The Costs of Lost Privacy- Consumer Harm and Rising Economic Inequality in the Age of Google

William Mitchell Law Review
Volume 40 | Issue 2

Article 12

2014

The Costs of Lost Privacy: Consumer Harm and
Rising Economic Inequality in the Age of Google
Nathan Newman

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Newman, Nathan (2014) "The Costs of Lost Privacy: Consumer Harm and Rising Economic Inequality in the Age of Google ,"
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Newman: The Costs of Lost Privacy: Consumer Harm and Rising Economic Ineq

THE COSTS OF LOST PRIVACY: CONSUMER HARM AND
RISING ECONOMIC INEQUALITY IN THE AGE OF
GOOGLE
Nathan Newman†
I. INTRODUCTION: LOSS OF PRIVACY AND CONSUMER HARM ... 850
A. The Pervasive Consumer Harm from Google’s Facilitation
of User Targeting by Its Advertisers..................................... 852
B. Using Antitrust to Address Economic Inequality Due to
Monopoly.......................................................................... 854
II. THE FAILURE OF THE GOOGLE “MARKET” FOR USER DATA .. 855
A. Users Overestimate the Value Added by Google’s Services
and Do Not Receive the Full Economic Value of the Data
They Share with Google...................................................... 857
B. Users Undervalue the Economic Value of the Data They
Share with Google .............................................................. 860
C. Why Aren’t Users Paid for Their Data?............................... 863
III. WHY USER DATA IS SO USEFUL TO ADVERTISERS: “PAIN
POINTS” AND THE CONSUMER HARM OF PRICE
DISCRIMINATION FACILITATED BY A MONOPOLY PLAYER
LIKE GOOGLE ......................................................................... 865
IV. THE CASE FOR LEGAL ACTION ON CONSUMER HARM FROM
PRICE DISCRIMINATION ......................................................... 874
V. SUBPRIME MORTGAGES, “AMBULANCE CHASERS AND
SNAKE OIL SALESPEOPLE”: HOW ONLINE ADVERTISING
UNLEASHES THE “TAWDRY” SIDE OF CAPITALISM .................. 876
A. Racial and Economic Profiling Online ............................... 877
B. Google and the Subprime Mortgage Crisis ........................... 879

†
Nathan Newman is a Fellow at New York University’s Information Law
Institute. He received his JD from Yale Law School and his PhD in Sociology from
the University of California at Berkeley and has written extensively about public
policy and technology in a range of academic and popular journals, including
publishing a book, NET LOSS: INTERNET PROPHETS, PRIVATE PROFITS, AND THE COSTS
TO COMMUNITY (2002).

849

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C. Google’s Continued Role in Facilitating Financial
Exploitation of Consumers ................................................. 881
D. Promoting Illegal Drug Advertisements Earned Google One
of the Largest Civil Forfeitures in American History............. 883
VI. CONCLUSION: THE BROAD CONSUMER HARM FROM
GOOGLE’S MONOPOLY IS NOT BEING CORRECTED BY
MARKET MECHANISMS ........................................................... 884
A. Remedies to Address Consumer Harm from Lost Privacy
Online .............................................................................. 885
B. How Government Intervention Addresses Rising Economic
Inequality ......................................................................... 888

I.

INTRODUCTION: LOSS OF PRIVACY AND CONSUMER HARM

Search and related online services have provoked debates in
recent years about the loss of individual privacy, but this is often
framed more around an individual sense of unease at the
surveillance of peoples’ private lives than how a shift in knowledge
about individuals to corporate hands should force us to reevaluate
our economic models and regulatory tools.
The lack of analysis of the consumer harm from loss of data
privacy is one reason Google, despite its clear dominance of search
advertising, has escaped antitrust prosecution so far in the United
1
States. An antitrust case must show harm to consumers, and
Google’s defenders often deny that consumers lose anything from
their interaction with Google. “It’s . . . impossible to find any way in
which consumer welfare is currently being harmed by Google,”
writes George Mason University’s Adam Thierer, “[a]ll their
2
products are free and constantly evolving.” Or as David Balto

1. Brook Group Ltd. v. Brown & Williamson Tobacco Corp., 509 U.S. 209,
224 (1993) (“It is axiomatic that the antitrust laws were passed for ‘the protection
of competition, not competitors.’”); Reiter v. Sonotone Corp., 442 U.S. 330, 343
(1979) (“Congress designed the Sherman Act as a ‘consumer welfare
prescription.’”); Brown Shoe Co. v. United States, 370 U.S. 294, 344 (1962) (“It is
competition, not competitors, which the [Sherman] Act protects.”); see also United
States v. Microsoft Corp., 253 F.3d 34, 58 (D.C. Cir. 2001) (per curiam) (“[T]o be
condemned as exclusionary, a monopolist’s act must . . . harm the competitive
process and thereby harm consumers. In contrast, harm to one or more competitors
will not suffice.”).
2. Adam Thierer, Can There Be a Market for Unpaid Search Results and Could

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elegantly puts it, “Consumers’ pocketbooks do not see Google as
3
any type of monopolist.” Complaints about Google are largely
dismissed as the whining of competitors, who might gain at the
expense of Google, but not to the benefit of consumers, according
4
to these Google defenders.
When the Federal Trade Commission (FTC) found no
antitrust violation in Google’s dominance of “search” in January
2013, the FTC majority similarly argued for their position largely
from finding no consumer harm from how Google might
manipulate search results to the disadvantage of potential rival
5
websites. Yet the analysis of the FTC’s majority opinion looked only
at users’ interests in accurate search results without ever analyzing
6
how Google’s control of user data might impact consumer welfare.
Only FTC Commissioner J. Thomas Rosch expressed in a partial
dissent the concern that Google’s “monopoly or near-monopoly

Google Be Classified as a Public Utility?, ANTITRUST & COMPETITION POL’Y BLOG
(May 21, 2012), http://lawprofessors.typepad.com/antitrustprof_blog/2012
/05/can-there-be-a-market-for-unpaid-search-results-and-could-google-be-classified
-as-a-public-utility-c-1.html. See also Jim Miller & Dan Oliver, An Antitrust Probe of
Google?, NAT’L REV. ONLINE (Dec. 20, 2011, 5:00 PM), http://www.nationalreview
.com/bench-memos/286349/antitrust-probe-google-jim-miller (“[C]onsumers are
reaping enormous benefits from the free service designed to reflect their
choices.”).
3. David Balto, Google Is No Microsoft, HUFFINGTON POST (June 30, 2011, 6:41
PM), http://huff.to/jfDamv (“[C]onsumers face zero switching costs!”).
4. See U.S. DEP’T OF JUSTICE, ANTITRUST DIVISION POLICY GUIDE TO MERGER
REMEDIES 2 (2011), available at http://www.justice.gov/atr/public/guidelines
/272350.pdf (noting that a “remedy should focus on preserving competition, not
protecting individual competitors”); Geoffrey Manne & Berin Szoka, Some MuchNeeded Antitrust Skepticism on Senate Letter Urging FTC Google Investigation, TRUTH
ON MARKET (Dec. 20, 2011), http://truthonthemarket.com/2011/12/20/some
-much-needed-antitrust-skepticism-on-senate-letter-urging-ftc-google-investigation/
(“[H]arm to competitors is not the same thing as harm to consumers or
competition more generally . . . .”).
5. Google Inc., FTC File No. 111-0163, at 3 (Jan. 3, 2013), http://www
.ftc.gov/sites/default/files/documents/public_statements/statement-commission
-regarding-googles-search-practices/130103brillgooglesearchstmt.pdf (statement
of the Federal Trade Commission regarding Google’s search practices)
(“[C]hanges to Google’s search algorithm could reasonably be viewed as
improving the overall quality of Google’s search results . . . .”).
6. Id. at 3.

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power in the search advertising market” is derived from control of
7
user data obtained through deceptive means.
Expanding on the concerns expressed in Rosch’s dissent, this
article will detail how understanding the dynamics of data mining
and behavioral targeting reveal the clear harm to consumers from
Google’s monopoly of the online search advertising market.
A.

The Pervasive Consumer Harm from Google’s Facilitation of User
Targeting by Its Advertisers

The most obvious harm is the undermining of competition in
the online advertising market, where higher prices charged to
advertisers inevitably get passed onto consumers in the form of
higher prices for the advertised goods and services they buy. I have
detailed the clear monopoly dominance of the search advertising
sector by Google and the ensuing general consumer harm from
8
such dominance elsewhere. So, this article will focus on the more
pervasive harm to consumers from the stunted “market” for user
data itself, where lack of vigorous competition means users too
readily share that data at too low a price—usually for free in
exchange for software services that cost companies like Google far
less than the value of the user data they collect.
Linked to that extraction of user data is the way Google helps
facilitate the engagement of advertisers in user profiling that aids
those companies in extracting the maximum profit possible from
consumers in the overall economy. Advertisers can deliver ads not
just to the users most likely to be interested in the product, but can
tailor prices for individual consumers in ways that can maximize
the revenue extracted from each purchaser. A story in 2012 about
the travel site Orbitz steering Mac owners to higher-priced hotels
and PC owners to lower-priced ones is a basic example of such a

7. Google Inc., FTC File No. 111-0163, at 1 n.1 (Jan. 3, 2013) (Rosch,
Comm’r, concurring and dissenting), http://www.ftc.gov/sites/default/files
/documents/public_statements/concurring-and-dissenting-statement-commission
er-j.thomas-rosch-regarding-googles-search-practices/130103googlesearchstmt.pdf
(concurring and dissenting statement of Commissioner J. Thomas Rosch
Regarding Google’s Search Practices) [hereinafter Rosch’s Statement].
8. Nathan Newman, Search, Antitrust, and the Economics of the Control of
User Data, 31 YALE J. ON REG. (forthcoming Summer 2014), available at
http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2309547.

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9

strategy, although the practice encompasses everything from
offering promotional discounts only to selected customers to
targeting subprime mortgage offers online at likely victims—which
were advertised heavily on Google during the company’s economic
10
rise. There is also strong evidence, including massive financial
sanctions against Google, that this targeting of ads empowers
11
criminal and “tawdry” (in Internet analyst Jaron Lanier’s words)
companies to exploit users online. At its worst, this data-miningsupported targeting of consumers may be empowering racial
12
profiling in new and disturbing ways as well.
Joseph Stiglitz and allied economic thinkers argue increasing
information asymmetry feeds increasing economic inequality as
well, such that the “result from the new information economics is
13
that issues of efficiency and equity cannot easily be delinked.” The
fact that many of Google’s largest advertising customers in the midpart of the last decade were linked to the subprime mortgage
14
industry, as will be detailed later in this article, is just one
indicator that understanding the dynamics of the search
advertising sector may give insight into larger theoretical problems
of market failure, the harm from predatory firms, and why we have
seen rising economic inequality in the economy over recent
decades.
As this article will detail, Google’s ascension as a dominant
player across a range of Internet services is giving its advertisers a
whole series of tools to target customers based on their individual
preferences, physical location, and other characteristics. This is
part of a rising asymmetry in knowledge between companies and
their customers across the economy due to the rise of data mining
and the power of “big data.”
9. Dana Matiolli, On Orbitz, Mac Users Steered to Pricier Hotels, WALL ST. J., June
26, 2012, at A1, available at LEXIS.
10. See infra Part V.C.
11. John Brockman, The Local-Global Flip, or, “The Lanier Effect”: A Conversation
with Jaron Lanier, EDGE (Aug. 29, 2011), http://edge.org/conversation/the-local
-global-flip.
12. See infra Part V.A.
13. Joseph E. Stiglitz, Information and the Change in the Paradigm in Economics,
92 AM. ECON. REV. 460, 479 (2002); see also George A. Akerlof, The Market for
Lemons: Quality Uncertainty and the Market Mechanism, 84 Q.J. ECON. 488, 488–500
(1970).
14. See infra Part IV.

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B.

Using Antitrust to Address Economic Inequality Due to Monopoly

With the information asymmetries driven by data mining and
behavioral profiling, Google facilitates exploitation of user data in
the online marketplace in ways that de facto transfer wealth
between the broader population to the company’s corporate
advertisers. The primary user harm identified by this analysis is not
just narrow economic profits returned to Google, but a much more
fundamental enrichment of its advertisers at the expense of
average consumers’ wallets and privacy. Given that, this analysis
also challenges the narrow conception of antitrust as a tool for
maintaining competition in the abstract and argues for it being
seen as a broader tool for promoting economic equality in more
structural terms.
While many antitrust scholars such as Robert Bork have seen
antitrust action as a limited tool for restoring the natural allocative
15
efficiency of the market, information economics scholars such as
Stiglitz argue that information asymmetry creates continual
disruptions of any “natural” market equilibrium. With no simple,
single equilibrium price and no single measure of “efficiency”
based on such an equilibrium, any pure efficiency analysis fails.
This is especially true in information markets themselves like
online advertising, where promoting more demand and convincing
customers to pay a higher price than they might have under any
supposed equilibrium price is the goal of advertising in the first
place. Advertising’s very existence is based on the reality—often
ignored in Chicago School-style economics—that individuals are
not perfectly informed of prices and quality differences, so there is
16
not necessarily an equilibrium price. And in a case where firms
can differentiate between customers, as Google allows through
behavioral profiling based on user data, traditional neoclassical
market analyses further fail as sellers slice markets into segments
based as much on the relative ignorance of different market

15. See ROBERT BORK, THE ANTITRUST PARADOX 107–15 (1978).
16. S. Salop & J.E. Stiglitz, The Theory of Sales: A Simple Model of Equilibrium
Price Dispersion with Identical Agents, 72 AM. ECON. REV. 1121, 1121 (1982) (noting
where “information is costly to gather . . . [and] individuals may not be perfectly
informed about the prices (or qualities) of what is being sold . . . the law of the
single price does not obtain”).

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17

segments of consumers as on any abstract demand curve. Most
important to antitrust analysis, strategic decisions by dominant
sellers themselves can shape the multiple equilibria prices in ways
18
that can further entrench their dominance.
Other scholars have argued that the original intent of antitrust
was not to act as a meta-consumer protection law simply policing an
ideal market, but was focused more specifically on challenging the
wealth transfers from the public to monopolists and oligopolists.
“Congress passed the antitrust laws to further economic objectives,
but primarily objectives of a distributive rather than of an efficiency
nature,” writes Robert Lande, “[i]n other words, Congress was
concerned principally with preventing ‘unfair’ transfers of wealth
19
from consumers to firms with market power.” In the case of
search advertising, this article will illustrate how “unfair” can be
understood operationally in this case in terms of a dominant search
advertising company exploiting consumer ignorance through data
mining to enrich both itself and its advertisers at consumer
expense.
II. THE FAILURE OF THE GOOGLE “MARKET” FOR USER DATA
Most defenders of Google argue that users engage in a rational
market exchange. In exchange for providing some personal data to
20
Google, those users get access to a valuable service. However,

17. Id. at 1122–23 (“[I]f firms have access to devices . . . which allow the firm
to differentiate between different groups in the population . . . and, if it is costly to
enter the market, no equilibrium exists.”); Steven Salop, The Noisy Monopolist:
Imperfect Information, Price Dispersion and Price Discrimination, 44 REV. ECON. STUD.
393, 393 (1977) (“[Cost] dispersion acts as a costly device for sorting consumers
into submarkets to permit price discrimination.”); see Rosa-Branca Esteves & Joana
Resende, Competitive Targeted Advertising with Price Discrimination (Universidade do
Minho Núcleo de Investigação em Políticas Económicas, Working Paper No. 08,
2011), available at http://ideas.repec.org/p/nip/nipewp/08-2011.html (discussed
infra in Part III).
18. J. Stiglitz & A. Weiss, Alternative Approaches to Analyzing Markets with
Asymmetric Information: Reply, 73 AM. ECON. REV. 246, 246–49 (1983).
19. Robert Lande, Wealth Transfers as the Original and Primary Concern of
Antitrust: The Efficiency Interpretation Challenged, 34 HASTINGS L.J. 65, 68 (1982); see
also Louis B. Schwartz, “Justice” and Other Non-Economic Goals of Antitrust, 127 U. PA.
L. REV. 1076, 1078 (1979) (stating that American imposition of antitrust measures
in post-war Japan and Germany was a political move to shift power).
20. Robert Bork, Antitrust and Google, CHI. TRIB., Apr. 6, 2012, at 19, available

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assuming that the market is functioning in such a case requires
(1) that those users properly value the benefits they receive from
Google, (2) that they properly price their personal information and
the opportunity cost of giving it up, and (3) that there are no
economic byproducts of Google’s monopoly control of user data
that reduce consumer welfare more generally. As this section will
detail, there is strong evidence that users do not properly calculate
any of those three factors in the exchange with Google, leading to
large costs to the public from Google’s dominance.
Without viable alternatives to Google, you end up with a
stunted “market” for valuing user privacy, so Google feels less and
less compunction about violating personal privacy to benefit its
advertising customers. While scholars like Frank Pasquale have
noted the danger of analyzing loss of privacy and other harms from
Google in just economic terms since that misses many of its non21
economic harms, those clear economic harms merit antitrust

at 2012 WLNR 7311753 (“No agency or critic has articulated a coherent theory of
how Google harms consumers. . . . Search algorithms speed to consumers what
they most likely want and direct advertisers to consumers most likely to want to buy
from them.”). Geoffrey Manne and Joshua Wright argue that search advertising is
just like any form of advertising, where the goal is to help consumers find
advertising for products that might interest them. Geoffrey A. Manne & Joshua D.
Wright, Google and the Limits of Antitrust: The Case Against the Case Against Google,
34 HARV. J.L. & PUB. POL’Y 171, 222 (2011) (“[A]ll forms of advertising—and
related endeavors like store placement and design—are about bringing buyers and
sellers together by minimizing some of the transaction costs that otherwise keep
them apart.”); see also Eric Goldman, A Coasean Analysis of Marketing, 2006 WIS. L.
REV. 1151, 1162–64 (providing a formulaic approach to evaluating consumer
utility derived from marketing exposure).
21. Frank Pasquale, Beyond Innovation and Competition: The Need for Qualified
Transparency in Internet Intermediaries, 104 NW. U. L. REV. 105, 143 (2010)
(“Engaging in a cost-benefit analysis diminishes privacy’s status as a right.”); see also
C. Edwin Baker, Media Concentration: Giving up on Democracy, 54 FLA. L. REV. 839,
857 (2002) (noting antirust largely ignores loss to public from monopoly “power
over the content available for consumer choice”). Pasquale also details many noneconomic harms from Google’s search monopoly, from mistaken same-name
reputational harms to unearthing credit reports or expunged records. Pasquale,
supra, at 114. Siva Vaidhyanathan also analyzes a wide range of non-economic
harms of Google’s concentrated dominance as well. See generally SIVA
VAIDHYANATHAN, THE GOOGLIZATION OF EVERYTHING (AND WHY WE SHOULD WORRY)
(2011).

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action even if other regulatory actions or legislation may be needed
22
to address the full gamut of privacy losses.
The deeper harm to consumers from Google’s power in the
market—and one that is at the heart of the increasing economic
inequality in our society—is the way Google’s profiling of its users
for advertisers allows the kind of predatory marketing we saw in the
subprime housing bubble globally and in a range of other sectors.
Online profiling based on user data allows seedier companies, from
subprime mortgage lenders to payday lenders, to target the most
naïve and vulnerable potential consumers and facilitate new forms
of price discrimination even by more legitimate firms that allow
those companies to extract the highest potential price for goods
23
and services from each customer. The result is harm to those
victimized consumers and is a likely explanation for the more
24
pervasive increase in economic inequality.
A.

Users Overestimate the Value Added by Google’s Services and Do Not
Receive the Full Economic Value of the Data They Share with Google

Without discounting the value added by Google’s aggregation
services in search and a range of its other products, a basic truth is
that most of the value delivered by Google is access to other
peoples’ labor and knowledge, most of which Google accesses for
free itself. With Google seeming to be the gateway to the Internet
itself, whether in search, YouTube videos, or Android apps, its value
can seem literally incalculable.
Media studies professor Clay Shirky details in Cognitive Surplus
how profound a shift in our models of production and markets is
underway in a world where people can access the fruits of not only
commercial production but, even more dramatically, “user
25
generated content” created outside any traditional marketplace.
22. See Frank Pasquale and Oren Bracha, who have promoted just such an
alternative regulatory approach to address such non-antitrust concerns about a
search monopoly in Federal Search Commission? Access, Fairness, and Accountability in
the Law of Search, 93 CORNELL L. REV. 1149 (2008).
23. See infra Parts III, V.
24. See infra Part VI.
25. CLAY SHIRKY, COGNITIVE SURPLUS: CREATIVITY AND GENEROSITY IN A
CONNECTED AGE 27 (2010) (“[T]he wiring of humanity lets us treat free time as a
shared global resource, and lets us design new kinds of participation and sharing
that take advantage of that resource.”).

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Where home production has been largely marginal in modern
society, the Internet suddenly makes “free time” incredibly valuable
when aggregated, yet returns little of that value to those producers.
Companies like Google take advantage of this peer production in
ways writer Nicholas Carr has referred to as “digital sharecropping,”
where the Internet “provides an incredibly efficient mechanism to
harvest the economic value of the free labor provided by the very
26
many and concentrate it into the hands of the very few.”
The incredibly outsized stock valuations of web-based firms
such as Amazon (with its user-generated product reviews),
Facebook (with its user-generated content and social links), and
Google (with its ability to search for others’ content, usergenerated YouTube videos, etc.) can best be understood in terms
27
of the cognitive surplus each is harvesting. It is one way to explain
how Google can have a stock market capitalization roughly the
28
same as AT&T, while employing one-fifth as many employees.
While such social media companies provide a service, they are in
fact using what is a relatively small investment to leverage the value
of others’ free labor by becoming the gateway for users to other
29
online user’s content. Given that its content largely comes from
other people and companies and is delivered over the common
Internet system, this is one argument for applying common-carrier
rules to the company and the right of the public for regulations

26. Nicholas Carr, Sharecropping the Long Tail, ROUGH TYPE (Dec. 19, 2006,
8:55 AM), http://www.roughtype.com/?p=634; see also VAIDHYANATHAN, supra
note 21, at 30 (“Google is taking a free ride on the creative content of billions of
content creators.”).
27. Conversely, when the free contributions to a social network dry up, a
once highly-valued company can become nearly worthless. The social news site
Digg, for example, was valued at one point at $160 million, but was sold for
$500,000 in 2012 as its community of users contributing content “started to drift
away in early 2010.” See Joseph Walker & Spenser Ante, Once a Social Media Star,
Digg Sells for $500,000, WALL ST. J., July 13, 2012, at B3, available at LEXIS.
28. See Nathan Newman, Job Creation Will Come from the Wires, Not the
Software of Broadband Internet, HUFFINGTON POST (Oct. 10, 2011, 3:30 PM),
http://www.huffingtonpost.com/nathan-newman/corporate-outsourcing-jobs_b
_1005269.html.
29. VAIDHYANATHAN, supra note 21, at 16 (detailing how Google gained its
dominance because it delivers “video and text to users, even if much of that
content is hosted on other institutions’ sites”).

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ensuring fair and equitable access to the content that Google is
30
leveraging itself for free.
Google’s innovation in search technology was, in fact, built
around harvesting the diffuse labor of people across the Internet.
Its original PageRank algorithm used the links to other websites
created by website creators across the Internet as a tool to assess
and rank the likely value of websites containing similar information
31
or keywords. This system of highly ranking websites valued by
other users has been enhanced by also measuring what sites
32
Google’s own users click on when they make a particular search.
Each click adds to the algorithm that can direct users with similar
searches and interests to see the same link become highly ranked
when they make a search as well. The more people find and use
other people’s content via Google, the better Google’s algorithm
becomes, reinforcing the precision and strength of its search
engine vis-à-vis any challenger search technology, which would lack
access to the network of users and the information they generate
33
on search preferences. Other Google services such as YouTube or
Gmail play out much the same dynamic, with users gaining
important technological advantages from using Google but
ultimately getting greater value from the labor of other users,
thereby confusing any simple economic valuation of what Google is
providing. This also apparently confuses many analysts who
attribute greater innovation to Google when its search quality
advantages are in fact due to the monopoly dominance that gives it
such a disproportionate share of user data.
What Google, Facebook, and other online gateways are
tapping is a psychological drive to share with others that is quite
distinct from the simple self-interested economic market models
most economists depend upon for understanding how value in
both production and consumption is measured and where the
34
motivation for its creation is derived. To encourage its users to

30. See Newman, supra note 8, (manuscript at 68–69).
31. VAIDHYANATHAN, supra note 21, at 21.
32. See James Grimmelmann, The Google Dilemma, 53 N.Y. L. SCH. L. REV. 939,
941–42 (2008/09); Pasquale, supra note 21, at 116 n.50.
33. See Pasquale, supra note 21, at 116 n.50.
34. Scholars Yochai Benkler and Helen Nissenbaum have described how
“common-based peer production” systems tap a whole complex of social desires
for autonomy and competence whose rewards are more related to social

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share content freely on its services, Google has publicly adopted
multiple markers of peer-based production. Most famously, Google
adopted in its early mission statement that it would “make money
35
without doing evil,” or more simply, “don’t be evil” as stated in the
36
first words of Google’s code of conduct. Combined with ostensibly
providing its own free content to users, this mantra was a clear
signal to users that the company was “one of them” in promoting
37
shared value through collaboration. However, Google could seem
to be acting in a collaborative way with its users because its key
advertising revenue source was based on collecting—and not
sharing—intimate user data from those “collaborators.”
B.

Users Undervalue the Economic Value of the Data They Share with
Google

If users attribute too much of the value they gain from
accessing online content to Google, they also clearly underestimate
the economic value of the personal data they share with Google in
exchange for accessing its services. Because there is no price paid
for the data by Google, or paid by users for the Google products
those users use, the result is a zero price barter exchange. As David
Evans notes, this results in “conundrums and confusion in antitrust
analysis” since gains or losses on price, quality, and other factors for
38
users in a zero price exchange are disguised. Standard antitrust
analysis loses the price measure for evaluating such issues, since, as
39
Evans highlights, “[five] percent of zero is still zero.”
On the face of it, the fact that Google is de facto involved in a
barter relationship with its users—trading its tools for their

relationships than traditional market forces. See generally Yochai Benkler & Helen
Nissenbaum, Commons-Based Peer Production and Virtue, 14 J. POL. PHIL. 394 (2006).
35. Ten Things We Know to Be True, GOOGLE, http://www.google.com/about
/company/philosophy/ (last visited Dec. 8, 2013).
36. Code of Conduct, GOOGLE, http://investor.google.com/corporate/code-of
-conduct.html (last visited Dec. 8, 2013).
37. See Jeffrey Van Camp, Is Google Still Worth Our Love, or Has It Become
Another Selfish Corporation?, DIGITAL TRENDS (Mar. 15, 2012), http://www
.digitaltrends.com/opinion/is-google-still-worth-our-love-or-has-it-become-another
-selfish-corporation.
38. David S. Evans, The Antitrust Economics of Free, 7 COMPETITION POL’Y INT’L
71, 72 (2011).
39. Id.

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individual private information—is a pretty clear indication that
users are unlikely to be getting the full market value of their data—
and means that analyzing the situation in terms of economic
40
models of market exchange makes little sense. Like most barter
economies, pricing is opaque and creates massive opportunities for
economic arbitrage by the sophisticated side of the barter
transaction—i.e., Google. Essentially Google users are the primitive
tribes of the Internet, accepting the shiny trinkets of Gmail and
free search in exchange for their privacy. As anthropologists will
attest about such primitive systems of nonmarket exchange, they
can be dynamic and productive in ways market economies may not
41
be in certain situations, just as writers like Clay Shirky, Yochai
Benkler, and Helen Nissenbaum describe how modern
42
collaborative “peer production” online can be wildly productive.
But what is true is that the interaction of the market with such
43
nonmarket systems is a recipe for economic exploitation.
A large part of the problem is that multiple studies show most
users do not even understand that their private data shared with
online companies like Google are being shared with third parties to
44
assist in marketing advertising. This largely reflects that sharing

40. There is a rich anthropological tradition critiquing the reduction of
nonmarket barter relationships to a simple market equivalence. Caroline
Humphrey has written, “No example of a barter economy, pure and simple, has
ever been described.” DAVID GRAEBER, DEBT: THE FIRST 5000 YEARS 29 (2011).
41. See MARCEL MAUSS, THE GIFT: FORMS AND FUNCTIONS OF EXCHANGE IN
ARCHAIC SOCIETIES (Ian Cunnison trans., 1966).
42. SHIRKY, supra note 25, at 78–82; see also Benkler & Nissenbaum, supra note
34, at 402.
43. Karl Polanyi has been one of the foremost documenters of the historical
disruptions where market and nonmarket systems have collided. See KARL POLANYI,
THE GREAT TRANSFORMATION (1944); KARL POLANYI, TRADE AND MARKET IN THE
EARLY EMPIRES: ECONOMIES IN HISTORY AND THEORY (Karl Polanyi et al. eds., 1957);
see also Paul Bohannan, The Impact of Money on an African Subsistence Economy, 19 J.
ECON. HIST. 491, 491–503 (1959).
44. PONNURANGAM KUMARAGURU & LORRIE FAITH CRANOR, PRIVACY INDEXES:
A SURVEY OF WESTIN’S STUDIES 13 (2005), available at http://reports-archive.adm.cs
.cmu.edu/anon/isri2005/CMU-ISRI-05-138.pdf (finding about half of Americans
believe that “most businesses handle the personal information they collect about
consumers in a proper and confidential way”); Jan Whittington & Chris Jay
Hoofnagle, Social Networks and the Law: Unpacking Privacy’s Price, 90 N.C. L. REV.
1327, 1357 (2012) (“American consumers profoundly misunderstand the rules
underlying these transactions; they do not understand the terms of trade.”);

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the data is a default when signing up with a service, with little
information shared with users to educate them about the
consequences of sharing their data. The massive amount of data
being shared online does not reflect public preferences: a 2012
Pew survey shows that seventy-three percent of the American public
were opposed to search engines even tracking their search history
to improve search results, and sixty-eight percent opposed use of
45
user data to assist advertisers in targeting advertisements. But most
of those users expressed no capacity to control what data is shared
46
online. Other researchers found that desires to stop tracking,
aggregating, and disseminating personal information have been
47
increasing. Yet almost nowhere do defenders of Google factor in
the costs to consumers of loss of privacy, yet as Peter Swire has
noted, the nature of data aggregation is such that consumers with
high privacy desires lose as data is concentrated in one company’s
48
hands.
Notably, while dismissing the search bias antitrust claim
against Google, Federal Trade Commissioner J. Thomas Rosch
expressed concern that Google’s “monopoly or near-monopoly
power in the search advertising market” derives from Google
“telling ‘half-truths’—for example, that its gathering of information

see Alessandro Acquisti & Jens Grossklags, What Can Behavioral Economics Teach Us
About Privacy?, in DIGITAL PRIVACY: THEORY, TECHNOLOGIES AND PRACTICES 363,
363–64 (Alessandro Acquisti et al. eds., 2008) (stating that bounded rationality,
optimism bias, and information asymmetry lead consumers to undervaluing
personal information); Chris Jay Hoofnagle & Jennifer King, Research Report:
What Californians Understand About Privacy Offline 9–19 (May 15, 2008)
(unpublished manuscript), available at http://papers.ssrn.com/sol3/papers.cfm
?abstract_id= 1133075.
45. KRISTEN PURCELL ET AL., PEW RESEARCH CTR., SEARCH ENGINE USE 2012,
at 2 (2012), available at http://www.pewInternet.org/~/media/Files/Reports
/2012/PIP_Search_Engine_Use_2012.pdf.
46. Id. at 3 (“Just 38% of Internet users say they are generally aware of ways
they themselves can limit how much information about them is collected by a
website.”).
47. Avi Goldfarb & Catherine Tucker, Shifts in Privacy Concerns, 102 AM.
ECON. REV. 349, 349 (2012) (explaining that millions of online decisions analyzed
show a rising desire for privacy online).
48. Peter P. Swire, Submitted Testimony to the Federal Trade Commission for
Behavioral Advertising Town Hall, EUR. PARLIAMENT 4 (Oct. 18, 2007), available at
http://www.europarl.europa.eu/meetdocs/2004_2009/documents/dv/testimony
_peterswire_/Testimony_peterswire_en.pdf (written testimony of Peter Swire).

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about the characteristics of a consumer is done solely for the
consumer’s benefit, instead of also to maintain a monopoly or
49
near-monopoly position.” He cited precedent that a company’s
claims to be acting on behalf of consumers while downplaying
potential consumer harms not fully disclosed could create legal
50
liability.
Google’s barter for user privacy may be opaque and primitive,
but that contrasts sharply with the way the company monetizes that
personal data to advertisers who pay very precise dollar terms in the
51
modern part of the Google economy. And those advertisers pay
prices far above the costs spent by Google on the tools provided to
52
users—as highlighted by Google’s massive profits year after year.
That advertising side of Google’s internal economy is actually a
monument to converting privacy into a modern currency, with
sophisticated auctions for key words and phrases based on
particular user demographics and backgrounds that the advertiser
53
may be looking for. One analyst describes this has less to do with
the sale of privacy itself by Google, but rather the sale of a “privacy
derivative,” where companies invest in Google’s appraisal of
54
customers’ needs and wants.
C.

Why Aren’t Users Paid for Their Data?

Some Google defenders ask, what could be better for
consumers than getting all of Google’s services free? This is part of
49. Rosch’s Statement, supra note 7, at 1 n.1.
50. Id. (citing N. Am. Philips Corp., 111 F.T.C. 139, 188 (1988) (initial
decision) (arguing that half-truths can be deceptive); Int’l Harvester Co., 104
F.T.C. 949, 1057 (1984) (“[I]t can be deceptive to tell only half the truth, and to
omit the rest.”)).
51. Hal Varian, How Auctions Set Ad Prices, GOOGLE BLOG (May 12, 2008),
http://googleblog.blogspot.com/2008/05/how-auctions-set-ad-prices.html.
52. Google reported annual revenue of $50 billion in 2012—a thirty-two
percent increase from a year earlier––with annualized profits of over $14 billion
per year. Casey Newton, Google Revenue Hits $14.42B in Fourth Quarter, Up
36 Percent, CNET (Jan. 22, 2013, 1:10 PM PST), http://news.cnet.com/8301-1023
_3-57565236-93/google-revenue-hits-$14.42b-in-fourth-quarter-up-36-percent/.
53. Reach People Interested in Your Products or Services, GOOGLE SUPPORT,
https://support.google.com/adwords/answer/2497941?hl=en (last visited Dec.
25, 2013); Varian, supra note 51.
54. Karl T. Muth, Googlestroika: Privatizing Privacy, 47 DUQ. L. REV. 337, 343
(2009). For further discussion on how Google monetizes user privacy, see id.

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obscuring the economic value of personal data, much as early bank
customers might not have expected more of banks than protecting
their money in a vault for free until competitors began offering to
pay them interest on that money deposited and offering rewards to
customers using their credit cards. Economists regularly note that
in two-sided markets where commercial interests, such as credit
card companies, want a large base of users of a product, users on
one side of the transaction are regularly paid to adopt the
55
product. Just as banks leverage deposits to make money lending it
out, Google makes money off of personal data deposited with
them––yet a legal question is, why don’t most Google users get a
cut of the money Google makes off of their data?
Along with the general ignorance discussed above, Google
thrives on the expectations of freely shared, online “peer
production,” which, as media professor Clay Shirky highlights, has
a whole value system eschewing expectation of any precise quid pro
56
quo exchange of value. Based on research that shows more
57
voluntary activity when payment is not involved, Google’s quasibarter relationship with its users may potentially be eliciting more
free content and information from its users than if it actually paid
them for it.
With all this, the first step in the transfer of wealth via Google
is from users selling their privacy for too little and Google
arbitraging user ignorance and their psychological mode of
collaboration over market exchange for profit. This is the product
of Google largely having the field to itself without serious
competitive pressure to actually offer users the real value of their
data. Competitors have tried to introduce models where users get a
58
cut of the advertising revenue generated, but with Bing losing
55. See, e.g., Marc Rysman, The Economics of Two-Sided Markets, 23 J. ECON.
PERSP. 125, 129 (2009).
56. See SHIRKY, supra note 25, at 131–59. See generally Benkler & Nissenbaum,
supra note 34, at 394.
57. See Bruno S. Frey & Lorenz Goette, Does Pay Motivate Volunteers? (Univ. of
Zurich Inst. for Empirical Research in Econ., Working Paper No. 7, 1999),
available at http://ideas.repec.org/s/zur/iewwpx.html (offering money depressed
the number of hours of labor the average volunteer contributed).
58. Boaz Berkowitz, Cha-Ching: Microsoft Pays Users to Search with Bing, SEEKING
ALPHA (Aug. 10, 2009, 1:16 PM), http://seekingalpha.com/article/155148-cha
-ching-microsoft-pays-users-to-search-with-bing; Robin Harris, Microsoft Stops Paying
Us to Use Bing, ZDNET (June 6, 2010, 11:14 AM), http://www.zdnet.com/blog

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59

$2.5 billion per year already, it’s hardly surprising few companies
have moved very far in the direction of further increasing their
losses.
The result is that there is then little pressure on Google to
offer anything to users out of its quite substantial profits from
marketing user data to advertisers. Google did begin a small pilot
program in 2012 called Google Search Screenwise that offers
twenty-five dollars per year to a select set of people using the
Chrome browser, although the numbers were limited and Google
framed the plan not as a general reimbursement of users for using
60
their data but merely a market research survey. So Google can dip
its toe into paying a few users for even deeper revelations of their
private activity while encouraging the vast majority of its users to
continue thinking of participation in its services and sharing their
data in nonmarket terms.
However, if Google had less dominance of the online
advertising field, there would be far greater pressure for Google to
develop as sophisticated a market for users to be compensated for
their privacy as the precision of the markets in which it resells that
61
lost privacy to advertisers.
III. WHY USER DATA IS SO USEFUL TO ADVERTISERS: “PAIN POINTS”
AND THE CONSUMER HARM OF PRICE DISCRIMINATION FACILITATED
BY A MONOPOLY PLAYER LIKE GOOGLE
62

Clearly, given Google’s advertising profits, the user data the
company collects is incredibly valuable and a number of analysts
have put a price on what that data is worth for each individual user.
For example, Michael Fertik, CEO of the company
Reputation.com, a service to help consumers keep their personal
information anonymous online, estimates that data can be worth
up to $5000 per person per year to advertisers, depending on how
/storage/microsoft-stops-paying-us-to-use-bing/960.
59. Robert Cyran, Microsoft Ought to Kick off Search for Bing Buyer, REUTERS
(July 22, 2011, 4:01 PM), available at Westlaw.
60. Jeff Bertolucci, Google Search’s Screenwise vs. Bing Rewards: Which Pays
More?, PCWORLD (Feb 9, 2012, 2:27 PM), http://www.pcworld.com/article
/249683/google_searchs_screenwise_vs_bing_rewards_which_pays_more_.html.
61. See Rysman, supra note 55, at 131 (noting how competition in credit card
payment systems has increased rewards payment to consumers).
62. See Newton, supra note 52.

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much those users spend and how the data is used by online
63
companies like Google. McKinsey has estimated that data mining
broadly can increase operating margins by sixty percent for
64
companies.
To get some sense of the value of user information, look at the
recent controversy over another big Internet player, namely Apple,
when it demanded that sellers of subscriptions to apps on the
iPhone give them not just thirty percent of sales, but sole control of
65
user information as well. Analyst Lauren Idvik noted that
publishers like the Financial Times may not have liked the thirty
percent cut Apple wanted from subscriptions, but “the main
problem is that Apple will not share subscriber data with
publishers, long one of publishers’ most valuable assets, particularly
66
to advertisers.” That the personal data, not the thirty percent cut,
was the real sticking point in negotiations indicates that personal
information is worth potentially more than thirty percent of the
cost of what you purchase online, yet most users give it away for
free to companies like Google and Apple.
As discussed further in the remedies section, any governmental
action that strengthens user privacy rights, such as requiring an
opt-in agreement for each specific use of their data by anyone
collecting the information, would both reduce the amount of
personal data being extracted and create a potential “friction”
point where Google and other related data miners might feel
compelled to pay users at least part of what that data is worth to
convince them to share their private data, as well as guarantee
better security for that data.

63. Quentin Fottrell, Who Would Pay $5,000 to Use Google? (You), MARKET
WATCH (Jan. 25, 2012, 12:24 PM), http://blogs.smartmoney.com/advice/2012/01
/25/who-would-pay-5000-to-use-google-you/ (“‘Their entire market cap is related
to how much data is being collected and used,’ says Jules Polonetsky, director of
the Future of Privacy Forum, a Washington, D.C.-based think-tank.”).
64. JAMES MANYIKA ET AL., MCKINSEY GLOBAL INST., BIG DATA: THE NEXT
FRONTIER FOR INNOVATION, COMPETITION, AND PRODUCTIVITY 2 (2011),
available at http://www.mckinsey.com/insights/business_technology/big_data
_the_next_frontier_for_innovation.
65. Lauren Indvik, Financial Times Refuses to Give up Subscriber Data to Apple,
MASHABLE (Apr. 4, 2011), http://mashable.com/2011/04/04/financial-times
-subscriptions-apple/.
66. Id.

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That initial loss by users of giving their private information
away too cheaply is just the start of the consumer harm from
Google’s dominance of the online advertising marketplace and its
control of user data. The deeper potential harm, as will be
discussed below, stems from the reason companies pay Google such
a premium for that data in serving up advertisements to them
based on that personal information.
The most positive spin on this use of user data for targeting
ads is that it helps those companies find the customers interested in
their products—and that’s part of the story. But it’s not just finding
customers; it’s finding out what price different groups of customers
will pay for the same product or service and marketing it separately
to them at those different prices.
The darker version of online marketing is that it can facilitate
what economists call “price discrimination,” selling the same exact
67
good at a variety of prices, often in ways unknown to the buyers.
This is based on the reality that people have different maximum
prices that they are willing to pay, a so-called “pain point” after
68
which they won’t buy the product. The ideal for a seller would be
to sell a product to each customer at their individual “pain point”
price without them knowing that any other deal is available. In
general, economists believe that where consumers do know all the
pricing options, they can potentially benefit from price
69
discrimination. The classic example is airline pricing, where
consumers willing to book ahead and take only certain flights get a
lower price, while more well-off or time-sensitive consumers will pay

67. Price Discrimination, MERRIAM-WEBSTER, http://www.merriam-webster.com
/dictionary/price%20discrimination (last visited Jan. 30, 2014) (“the offering of
similar or identical goods at different prices to different buyers”).
68. IAN AYRES, SUPER CRUNCHERS: WHY THINKING-BY-NUMBERS IS THE NEW WAY
TO BE SMART 190 (2007) (analyzing ways firms use data mining to set
individualized coupon discounts even at traditional stores and noting “[firms] are
becoming more adept at figuring out how much pricing pain individual
consumers are willing to endure and still come back for more”).
69. For a general survey of the literature, see WILLIAM W. FISHER III
& TALHA SYED, INFECTION: THE HEALTH CRISIS IN THE DEVELOPING WORLD
AND WHAT WE SHOULD DO ABOUT IT (forthcoming) (manuscript at ch. 6),
available at https://cyber.law.harvard.edu/people/tfisher/Infection.htm (“[P]rice
discrimination almost always benefits manufacturers. Sometimes it also benefits
society at large; sometimes not.”). See generally Hal Varian, Price Discrimination and
Social Welfare, 75 AM. ECON. REV. 870 (1985).

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more for the same seat to book at the last minute for a specific
flight. This arguably fills seats, increases revenues for the airline,
and gives some people access to cheaper seats that might not be
70
available at all at the lower price without price discrimination.
The problem arises when consumers don’t have all needed
information. As economist Joseph Stiglitz describes, “the presence
of information imperfections give rise to market power in product
markets. Firms can exploit this market power through ‘sales’ and
other ways of differentiating among individuals who have different
71
search costs.”
With public advertising, a customer willing to pay a higher
price will generally demand the lower price advertised to someone
else, although they may not notice the alternative ad, creating some
imperfections in the marketplace. However, data mining and
targeted Internet advertising allows sellers to make different
advertising offers to particular groups of consumers based on
correlations derived from past behavior or user location that are
essentially invisible to anyone charged a higher price or missing out
on a coupon. A 2012 Wall Street Journal report found that major
companies, including Staples, Home Depot, Discover Financial
Services, and Rosetta Stone, were systematically using information
on user physical locations to display different online prices to
72
different customers. And contrary to the hope that such price
discrimination might benefit low-income bargain hunters, the Wall
Street Journal found that “areas that tended to see the discounted
prices had a higher average income than areas that tended to see
higher prices,” largely on the assumption that poor areas have

70. John Lazarev, The Welfare Effects of Intertemporal Price Discrimination:
An Empirical Analysis of Airline Pricing in U.S. Monopoly Markets 4–5 (Jan. 7,
2013) (unpublished manuscript), available at https://files.nyu.edu/jl5214/public
/Lazarev_JMP.pdf.
71. Stiglitz, supra note 13, at 470; see also Salop, supra note 17, at 393–406;
Steven Salop & Joseph Stiglitz, Bargains and Ripoffs: A Model of Monopolistically
Competitive Price Dispersion, 44 REV. ECON. STUD. 493 (1977), reprinted in 1 THE
ECONOMICS OF INFORMATION 198 (David K Levine & Steven A. Lippmann eds.,
1995); Joseph E. Stiglitz, Monopoly, Non-Linear Pricing and Imperfect Information: The
Insurance Market, 44 REV. ECON. STUD. 407, 407–30 (1977).
72. Jennifer Valentino-Devries et al., Websites Vary Prices, Deals Based on Users’
Information, WALL ST. J., Dec. 24, 2012, at A1, available at LEXIS.

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fewer retail options locally so a higher price can be extracted from
73
them by online retailers.
In the case of search advertising, the New York Times in 2010
profiled how web coupons are deployed to target offers based on
user behavior, including with different coupon offers being made
based on different search terms on Google. As Ed Mierzwinski,
consumer program director for the United States Public Interest
Research Group (USPIRG) noted in a New York Times interview,
companies “offer you, perhaps, less desirable products than they
offer me, or offer you the same product as they offer me but at a
74
higher price.” USPIRG has asked the Federal Trade Commission
for tighter rules on all online advertising precisely because of this
75
problem. In his book Super Crunchers, Ian Ayers describes how data
mining and selective discount offers to individuals is making prices
76
increasingly opaque to consumers. Offering only full-price offers
to some online buyers while selectively offering discounts to others
based on online profiling is one of the most pervasive forms of
77
price discrimination operating in online sales.
Despite hopes that online commerce would create greater
consumer empowerment to engage in price comparisons, such
hidden price discrimination frustrates that hope and adds to the
shifting of power in overall online bargaining to sellers. Firms have
also invested in a range of online strategies, from mandatory addons to multiple versions of a product to deliberately complicated
descriptions designed to frustrate simple price comparisons
between sites. Glenn and Sara Fisher Ellison have detailed these
“price obfuscation” strategies and found they can regularly lead to
far higher markups, even for commodity technology goods like
memory modules, than would be expected in a more frictionless

73. Id.
74. Stephanie Clifford, Coupons from Internet Know a Lot About You, and They
Tell, N.Y. TIMES, Apr. 17, 2010, at A1, available at 2010 WLNR 7964510.
75. Id.
76. AYERS, supra note 68, at 190 (“[Retail stores] can print out tailored
coupons with prices just for you. . . . In a world of Super Crunching, it’s going to
be a lot harder to rely on other consumers to keep your price in line.”).
77. Natasha Singer, You for Sale: Mapping, and Sharing, the Consumer Genome,
N.Y. TIMES (June 17, 2012), 2012 WLNR 12625198 (“Acxiom . . . assigns consumers
to one of 70 detailed socioeconomic clusters and markets to them accordingly. . . .
[with sellers making] customized appeals anytime, anywhere.”).

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market. For example, where the Ellisons argue a markup of three
percent to six percent would be expected for commodity products
like memory modules, they found markups of twelve percent on
78
average.
This all undercuts any model of online commerce that
resembles the neoclassical ideal of a single equilibrium price for
goods. Instead it far more reflects the information economics
model of high search costs and variations in consumer rationality
being used by firms to create a dispersion of prices. This allows
firms to evaluate those search costs for different consumers and set
prices in ways that extract the maximum revenue from each
79
transaction. A key point from evaluating consumer welfare is that
despite any advertised “bargains” or sales, overall prices in such a
regime of obscured prices and seller price discrimination end up
higher than any model of competitive prices where all price
80
information was openly known and advertised. Where such price
dispersion and obscured information exists, firms have a quasimonopolistic power to set prices which, as Steven Salop and Joseph
Stiglitz outline, “they would be unable to do in a competitive
81
market with perfect [price] information.”
The Economics of Price Discrimination in Google’s Business Plan
The question is how central facilitating such price
discrimination is to Google’s business model. Given that Google
appointed Hal Varian, who has written extensively about price
82
discrimination in online advertising for decades, to be the
company’s Chief Economist in 2005, the answer seems to be that
it’s likely quite central to their model.
That same year, Varian outlined the advantages to advertisers
of online marketing and price discrimination in a piece he
coauthored for the journal Marketing Science that echoed many of
78. Glenn Ellison & Sara Fisher Ellison, Search, Obfuscation, and Price
Elasticities on the Internet, 77 ECONOMETRICA 427, 427–29 (2009) (“Obfuscation can
be thought of as an action that raises search costs, which can lead to less consumer
learning and higher profits.”).
79. Salop & Stiglitz, supra note 71, at 493–96.
80. Id. at 502.
81. Id. at 509.
82. Hal Varian’s writing on price discrimination dates back at least to 1980 in
his paper, Hal R. Varian, A Theory of Sales, 70 AM. ECON. REV. 651 (1980).

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the basic insights of information economics in the context of
83
online sales. Varian, Google’s Chief Economist, highlights the
failure of most price discrimination to yield profits in traditional
marketing because of the visibility of different prices to most
customers, but that “significant initial investments in information
technology can lead to competitive advantages” that lock in user
loyalty while collecting personal information to make price
84
discrimination profitable. As he describes:
Because so many transactions are now computer
mediated, and these computers can easily be networked to
data centers, sellers now have the ability to access
databases of past purchases in real time. This allows them
to condition current offers to consumers on their previous
purchase behavior. Sellers can offer each individual a
different price, a particular prize or coupon, or
personalized recommendations. With computer-mediated
transactions, price discrimination on an individual basis
85
becomes quite feasible.
Varian notes that differential pricing will be most effective on the
“fraction of the potential population [that] is myopic and ignores
the impact of their current behavior on future offerings” and how
undermining the ability of users to make their behavior anonymous
increases the costs to users of evading price discrimination—
a point he hits repeatedly in the piece and a good explanation of
86
Google’s focus on obliterating anonymous browsing online.
By locking users in to particular services, building loyalty (or
just making it a chore to log in or out of the online service), and
designing a “selling platform with the goal of making the adoption
87
of defensive technologies prohibitively costly for the consumer,”
companies will increase their profits at the expense of their
customers, particularly the “myopic” ones, even under competitive
markets.
While Varian’s example in 2005 was clearly about Amazon, the
measures he focused on—user lock-in, integrated user profiles,

83. Alessandro Acquisti & Hal R. Varian, Conditioning Prices on Purchase
History, 24 MARKETING SCI. 367 (2005).
84. Id. at 380.
85. Id. at 367.
86. Id. at 380.
87. Id. at 374.

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defeating anonymity—describe exactly the systematic deployment
of products and systems Google has pursued as well. As early as
2004, Google was applying for patents on how to sell advertising
based on such behavioral and demographic tracking, where one
patent specified, “advertisements are personalized in response to a
88
search profile that is derived from personalized search results.”
Since 2009, Google has been rolling out beta tests of such
behavioral profiling for advertisers and in 2011 fully implemented
its coordination of advertising with targeting demographic groups
identified by Google based on user browsing activity, behavior, and
89
physical location. So companies working with Google can more
and more effectively segment the market by demographic profiles
yielding the “myopic” customers who will pay the maximum price
90
based on their demographic and behavioral characteristics.
Varian’s analysis focuses on a number of scenarios where
sellers use price discrimination to increase overall sales. In many,
any overall economic value added in the economy “is entirely due
91
to the increased profit received by the seller,” while in a number
of other scenarios outlined by Varian, consumer welfare as a whole
actually falls. Even if economic efficiency overall strengthened in
some scenarios, the fact that those gains include a large loss for
some or, in many cases, all consumers to the advantage of sellers
emphasizes that the argument that technology increases overall
“consumer welfare” means little if all of the increased economic
growth goes only to sellers at the expense of actual consumers.
Courts and many scholarly analysts have emphasized that the

88. U.S. Patent Application No. 10/877775 (filed June 24, 2004),
available at http://appft1.uspto.gov/netahtml/PTO/search-adv.html (search for
“20050222989”).
89. Pamela Parker, Google Rolls Out Behavioral Targeting to All AdWords
Advertisers, SEARCH ENGINE LAND (June 23, 2011, 6:09 PM), http://searchengine
land.com/google-rolls-out-behavioral-targeting-to-all-adwords-advertisers-82976.
90. See Ahmadali Arabshahi, Google’s Groupon Strategy: Algorithmic PriceSensitivity Quotients, AHMADALI’S BLOG (Jan. 17, 2011), http://www.ahmadalia.com
/blog/2011/01/google-groupon-strategy.html (detailing how such behavioral
tracking can work for Google in creating a profile for advertisers that helps
identify price-sensitive versus price-insensitive customers). Arabshahi sees Google’s
launch into Groupon-like offers working with local businesses as a way for Google
to better monetize its data on its users. Id.
91. Acquisti & Varian, supra note 83, at 372.

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92

Sherman Act is not an economic efficiency maximization statute
and that productivity gains from monopoly-maintaining innovations that benefit sellers at the expense of consumers still
93
constitute a violation of antitrust law.
Rosa-Branca Esteves and Joana Resende in more recent
research highlight the ways that, because of the low costs of online
94
advertising,
such online price discrimination can reduce
95
consumer surplus to the advantage of corporate profits. They
emphasize that models of price discrimination that benefit
consumers are based on the assumption that consumers are
perfectly informed of all available prices, but with imperfect
consumer information and targeted advertising, models shift
towards price discrimination benefiting company profits at the
96
expense of consumers. One implication of their models is that
“average prices with mass advertising (nondiscrimination) are
below those with targeted advertising,” which follows the idea that
firms will target certain consumers with promotions while enjoying
higher prices paid by Varian’s “myopic” consumers unaware of
97
discounts offered to others.

92. 15 U.S.C. §§ 1–7 (2012).
93. See, e.g., Weyerhaeuser Co. v. Ross-Simmons Hardwood Lumber Co.,
549 U.S. 312, 323 (2007); Brooke Grp. Ltd. v. Brown & Williamson Tobacco Corp.,
509 U.S. 209, 224 (1993); Jefferson Parish Hosp. Dist. No. 2 v. Hyde, 466 U.S. 2, 15
(1984), abrogated by Ill. Tool Works Inc. v. Indep. Ink, Inc., 547 U.S. 28 (2006);
Reiter v. Sonotone Corp., 442 U.S. 330, 343 (1979); Einer Elhauge, Tying, Bundled
Discounts, and the Death of the Single Monopoly Profit Theory, 123 HARV. L. REV. 397,
435–36 (2009) (citing NCAA v. Bd. of Regents of Univ. of Okla., 468 U.S. 85, 107
(1984)).
94. See generally Esteves & Resende, supra note 17. Esteves and Resende
contrast their results when low advertising costs are assumed with disputed studies
over whether, in cases of more costly conventional advertising, targeted advertising
increases profits. Id. Compare Nada Ben Elhadj-Ben Brahim et al., Is Targeted
Advertising Always Beneficial?, 29 INT’L J. INDUS. ORG. 678, 685 (2011) (“When the
advertising cost is high, targeting reduces firms’ profits relative to random
advertising.”), with Ganesh Iyer et al., The Targeting of Advertising, 24 MARKETING
SCI. 461, 461 (2005) (“[T]he targeting of advertising increases equilibrium
profits.”).
95. Esteves & Resende, supra note 18, at 1 (“[P]rice discrimination through
targeted advertising may be detrimental to social welfare since it boosts industry
profits at the expense of consumer surplus.”).
96. Id. at 6–7.
97. Id. at 28.

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IV. THE CASE FOR LEGAL ACTION ON CONSUMER HARM FROM PRICE
DISCRIMINATION
With so much of seller profit from price discrimination online
derived from exploitation of “myopic” customers failing to know
98
about or find cheaper alternatives to the prices offered them, a
number of antitrust theorists who focus on allocative efficiency
argue price discrimination is one category of consumer harm that
demands legal action.
99
In his article Unconscionability and Price Discrimination, Mark
Klock, while accepting most traditional Chicago School skepticism
of government regulation in the marketplace, argues that any
situation where one set of consumers is unknowingly paying more
for the same product than others is a clear sign of a failure in the
marketplace that calls for government intervention. He is skeptical
100
of hypothetical cases of consumer gain from price discrimination
and argues, “[a] sound policy would prohibit firms from charging
101
different prices based solely on the identity of the customer.”
Echoing the studies discussed above, Klock and others argue such
price discrimination established under the aegis of a monopolist in
102
the marketplace is even more harmful to consumer welfare.
Douglas M. Kochelek has also highlighted that the rise of data
mining online has made the problem of price discrimination far
more pervasive in the economy, raising the importance of
103
deploying antitrust as a curb on dominant players using it.
Given that Google’s control of user data to facilitate price
discrimination is based at least partially on tying so many services
that extract that data into its core search advertising product, it’s
worth emphasizing that the Supreme Court has condemned
traditional tying in many cases because it allowed companies to
98. Acquisti & Varian, supra note 83, at 380.
99. Mark Klock, Unconscionability and Price Discrimination, 69 TENN. L. REV. 317
(2002).
100. See id. at 358 (dismissing the “empirically unsubstantiated case in which
price discrimination achieves allocative efficiency”).
101. Id. at 367.
102. Id. at 329 (“Economists consider the price-discriminating monopolist to
be very undesirable.”); Douglas M. Kochelek, Note, Data Mining and Antitrust,
22 HARV. J.L. & TECH. 515, 531 (2009) (“[D]ata mining technologies are able to
facilitate price discrimination within a monopoly market.”).
103. Kochelek, supra note 102, at 521.

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identify different classes of consumers and, as stated in Jefferson
Parish Hospital District No. 2 v. Hyde, use that power “to impair
competition . . . by facilitating price discrimination, thereby
increasing monopoly profits over what they would be absent the
104
tie.”
What’s unique about Google is that it can use its monopoly
power not just to engage in price discrimination directly in regards
to its advertising customers and potentially with users in its own
e-commerce efforts, but also as a vehicle for companies across the
economy to engage in such consumer harm via price
discrimination, which should raise the priority for restraining its
power in the marketplace. While firms would no doubt be taking
advantage of targeted advertising to engage in price discrimination
whatever the competitive nature of the search advertising industry,
the lack of competition in the sector feeds the monopoly ability of
Google to extract user data. A more developed market where users
are more able to refuse to share their data combined with a more
fractured set of players in the sector where no one player like
Google would have so much data about all users would weaken the
ability of advertisers to engage in price discrimination.
Both Klock and Kochelek argue that, in the ideal, the explicit
105
antitrust language in the Robinson-Patman Act
on price
106
discrimination should be a tool to address the problem. While
the Robinson-Patman Act arguably does not address the harm of
107
price discrimination to primary consumers, it does potentially

104. 466 U.S. 2, 14–15 (1984), abrogated by Ill. Tool Works, Inc. v. Indep. Ink,
Inc., 547 U.S. 28, 31 (2006). For a general analysis of this line of cases, noting that
courts disfavor the way tying facilitates price discrimination, see Elhauge,
supra note 93, at 421–26. See also United States v. Loew’s, Inc., 371 U.S. 38 (1962),
abrogated by Ill. Tool Works, 547 U.S. at 31; N. Pac. Ry. Co. v. United States, 356
U.S. 1 (1958), superseded by statute, 35 U.S.C. § 271(d)(4)–(5) (2006); United Shoe
Mach. Corp. v. United States, 347 U.S. 521 (1954); Int’l Salt Co. v. United States,
332 U.S. 392 (1947), abrogated by Ill. Tool Works, 547 U.S. at 31–33.
105. 15 U.S.C. § 13 (2012).
106. Klock, supra note 99, at 383 (“The treble damage framework of the
Robinson-Patman Act with application to services and consumers would be a good
start.”); Kochelek, supra note 102, at 524. Both Klock, supra note 99, at 330, and
Kochelek, supra note 102, at 526, have doubts, however, that courts will accept
their arguments.
107. See FREDERICK M. ROWE, PRICE DISCRIMINATION UNDER THE ROBINSONPATMAN ACT 173 (1962) (arguing Robinson-Patman does not apply to consumer

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address situations where the ability, which Google has, to facilitate
price discrimination is a primary attribute strengthening its
108
monopoly power vis-à-vis competitors. In any case, more general
antitrust enforcement under the Sherman Act should be sufficient
in cases of monopoly players wielding price discrimination and
imposing the dead weight losses for consumer welfare discussed
109
above.
V. SUBPRIME MORTGAGES, “AMBULANCE CHASERS AND SNAKE OIL
SALESPEOPLE”: HOW ONLINE ADVERTISING UNLEASHES THE
“TAWDRY” SIDE OF CAPITALISM
How widespread the use of price discrimination and
behavioral marketing is among legitimate businesses using Google
to increase their profits at the expense of consumers is largely a
matter for investigation by federal agencies, since Google quite
obviously keeps such data closely held. There is of course wideranging use of selectively offered promotions on websites
throughout e-commerce promoted through Google search and
display advertising, so that basic form of price discrimination is
clearly in place. Evaluating the broad ways consumers are harmed
by such selective price discrimination, a harm that even Google’s
own Chief Economist admits is far more than a theoretical

transactions). Kochelek largely dismisses the likelihood of using Robinson-Patman
for this reason. Kochelek, supra note 102, at 525–26 (“Accordingly, the practice
likely cannot be regulated under the primary-line theory of the Robinson-Patman
Act.”).
108. While Klock agrees that case law makes him skeptical of using RobinsonPatman, he argues agencies and courts might broaden their interpretation of
Robinson-Patman in light of the expansion of price discrimination in the
marketplace. Klock, supra note 99, at 379. However, neither of the authors
consider a case such as Google where the ability to engage in price discrimination
is largely the basis of undermining the ability of competitors to enter the same
market, so Robinson-Patman might be more applicable in this case.
109. Kochelek, supra note 102, at 526 (“Regardless of the particular theory of
the purpose of antitrust regulation one accepts, the economic effects of datamining-based price discrimination suggest that such conduct ought to be
proscribed by the Sherman Act.”). However, Klock in particular thinks the
potential enforcement threat of direct class action lawsuits by consumers wielding
Robinson-Patman is a potentially better deterrence than depending on agency or
competitor lawsuits against price discrimination under the Sherman Act. See Klock,
supra note 99, at 377–78.

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110

possibility, should be a primary focus for antitrust investigations
into Google.
However, while Google’s facilitation of price discrimination
can increase profits for all businesses, targeted advertising has
maximum appeal to the unethical and even illegal businesses
seeking to prey on such “myopic” consumers that Google can help
them identify. Early Internet visionary Jaron Lanier, who pioneered
ideas like “virtual reality” two decades ago, has noted that such
access to behavioral targeting has even more appeal to the “tawdry”
kinds of firms than the “dignified side of capitalism,” since
“ambulance chasers . . . and snake oil salespeople” among the
111
capitalist class thrive on such targeted access to their victims.
Lanier argues that:
Google’s thing is not advertising . . . . It’s a link. It’s just
a little tiny minimalist link . . . . What they’re doing is
they’re saying, “You give us money, we give you access to
these people, and then what you do with them is up to
you.” It’s a gate keeping function. It’s an arbiter of access.
It’s turning connections instead of being open into being
112
paid.
This also emphasizes that Google’s version of advertising is distinct
in its function from other traditional advertising.
A.

Racial and Economic Profiling Online
113

114

after study
has shown that employers, financial
Study
lenders, car salesmen, and other merchants use profiling to charge
black and Hispanic customers more for the same product or service
when they can identify them. For example, a study by the Urban
Institute using paired “testers”—one white person and one person
of color with similar economic profiles—found that nonwhite

110. See Acquisti & Varian, supra note 83, at 373.
111. Brockman, supra note 11.
112. Id.
113. MARGERY AUSTIN TURNER ET AL., U.S. DEP’T OF HOUS. & URBAN DEV.,
ALL OTHER THINGS BEING EQUAL: A PAIRED TESTING STUDY OF MORTGAGE LENDING
INSTITUTIONS (2002), available at http://www.urban.org/UploadedPDF/1000504
_All_Other_Things_Being_Equal.pdf.
114. Marianne Bertrand & Sendhil Mullainathan, Are Emily and Greg More
Employable Than Lakisha and Jamal? A Field Experiment on Labor Market Discrimination,
94 AM. ECON. REV. 991 (2004).

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homebuyers received less favorable financial terms from mortgage
115
lending institutions. Job seekers face similar discrimination. One
study, where nearly identical resumes were sent to 1300 help
wanted ads, found that resumes with a “white-sounding” name were
fifty percent more likely to get a call for an interview than one with
116
a “black-sounding” name. Just in 2012, the U.S. Department of
Justice negotiated a $175 million settlement with Wells Fargo for
illegally steering more than 30,000 black and Hispanic borrowers
between 2004 and 2009 into more costly subprime mortgages or
117
charging them higher fees than comparable white borrowers.
Online behavioral targeting can combine a home address and
a few more characteristics to create an almost perfect proxy for
race. Rebecca Goldin, a George Mason University professor, argued
in a 2009 article that while it’s clearly illegal to discriminate based
on race, if companies offer loan rates based on shopping habits, it
raises the question, “[w]ould it be legal or ethical to use the kind of
118
music one buys to determine his or her loan rate . . . ?” The
Supreme Court has essentially invited such data-driven
discrimination by prohibiting explicit race preferences or
discrimination but allowing disparate impact along racial lines as
119
long as decisions were made based on “race-neutral” criteria.

115. TURNER ET AL., supra note 113, at 1.
116. Bertrand & Mullainathan, supra note 114, at 991.
117. James O’Toole, Wells Fargo in $175M Discriminatory Lending Settlement,
CNN MONEY (July 12, 2012, 1:12 PM), available at LEXIS (stating that a typical
African-American borrower paid nearly $3000 more in fees than a similarly
qualified white applicant). In an echo of the search for “myopic” customers
promoted by Google’s Varian, in a subprime-mortgage-related lawsuit, Washington
Mutual loan officer Greg Saffer related in a legal filing that trainers at his bank
instructed loan officers to target subprime loans to poor areas and that the “best
areas to market are in lower income areas like Compton and Long Beach because
the people are less sophisticated there.” Confessions of an Economic Hate Crime, DAS
KRAPITAL (July 30, 2012), http://www.daskrap.com/2012/7/confessions-economic
-hate-crime.
118. Rebecca Goldin, Doting on Data, 56 NOTICES AM. MATHEMATICAL SOC’Y
483, 486 (2009), available at http://www.ams.org/notices/200904/rtx090400483p
.pdf (reviewing AYRES, supra note 68).
119. Justice O’Connor argued for “race-neutral means to increase minority
business participation” in City of Richmond v. J.A. Croson Co., 488 U.S. 469, 507
(1989). See also Owens v. Nationwide Mut. Ins. Co., No. 3:03-CV-1184-H, 2005
WL 1837959, at *14–15 (N.D. Tex. Aug. 2, 2005) (stating even if credit scores have
disparate impact on minorities, race-neutral business reasons for credit scores

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As Colorlines has noted, “a user’s browsing history, their
location and IP information . . . combined with information
available in Google’s public data explorer (including [U.S.] census,
education, population, STD stats, and state financial data)
presumably could also be folded into the personalized search
120
algorithm to surmise a lot more than your race.” While not
conclusive, there is evidence of companies using names or other
evidence such as physical location to offer differential advertising
121
through Google based on race and ethnicity.
B.

Google and the Subprime Mortgage Crisis

What is unquestionable is that Google advertising lay at the
heart of the largest example of price discrimination and consumer
harm of the last few decades, namely the subprime mortgage
destruction of family wealth and the financial crisis that followed.
Google isn’t usually identified as a big player in the subprime
mortgage debacle and its aftermath, but a significant portion of
Google’s profits in the mid-2000s were coming straight from
subprime mortgage lenders advertising on its site. As Jeff Chester of
the Center for Digital Democracy said back in 2007, “[m]any
online companies depend for a disproportionate amount of their
income on financial services advertising, with subprime in some
122
cases accounting for a large part of it.” To give some sense of its

allow their use); Powell v. Am. Gen. Fin., Inc., 310 F. Supp. 2d 481, 488 (N.D.N.Y.
2004) (stating that nonsubjective credit indicators that have disparate impact on
minorities are permissible).
120. Jorge Rivas, Google Calls Racial Profiling Claims ‘Wildly Inaccurate’,
COLORLINES (Sept. 28, 2011, 10:10 AM), http://colorlines.com/archives/2011
/09/google_responds_to_preliminary_study_says_their_ads_dont_racially_profile
.html.
121. See Latanya Sweeney, Discrimination in Online Ad Delivery, 56 COMM. ASS’N
COMPUTING MACHINERY 44, 44 (2013) (finding ads associate term “arrested” with
black-sounding names more than with white-sounding names); Nathan Newman,
Racial and Economic Profiling in Google Ads: A Preliminary Investigation (Updated),
HUFFINGTON POST (Sept. 20, 2011, 3:17 PM), http://www.huffingtonpost.com
/nathan-newman/racial-and-economic-profi_b_970451.html (discussing a survey
that found examples of different ads being served up based on the ethnicity of
names and location of the computer).
122. Jeff Chester, Role of Interactive Advertising and the Subprime Scandal: Another
Wake-up Call for FTC, DIGITAL DESTINY (Aug. 28, 2007, 11:00 AM), http://www
.democraticmedia.org/jcblog/?p=349.

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importance, Nielsen//Netratings released research in July 2007 of
123
the online display advertisers spending the most money. The top
five online advertisers were involved in the mortgage lending
industry to some extent, delivering almost $200 million in monthly
revenue to online advertising companies like Google, with literally
over a hundred billion views of those online ads driving the frenzy
for refinancing and subprime mortgages with ads like
124
“LowerMyBills” and other online enticements.
Those numbers above are for display ads only, a segment in
which Google was and is a prime player through its Doubleclick
purchase. Google does not share data on specific revenue from
particular companies on its AdWords and related search
advertising, but reports at the time showed the mortgage
companies paying top dollar for related keywords like “mortgage”
and “refinance,” with prices going as high as twenty to thirty dollars
125
for each user that clicked on an ad using those terms.
Companies enticed customers with unrealistic “teaser rates”—
heavily advertised online—that burdened borrowers with toxic
126
terms and unmanageable obligations that exploded in later years.
And the racial and exploitive aspect of the mortgage meltdown was
endemic with what some scholars described as reverse redlining,
“the practice of targeting borrowers of color for loans on
127
unfavorable terms.” This offering of differential rates based on
the characteristics of the borrower constitutes the most damaging
price discrimination inflicting consumer harm in American
128
history, for which Google played an integral (and profitable) role

123. Press Release, Nielsen//NetRatings, Nielsen//NetRatings Reports
Topline U.S. Data for July 2007 (Aug. 13, 2007), http://www.nielsen-online
.com/pr/pr_070813.pdf.
124. Id.
125. Faisal Laljee, Subprime Mortgage Bust Could Create Ad Trouble for Google,
SEEKING ALPHA (Feb. 22, 2007, 4:04 AM), http://seekingalpha.com/article/27736
-subprime-mortgage-bust-could-create-ad-trouble-for-google.
126. See Chester, supra note 122.
127. Raymond H. Brescia, Subprime Communities: Reverse Redlining, the Fair
Housing Act and Emerging Issues in Litigation Regarding the Subprime Mortgage Crisis,
2 ALB. GOV’T L. REV. 164, 167 (2009).
128. See Michelle Singletary, King’s Dream Deferred, One More Victim of the
Subprime Mortgage Crisis, WASH. POST, Feb. 10, 2008, at F01, available at LEXIS
(“[T]he subprime mortgage crisis has caused the largest loss of wealth for black
and Latino homeowners in modern U.S. history.”).

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as an advertising intermediary where it was earning billions of
dollars a year.
C.

Google’s Continued Role in Facilitating Financial Exploitation of
Consumers

The financial industry remains the bedrock of Google’s
129
According to WordStream, a company
advertising revenues.
specializing in helping companies bid effectively on Google Ads,
the three most expensive categories of keyword searches as
measured by cost per click are in financial services—insurance,
loans, and mortgages—with 45.8% of the top 10,000 advertising
130
keywords falling in those categories.
And many of those advertising bidders at Google are from the
more bottom-feeding aspects of the industry, particularly payday
loan lenders, who offer extremely high-interest loans for consumers
made in exchange for a commitment to repayment from the
131
person’s next paycheck. Such loans have been banned or severely
132
restricted as exploitative in multiple states. The new Consumer
Financial Protection Bureau (CFPB) has been holding hearings
specifically on abuses in the industry, with CFPB head Richard
Cordray saying that “some payday lenders [are] engaged in
practices that present immediate risk to consumers and are clearly
133
illegal.”
Yet Google actively solicits ads from the industry, including
setting up a trade booth at the Online Lenders Alliance, a trade
134
group comprised mainly of payday lenders. Industry observers

129. Larry Kim, The Most Expensive Keywords in Google AdWords,
WORDSTREAM (July 18, 2011), http://www.wordstream.com/blog/ws/2011/07/18
/most-expensive-google-adwords-keywords.
130. Id.
131. Robert X. Cringely, Google’s Pound of Flesh, CRINGELY (Sept. 27, 2010),
http://www.cringely.com/2010/09/27/googles-pound-of-flesh.
132. Payday Lending State Statutes, NAT’L CONF. ST. LEGISLATURES, http://www
.ncsl.org/issues-research/banking/payday-lending-state-statutes.aspx (last updated
Sept. 12, 2013).
133. Press Release, Richard Cordray, Dir., Consumer Fin. Prot. Bureau,
Prepared Remarks at the Payday Loan Field Hearing in Birmingham, Ala.,
(Jan. 19, 2012), http://www.consumerfinance.gov/newsroom/remarks-by-richard
-cordray-at-the-payday-loan-field-hearing-in-birmingham-al.
134. Cringely, supra note 131.

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like Robert X. Cringely, who has covered Silicon Valley for over
twenty-five years, have cited this involvement as a step beyond
passively accepting ads from dubious sources to actively enabling
evil. He argues that out of financial self-interest, Google is burying
bad news about the industry for consumers, since he found Google
“placed the uniformly negative news items near the bottom of the
results, below the fold as we used to say in the newspaper
135
business.”
Whether, as Cringely argues, Google is actively hiding
damning consumer analysis of the evils of its financial advertisers,
what is true is that Google maintained ads from illegal mortgage
“loan modification” firms preying on desperate homeowners even
136
after the company was alerted to the problem.
Such firms
advertise heavily online with consumers looking for keywords such
as “stop foreclosure,” then promise solutions that never deliver and
137
further impoverish those homeowners facing financial default.
Back in February 2011, the consumer group Consumer Watchdog
published a scathing report highlighting the concentration of such
138
firms advertising on Google, but Google did nothing about the
problem until the Treasury Department took regulatory action in
November of that year under its TARP authority to shut down
eighty-five of these scam advertisers who were luring customers
139
through Google. ‘“Many homeowners who fall prey to these
scams, initially do so through these Web banners and other Web
advertising,’ Christy Romero, Deputy Special Inspector General for
140
the Troubled Asset Relief Program, said in an interview.”

135. Id.
136. See CONSUMER WATCHDOG, LIARS AND LOANS: HOW DECEPTIVE ADVERTISERS
USE GOOGLE 5–7 (2011), available at http://www.consumerwatchdog.org
/resources/liarsandloansplus021011.pdf.
137. Id.
138. Id.
139. Feds Shut Down High-Tech Mortgage Scammers, CBS NEWS (Nov. 16, 2011,
3:30 PM), http://www.cbsnews.com/8301-205_162-57326180/feds-shut-down-high
-tech-mortgage-scammers/.
140. Id.

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Promoting Illegal Drug Advertisements Earned Google One of the
Largest Civil Forfeitures in American History

In a similar vein to Google’s promotion of unethical and
illegal financial advertisers, in August 2011, Google agreed to pay a
$500 million civil forfeiture to the federal government, one of the
largest in history, as part of a settlement penalizing the company
for illegally and—significantly—knowingly allowing illegal phar141
macies to advertise on its site. This was not passive activity by
Google, but active complicity with advertisers often selling fake
prescription medicine to desperately ill individuals or marketing
illegal steroids. “‘[Google founder and CEO] Larry Page knew what
was going on,’ Peter Neronha, the Rhode Island U.S. Attorney who
142
led the probe, told The Wall Street Journal.”
As early as 2003, Google was put on notice by the government
that its advertisements for various foreign-based pharmacies were
143
illegal, yet the company continued to assist many of them in
144
placing and optimizing their AdWords advertisements. In fact, a
follow-up story by the Wall Street Journal detailed how a felon, David
Whitaker, who ended up collaborating with the federal government
to target Google, had fled to Mexico and was advanced credit by
Google and assisted by Google ad executives in designing ads to sell
145
illegal steroids and similar products. Federal agents created a
website designed to look “as if a Mexican drug lord had built a
website to sell HGH and steroids” and Google ad executives worked
with Mr. Whitaker to find ways around Google’s official rules
146
barring such ads. Whitaker went on to tape record conversations
where he directly told Google ad executives that his goal was to be
147
“the biggest steroid dealer in the United States.” Disturbingly,

141. Thomas Catan & Amir Efrati, New Heat for Google CEO: U.S. Says Google’s
Larry Page Knew About Improper Online Pharmacy Ads, WALL ST. J., Aug. 27, 2011, at
B1, available at LEXIS.
142. Clint Boulton, Google’s Page Knew of Illegal Pharmacy Ads: DOJ, EWEEK
(Aug. 28, 2011), http://www.eweek.com/c/a/Search-Engines/Googles-Page-Knew
-of-Illegal-Pharmacy-Ads-DOJ/.
143. Catan & Efrati, supra note 141.
144. Thomas Catan, Con Artist Starred in Sting That Cost Google Millions, WALL
ST. J., Jan. 25, 2012, at A1, available at LEXIS.
145. Id.
146. Id.
147. Id.

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documentation about the individual culpability of Google
executives was sealed as part of the settlement with prosecutors,
which prevents other government officials from evaluating the
evidence in light of broader antitrust and other regulatory
148
concerns.
VI. CONCLUSION: THE BROAD CONSUMER HARM FROM GOOGLE’S
MONOPOLY IS NOT BEING CORRECTED BY MARKET MECHANISMS
These examples are just the most obvious unethical and illegal
categories of advertisers that have been highlighted due to
government investigations. What is most worrying is that the nature
of targeted advertising means that a whole range of niche scams
and economically exploitive relationships can be focused on those
most vulnerable to the scam’s appeal, while remaining essentially
invisible to everyone else, including reporters and researchers
trying to evaluate the harms from Google’s advertising methods.
As detailed above, there are broad reasons why consumers are
not demanding a fair return from Google when trading their
privacy in exchange for using Google’s services. However, there are
even more obvious market failures from these broader financial
losses where consumers lack information on the operations of price
discrimination and the danger of many of these predatory firms
advertising online.
In measuring consumer harm, then, it is therefore the broad
financial losses to consumer welfare facilitated by lost privacy and
Google’s data mining efforts, including the predatory behavioral
targeting of users provided by Google based on its control of user
data, that should be a prime focus for investigation by antitrust
regulators and legislative leaders. Much of this is no doubt in the
day-to-day price discrimination encouraged for businesses using
online advertising, but a significant fraction is also from companies
engaged in unethical to illegal activities facilitated by the company.
The fact that profitable price discrimination depends on a
combination of user ignorance and service lock-in, according to
149
Google’s own Chief Economist Hal Varian, means the market
148. Boulton, supra note 142; see also Nathan Newman, Erosion of Public Scrutiny
of Litigation—and Irony of Google Wanting Privacy for Its Judicial Dealings, TECHPROGRESS (Feb. 18, 2011), http://www.tech-progress.org/?p=101.
149. Acquisti & Varian, supra note 83, at 380.

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alone cannot address that issue of equity and market power by
Google. Similarly, markets have shown themselves incapable of
policing the broader harms to society that stem from wide-scale
harms such as the subprime mortgage crisis, which stemmed from
combinations of consumer ignorance and price discrimination in
mortgage offers. Public action is equally needed to police the
“tawdry” side of capitalism, whose advertisers seem endemic on
Google, from its fake “loan modification” scams to illegal
pharmacies.
A.

Remedies to Address Consumer Harm from Lost Privacy Online

Traditional antitrust enforcement would help accomplish
some of these goals and I have described some antitrust remedies,
including strengthening consumer control over their own data, as a
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way to limit the consumer harm from Google’s monopoly.
However, because of the complexity of implementing some of
these remedies through agencies and the courts, some reforms
might be implemented better through existing powers of the
Federal Trade Commission and other agencies. Other measures
may call for additional legislation to bring both antitrust and
consumer protection laws more explicitly up-to-date to address the
broad consumer harm and rising economic inequality stemming
from data mining online.
In March 2012, the FTC issued a report, Protecting Consumer
Privacy in an Era of Rapid Change, that sought to outline a
framework for privacy protection for businesses to adopt voluntarily
and, where necessary, policymakers to mandate as part of general
151
consumer protection. The framework includes so-called “Do Not
Track” rules for web browsers such as Google’s Chrome browsers to
ensure user activity can be hidden from advertisers, data portability
to allow users to switch easily between email and social networking
services and take their data with them, and greater transparency
and choice by consumers on where and how they share their data
152
with companies.
There is good evidence from Europe that

150.
151.

Newman, supra note 8 (manuscript at 62–69).
FED. TRADE COMM’N, PROTECTING CONSUMER PRIVACY IN AN ERA OF RAPID
CHANGE: RECOMMENDATIONS FOR BUSINESSES AND POLICYMAKERS 72–73 (2012),
available at http://www.ftc.gov/os/2012/03/120326privacyreport.pdf.
152. See generally id.

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privacy regulation can in fact decrease behavioral tracking of users
153
online.
The FTC framework also suggests companies should be
required to obtain “express consent” when collecting “sensitive
data,” such as health and other data regulators might deem most
154
subject to abuse.
While one FTC commissioner questioned
whether “opt-in” requirements would work for smaller
155
companies, I would argue that in the case of Google, whether
through regulation or as a specific antitrust remedy, a detailed and
explicit “opt-in” consent should be required for any use of the data
with specific express consent required for any change or new use of
the data in the future. If users were reluctant to invest the time to
complete the process of giving such consent, that would actually
serve a positive purpose in encouraging Google to offer economic
incentives for users to do so. By jumpstarting a real market for user
data, not only would that reverse some of the economic
distribution towards Google, it would open up more space for
other companies to compete on incentives at that point of friction
and thereby ease monopoly concerns. Limiting such an opt-in
requirement for sharing data to Google and other similar large,
dominant players would avoid the problem that general opt-in
requirements might lead to users favoring large players to avoid the
transaction costs of dealing with multiple, smaller players for their
156
online needs.
One other way to address the fundamental information
asymmetry between Google and its users in pricing the value of
157
user data would be to adopt proposals that would require greater

153. Avi Goldfarb & Catherine E. Tucker, Privacy Regulation and Online
Advertising, 57 MGMT. SCI. 57, 69–70 (2011), available at http://dspace.mit.edu
/openaccess-disseminate/1721.1/64920 (study using 3.3 million survey responses
to 9,596 different online ads found sixty-five percent drop in effectiveness of
banner ads in Europe under Privacy Directive compared to countries without
privacy regulation).
154. FED. TRADE COMM’N, supra note 151, at viii.
155. See id. at C-7.
156. See James Campbell et al., Privacy Regulation and Market Structure 2
(Aug. 15, 2013) (unpublished manuscript), available at http://ssrn.com/abstract
=1729405 (arguing that general privacy rules favor larger companies).
157. Alexander Furnas, It’s Not All About You: What Privacy Advocates Don’t Get
About Data Tracking on the Web, ATLANTIC (Mar. 15, 2012, 3:23 PM), http://www
.theatlantic.com/technology/archive/2012/03/its-not-all-about-you-what-privacy

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transparency in how Google monetizes that data, such as regular
reports on the cost per click or other payments to Google based on
158
user activities.
Such information, along with greater data
portability between services, might actually encourage a market
where users “vote with their feet”—or, more accurately, their
data—and demand either a greater share of Google’s profits based
on that data, switch to competing providers for a better deal, or
withhold their data altogether after recognizing the pervasive use
by third parties that they may not want tracking them. Any of those
outcomes would lessen Google’s power over user data and lessen
the consumer harm from that control.
Google accepting some forms of public interest responsibilities
and regulation, potentially in the form of a consent decree as an
alternative to divestiture of product assets, might open the doorway
for a more fundamental restructuring of Google’s guardianship of
user data to reduce and ideally eliminate the pervasive consumer
harms from data misuse by its advertisers. A clear first step would
be to bar Google from engaging in price discrimination itself or
from knowingly facilitating price discrimination where different
groups are secretly offered different prices by its advertisers. As
Stiglitz and Salop argue, a “rational economic planner”—in this
case a government-backed consent antitrust decree—could
economize on wasteful information-seeking costs by “eliminating
159
the price dispersion” associated with price discrimination.
Such an approach to Google should also bring the company
under Dodd-Frank Financial Services regulation, given the
percentage of its advertising revenue derived from the financial
services industry. It would be appropriate for the new CFPB to
regularly audit practices by Google, such as facilitating predatory
price discrimination and other financial scams online, which harm
consumers. The CFPB is tasked not only with regulating abuses by
the banking industry, but it is also required to restrain abuses by
160
larger nonbank participants in the financial system. Precisely
-advocates-dont-get-about-data-tracking-on-the-web/254533/ (“The data collectors
have more information than those they are they are [sic] collecting the data from;
the persuaders more [sic] power than the persuaded.”).
158. Whittington & Hoofnagle, supra note 44, at 1367 (outlining a version of
such a proposal).
159. Salop & Stiglitz, supra note 71, at 494.
160. The CFPB, in developing its rules, noted the source of this authority.

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because so many of these predatory offers are hidden from public
view, the CFPB could play a prime role in improving data collection
and better assessing the financial harm to consumers from these
advertiser practices online. By closely overseeing how Google and
other related online advertising players collect and share the
personal data they control with financial services firms, many of the
abuses that fueled the concern that created the CFPB in the first
place could be reined in before consumers fall victim to fraudulent
or discriminatory offers.
B.

How Government Intervention Addresses Rising Economic Inequality

As more of the economy moves online, the importance of data
mining and asymmetry of control of information becomes ever
more critical in economic markets. Addressing this change calls for
reevaluating both the economic assumptions underlying much
recent antitrust scholarship, especially the scholarship influenced
161
by the Chicago School, and taking far more active regulatory
action to reverse the trends undermining user privacy and
increasing economic inequality due to that rising information
asymmetry.
With an eye on Google, such pressure might translate into a
greater focus on sharing the financial bounty of user information
with those users, serving both equity and competition. The less
companies like Google are able to use privacy violations for anticompetitive purposes, the better guardian of legitimate privacy
concerns such companies will become. At least one writer has
compared the market failure of providing privacy and data
protection to that of poor user information on food and safety a
hundred years ago, explicitly highlighting the way equity and

See Defining Larger Participants in Certain Consumer Financial Product and
Service Markets, 77 Fed. Reg. 9592 n.3 (Feb. 17, 2012) (codified at 12 C.F.R.
§ 1090 (2013)) (“Section 1024 of the Act applies to nondepository (nonbank)
covered persons and expressly excludes from coverage persons described in
sections 1025(a) or 1026(a) of the Act. Under section 1002(6) of the Act, a
‘covered person’ means ‘(A) any person that engages in offering or providing a
consumer financial product or service; and (B) any affiliate of a person described
[in (A)] if such affiliate acts as a service provider to such person.’”).
161. See Manne & Wright, supra note 20, at 179 n.21.

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consumer safety concerns of crusaders like Upton Sinclair should
162
be the precedent for action today.
What the case of Google highlights most of all is the way the
data mining of individual privacy is fundamentally reshaping
markets by transferring so much knowledge about user interests,
behavior, and desires into a few corporate hands. Such information
asymmetry is easily converted into economic inequality when one
side of every transaction has so much more knowledge about the
other during bargaining. The last four decades have seen a steady
163
increase in economic inequality, which is only partially explained
by standard explanations centered on the rise of economic returns
to education, globalized trade, and political changes. The
increasing information asymmetry in consumer markets, driven by
data mining and facilitated by online services such as Google, may
be an additional significant cause of this overall increase in
economic inequality. Internet visionary Jaron Lanier sums up the
change as “wealth is measured by how close you are to one of the
big servers” and Google sits on one of the largest network of servers
in the world acting as “private spying agencies” on behalf of its
164
advertising clients.
Government authorities using antitrust and other regulatory
tools can stem at least part of this trend by restoring a degree of
control by individuals over what personal data is shared online and
the financial terms on which that data is shared. This in turn can
eliminate some of the information-based inequality in the modern
marketplace that is driving the overall economic inequality. If
nothing else, a broad antitrust investigation of Google can be a
chance for a much broader public debate on the abuses of data
mining online and how to make all markets work more fairly for
average working families.

162. Benjamin R. Sachs, Note, Consumerism and Information Privacy: How Upton
Sinclair Can Again Save Us from Ourselves, 95 VA. L. REV. 205, 239–50 (2009)
(suggesting a tort liability standard for companies experiencing data breaches to
force them to tighten security for users).
163. Kathy Ruffing, Ctr. on Budget & Policy Priorities, “Gini Index” from
Census Confirms Rising Inequality over Four Decades, OFF THE CHARTS (Sept. 19,
2013, 4:10 PM), http://www.offthechartsblog.org/gini-index-from-census-confirms
-rising-inequality-over-four-decades/.
164. Brockman, supra note 11.

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