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social research Vol. 84 : No. 1 : Spring 2017 147
Jacob Silverman Privacy under Surveillance Capitalism
in 1982, the national science foundation published a report about
the prospects for teletext and videotex in the United States. The report,
written by a RAND Corporation–affiliated think tank known as the
Institute for the Future, examined the market potential and public-
policy issues of these information-services technologies, which at the
time were just two protocols among many competing to be the future
of networked communications. (The report, “Teletext and Videotex in
the United States,” discusses “packet switching,” but the word “Inter-
net” does not appear in its 300-plus pages.) Envisioning a range of possi-
bilities for teletext and videotex that spanned entertainment, news,
shopping, banking, and other information services, the report also
warned that “at the same time that these systems will bring a greatly
increased flow of information and services into the home, they will also
carry a stream of information out of the home about the preferences
and behavior of its occupants” (Adler et al. 1982).
Teletext and videotex may have been banished to the dustbin
of technological history, yet the report’s warning proved prophetic.
But what may have been a cause for alarm to some has proven to be
an immense commercial opportunity for others, as personal informa-
tion and behavioral tracking have emerged as major assets in today’s
surveillance capitalism (Zuboff 2015). A Senate report estimated the
US data broker industry to be worth $150 billion per year (US Sen-
ate Committee on Commerce 2013). Data and personally identifiable
information (PII) are the new extractive commodities of the age. Of-
ten compared to oil, data may be a more renewable resource, albeit
148 social research
at a cost to privacy, autonomy, democratic accountability, consumer
choice, and indeed, the environment (in the form of massive energy
costs for data centers, e-waste, and the mining of rare minerals).
With the proliferation of networked devices in our homes and
on our bodies, our surrounding environments now overflow with sen-
sors and other data producers. Earlier generations saw some forms
of governmental and commercial data collection about the home
and what goes on in it. Market research, census records, consumer
surveys, loyalty cards, credit bureaus, property records—these were
common predigital data streams, and many still exist in one form or
another. Now the home—and the activities, behaviors, and prefer-
ences of those within it—is becoming transparent, as mappable as a
city street. Internet of Things (IoT) devices track the comings and go-
ings of a home’s occupants. Roomba, the autonomous robot vacuum,
maps the rooms it cleans (although it does not transmit the maps
it creates anywhere), and future versions will be able to recognize
household objects. Researchers have successfully used slight varia-
tions in WiFi signal coverage to map the interiors of rooms and the
people in them—in other words, to “see” through walls (Condiliffe
2015). Intelligence agencies are able to use the sounds of computers’
fans to exfiltrate data from air-gapped machines (Zetter 2016). Law
enforcement officials have begun subpoenaing data and records from
always-on, always-listening IoT devices, like the Amazon Echo, for use
in criminal investigations (Steele 2016). Subtle vibrations of everyday
objects can be measured to reconstruct the sounds in a room (Timmer
2014). Some of these techniques are the product of cutting-edge hacks
or secret operations by intelligence agencies, but they reflect a grow-
ing technological capacity. What may now be the province of a secu-
rity service or a rogue tech firm will soon enough be commonplace.
The home was never an inviolable site of total privacy. For
some children, women, the disabled, the elderly, domestic workers,
or those caught in abusive relationships, the home is neither a place
of privacy nor comfortable domesticity, but an arena of contentious
power relationships. Children are well-practiced at navigating the
Privacy under Surveillance Capitalism 149
shoals of disclosure with their parents—sharing some information,
concealing more, demanding a lock on their door, perhaps, or regu-
larly clearing their browser histories. A great deal of subversive be-
havior in childhood revolves around keeping information secret from
parents and avoiding their watchful surveillance.
In the realm of personal privacy and digital technologies, then,
the “invasive other” might be best characterized as those forces of
power and authority that collect information about us and exert in-
fluence over us. The “other” might be one’s boss or parents or a dis-
tant government overseer, but the means of surveillance and control
are mostly embodied in new digital technologies and data-collection
schemes. Central to this paradigm is the objectification of a human
being into a data source capable of being parsed, scanned, assessed,
and monetized by other, invasive interests. A human being becomes
subject to an algorithmic gaze, a machine vision that emphasizes
market values like productivity, efficiency, profit, and mitigation of
risk and liability.
Amidst the profound changes in privacy norms wrought by the
advent of digital technologies and cultures, one trend is clear: individ-
uals have been made vastly more transparent, while authorities and
corporations have become more opaque. These changes in privacy
and surveillance track with growth in the US surveillance state, in the
ability of the executive branch to wage undeclared war indefinitely,
and in the advent of corporate personhood, which serves as a legal
manifestation of a vast expansion of corporate power in all facets of
American life. At the same time, individual rights—while lionized in
the public discourse of liberty, freedom, and American exceptional-
ism—have become frighteningly contingent. Rights for voting, free
speech, habeas corpus, to consent to searches, and much more are
prone to sudden abrogation under laws that reflect a generalized
state of emergency. The enforcement of these measures, in turn, is
enabled by the institutionalization of mass surveillance, which allows
authorities to monitor social media, record phone calls, film public
spaces, track vehicle movements, and strictly control passage at bor-
150 social research
ders with biometric identification. It is now possible for many coun-
tries to record virtually all telecommunications and internet traffic
within their borders (Villasenor 2011), and the US intelligence com-
munity’s unofficial mantra of “collect it all” would seem to place it in
this class (Nakashima and Warrick 2013).
As these shifts in privacy occur, the home will not become
completely transparent, as if lit by klieg lights. The various power
relations will not dissolve overnight, nor will all forms of surveillance
and data collection be equal. The invasive others will sometimes clash
as they reach for their ultimate prize: us. There will be—there are—
many privacies, overlapping, intersecting, a cross-hatching of com-
peting data-collection schemes and struggles for consumers’ atten-
tion. The home, and many of the people and things in it, has been
plugged into the tributaries of surveillance capitalism.
The home is also just one context. Thanks to the explosion
of social networks, “dataveillance,” and networked communications,
our once-discrete social contexts are increasingly permeable. The in-
vasive other sees into all aspects of our lives. Many media theorists
have turned to the phrase “context collapse” to explain this phenom-
enon. Essentially, context collapse refers to the dissolution of borders
between formerly separate social spaces. Various contexts combine,
particularly on social networks, where they are all part of the same
informational flux. On Facebook, for instance, one might limit posts
to certain people, but by default, one’s posts are available to all one’s
friends (and perhaps the public, too). Your boss, your landlord, your
ex, your closest friends, and people who you might have long forgot-
ten about, old online acquaintances who have lapsed into invisibility,
buried in your feed—all might see your posts. The change in audience
composition in turn affects how we present ourselves, how we write
about ourselves, and what we might think constitutes privacy. It is
not so easy to calibrate our behavior or expressions for our audience
or even to know who our audience is.
This emerging awareness of collapsed contexts could spur a
reactionary stance, a sense that one is too exposed. (The often-cited
Privacy under Surveillance Capitalism 151
Dunbar’s number purports to represent the number of people that
one can maintain an active social network with; the number varies
but is often pegged at around 150.) It might be easy, then, to lapse
into default forms and gestures—to simply retweet popular memes or
cultivate a manicured Instagram page in which nothing seems askew
and every filter is carefully applied. On Facebook, you might only
share mainstream news articles that flatter the views of your friends.
This homogenization of style is an act of public relations. It shows
that one fits in, isn’t too distinctive, is abreast of the viral zeitgeist. It
is also, potentially, the death of the personal. But that’s what happens
when contexts collapse in upon one another. The audience becomes
too broad, the glare of public scrutiny too apparent. Who would want
to say the same thing to his grandfather as to his old college room-
mate? And that is only the fear of a minor social faux pas, rather than
the greater fears that often accompany online overexposure: job loss,
verbal abuse, threats, a sense of vulnerability, a permanent data trail,
a feeling that anyone could be watching.
In April 2016, Facebook found itself facing precisely this prob-
lem. A representative of the social network, speaking with a Bloom-
berg News reporter, claimed that the company was concerned about
context collapse. While people were sharing just as much content,
they were posting less information of a personal nature and more
about news stories and public events. As friend lists grew, people
seemed less willing to be open about themselves. “Personal sharing
has shifted to smaller audiences on Snapchat, Facebook’s Instagram
and other messaging services,” the article noted (Frier 2016).
Facebook had calculated the relative decline in personal shar-
ing at 21 percent year-over-year (Frier 2016). This number revealed
a great deal about Facebook’s strategy and self-image. The statistic
is presented exactly as revenues or profits might be, as a percentage
relative to the previous year. This metric is clearly something that
Facebook values, and it reflects the growing relationship between a
company’s ability to gather PII and its bottom line. Personal data,
behavior, preferences, memories, responses to events, feelings, loca-
152 social research
tions—these intimate and private bits of information constitute the
larger stratum of information that most large tech companies, and
certainly all large social platforms, mine for profit. While Facebook
is expert at tracking and surveilling its users, it still depends on vol-
untary disclosures of personal information, on users seeing Facebook
as a place in which they can retain a sense of privacy and safety so
as to feel comfortable airing out their personal lives. (The invasive
other must be hidden from view, even as it monitors everything users
do.) This personal information is essential for Facebook’s ad-targeting
efforts, which seek to match users with advertisements that reflect
their interests and concerns. Context collapse describes the compa-
ny’s anxiety that its users may not feel so forthcoming about sharing
and that this decline in personal sharing will, in turn, lead to less ef-
fectively targeted ads.
At the center of the blast crater left by context collapse stands
the smartphone. Here is where all social contexts and data converge,
and are made mobile. The smartphone is the universal prosthesis, a
veritable Star Trek tricorder or Swiss army knife of omni-utility. It is,
increasingly, the vehicle through which many people communicate,
entertain themselves, and find their way in the world. It is a constant
hub of personally revealing activity, which is why metadata from mo-
bile devices is as important to police officers looking to solve a mur-
der as to a marketer looking to serve up location-dependent ads. And
like the Star Trek tricorder, which crew members often jerry-rigged
to unlock some new capability in a moment of need, the smartphone
is prone to feature creep. New uses are found for its sensors, with
more added each product cycle. Smartphones can count steps, track
sleep patterns, and perform other kinds of bio-behavioral monitor-
ing, but these and other capabilities were mostly introduced later by
independent app-makers and tinkerers who realized that the device’s
gyroscopes and sensors could be repurposed to track all manner of
activity.
Besides its role as the universal tool, the smartphone is a con-
stant companion, a salve against loneliness. With its notifications and
Privacy under Surveillance Capitalism 153
persistent demands for our attention, it asks to be tended to, like
a pet. In a time of precarity, the smartphone, or just the Internet
writ large, promises something new, a way out of our current situa-
tion. There is always something novel to consume. Simply refresh the
feed—the archetypal interface of digital life, an endlessly scrolling,
algorithmically sorted information-scape; sorted because it’s over-
whelming, because consumers can’t be trusted to handle the infor-
mational load coming at them, and because of one of the few iron-
clad rules of surveillance capitalism: it serves advertisers. Everything
comes through a feed: jobs, news, relationships, Uber rides, photos,
Amber alerts, trivial entertainments and diversions that help get us
through the small interstitial periods while waiting in line or riding
the bus. These moments, once spent idly daydreaming perhaps (if one
wishes to romanticize), are now ripe moments for information pro-
cessing and data production.
The smartphone is a personalized surveillance machine, pro-
ducing ever more granular reports about its user. This individualized
tendency—so important to advertisers who wish to target consum-
ers on a personal level with customized appeals—reflects how digital
surveillance and data analytics are perfect neoliberal technologies,
allowing markets to be the handmaidens of digitization. As we digi-
tize more of the world, we measure and define more of it in terms of
specialized metrics. And as so much is tracked and measured, it can
be monetized and marketized and subjected to the larger forces of
financial capitalism. Prices for anything from taxis to insurance can
fluctuate in real time, reflecting ostensibly computer-derived calcu-
lations about supply, demand, risk, or market efficiency. Of course,
these shifts in pricing may be motivated just as much by a desire to
maximize revenue, to see how much a consumer is willing to pay and
whether he can be made to surrender to variable pricing schemes
over which he has no control. That is why, for instance, online re-
tailers have been experimenting with differential pricing, offering
customized prices derived from a customer’s personal information.
The retailer can point to some dubious promise of personalization or
efficiency while padding its margins.
154 social research
Amazon has indicated that variable pricing structures may be
tested in some of its brick-and-mortar stores, which serve—in an iron-
ic reversal of the classic analog-to-digital shift—as veritable laborato-
ries for bringing digital surveillance technologies into the physical
world. In these stores, a customer’s smartphone and faceprint would
identify him, allowing the store’s systems to offer different prices
for each item for each customer (displayed on a small screen or on
the user’s own device—to preserve his “privacy,” perhaps). And with
much of a store’s functions automated—McDonald’s, for example, is
investing heavily in replacing cashier workers with digital kiosks—
that other holy grail of surveillance capitalism may take center stage:
efficiency. This is one of the fundamental, almost tautological prin-
ciples underpinning data-driven information technologies. Efficiency
justifies everything else. It reflects the perfection of a system and the
elimination of bias, waste, and error, which are lamented as all-too-
human phenomena.
Here we brush up against the essentially positivist nature of
today’s surveillance capitalism, which is characterized by feedback
loops, the assumed “neutrality” of algorithms, and the ideological no-
tion that computers carry an inherent authority—i.e., they can never
be wrong. The system, with its impressive processing power, its enor-
mous storage capacity, and its multitasking capabilities, is treated as
a more neutral arbiter than a human being, for whom efficiency and
speed might be less important values than ethics, deliberation, or
questioning assumptions. A human store clerk can converse with a
customer and make nuanced decisions about how to interact with her,
while a digital kiosk is limited to binary decisions based on a crude
data profile. A consequence of this kind of thinking is that digital
systems incorporate error and bias, like racism, in a self-reinforcing
manner for which there are few incentives to provide a fix. Respon-
sibility gets abstracted away, as undesired outcomes are attributed to
quirks in the system or some kind of human misunderstanding. Code,
from the perspective of a user who has no ability to change it, is law.
Privacy under Surveillance Capitalism 155
Consider the example of predictive policing software, increas-
ingly a preferred tool for forward-thinking metropolitan police de-
partments. Often this software is furnished by private companies that
use crime data that may already be the product of unjust, racist, or
otherwise politicized policies. A black neighborhood might generate
an abundance of crime data (and be designated by the system as high
crime) because racist politicians or police commanders have histori-
cally subjected these communities to overpolicing and discrimina-
tory treatment. The raw data, however, doesn’t see these complexi-
ties. That data is then plugged into software that uses proprietary
algorithms to perform a threat assessment of a particular house or
individual—a determination that might be passed along to an officer
in the field. On his way to answer a call, an officer might learn that
Joe Steve living at 2666 Elm is “high risk,” which may affect his ap-
proach to the scene, but he has almost no information about how
that determination was reached. More perniciously, the threat assess-
ment may be presented as a quantified metric, as a so-called “threat
score” of, say, 85, which implies a degree of mathematical certitude.
But this number is largely meaningless, even if the officer knows the
range of possible scores. He still doesn’t know how the data was col-
lected, or whether it’s accurate at all, and he doesn’t know how the
software reached its decision because its algorithmic decision-making
process is a protected commercial secret. The problems extend up the
institution’s hierarchy, as the police force’s management doesn’t un-
derstand the inner workings of this software because a private com-
pany is under no obligation to share that information.
In the same way, we cannot know how Google determines its
search results or what factors are influential in how Facebook sorts its
news feed. Some outcomes may be adverse, but we can never fully in-
vestigate or understand them because they are concealed behind the
veil of algorithmic secrecy. A study can then find that Google searches
for names commonly thought to be African-American produce ads for
bail bondsmen and arrest records—clearly a product of discriminato-
ry thinking—but without greater transparency surrounding Google’s
156 social research
highly sophisticated ad network, it’s impossible to know why such
searches produce racist ads alongside them (Sweeney 2013).
Digitization, automation, and the parsing of the world through
algorithmic systems allow for the swift movement of information and
capital. They may even advance a kind of efficiency. But this all pro-
ceeds according to an inhumane market logic that elides complexity
and, in the name of individual freedom, actually stifles personal pri-
vacy and autonomy. We can see, in the predictive policing example,
how flawed data becomes legitimized within a larger system that
carries the imprimatur of mathematical authority. It also points to
an important distinction in varying types of privacy, between an in-
dividual’s privacy in relation to other individuals, and between an
individual’s privacy in relation to machines. This latter type, which
might be termed “data privacy,” concerns what surveillance, data col-
lection, analytics systems, and software know about us. It is the data-
fied version of oneself, spread between varying networks, databases,
and systems of sorting and assessment.
These varying informational selves increasingly dictate ac-
cess and opportunity in the world—whether one might get a job, or
whether one might be investigated by police. But they also exist with-
in a larger framework, where so much data production is machine-to-
machine, with no humans in the loop (even if the actual data may de-
scribe a person). The financial motive behind digitization is to make
the world machine-readable, to provide more processes and behaviors
to surveil and digitize, and to use these new streams of information to
monetize more of life. But in this welter of information, humans can
seem secondary, at least insofar as informational production is con-
cerned. As the artist and writer Trevor Paglen notes, most images now
are made by machines to be consumed by other machines. “The fact
that digital images are fundamentally machine-readable regardless of
a human subject has enormous implications,” he writes. “It allows for
the automation of vision on an enormous scale and, along with it, the
exercise of power on dramatically larger and smaller scales than have
ever been possible” (Paglen 2016).
Privacy under Surveillance Capitalism 157
To see this bifurcation of privacy between the personal and
the data selves, consider a photo shared on Instagram. A person’s
decision to stage, capture, and post a photo carries with it implied
considerations about who might see it, how she wants to appear, and
whether she feels comfortable offering it up for something like public
consumption. These are valid and natural privacy concerns, but these
fears about one’s personal privacy exist in parallel to another process,
namely the photo’s consumption as a data object. From this perspec-
tive, the photo is even more exposed than the person it depicts. The
photo is parsed by object and facial recognition programs; marketers
scan it to see how their clients’ products are appearing; metadata re-
veals to advertisers where the photo was taken; law enforcement and
intelligence agencies run the photo’s comments through sentiment-
analysis software, looking for illegal activity or signs of radicalization;
shady bots appear using the photo as an avatar; untold numbers of
computers in data centers and internet hubs around the world chop
up the photo and transport it around as packets of information, pro-
ducing records about its transit in the process. The photo’s lifecycle
and all the useful information that may be extracted from it extend
far beyond the view or control of the person who posted it.
These variations in privacy may lead anyone—from advertisers
to police officers—to manipulate people. In short, they know more
than you. The process of automation on a vast scale leads to thoughts
of what mass-scale coercion, enabled by this flow of data, might look
like. Not all forms of suasion are equal. One study found that wom-
en were shown lower-paying listings in online job ads—a result of
sexism manifesting itself in the ads’ decision-making engine (Yachot
2016). Facebook has studied hundreds of thousands of users, without
their consent, and found that it can provoke slightly happier or sad-
der emotions and observe them traveling, as a contagion, through
the network (Kramer, Guillory, and Hancock 2014). The invasive other
here becomes a pathogen, a vector for inducing the behavioral and
emotional responses desired by the network’s corporate owners.
158 social research
Facebook has also, perhaps more nobly, found that encourag-
ing users to vote increases voter turnout (Corbyn 2012). This study,
while reflecting a heartening truism about the benefits of civic par-
ticipation, appears more malevolent if you consider how this knowl-
edge might be repurposed. Could Facebook encourage people in some
districts to vote while saying nothing to others? With its vast power
to sort the information users see and to prod people toward certain
behaviors, could it influence the fate of elections, not to mention spe-
cific policies? And would we ever know if it did?
The prospect seems increasingly less fanciful. The election of
Donald Trump as president provoked some soul-searching in this re-
gard, with focus landing on the subject of “fake news.” Before the
election, this was seen as a perverse but mostly harmless internet phe-
nomenon, but it later came to be seen as a major problem, a symptom
of a deeply dysfunctional informational and news culture. As much
merit as there is to this idea, there is also the necessary caveat that
fake news is sometimes a matter of epistemological debate. Some sto-
ries or websites or forms of reporting are obviously fiction. Others
are more subtly designed to manipulate, reflect a political bias, lie by
omission, or otherwise mislead, but they might not be strictly fake.
And allegedly “real news” can still produce horrific outcomes—incit-
ing a needless war or demonizing a vulnerable population.
Still, the outcry over fake news reflects, like the criticism over
Facebook’s contagion study, a concern that network effects can be
manipulated to illiberal or harmful ends. (It is also a reminder that
calling a communication “viral” describes both a means of transmis-
sion and its unmanageable, pathogenic character.) After the election,
members of the Trump campaign’s previously secret data-mining op-
eration bragged to journalists about their micro-targeting abilities on
social media (Lever 2016). Users were targeted with highly personal-
ized ads, direct appeals based on the person’s data profile. Whether
or not this kind of granular targeting was as successful as its pro-
ponents claim, it certainly reflects the greater ambition of using PII
data profiles to target and manipulate large populations. And barring
Privacy under Surveillance Capitalism 159
legislative prohibitions against this kind of tactic, tech companies
and political campaigns seem to be among their most likely users,
particularly as these practices are refined.
One worries what happens when facial-recognition technology
improves and proliferates ever further, enabling relative convenienc-
es like Amazon’s automated brick-and-mortar stores while ensuring
that people can be identified, by a host of unknown actors, wherever
they go. One dark scenario is the “Minority Report” option, as in the
film where public advertisements, cameras, and sensors scan Tom
Cruise’s eyes and provide him with personalized offers and ads wher-
ever he goes, with advertising flowing from one interface to another.
Much of this technology already exists, and advertisers are focused
on tracking users wherever they go, including across devices, and (by
closely tracking behaviors) distinguishing between multiple users
sharing the same device.
Alarming as these possibilities are, they represent the quid pro
quo of personalized digital services: total surveillance. Surveillance
remains the preeminent business model of the internet. The possi-
bilities for suasion and influence, for outright manipulation, are now
more apparent. But the discourse surrounding these issues remains
immature, and all too often policymakers pay tribute to the indepen-
dence of the information-aware consumer without considering the
fundamental role of corporate power. No one wants to think that he
is a rube or is subject to manipulation by unseen forces (not least
for the paranoia this betrays). But it would be reckless to deny that
these kinds of capabilities—the power to observe almost everything
someone does, to control what he sees, to push him with alerts, ads,
and opportunities—could eventually be leveraged on a large scale.
That is precisely what civil libertarians warn against in discussing
the dangers of mass government surveillance, and the mass corpo-
rate surveillance of public and private life seems no different. These
systems are, in the end, deeply intertwined. Private companies sell
personal data to government agencies. They depend on federal con-
tracts and lobby for favorable legislation. Intelligence agencies make
160 social research
backroom deals with telecom giants like AT&T and security firms like
RSA. And where deals can’t be made, intel agencies hack into internet
backbones, pillage databases, and use existing ad networks to surveil
web users, turning the ostensibly benign commercial surveillance of
web browsing into a covert intelligence-gathering operation. In the
larger digital economy, it is hard to disentangle one from the other,
especially as personnel increasingly flow from government intelli-
gence agencies and hacking teams to more lucrative opportunities at
private cybersecurity firms.
Amidst this array of compromises, ethical disasters, and oppor-
tunities for manipulation, how can the surveillance-driven internet
economy be opposed? One response is to embark on some program
of digital hygiene or security planning. Securitize the self: this is the
smart, informed consumer’s response. He uses Tor, Signal, and other
encrypted, anonymizing products. He opts out of all that he can, pre-
fers open-source software, updates his devices and software frequent-
ly. He might use a password manager, get a PGP key, and take other se-
curity measures, such as installing alternative operating systems like
Tails or Qubes. Gradually, he begins to think like a spy, speaking of at-
tack surfaces, advanced persistent threats, adversaries, opsec, and all
other manner of jargon. It is him, alone, against the invasive, patho-
genic forces arrayed against him. This kind of clandestine thinking
has its place for some—dissidents, journalists, diplomats, artists—but
it is largely an indulgent form of spytalk, one that reflects underlying
principles of secrecy, vigilance, self-reliance, and suspicion of others.
It is also an essentially consumerist and individualist response, which
precludes showing much solidarity with a larger public (except in the
form of using the same expert-approved encrypted chat apps). The
larger result is a vast disparity in privacy conditions and outcomes.
Privacy itself becomes a boutique good, affordable to those who know
how to navigate this tangled landscape of best practices, firmware up-
dates, threat assessments, cryptographic keybases, and virtual private
networks. All this feverish activity also reveals how liminal privacy
is, particularly data privacy. A person may succeed in obfuscating his
Privacy under Surveillance Capitalism 161
data trail, in masking his activities from marketers and perhaps even
some intelligence agencies. But there is always, it seems, another leak
that must be patched, and not all can be. Some major telecoms, for
example, install surreptitious “super cookies” that monitor a phone’s
browsing information and prove near impossible to remove. Verizon
sells location data to marketers—something that no Verizon custom-
er can avoid, unless he places his device in a Faraday bag.
When we recognize how much labor is involved with these ac-
tivities—labor that technology firms may successfully harness for prof-
itable data about user behavior—their insufficiency becomes clearer.
So does the inherently reactionary nature of this kind of thinking. By
undergoing these regimens of digital hygiene and securitization, we
are operating on the terms of surveillance capitalism, fashioning per-
sonalized, market-based solutions for the problems of personal pri-
vacy and exploitation of PII. While one should not dismiss pragmatic
acts like reforming government regulations or empowering the press
to report on abuses, we would still be acting within the current para-
digm, which fails to acknowledge privacy as a shared, social good,
one that benefits everyone, particularly the most vulnerable. Some
form of radical change necessitates going beyond tinkering with or
challenging surveillance capitalism on its own terms; it will require a
dramatic, seemingly unthinkable alternative. In this context, a mili-
tant rejection of digital technologies, even a kind of Luddism, is un-
derstandable, provided it is foregrounded in such a critique. A person
tarred as a Luddite is not rejecting “technology” or a specific gadget
or modernity itself. She is rejecting the monetizing and mediation by
commercial interests of all her communications. Or she is protesting
tech companies’ wrapping their regressive politics in the slick pack-
age of techno-liberation. Or perhaps she just wants to own the things
she owns, to not have her possessions spy on her, to not have every
choice and action be fed into a great analytic mega-machine whose
ultimate purpose is to extract more money, knowledge, attention, or
small strategic advantage out of her. She wants the invasive other,
which operates through the larger forces of surveillance capitalism
and digital technologies, to leave her alone.
162 social research
We are all entangled in these networks of information con-
sumption and production. The occasional rebel or eccentric forsakes
mobile devices entirely, or someone who is destitute finds no use for
them. But they are not off the grid—there is almost no possibility of
such. Their personal information is still being sold to and from pri-
vate data brokers and government agencies. Automated license-plate
readers scan their cars and track their movements. Insurers study
their purchasing habits or social media accounts for signs of liability.
Other digital traces of their actions prove surprisingly enduring and
fluid, showing up in unexpected places. They become data objects,
whether they know it or not. From this position of entanglement,
it can be hard to see outward, to imagine other possibilities. But for
how long can increasingly personalized surveillance and the rhetoric
of consumer empowerment go hand-in-hand? When will consumers
realize that what has been peddled as convenience is really a kind of
infantilization, swaddling us in personalized services while depriving
us of autonomy and choice? It is time to start envisioning other para-
digms, whether they be social networks without metrics, communi-
cations without surveillance, or business models that do not depend
on personal data. It may be all of these or something else entirely, but
down one of these roads lies the future, if not progress.
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