. That was
because it had a simple and appealing idea.
Alphabet ultimately controlled every facet of the
LW, and they subsidised all of the hardware that people
needed to access it. It even offered subsidised nutro
powder and 2CQ in some of the inner loops.
Initially people went in as visitors in order to
see what the fuss was all about. To see what it meant
that somewhere like Berlin could exist in another di
-
mension. To see how life could play out in a world that
looked like a mirror image. Very quickly, the first loop
became a reflection of all manner of human desires
that were illegal, out of reach, or hard to obtain on the
datum. Early loopers still talk about some of the crazy
month-long hypnoraves they had in the fourth loop.
But those seeking escapism would be quickly
disappointed. In order to make the loops family-friendly
107
110
111
112
113

areas, Alphabet implemented a trans-loop crackdown
on adult-themed activities. This was about the time that
looping went mainstream.
The recursive temporality of loops gave way
to a booming economy outside of the datum. Two of
the key constraints to economic expansion—time
and space—had been fundamentally transformed,
and the LW was full of previously unthought of eco-
nomic activity. Because Alphabet was the platform
for all economic transactions throughout the LW, the
small commissions that they took on every transaction
throughout the LW accumulated into enormous profits.
And even though transactions were tiny in some of the
outer loops, the sheer volume of human economic ac-
tivity across all of the loops gave them a captive market
that was expanding at an exponential rate.
However, because the scarcity of time had
been fundamentally transformed, there was a huge
oversupply of labour power within the LW. The creation
of a trans-loop labour market also crashed wages back
on the datum: forcing many people to head into the LW
to look for new ways of generating earnings. People
were willing to work for almost nothing:
4
sometimes
saving up to transfer those remittances back towards
in the inner loops or even the datum, but sometimes
spending the money they made in any of the augment-
ed cities that they made their home. The
fourth
loop, and
sometimes even the fifth, became ever more of a draw
because of the recursive time extensions that they
permitted. The further you went out, the more time you
had to generate value that one day might find its way
home. Then people started venturing into the
sixth
loop...
The problem is, that as minds went deeper and deep-
er into the LW, they sometimes forgot why they went
4 Due to the mass ive oversupply
of labour powe r, along with th e
expansion of t ime and space, the
cost of livin g dropped substantial ly:
meaning that l oopers could
actually subsist on infinitesimally
small wages.
114
116
115

there in the first place. The human mind is simply not
equipped to process thousands of years of memory.
‘The Looped Web should not just be
controlled by one corporation!’ started
GregoꞂ. ‘Alphabet has found a way
of profiting from a now almost-infinite
amount of human lives doing an almost-
infinite amount of human labour. Here
in the sixth, we don’t know how many
worlds, lives, and souls are beyond
us. But we do know that one company
profits from all of it.
How many of you have now resorted to
button entry jobs in the n


a



ľ





a
s








 

l





-sphere?’
A sea of hands, fins, and paws shot into the air.
‘How many of you are collecting points
in VirtuaMinecraft or Civ 12? And this
gave you what? A nano-cent for a few
decades of work!?’
One of the gabbers tightened her jaw and clenched
her paw.
Ꞃ
‘I’ve been out here for many lifetimes,
but has been in the sixth for
longer than most of us. Over two million
years. Right,?’

GregoꞂ thought about telling the crowd about
119
124
125
120
121

the promises of the LW in the early days; the dreams of
a better world that they all once had; and then the reali-
sation that that they were just that: dreams. He consid-
ered talking about how the augmented worlds Alphabet
governed were locked-down, limited societies. They
were created to maximise one thing only: a form of user
engagement that would ultimately lead to revenue gen-
eration. But the crowd knew all of this already.
He took a pause.
‘We can do better.’
This time he took an even longer pause for
dramatic effect.
‘We will do better.
We can rethink the architecture
of the LW!
We can create our digital environments
to maximise happiness, joy, creativity!
The platform should add value to our
lives instead of us creating value for it!
Right now, a small group of people
control the LW.
But we can build a world in which we
own and control our world.
The Un⍴latform Society has therefore de-
cided to build a more free and equitable
126
128
130
135

layer in the LW. Our engineers finished
working on it last week, and it is ready
for use. We’re calling it the communos-
eventh. You are all invited to join us in it.’
Nobody in the assembly had ever really considered go-
ing beyond the
sixth
before. But this was an alluring idea.
‘HꝺW D⬖ ꟿE KNOW TH⡝Š WILL
ꟿshouted someone over the
background hum.
GregoꞂ watched those words spin around as they
slowly melted into the air.
‘Shouldn’t l 

s


i

g


i

 have s tarte 
d this  on the
datuma
ja 

j
, rather than he re on the sixth?’
asked another.
Ꞃ responded, and, from their expressions,
he could see that many in the crowd were already
convinced:
‘Have 
faith in our techn 




ology. Our
engine 
e
rs know what they are d
oing.
Join us ’
With that, GregoꞂ walked towards a nearby building
that housed the Un
⍴
latform Society’s body tanks and
neuro-nodes. Many from the assembly followed.
At some unclear point in the future, GregoꞂ and
the others looked around. But instead of the expected
silence, the humming was now extremely loud. The
sixth was already only a distant memory...
Mark Graham is a professor at Oxford U niversity, a
Visiting Researcher at the Wissenschaftszentrum
Berlin für Sozialforschung (WZB), and the Dire ctor of
the Fairwor k Foundation. His work focu ses on digital
geograph ies and how they both reflec t and reproduce
digital inequalities. His full list of publications is
available at www.markgraham.space
138
136
140
142
143

I_AM_THE_
SCORE_
MACHINE
ANT FINANCIAL1
Jathan Sadowski,
University of Sydney
Created: 1_October_2039
Readme
Ant Financial offers the latest in fintech innovation. An affiliate of
Alibaba, the Chinese e-commerce conglomerate, Ant Financial made its
first $150bn by operating the world’s largest mobile payment ecosystem,
Alipay. Rather than coast on their early success, Ant Financial is always
looking to the future. Based on Alipay’s data collection and analytics
platform, and enhanced by Alibaba’s advancements in artificial
intelligence, Ant Financial created a social credit scoring system
that solves the problem of trust and reputation. With support from the
Chinese government and par tners in the US and Europe, the scoring
system now has billions of daily users worldwide. It is the infrastructure
for ensuring honest relationships. It is the foundation for building a
fair societ y. This file describes the score machine’s operations.
1 The follow ing poem imagines the op erations of social
credit sco ring as devised by Ant Fina ncial for the Chinese
government . Such a thought experim ent could equally apply
to any data broker o r state that is using AI to so cial sort
individual s. Product or corpor ate names may be trademar ks
or register ed trademarks, and are u sed only for the purpos e of
conductin g a thought experiment w ithout intent to infringe.
145

I am the algorithm
I am a refraction of reality
an organiser of society
a processor that’s proprietary
I am a social scoring system
mathematical morality applied
each life simplified, datafied
I am the judge, no jury
an all-knowing actuary
issuing three digit decrees
I am the authority of reputation
preceding people in every situation
accounting the virtue of every action
I am the administer of privilege
putting people in their proper place
granting rights by quantified grace
I am the arbiter of access
opening the world for the trusted
meting out data-driven justice
I am the apex of power/knowledge
my score is bond, beyond bias
beyond reproach, beyond recourse
I am an algorithm governing the city
a ubiquitous score in urban society
deployed by a technology company
150

I am the scored city
I am the ultimate, unified smart urbanism
a city built on colle