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<nettime> Evgeny Morozov: The rise of data and the death of politics
Patrice Riemens on Tue, 22 Jul 2014 17:46:06 +0200 (CEST)


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<nettime> Evgeny Morozov: The rise of data and the death of politics


Original to:
http://www.theguardian.com/technology/2014/jul/20/rise-of-data-death-of-politics-evgeny-morozov-algorithmic-regulation

bwo Kees Stad, with thanks


The rise of data and the death of politics
By Evgeny Morozov
Sunday, July 20, 2014


Tech pioneers in the US are advocating a new data-based approach to
governance -- 'algorithmic regulation'. But if technology provides the
answers to society's problems, what happens to governments?

On 24 August 1965 Gloria Placente, a 34-year-old resident of Queens,
New York, was driving to Orchard Beach in the Bronx. Clad in shorts
and sunglasses, the housewife was looking forward to quiet time at
the beach. But the moment she crossed the Willis Avenue bridge in
her Chevrolet Corvair, Placente was surrounded by a dozen patrolmen.
There were also 125 reporters, eager to witness the launch of New
York police department's Operation Corral -- an acronym for Computer
Oriented Retrieval of Auto Larcenists.

Fifteen months earlier, Placente had driven through a red light and
neglected to answer the summons, an offence that Corral was going to
punish with a heavy dose of techno-Kafkaesque. It worked as follows:
a police car stationed at one end of the bridge radioed the licence
plates of oncoming cars to a teletypist miles away, who fed them to
a Univac 490 computer, an expensive $500,000 toy ($3.5m in today's
dollars) on loan from the Sperry Rand Corporation. The computer
checked the numbers against a database of 110,000 cars that were
either stolen or belonged to known offenders. In case of a match the
teletypist would alert a second patrol car at the bridge's other exit.
It took, on average, just seven seconds.

Compared with the impressive police gear of today -- automatic number
plate recognition, CCTV cameras, GPS trackers -- Operation Corral looks
quaint. And the possibilities for control will only expand. European
officials have considered requiring all cars entering the European
market to feature a built-in mechanism that allows the police to stop
vehicles remotely. Speaking earlier this year, Jim Farley, a senior
Ford executive, acknowledged that "we know everyone who breaks the
law, we know when you're doing it. We have GPS in your car, so we know
what you're doing. By the way, we don't supply that data to anyone."
That last bit didn't sound very reassuring and Farley retracted his
remarks.

As both cars and roads get "smart," they promise nearly perfect,
real-time law enforcement. Instead of waiting for drivers to break
the law, authorities can simply prevent the crime. Thus, a 50-mile
stretch of the A14 between Felixstowe and Rugby is to be equipped with
numerous sensors that would monitor traffic by sending signals to and
from mobile phones in moving vehicles. The telecoms watchdog Ofcom
envisions that such smart roads connected to a centrally controlled
traffic system could automatically impose variable speed limits to
smooth the flow of traffic but also direct the cars "along diverted
routes to avoid the congestion and even [manage] their speed".

Other gadgets -- from smartphones to smart glasses -- promise even more
security and safety. In April, Apple patented technology that deploys
sensors inside the smartphone to analyse if the car is moving and if
the person using the phone is driving; if both conditions are met, it
simply blocks the phone's texting feature. Intel and Ford are working
on Project Mobil -- a face recognition system that, should it fail to
recognise the face of the driver, would not only prevent the car being
started but also send the picture to the car's owner (bad news for
teenagers).

The car is emblematic of transformations in many other domains, from
smart environments for "ambient assisted living" where carpets and
walls detect that someone has fallen, to various masterplans for the
smart city, where municipal services dispatch resources only to those
areas that need them. Thanks to sensors and internet connectivity, the
most banal everyday objects have acquired tremendous power to regulate
behaviour. Even public toilets are ripe for sensor-based optimisation:
the Safeguard Germ Alarm, a smart soap dispenser developed by Procter
& Gamble and used in some public WCs in the Philippines, has sensors
monitoring the doors of each stall. Once you leave the stall, the
alarm starts ringing -- and can only be stopped by a push of the
soap-dispensing button.

In this context, Google's latest plan to push its Android operating
system on to smart watches, smart cars, smart thermostats and, one
suspects, smart everything, looks rather ominous. In the near future,
Google will be the middleman standing between you and your fridge, you
and your car, you and your rubbish bin, allowing the National Security
Agency to satisfy its data addiction in bulk and via a single window.

This "smartification" of everyday life follows a familiar pattern:
there's primary data -- a list of what's in your smart fridge and
your bin -- and metadata -- a log of how often you open either of
these things or when they communicate with one another. Both produce
interesting insights: cue smart mattresses -- one recent model promises
to track respiration and heart rates and how much you move during the
night -- and smart utensils that provide nutritional advice.

In addition to making our lives more efficient, this smart world
also presents us with an exciting political choice. If so much of
our everyday behaviour is already captured, analysed and nudged, why
stick with unempirical approaches to regulation? Why rely on laws
when one has sensors and feedback mechanisms? If policy interventions
are to be -- to use the buzzwords of the day -- "evidence-based" and
"results-oriented," technology is here to help.

This new type of governance has a name: algorithmic regulation. In
as much as Silicon Valley has a political programme, this is it. Tim
O'Reilly, an influential technology publisher, venture capitalist and
ideas man (he is to blame for popularising the term "web 2.0") has
been its most enthusiastic promoter. In a recent essay that lays out
his reasoning, O'Reilly makes an intriguing case for the virtues of
algorithmic regulation -- a case that deserves close scrutiny both for
what it promises policymakers and the simplistic assumptions it makes
about politics, democracy and power.

To see algorithmic regulation at work, look no further than the
spam filter in your email. Instead of confining itself to a narrow
definition of spam, the email filter has its users teach it. Even
Google can't write rules to cover all the ingenious innovations of
professional spammers. What it can do, though, is teach the system
what makes a good rule and spot when it's time to find another rule
for finding a good rule -- and so on. An algorithm can do this, but
it's the constant real-time feedback from its users that allows the
system to counter threats never envisioned by its designers. And it's
not just spam: your bank uses similar methods to spot credit-card
fraud.

In his essay, O'Reilly draws broader philosophical lessons from such
technologies, arguing that they work because they rely on "a deep
understanding of the desired outcome" (spam is bad!) and periodically
check if the algorithms are actually working as expected (are too many
legitimate emails ending up marked as spam?).

O'Reilly presents such technologies as novel and unique -- we are
living through a digital revolution after all -- but the principle
behind "algorithmic regulation" would be familiar to the founders
of cybernetics -- a discipline that, even in its name (it means "the
science of governance") hints at its great regulatory ambitions.
This principle, which allows the system to maintain its stability by
constantly learning and adapting itself to the changing circumstances,
is what the British psychiatrist Ross Ashby, one of the founding
fathers of cybernetics, called "ultrastability".

To illustrate it, Ashby designed the homeostat. This clever device
consisted of four interconnected RAF bomb control units -- mysterious
looking black boxes with lots of knobs and switches -- that were
sensitive to voltage fluctuations. If one unit stopped working
properly -- say, because of an unexpected external disturbance -- the
other three would rewire and regroup themselves, compensating for its
malfunction and keeping the system's overall output stable.

Ashby's homeostat achieved "ultrastability" by always monitoring its
internal state and cleverly redeploying its spare resources.

Like the spam filter, it didn't have to specify all the possible
disturbances -- only the conditions for how and when it must be updated
and redesigned. This is no trivial departure from how the usual
technical systems, with their rigid, if-then rules, operate: suddenly,
there's no need to develop procedures for governing every contingency,
for -- or so one hopes -- algorithms and real-time, immediate feedback
can do a better job than inflexible rules out of touch with reality.

Algorithmic regulation could certainly make the administration of
existing laws more efficient. If it can fight credit-card fraud,
why not tax fraud? Italian bureaucrats have experimented with the
redditometro, or income meter, a tool for comparing people's spending
patterns -- recorded thanks to an arcane Italian law -- with their
declared income, so that authorities know when you spend more than you
earn. Spain has expressed interest in a similar tool.

Such systems, however, are toothless against the real culprits of tax
evasion -- the super-rich families who profit from various offshoring
schemes or simply write outrageous tax exemptions into the law.
Algorithmic regulation is perfect for enforcing the austerity agenda
while leaving those responsible for the fiscal crisis off the hook.
To understand whether such systems are working as expected, we need
to modify O'Reilly's question: for whom are they working? If it's
just the tax-evading plutocrats, the global financial institutions
interested in balanced national budgets and the companies developing
income-tracking software, then it's hardly a democratic success.

With his belief that algorithmic regulation is based on "a deep
understanding of the desired outcome", O'Reilly cunningly disconnects
the means of doing politics from its ends. But the how of politics
is as important as the what of politics -- in fact, the former often
shapes the latter. Everybody agrees that education, health, and
security are all "desired outcomes", but how do we achieve them? In
the past, when we faced the stark political choice of delivering them
through the market or the state, the lines of the ideological debate
were clear. Today, when the presumed choice is between the digital and
the analog or between the dynamic feedback and the static law, that
ideological clarity is gone -- as if the very choice of how to achieve
those "desired outcomes" was apolitical and didn't force us to choose
between different and often incompatible visions of communal living.

By assuming that the utopian world of infinite feedback loops is so
efficient that it transcends politics, the proponents of algorithmic
regulation fall into the same trap as the technocrats of the past.
Yes, these systems are terrifyingly efficient -- in the same way that
Singapore is terrifyingly efficient (O'Reilly, unsurprisingly, praises
Singapore for its embrace of algorithmic regulation). And while
Singapore's leaders might believe that they, too, have transcended
politics, it doesn't mean that their regime cannot be assessed
outside the linguistic swamp of efficiency and innovation -- by using
political, not economic benchmarks.

As Silicon Valley keeps corrupting our language with its endless
glorification of disruption and efficiency -- concepts at odds with
the vocabulary of democracy -- our ability to question the "how" of
politics is weakened. Silicon Valley's default answer to the how of
politics is what I call solutionism: problems are to be dealt with
via apps, sensors, and feedback loops -- all provided by startups.
Earlier this year Google's Eric Schmidt even promised that startups
would provide the solution to the problem of economic inequality: the
latter, it seems, can also be "disrupted". And where the innovators
and the disruptors lead, the bureaucrats follow.

The intelligence services embraced solutionism before other government
agencies. Thus, they reduced the topic of terrorism from a subject
that had some connection to history and foreign policy to an
informational problem of identifying emerging terrorist threats via
constant surveillance. They urged citizens to accept that instability
is part of the game, that its root causes are neither traceable nor
reparable, that the threat can only be pre-empted by out-innovating
and out-surveilling the enemy with better communications.

Speaking in Athens last November, the Italian philosopher Giorgio
Agamben discussed an epochal transformation in the idea of government,
"whereby the traditional hierarchical relation between causes and
effects is inverted, so that, instead of governing the causes -- a
difficult and expensive undertaking -- governments simply try to govern
the effects".

For Agamben, this shift is emblematic of modernity. It also explains
why the liberalisation of the economy can co-exist with the growing
proliferation of control -- by means of soap dispensers and remotely
managed cars -- into everyday life. "If government aims for the effects
and not the causes, it will be obliged to extend and multiply control.
Causes demand to be known, while effects can only be checked and
controlled." Algorithmic regulation is an enactment of this political
programme in technological form.

The true politics of algorithmic regulation become visible once its
logic is applied to the social nets of the welfare state. There are no
calls to dismantle them, but citizens are nonetheless encouraged to
take responsibility for their own health. Consider how Fred Wilson, an
influential US venture capitalist, frames the subject. "Health? is the
opposite side of healthcare," he said at a conference in Paris last
December. "It's what keeps you out of the healthcare system in the
first place." Thus, we are invited to start using self-tracking apps
and data-sharing platforms and monitor our vital indicators, symptoms
and discrepancies on our own.

This goes nicely with recent policy proposals to save troubled public
services by encouraging healthier lifestyles. Consider a 2013 report
by Westminster council and the Local Government Information Unit, a
thinktank, calling for the linking of housing and council benefits
to claimants' visits to the gym -- with the help of smartcards. They
might not be needed: many smartphones are already tracking how many
steps we take every day (Google Now, the company's virtual assistant,
keeps score of such data automatically and periodically presents it to
users, nudging them to walk more).

The numerous possibilities that tracking devices offer to health and
insurance industries are not lost on O'Reilly. "You know the way
that advertising turned out to be the native business model for the
internet?" he wondered at a recent conference. "I think that insurance
is going to be the native business model for the internet of things."
Things do seem to be heading that way: in June, Microsoft struck a
deal with American Family Insurance, the eighth-largest home insurer
in the US, in which both companies will fund startups that want to put
sensors into smart homes and smart cars for the purposes of "proactive
protection".

An insurance company would gladly subsidise the costs of installing
yet another sensor in your house -- as long as it can automatically
alert the fire department or make front porch lights flash in case
your smoke detector goes off. For now, accepting such tracking systems
is framed as an extra benefit that can save us some money. But when
do we reach a point where not using them is seen as a deviation -- or,
worse, an act of concealment -- that ought to be punished with higher
premiums?

Or consider a May 2014 report from 2020health, another thinktank,
proposing to extend tax rebates to Britons who give up smoking, stay
slim or drink less. "We propose 'payment by results', a financial
reward for people who become active partners in their health, whereby
if you, for example, keep your blood sugar levels down, quit smoking,
keep weight off, [or] take on more self-care, there will be a tax
rebate or an end-of-year bonus," they state. Smart gadgets are the
natural allies of such schemes: they document the results and can even
help achieve them -- by constantly nagging us to do what's expected.

The unstated assumption of most such reports is that the unhealthy
are not only a burden to society but that they deserve to be punished
(fiscally for now) for failing to be responsible. For what else could
possibly explain their health problems but their personal failings?
It's certainly not the power of food companies or class-based
differences or various political and economic injustices. One can
wear a dozen powerful sensors, own a smart mattress and even do a
close daily reading of one's poop -- as some self-tracking aficionados
are wont to do -- but those injustices would still be nowhere to be
seen, for they are not the kind of stuff that can be measured with a
sensor. The devil doesn't wear data. Social injustices are much harder
to track than the everyday lives of the individuals whose lives they
affect.

In shifting the focus of regulation from reining in institutional and
corporate malfeasance to perpetual electronic guidance of individuals,
algorithmic regulation offers us a good-old technocratic utopia of
politics without politics. Disagreement and conflict, under this
model, are seen as unfortunate byproducts of the analog era -- to be
solved through data collection -- and not as inevitable results of
economic or ideological conflicts.

However, a politics without politics does not mean a politics without
control or administration. As O'Reilly writes in his essay: "New
technologies make it possible to reduce the amount of regulation
while actually increasing the amount of oversight and production of
desirable outcomes." Thus, it's a mistake to think that Silicon Valley
wants to rid us of government institutions. Its dream state is not the
small government of libertarians -- a small state, after all, needs
neither fancy gadgets nor massive servers to process the data -- but
the data-obsessed and data-obese state of behavioural economists.

The nudging state is enamoured of feedback technology, for its
key founding principle is that while we behave irrationally, our
irrationality can be corrected -- if only the environment acts upon
us, nudging us towards the right option. Unsurprisingly, one of the
three lonely references at the end of O'Reilly's essay is to a 2012
speech entitled "Regulation: Looking Backward, Looking Forward" by
Cass Sunstein, the prominent American legal scholar who is the chief
theorist of the nudging state.

And while the nudgers have already captured the state by making
behavioural psychology the favourite idiom of government bureaucracy
--Daniel Kahneman is in, Machiavelli is out -- the algorithmic
regulation lobby advances in more clandestine ways. They create
innocuous non-profit organisations like Code for America which then
co-opt the state -- under the guise of encouraging talented hackers to
tackle civic problems.

Such initiatives aim to reprogramme the state and make it
feedback-friendly, crowding out other means of doing politics. For
all those tracking apps, algorithms and sensors to work, databases
need interoperability -- which is what such pseudo-humanitarian
organisations, with their ardent belief in open data, demand. And when
the government is too slow to move at Silicon Valley's speed, they
simply move inside the government. Thus, Jennifer Pahlka, the founder
of Code for America and a protege of O'Reilly, became the deputy chief
technology officer of the US government -- while pursuing a one-year
"innovation fellowship" from the White House.

Cash-strapped governments welcome such colonisation by technologists
-- especially if it helps to identify and clean up datasets that can
be profitably sold to companies who need such data for advertising
purposes. Recent clashes over the sale of student and health data in
the UK are just a precursor of battles to come: after all state assets
have been privatised, data is the next target. For O'Reilly, open data
is "a key enabler of the measurement revolution".

This "measurement revolution" seeks to quantify the efficiency of
various social programmes, as if the rationale behind the social nets
that some of them provide was to achieve perfection of delivery.
The actual rationale, of course, was to enable a fulfilling life by
suppressing certain anxieties, so that citizens can pursue their
life projects relatively undisturbed. This vision did spawn a vast
bureaucratic apparatus and the critics of the welfare state from the
left -- most prominently Michel Foucault -- were right to question
its disciplining inclinations. Nonetheless, neither perfection nor
efficiency were the "desired outcome" of this system. Thus, to compare
the welfare state with the algorithmic state on those grounds is
misleading.

But we can compare their respective visions for human fulfilment --
and the role they assign to markets and the state. Silicon Valley's
offer is clear: thanks to ubiquitous feedback loops, we can all become
entrepreneurs and take care of our own affairs! As Brian Chesky, the
chief executive of Airbnb, told the Atlantic last year, "What happens
when everybody is a brand? When everybody has a reputation? Every
person can become an entrepreneur."

Under this vision, we will all code (for America!) in the morning,
drive Uber cars in the afternoon, and rent out our kitchens as
restaurants -- courtesy of Airbnb -- in the evening. As O'Reilly writes
of Uber and similar companies, "these services ask every passenger to
rate their driver (and drivers to rate their passenger). Drivers who
provide poor service are eliminated. Reputation does a better job of
ensuring a superb customer experience than any amount of government
regulation."

The state behind the "sharing economy" does not wither away; it might
be needed to ensure that the reputation accumulated on Uber, Airbnb
and other platforms of the "sharing economy" is fully liquid and
transferable, creating a world where our every social interaction is
recorded and assessed, erasing whatever differences exist between
social domains. Someone, somewhere will eventually rate you as a
passenger, a house guest, a student, a patient, a customer. Whether
this ranking infrastructure will be decentralised, provided by a
giant like Google or rest with the state is not yet clear but the
overarching objective is: to make reputation into a feedback-friendly
social net that could protect the truly responsible citizens from the
vicissitudes of deregulation.

Admiring the reputation models of Uber and Airbnb, O'Reilly wants
governments to be "adopting them where there are no demonstrable ill
effects". But what counts as an "ill effect" and how to demonstrate
it is a key question that belongs to the how of politics that
algorithmic regulation wants to suppress. It's easy to demonstrate
"ill effects" if the goal of regulation is efficiency but what if it
is something else? Surely, there are some benefits -- fewer visits
to the psychoanalyst, perhaps -- in not having your every social
interaction ranked?

The imperative to evaluate and demonstrate "results" and "effects"
already presupposes that the goal of policy is the optimisation of
efficiency. However, as long as democracy is irreducible to a formula,
its composite values will always lose this battle: they are much
harder to quantify.

For Silicon Valley, though, the reputation-obsessed algorithmic state
of the sharing economy is the new welfare state. If you are honest and
hardworking, your online reputation would reflect this, producing a
highly personalised social net. It is "ultrastable" in Ashby's sense:
while the welfare state assumes the existence of specific social evils
it tries to fight, the algorithmic state makes no such assumptions.
The future threats can remain fully unknowable and fully addressable --
on the individual level.

Silicon Valley, of course, is not alone in touting such ultrastable
individual solutions. Nassim Taleb, in his best-selling 2012 book
Antifragile, makes a similar, if more philosophical, plea for
maximising our individual resourcefulness and resilience: don't get
one job but many, don't take on debt, count on your own expertise.
It's all about resilience, risk-taking and, as Taleb puts it, "having
skin in the game". As Julian Reid and Brad Evans write in their new
book, Resilient Life: The Art of Living Dangerously, this growing cult
of resilience masks a tacit acknowledgement that no collective project
could even aspire to tame the proliferating threats to human existence
-- we can only hope to equip ourselves to tackle them individually.
"When policy-makers engage in the discourse of resilience," write Reid
and Evans, "they do so in terms which aim explicitly at preventing
humans from conceiving of danger as a phenomenon from which they might
seek freedom and even, in contrast, as that to which they must now
expose themselves."

What, then, is the progressive alternative? "The enemy of my enemy
is my friend" doesn't work here: just because Silicon Valley is
attacking the welfare state doesn't mean that progressives should
defend it to the very last bullet (or tweet). First, even leftist
governments have limited space for fiscal manoeuvres, as the kind
of discretionary spending required to modernise the welfare state
would never be approved by the global financial markets. And it's the
ratings agencies and bond markets -- not the voters -- who are in charge
today.

Second, the leftist critique of the welfare state has become only
more relevant today when the exact borderlines between welfare and
security are so blurry. When Google's Android powers so much of our
everyday life, the government's temptation to govern us through
remotely controlled cars and alarm-operated soap dispensers will be
all too great. This will expand government's hold over areas of life
previously free from regulation.

With so much data, the government's favourite argument in fighting
terror -- if only the citizens knew as much as we do, they too would
impose all these legal exceptions -- easily extends to other domains,
from health to climate change. Consider a recent academic paper
that used Google search data to study obesity patterns in the US,
finding significant correlation between search keywords and body
mass index levels. "Results suggest great promise of the idea of
obesity monitoring through real-time Google Trends data", note the
authors, which would be "particularly attractive for government health
institutions and private businesses such as insurance companies."

If Google senses a flu epidemic somewhere, it's hard to challenge its
hunch -- we simply lack the infrastructure to process so much data
at this scale. Google can be proven wrong after the fact -- as has
recently been the case with its flu trends data, which was shown to
overestimate the number of infections, possibly because of its failure
to account for the intense media coverage of flu -- but so is the case
with most terrorist alerts. It's the immediate, real-time nature of
computer systems that makes them perfect allies of an infinitely
expanding and pre-emption&#8209;obsessed state.

Perhaps, the case of Gloria Placente and her failed trip to the beach
was not just a historical oddity but an early omen of how real-time
computing, combined with ubiquitous communication technologies,
would transform the state. One of the few people to have heeded that
omen was a little-known American advertising executive called Robert
MacBride, who pushed the logic behind Operation Corral to its ultimate
conclusions in his unjustly neglected 1967 book, The Automated State.

At the time, America was debating the merits of establishing a
national data centre to aggregate various national statistics and
make it available to government agencies. MacBride attacked his
contemporaries' inability to see how the state would exploit the
metadata accrued as everything was being computerised. Instead of "a
large scale, up-to-date Austro-Hungarian empire", modern computer
systems would produce "a bureaucracy of almost celestial capacity"
that can "discern and define relationships in a manner which no human
bureaucracy could ever hope to do".

"Whether one bowls on a Sunday or visits a library instead is [of]
no consequence since no one checks those things," he wrote. Not so
when computer systems can aggregate data from different domains and
spot correlations. "Our individual behaviour in buying and selling
an automobile, a house, or a security, in paying our debts and
acquiring new ones, and in earning money and being paid, will be noted
meticulously and studied exhaustively," warned MacBride. Thus, a
citizen will soon discover that "his choice of magazine subscriptions?
can be found to indicate accurately the probability of his maintaining
his property or his interest in the education of his children." This
sounds eerily similar to the recent case of a hapless father who found
that his daughter was pregnant from a coupon that Target, a retailer,
sent to their house. Target's hunch was based on its analysis of
products -- for example, unscented lotion -- usually bought by other
pregnant women.

For MacBride the conclusion was obvious. "Political rights won't be
violated but will resemble those of a small stockholder in a giant
enterprise," he wrote. "The mark of sophistication and savoir-faire in
this future will be the grace and flexibility with which one accepts
one's role and makes the most of what it offers." In other words,
since we are all entrepreneurs first -- and citizens second, we might
as well make the most of it.

What, then, is to be done? Technophobia is no solution. Progressives
need technologies that would stick with the spirit, if not the
institutional form, of the welfare state, preserving its commitment
to creating ideal conditions for human flourishing. Even some
ultrastability is welcome. Stability was a laudable goal of the
welfare state before it had encountered a trap: in specifying the
exact protections that the state was to offer against the excesses of
capitalism, it could not easily deflect new, previously unspecified
forms of exploitation.

How do we build welfarism that is both decentralised and ultrastable?
A form of guaranteed basic income -- whereby some welfare services are
replaced by direct cash transfers to citizens -- fits the two criteria.

Creating the right conditions for the emergence of political
communities around causes and issues they deem relevant would
be another good step. Full compliance with the principle of
ultrastability dictates that such issues cannot be anticipated or
dictated from above -- by political parties or trade unions -- and must
be left unspecified.

What can be specified is the kind of communications infrastructure
needed to abet this cause: it should be free to use, hard to
track, and open to new, subversive uses. Silicon Valley's existing
infrastructure is great for fulfilling the needs of the state, not
of self-organising citizens. It can, of course, be redeployed for
activist causes -- and it often is -- but there's no reason to accept
the status quo as either ideal or inevitable.

Why, after all, appropriate what should belong to the people in the
first place? While many of the creators of the internet bemoan how low
their creature has fallen, their anger is misdirected. The fault is
not with that amorphous entity but, first of all, with the absence of
robust technology policy on the left -- a policy that can counter the
pro-innovation, pro-disruption, pro-privatisation agenda of Silicon
Valley. In its absence, all these emerging political communities will
operate with their wings clipped. Whether the next Occupy Wall Street
would be able to occupy anything in a truly smart city remains to be
seen: most likely, they would be out-censored and out-droned.

To his credit, MacBride understood all of this in 1967. "Given
the resources of modern technology and planning techniques," he
warned, "it is really no great trick to transform even a country
like ours into a smoothly running corporation where every detail of
life is a mechanical function to be taken care of." MacBride's fear
is O'Reilly's master plan: the government, he writes, ought to be
modelled on the "lean startup" approach of Silicon Valley, which
is "using data to constantly revise and tune its approach to the
market". It's this very approach that Facebook has recently deployed
to maximise user engagement on the site: if showing users more happy
stories does the trick, so be it.

Algorithmic regulation, whatever its immediate benefits, will give
us a political regime where technology corporations and government
bureaucrats call all the shots. The Polish science fiction writer
Stanislaw Lem, in a pointed critique of cybernetics published, as
it happens, roughly at the same time as The Automated State, put it
best: "Society cannot give up the burden of having to decide about its
own fate by sacrificing this freedom for the sake of the cybernetic
regulator."

. . . . . . . . . . . . . . .
To Save Everything, Click Here: Technology, Solutionism, and the Urge to
Fix Problems That Don't Exist by Evgeny Morozov is out now in paperback


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