Digital market manipulation

George Washington Law Review

Volumn 82, Issue 4, 2014, Pages 995-1051

  Calo, Ryan ^a  

^a UNIVERSITY OF WASHINGTON   (United States)

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EID: 84961317182     PISSN: 00168076     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

References (223)

1. See Rebecca J. Rosen, Is This the Grossest Advertising Strategy of All Time?, ATLANTIC (Oct. 3, 2013, 1:46 PM), http://www.theatlantic.com/technology/archive/2013/10/is-this-the-gross-est-advertising-strategy-of-all-time/280242/.
2. See, e.g., ROY F. BAUMEISTER & JOHN TIERNEY, WILLPOWER: REDISCOVERING THE GREATEST HUMAN STRENGTH 1-5 (2011) (collecting various studies).
3. Charles Duhigg, Psst, You in Aisle 5, N.Y. TIMES MAG., Feb. 19, 2012, at 30, 54-55.
4. 2) / Satisfying Crunch) × Pleasing Mouth Feel = A Food Designed to Addict, N.Y. TIMES MAG., Feb. 24, 2013, at 34
5. see also John Tierney, To Choose Is to Lose, N.Y. TIMES MAG., Aug. 21, 2011, at 32, 34 ("When people fended off the temptation to scarf down M&M's [sic] or freshly baked chocolate-chip cookies, they were then less able to resist other temptations.").
6. Furthermore, companies as ubiquitous as Mondelez International, the brand behind Cadbury chocolates and Trident gum, are investigating how to increase impulse buying with digitally-enhanced shelves that detect and respond to the individual aspects of the shopper. See Clint Boulton, Snackmaker Modernizes the Impulse Buy with Sensors, Analytics, WALL ST. J. CIO J. BLOG (Oct. 11, 2013, 3:13 PM), http://blogs.wsj.com/cio/2013/10/11/snackmaker-modern-izes-the-impulse-buy-with-sensors-analytics/.
7. VANCE PACKARD, THE HIDDEN PERSUADERS 11-17 (rev. ed. 1981) (describing the ascension of the "depth approach").
8. See Stuart Rogers, How a Publicity Blitz Created the Myth of Subliminal Advertising, PUB. REL. Q., Winter 1992-1993, at 12, 12-17 (discussing James Vicary's work).
9. Public Notice Concerning the Use of "Subliminal Perception" Advertising by Television Stations, 40 F.C.C. 10 (1957).
10. The controversy resurfaced just a few years ago when two United States Senators wrote a letter to the FCC saying they had "reason to believe that broadcasters are airing television advertisements that contain subliminal messages." See Press Statement of Gloria Tristani, Comm'r, Fed. Commc'ns Comm'n (Mar. 9, 2001) (on file with The George Washington Law Review) (explaining that the Senators believed the Republic National Committee had created ads attempting subliminally to associate Vice President Al Gore with the word "RATS" and that the Commission investigated but ultimately dismissed the allegation).
11. E.g., ELI PARISER, THE FILTER BUBBLE: WHAT THE INTERNET IS HIDING FROM YOU 14-18 (2011)
12. JOSEPH TUROW, NICHE ENVY: MARKETING DISCRIMINATION IN THE DIGITAL AGE 1-2 (2006) [hereinafter TUROW, NICHE ENVY]
13. JOSEPH TUROW, THE DAILY YOU: HOW THE NEW ADVERTISING INDUSTRY IS DEFINING YOUR IDENTITY AND YOUR WORTH 1-2 (2011) [hereinafter TUROW, THE DAILY YOU]
14. see also Lior Jacob Strahilevitz, Toward a Positive Theory of Privacy Law, 126 HARV. L. REV. 2010, 2022-33 (2013) (analyzing the discriminatory effect of big data on some consumers).
15. E.g., Neil M. Richards, The Dangers of Surveillance, 126 HARV. L. REV. 1934, 1955-56 (2013) (noting that "[surveillance also gives the watcher increased power to persuade").
16. Tal Zarsky devotes a few paragraphs to the relationship between profiling and persuasion in a short book chapter, but without offering an account of its mechanics, contours, or harms, beyond noting that personalized persuasion is "manipulative." Tal Z. Zarsky, Online Privacy, Tailoring, and Persuasion, in PRIVACY AND TECHNOLOGIES OF IDENTITY: A CROSS-DISCIPLINARY CONVERSATION 209, 219-21 (Katherine J. Strandburg & Daniela Stan Raicu eds., 2006).
17. See Conference Program, 32nd Annual Advertising and Consumer Psychology Conference: Consumer Psychology in a Social Media World 11 (June 13-15, 2013), http://www.myscp.org/pdf/ACP%20Final%20Schedule.pdf [hereinafter Conference Program, Consumer Psychology in a Social Media World) (describing panel entitled Visceral Targeting: Using Personalized Face Composites for Implicit Targeted Marketing)
18. see also Jeremy N. Bailenson et al., Facial Similarity Between Voters and Candidates Causes Influence, 72 PUB. OPINION. Q. 935, 935-61 (2008).
19. Nothing in a social network's terms of service or privacy policy would stand in the way of this potentially lucrative practice. See, e.g., Privacy Policy, INSTAGRAM (Jan. 19, 2013), http://instagram.com/legal/privacy/# ("[W]e may use information that we receive to⋯ provide personalized content and information to you and others, which could include online ads or other forms of marketing⋯.")
20. Terms of Use, INSTAGRAM (Jan. 19, 2013), http://instagram.com/legal/terms/# ("[Y]ou hereby grant to Instagram a non-exclusive, fully paid and royalty-free, transferable, sub-licensable, worldwide license to use the Content that you post on or through the Service, subject to the Service's Privacy Policy⋯."). Moreover, in its Terms of Use, Instagram states, "You acknowledge that we may not always identify paid services, sponsored content, or commercial communications as such." Terms of Use, supra.
21. Richard Craswell and others have explored the line between deceptive and nondeceptive advertising. See generally Richard Craswell, Interpreting Deceptive Advertising, 65 B.U. L. REV. 657 (1985) [hereinafter Craswell, Interpreting Deceptive Advertising]
22. Richard Craswell, Regulating Deceptive Advertising: The Role of Cost-Benefit Analysis, 64 S. CAL. L. REV. 549 (1991).
23. David Hoffman has developed a comprehensive account of "puffery," meaning the practice of exaggerating the quality of goods and services. David A. Hoffman, The Best Puffery Article Ever, 91 IOWA L. REV. 1395 (2006). These and other accounts, however, do not account for the mediating effects of contemporary technology.
24. See Cass R. Sunstein, Empirically Informed Regulation, 78 U. CHI. L. REV. 1349, 1399 (2011) ("Other default rules are personalized, in the sense that they draw on available information about which approach best suits individuals, and potentially even each individual, in the relevant population.")).
25. See Ariel Porat & Lior Jacob Strahilevitz, Personalizing Default Rules and Disclosure with Big Data, 112 MICH. L. REV. 1417, 1421 (2014) (observing that variable legal defaults may be more effective in changing citizen behavior).
26. See Jon D. Hanson & Douglas A. Kysar, Taking Behavioralism Seriously: Some Evidence of Market Manipulation, 112 HARV. L. REV. 1420, 1564-65 (1999).
27. See Hanson & Kysar, supra note 16, at 1425; Jon D. Hanson & Douglas A. Kysar, Taking Behavioralism Seriously: The Problem of Market Manipulation, 74 N.Y.U. L. REV. 630, 747 (1999).
28. See Christine Jolls et al., A Behavioral Approach to Law and Economics, 50 STAN. L. REV. 1471, 1474 (1998).
29. See DAN ARIELY, PREDICTABLY IRRATIONAL: THE HIDDEN FORCES THAT SHAPE OUR DECISIONS, at xx (2008) ("[Human] irrationality happens the same way, again and again.").
30. This is particularly true of the many regimes that rely on mandatory disclosure. See, e.g., M. Ryan Calo, Against Notice Skepticism in Privacy (and Elsewhere), 87 NOTRE DAME L. REV. 1027, 1031-32 (2012) (privacy)
31. Matthew A. Edwards, Empirical and Behavioral Critiques of Mandatory Disclosure: Socio-Economics and the Quest for Truth in Lending, 14 CORNELL J.L. & PUB. POL'Y 199, 242 (2005) (lending)
32. Geoffrey A. Manne, The Hydraulic Theory of Disclosure Regulation and Other Costs of Disclosure, 58 ALA. L. REV. 473, 494-97 (2007) (securities)
33. Lauren E. Willis, Decisionmaking and the Limits of Disclosure: The Problem of Predatory Lending: Price, 65 MD. L. REV. 707, 713-14 (2006) (lending).
34. Christine Jolls & Cass R. Sunstein, Debiasing Through Law, 35 J. LEGAL STUD. 199, 200-01 (2006)
35. see also Richard P. Larrick, Debiasing, in BLACKWELL HANDBOOK OF JUDGMENT AND DECISION MAKING 316, 317 (Derek J. Koehler & Nigel Harvey eds., 2007).
36. E.g., RICHARD H. THALER & CASS R. SUNSTEIN, NUDGE: IMPROVING DECISIONS ABOUT HEALTH, WEALTH, AND HAPPINESS 4-8 (2008)
37. Cass R. Sunstein & Richard H. Thaler, Libertarian Paternalism Is Not an Oxymoron, 70 U. CHI. L. REV. 1159, 1161-62 (2003)
38. Richard H. Thaler & Cass R. Sunstein, Behavioral Economics, Public Policy, and Paternalism: Libertarian Paternalism, AM. ECON. REV., May 2003, at 175, 175-79.
39. See generally FTC v. Willms, No. 2:11-cv-00828-MJP (W.D. Wash. Mar. 6, 2012) (stipulated final judgment and order)
40. One example is bid-to-pay auctions, which leverage the endowment effect and optimism bias to generate as high as 500 percent profits on average consumer goods. See Jeff Atwood, Profitable Until Deemed Illegal, CODING HORROR (Dec. 11, 2008), http://blog.codinghorror.com/profitable-until-deemed-illegal/.
41. If anything, regulators have themselves developed a taste for nudging citizens toward policy goals. See Adam Burgess, 'Nudging' Healthy Lifestyles: The UK Experiments with the Behavioural Alternative to Regulation and the Market, 1 EUR. J. RISK REG. 3, 4 (2012)
42. Michael Grunwald, How Obama Is Using the Science of Change, TIME, Apr. 13, 2009, at 28, 29-30.
43. I use the term "mediated" in a practical sense to refer to the fact that consumers literally experience commercial, civic, and personal life through the technology they use, including mobile phones, tables, kiosks, and the like. There is a long-standing, but recently accelerating, surveillance literature that explores the mediating influence of society on subjects in a more theoretical frame. See, e.g., Kevin D. Haggerty & Richard V. Ericson, The Surveillant Assemblage, 51 BRIT. J. SOC. 605, 605-06 (2000)
44. Katarina Giritli Nygren & Katarina L. Gidlund, The Pastoral Power of Technology. Rethinking Alienation in Digital Culture, 10 TRIPLEC 509, 510-11 (2012).
45. Thank you to Julie Cohen for flagging this helpful distinction. This Article self-consciously adopts a technocratic stance which assumes, with the liberal tradition, the existence of a market and of market actors who can take material advantage of one another. Cf. Julie E. Cohen, Irrational Privacy?, 10 J. TELECOMM. & HIGH TECH. L. 241, 245 (2012) (describing "[s]cholarship in the technocratic market-calibration mode").
46. In a comic book depicting the effect of technology on society, Gérald Santucci estimates that about fifty billion devices will be networked by 2015 into an "Internet of Things." See Gérald Santucci, Foreword to ALEXANDRA INST., INSPIRING THE INTERNET OF THINGS! 3, 3 (Mirko Presser ed., 2011), available at http://www.alexandra.dk/uk/services/publications/documents/iot-comic-book.pdf.
47. See Steven C. Bennett, Regulating Online Behavioral Advertising, 44 J. MARSHALL L. REV. 899, 901-04 (2011).
48. See Tal Z. Zarsky, "Mine Your Own Business!": Making the Case for the Implications of the Data Mining of Personal Information in the Forum of Public Opinion, 5 YALE J.L. & TECH. 1, 6-8 (2002-2003)
49. see also Ira S. Rubinstein et al., Data Mining and Internet Profiling: Emerging Regulatory and Technological Approaches, 75 U. CHI. L. REV. 261, 272-73 (2008) (describing the capabilities of data mining).
50. See, e.g., Project, The Direct Selling Industry: An Empirical Study, 16 UCLA L. REV. 883, 895-922 (1969). The FTC promulgated regulations in 1972, for instance, by imposing a "cooling off" period for door-to-door sales.
51. Cooling-off Period for Door-to-Door Sales, 37 Fed. Reg. 22934, 22937 (1972) (codified as amended at 16 C.F.R. § 429.1 (2014)).
52. 37 Fed. Reg. at 22939 n. 44 ("The door to door selling technique strips from the consumer one of the fundamentals in his role as an informed purchaser, the decision as to when, where, and how he will present himself to the marketplace."); cf. James G. Webster, User Information Regimes: How Social Media Shape Patterns of Consumption, 104 NW. U. L. REV. 593, 598 (2010) (describing the difference between the "pull" method of audience building and the "push" or "interruption" method)).
53. See DAVE EVANS, CISCO, THE INTERNET OF THINGS: HOW THE NEXT EVOLUTION OF THE INTERNET IS CHANGING EVERYTHING 3 (2011)
54. Scott R. Peppet, Freedom of Contract in an Augmented Reality: The Case of Consumer Contracts, 59 UCLA L. REV. 676, 679 (2012).
55. Eric Goldman, A Coasean Analysis of Marketing, 2006 WIS. L. REV. 1151, 1202-09. Although possible in theory, today's filters are not run for the benefit of consumers and how these filters will be used in the future is unclear. Furthermore, as Goldman acknowledges, "[m]arketers are notorious for finding ways to bypass filters." Id. at 1207 n. 285.
56. West Point computer scientist Gregory Conti refers to "malicious interfaces" that are the opposite of usable or user-centric. See Gregory Conti & Edward Sobiesk, Malicious Interface Design: Exploiting the User, in PROCEEDINGS OF THE 19TH INTERNATIONAL CONFERENCE ON THE WORLD WIDE WEB 271, 271-80 (2010), available at http://dl.acm.org/citation.cfm?id=1772719.
57. British user experience designer Harry Brignull refers to user interface designs that work against the user as "dark patterns." See DARK PATTERNS, http://darkpatterns.org (last visited Aug. 21, 2014).
58. See Julius Genachowski, Chairman, Fed. Commc'ns Comm'n, Remarks on the Measuring Broadband America 2012 Report Presentation (July 19, 2012), https://apps.fcc.gov/edocs-public/attachmatch/DOC-315312A1.pdf.
59. Chris Harrison et al., Faster Progress Bars: Manipulating Perceived Duration with Visual Augmentations, in PROCEEDINGS OF THE SIGCHI CONFERENCE ON HUMAN FACTORS IN COMPUTING SYSTEMS 1545, 1545-48 (2010), available at http://dl.acm.org/citation.cfm?id=1753556&CFID=391340722&CFTOKEN=55472072 (finding new progress bar reduces perceived duration by eleven percent in subjects).
60. Jesus Diaz, This Is How Much the New iPhone 4 Signal Bars Have Grown, GIZMODO (July 15, 2010, 2:03 AM), http://gizmodo.com/5587535/this-is-how-much-the-new-iphone-4-signal-bars-have-grown ("Free tip: If you paint flames on the back of your iPhone 4, it runs 2.3x faster."). Chances are Apple is using what it understands about the psychology of design to substitute illusion for greater quality. At the extremes, the ability to design an interface from scratch means slot machines at a casino that create "near wins" to trigger the release of dopamine by the gambler's brain.
61. See Luke Clark et al., Gambling Near-Misses Enhance Motivation to Gamble and Recruit Win-Related Brain Circuitry, 61 NEURON 481, 481 (2009).
62. E.g., CASS SUNSTEIN, REPUBLIC.COM 71-73 (2001)
63. HERBERT A. SIMON, Rationality and Administrative Decision Making, in MODELS OF MAN: SOCIAL AND RATIONAL 196, 200-01 (1957).
64. See Owen D. Jones, Time-Shifted Rationality and the Law of Law's Leverage: Behavioral Economics Meets Behavioral Biology, 95 NW. U. L. REV. 1141, 1150-51 & nn. 30-32 (2001).
65. See, e.g., Amos Tversky & Daniel Kahneman, Judgment Under Uncertainty: Heuristics and Biases, 185 SCI. 1124, 1124 (1974).
66. See, e.g., Id.; Amos Tversky & Daniel Kahneman, Belief in the Law of Small Numbers, 76 PSYCHOL. BULL. 105, 105-10 (1971) [hereinafter Tversky & Kahneman, Belief]
67. Amos Tversky & Daniel Kahneman, The Framing of Decisions and the Psychology of Choice, 211 SCI. 453, 453-58 (1981).
68. See Amitai Etzioni, Behavioral Economics: Toward a New Paradigm, 55 AM. BEHAV. SCIENTIST 1099, 1100 (2011) ("The effect demonstrated by [Tversky and Kahneman], which the two scholars labeled anchoring and adjustment, has been replicated using a wide variety of stimuli and participants.")).
69. E.g., Dan Ariely, Controlling the Information Flow: Effects on Consumers' Decision Making and Preferences, 27 J. CONSUMER RES. 233, 233 (2000)
70. George Loewenstein, Out of Control: Visceral Influences on Behavior, 65 ORGANIZATIONAL BEHAV. & HUM. DECISION PROCESSES 272, 272 (1996) (exploring effect of "visceral factors" such as hunger, thirst, and sexual desire on decisionmaking)).
71. The number of biases consistently discussed by the literature has remained relatively stable since the field began. Compare Daniel Kahneman & Amos Tversky, Prospect Theory: An Analysis of Decision Under Risk, 47 ECONOMETRICA 263, 263-91 (1979) (discussing approximately fifteen biases)
72. Rüdiger F. Pohl, Introduction to COGNITIVE ILLUSIONS: A HANDBOOK ON FALLACIES AND BIASES IN THINKING, JUDGEMENT AND MEMORY 1, 1 (Rüdiger F. Pohl ed., 2004) (noting that collection surveys twenty-one "cognitive illusions"). Varying definitions of "bias," as well as differing systems of categorization, may lead to very different estimates as to the absolute number of known irrational tendencies. Regardless of the total given in a specific study or article, it is in no way near the many thousands this Section contemplates.
73. See id. at 280-81; see also Richard Thaler, Toward a Positive Theory of Consumer Choice, 1 J. ECON. BEHAV. & ORG. 39, 41-43 (1980).
74. See, e.g., CLIFFORD NASS & SCOTT BRAVE, WIRED FOR SPEECH: HOW VOICE ACTIVATES AND ADVANCES THE HUMAN-COMPUTER RELATIONSHIP 3-4 (2005).
75. See id.; BYRON REEVES & CLIFFORD NASS, THE MEDIA EQUATION: HOW PEOPLE TREAT COMPUTERS, TELEVISION, AND NEW MEDIA LIKE REAL PEOPLE AND PLACES 12 (1st paperback ed. 1996).
76. For a more detailed definition of big data and an optimistic account of its impact on society, see generally VIKTOR MAYER-SCHÖNBERGER & KENNETH CUKIER, BIG DATA: A REVOLUTION THAT WILL TRANSFORM HOW WE LIVE, WORK, AND THINK (2013).
77. For a more critical account, see generally Danah Boyd & Kate Crawford, Critical Questions for Big Data: Provocations for a Cultural, Technological, and Scholarly Phenomenon, 15 INFO. COMM. & SOC'Y 662 (2012).
78. See, e.g., Omer Tene & Jules Polonetsky, Big Data for All: Privacy and User Control in the Age of Analytics, 11 NW. J. TECH. & INTELL. PROP. 239, 245-46 (2013).
79. See id. But see Paul Ohm, Response, The Underwhelming Benefits of Big Data, 161 U. PA. L. REV. ONLINE 339, 345 (2013), http://www.pennlawreview.com/online/161-U-Pa-L-Rev-Online-339.pdf (urging caution in overestimating the benefits of big data, relative to the potential harms).
80. See Chris Anderson, The End of Theory, WIRED, July 2008, at 108, 108-09.
81. See id. But see Julie E. Cohen, What Privacy Is For, 126 HARV. L. REV. 1904, 1920-22 (2013) ("Considered more soberly, the claim that Big Data will eliminate the need for scientific modeling simply does not make sense.")). Cohen's concerns are largely ethically based. See id. at 1922-27.
82. See Graeme Wood, Anthropology Inc., ATLANTIC, Mar. 2013, at 48, 51, available at http://www.theatlantic.com/magazine/archive/2013/03/anthropology-inc/309218/.
83. See ASK ARIELY BLOG, http://www.danariely.com (last visited Aug. 21, 2014).
84. If the result of the big data process is highly individualized, then why is this Section titled "mass production" of bias? Sometimes personalization is the upshot of mass production; for example, when Henry Ford's assembly lines displaced public transportation in favor of a car for each family. See Thomas J. Sugrue, From Motor City to Motor Metropolis: How the Automobile Industry Reshaped Urban America, AUTOMOBILE AM. LIFE & SOC'Y, http://www.autolife.umd.umich.edu/Race/R-Overview/R-Overview.htm (last visited Aug. 21, 2014).
85. In recognizing a possible critique to this interview-based approach, Frank Easterbrook took the occasion of an inaugural cyberlaw conference to point out that lawyers risk dilettantism when they talk about technology. Frank H. Easterbrook, Cyberspace and the Law of the Horse, 1996 U. CHI. LEGAL F. 207, 207 ("I regret to report that no one at this Symposium is going to win a Nobel Prize any time soon for advances in computer science."). What Easterbrook misses, of course, is that lawyers can and do consult with professionals (e.g., expert witnesses) and colleagues in other disciplines.
86. See, e.g., Varun Chandola et al., Anomaly Detection: A Survey, ACM COMPUTING SURVS., July 2009, at 15, 15:2 ("Anomaly detection finds extensive use in a wide variety of applications such as fraud detection for credit cards, insurance, or health care, intrusion detection for cyber-security, fault detection in safety critical systems, and military surveillance for enemy activities.").
87. See generally Animesh Patcha & Jung-Min Park, An Overview of Anomaly Detection Techniques: Existing Solutions and Latest Technological Trends, 51 COMPUTER NETWORKS 3448 (2007) (surveying the anomaly detection literature in computer security context).
88. Cf. Quentin Hardy, Bizarre Insights From Big Data, N.Y. TIMES BITS BLOG (Mar. 28, 2012, 8:17 PM), http://bits.blogs.nytimes.com/2012/03/28/bizarre-insights-from-big-data/ (listing revelations from pattern spotting in large datasets).
89. See STEPHEN T. ZILIAK & DEIRDRE N. MCCLOSKEY, THE CULT OF STATISTICAL SIGNIF-ICANCE: HOW THE STANDARD ERROR COSTS US JOBS, JUSTICE, AND LIVES 1 (2008) ("For the past eighty years it appears that some of the sciences have made a mistake by basing decisions on statistical 'significance.' ")).
90. See Howard Latin, "Good" Warnings, Bad Products, and Cognitive Limitations, 41 UCLA L. REV. 1193, 1211-15 (1994) (describing the information overload phenomenon).
91. Omri Ben-Shahar & Carl E. Schneider, The Failure of Mandated Disclosure, 159 U. PA. L. REV. 647, 746 (2011).
92. See, e.g., Alessandro Acquisti & Jens Grossklags, What Can Behavioral Economics Teach Us About Privacy?, in DIGITAL PRIVACY: THEORY, TECHNOLOGIES, AND PRACTICES 363, 363-79 (Alessandro Acquisti et al. eds., 2008).
93. There is a revealing set of graphs in a 2012 communications paper showing how personal disclosure on the social network Facebook was trending fairly sharply downward until, around 2009, the company changed some of its privacy defaults. See Fred Stutzman et al., Silent Listeners: The Evolution of Privacy and Disclosure on Facebook, 4 J. PRIVACY & CONFIDENTIALITY, no. 2, 2012, at 7, 17, http://repository.cmu.edu/jpc/vol4/iss2/2/. From that point on, disclosure began steadily to climb again. See id.
94. See Leslie K. John et al., Strangers on a Plane: Context-Dependent Willingness to Divulge Sensitive Information, 37 J. CONSUMER RES. 858, 863-68 (2011).
95. Laura Brandimarte et al., Misplaced Confidences: Privacy and the Control Paradox, 4 SOC. PSYCHOL. & PERSONALITY SCI. 340, 340-47 (2013).
96. See, e.g., B.J. Fogg & Clifford Nass, How Users Reciprocate to Consumers: An Experiment That Demonstrates Behavior Change, in CHI '97 EXTENDED
97. For an in-depth look at the rise of A/B testing, see Brian Christian, The A/B Test, WIRED, May 2012, at 176.
98. One can already buy socalled "sucker lists" on the open market. These are people?the elderly, for instance?who analysts have classified as vulnerable. See Karen Blumenthal, How Banks, Marketers Aid Scams, WALL ST. J., July 1, 2009, at D3.
99. The "What They Know" series from The Wall Street Journal has, in particular, illustrated the extent of online tracking. This section of The Wall Street Journal's website collects all articles and information related to privacy concerns and tracking information. What They Know, WALL ST. J., http://online.wsj.com/public/page/what-they-know-digital-privacy.html (last visited Aug. 21, 2014).
100. For a more specific example, see Jennifer Valentino-Devries & Jeremy Singer-Vine, They Know What You're Shopping For, WALL ST. J. (Dec. 7, 2012), http://online.wsj.com/news/articles/SB10001424127887324784404578143144132736214.
101. See, e.g., Keith Wagstaff, Will Your Mall Be Tracking Your Cellphone Today?, TIME (Nov. 25, 2011), http://techland.time.com/2011/11/25/will-your-mall-be-tracking-your-cellphone-today/.
102. See, e.g., Robert Salladay, High-Tech Billboards Tune In to Drivers' Tastes: Roadside Signs Coming to Bay Area Listen to Car Radios, Then Adjust Pitch, S.F. CHRON., Dec. 22, 2002, at A1.
103. See Richard Warner & Robert H. Sloan, Behavioral Advertising: From One-Sided Chicken to Informational Norms, 15 VAND. J. ENT. & TECH. L. 49, 60 (2012).
104. The industry calls this practice "interest-based advertising." See NETWORK ADVER. INITIATIVE, 2013 NAI CODE OF CONDUCT 9 (2013), available at http://www.networkadvertising.org/2013-Principles.pdf.
105. See generally Julia Angwin, The Web's New Gold Mine: Your Secrets, WALL ST. J., July 31-Aug. 1, 2010, at W1.
106. See generally Maurits Kaptein & Steven Duplinsky, Combining Multiple Influence Strategies to Increase Consumer Compliance, 8 INT'L J. INTERNET MARKETING & ADVERTISING 32, 33-51 (2013)
107. Maurits Kaptein & Dean Eckles, Heterogeneity in the Effects of Online Persuasion,
108. J. INTERACTIVE MARKETING, 176, 176-88 (2012)
109. Maurits Kaptein et al., Means Based Adaptive Persuasive Systems, in PROCEEDINGS OF THE SIGCHI CONFERENCE ON HUMAN FACTORS IN COMPUTING SYSTEMS 335-44 (2011), available at http://dl.acm.org/citation.cfm?id=1978990.
110. See also Yin-Hui Cheng et al., The Effect of Companion's Gender on Impulsive Purchasing: The Moderating Factor of Cohesiveness and Susceptibility to Interpersonal Influence, 43 J. APPLIED SOC. PSYCHOL. 227, 227-36 (2013).
111. See id. at 187; see also Maurits Kaptein & Dean Eckles, Selecting Effective Means to Any End: Futures and Ethics of Persuasion Profiling, in PROCEEDINGS OF THE 5TH INTERNATIONAL CONFERENCE ON PERSUASIVE TECHNOLOGY 82, 82-93 (Thomas Ploug et al. eds., 2010), available at http://dl.acm.org/citation.cfm?id=2164027.
112. See, e.g., John R. Hauser et al., Website Morphing, 28 MARKETING SCI. 202, 202-06 (2009).
113. JOHN E. CALFEE, FEAR OF PERSUASION: A NEW PERSPECTIVE ON ADVERTISING AND REGULATION (1997).
114. See, e.g., John M. Church, A Market Solution to Green Marketing: Some Lessons from the Economics of Information, 79 MINN. L. REV. 245, 246-50 (1994)
115. Dean K. Cherchiglia, Note, Changing Channels in Broadcast Regulation: Leaving Television Advertising to Containment by Market Forces, 34 CASE W. RES. L. REV. 465, 465-70 (1984).
116. For example, some question whether contemporary advertising is effective at generating demand at all - though this claim seems to be in tension with contemporary advertising's purported benefits and the sheer amount of money that is spent on marketing. See Tamara R. Piety, "A Necessary Cost of Freedom"? The Incoherence of Sorrell v. IMS, 64 ALA. L. REV. 1, 19 n. 102 (2012).
117. See Int'l Harvester Co., 104 F.T.C. 949 app. at 1070, 1073 (1984) (FTC Policy Statement on Unfairness) ("To justify a finding of unfairness the injury must satisfy three tests. It must be substantial; it must not be outweighed by any countervailing benefits to consumers or competition that the practice produces; and it must be an injury that consumers themselves could not reasonably have avoided.")
118. Danielle Keats Citron, Law's Expressive Value in Combating Cyber Gender Harassment, 108 MICH. L. REV. 373, 392-95 (2009) (discussing how emotional distress torts often founder on damages).
119. For instance, Dean Eckles, co-author of several papers on persuasion profiling, now works on the "data science team" of the social network Facebook. See Dean Eckles, Curriculum Vitae, available at http://deaneckles.com/Dean-Eckles-CV.pdf. Of course, this does not mean that Facebook is using the technique, nor that the motivation behind Eckles' academic work is in any way suspect. Eckles appears aware of the potential for unethical use of the techniques he helped pioneer. See Kaptein & Eckles, supra note 128, at 82-93.
120. Letter from Mark Twain to J.H. Todd (Nov. 20, 1905), available at http://www.letter-sofnote.com/2010/01/youre-idiot-of-33rd-degree.html.
121. See, e.g., WILSON BRYAN KEY, SUBLIMINAL SEDUCTION: AD MEDIA'S MANIPULATION OF A NOT SO INNOCENT AMERICA 1-5 (Signet 1974) (describing subliminal techniques of advertising)
122. WILSON BRYAN KEY, THE AGE OF MANIPULATION: THE CON IN CONFIDENCE, THE SIN IN SINCERE 7-34 (Madison Books 1992) (describing subliminal techniques of advertising)
123. SUSAN LINN, CONSUMING KIDS: THE HOSTILE TAKEOVER OF CHILDHOOD 1-10 (2004) (criticizing practices of marketing to children)
124. See Jessica M. Choplin et al., A Psychological Investigation of Consumer Vulnerability to Fraud: Legal and Policy Implications, 35 LAW & PSYCHOL. REV. 61, 62 (2011) ("We hypothesize that when unscrupulous salespeople, including mortgage brokers and lenders, reassure consumers and explain away 'problematic' contract terms (i.e., terms inconsistent with what was previously promised and against the consumer's interest)), many consumers will acquiesce to the problematic terms.")
125. Wenxia Guo & Kelley J. Main, The Vulnerability of Defensiveness: The Impact of Persuasion Attempts and Processing Motivations on Trust, 23 MARKETING LETTERS 959, 962 (2012) (describing how a clever salesperson can exploit a consumer's very defensiveness to increase the likelihood of a sale).
126. See Debin Liu, The Economics of Proof-of-Work, 3 I/S: J.L. & POL'Y FOR INFO. SOC'Y 335, 336 (2007) (describing prevalence and mechanisms of spam).
127. See Jason C. Miller, Note, Regulating Robocalls: Are Automated Calls the Sound of, or a Threat to, Democracy?, 16 MICH. TELECOMM. & TECH. L. REV. 213, 214-17 (2009) (describing the prevalence and mechanisms of automated or "robo" calls).
128. Jolls, Sunstein, and Thaler discuss how a "severe departure from the reference transaction" can lead to official intervention even if such intervention does not maximize welfare. Jolls et al., supra note 18, at 1510-17. The authors use the practice of scalping tickets to an event as one such example. Id. at 1513; see also M. Ryan Calo, The Drone as Privacy Catalyst, 64 STAN. L. REV. ONLINE 29, 29-33 (2011), http://www.stanfordlawreview.org/online/drone-privacy-cata-lyst (arguing that society's visceral reaction to surveillance drones may change privacy law in ways that previous, readily analogous technologies did not).
129. See Brent T. White, Walking Away Scot-Free: Trust, Expert Advice, and Realtor Responsibility, 40 REAL EST. L.J. 312, 316-320 (2011) (describing the role of a buyers agent in detail).
130. See Paula C. Murray, The Real Estate Broker and the Buyer: Negligence and the Duty to Investigate, 32 VILL. L. REV. 939, 957 (1987).
131. The idea that harm should be a threshold question in law is a staple of Western political thought. See, e.g., JOHN STUART MILL, ON LIBERTY 21-22 (2d ed. 1859) ("[T]he only purpose for which power can be rightfully exercised over any member of a civilized community, against his will, is to prevent harm to others.")).
132. see also Doe v. Chao, 540 U.S. 614, 625-26 (2004) (remarking on the intent of Congress to "avoid[] giveaways to plaintiffs with nothing more than 'abstract injuries'"
133. (quoting Los Angeles v. Lyons, 461 U.S. 95, 101-02 (1983)).
134. See, e.g., Richard A. Musgrave, Merit Goods, in 3 THE NEW PALGRAVE: A DICTIONARY OF ECONOMICS 452-53 (John Eatwell et al. eds., 1987). Merit goods are goods authorities want to see greater consumption of; demerit goods are goods that should be consumed less. See id.
135. See, e.g., LOUIS PHLIPS, THE ECONOMICS OF PRICE DISCRIMINATION 1 (1983) ("[G]enerally, discriminatory prices [are] required for an optimal allocation of resources in real life situations." (emphasis omitted)).
136. See generally OREN BAR-GILL, SEDUCTION BY CONTRACT: LAW, ECONOMICS, AND PSYCHOLOGY IN CONSUMER MARKETS (2012).
137. See, e.g., Russell Korobkin, Bounded Rationality, Standard Form Contracts, and Unconscionability, 70 U. CHI. L. REV. 1203, 1234-35, 1290, 1294 (2003)
138. see also Woodrow Hartzog, Website Design as Contract, 60 AM. U. L. REV. 1635, 1664 (2011) (noting that the very design of a website might be frustrating enough to consumer choice as to be deemed unconscionable)).
139. See, e.g., Andrew Odlyzko, Privacy, Economics, and Price Discrimination on the Internet, in ECONOMICS OF INFORMATION SECURITY 187, 208 (L. Jean Camp & Stephen Lewis eds., 2004).
140. Cf. Amanda Conley & Laura Moy, Paying the Wealthy for Being Wealthy: Why We Should Care About Information Privacy Even If We Have "Nothing to Hide" (July 25, 2012) (unpublished manuscript) (on file with The George Washington Law Review) (arguing that price and offer discrimination may exacerbate economic inequality). Moy and Conley arguably go too far; economic inequality is a complex phenomenon with many causes. Still, the authors make an interesting point.
141. See Jan Whittington & Chris Jay Hoofnagle, Unpacking Privacy's Price, 90 N.C. L. REV. 1327, 1328-29 (2012) (discussing how consumers' expectations of social networking services result in unanticipated costs after joining such a service)).
142. See, e.g., Caveat Emptor.com, ECONOMIST, June 30, 2012, at 12 (canvassing steps consumers can take to avoid dynamic price discrimination).
143. See Amazon.com Privacy Notice, AMAZON.COM, http://www.amazon.com/gp/help/customer/display.html?nodeId=468496 (last updated Mar. 3, 2014) ("We receive and store certain types of information whenever you interact with us.
144. Amazon actually implemented such a practice for a brief time in 2000. See JONATHAN ZITTRAIN, THE FUTURE OF THE INTERNET AND HOW TO STOP IT 204 (2008).
145. More recently, The Wall Street Journal has uncovered extensive evidence of offers and prices changing from user to user by other companies. See Jennifer Valentino-Devries et al., Websites Vary Prices, Deals Based on Users' Information, WALL ST. J., Dec. 24, 2012, at A1.
146. See Daniel J. Solove, Conceptualizing Privacy, 90 CAL. L. REV. 1087, 1088-93 (2002) (canvassing theories of privacy harm and finding every single one either overor under-inclusive).
147. See, e.g., M. Ryan Calo, The Boundaries of Privacy Harm, 86 IND. L.J. 1131, 1132 (2011).
148. See, e.g., A. Michael Froomkin, The Death of Privacy?, 52 STAN. L. REV. 1461, 1468 (2000) ("Privacy-destroying technologies can be divided into two categories: those that facilitate the acquisition of raw data and those that allow one to process and collate that data in interesting ways.")).
149. See Paul M. Schwartz, Commentary, Internet Privacy and the State, 32 CONN. L. REV. 815, 820 (2000) ("The leading paradigm on the Internet and in the real, or offline world, conceives of privacy as a personal right to control the use of one's data.")).
150. Schmerber v. California, 384 U.S. 757 (1966).
151. Daniel J. Solove, Privacy and Power: Computer Databases and Metaphors for Information Privacy, 53 STAN. L. REV. 1393, 1419 (2001).
152. See supra Part III.B. 1. Peter Swire makes an analogous point in which he includes the costs associated with self-protection, entitled "cloaking costs," in his description of privacy harms. See Peter P. Swire, Financial Privacy and the Theory of High-Tech Government Surveillance, 77 WASH. U. L. Q. 461, 475 (1999).
153. Compare Paul Ohm, Broken Promises of Privacy: Responding to the Surprising Failure of Anonymization, 57 UCLA L. REV. 1701, 1703-04 (2010) (arguing that de-anonymizing is too routine for privacy statutes to exempt anonymized data from their ambit)
154. Jane Yakowitz, Tragedy of the Data Commons, 25 HARV. J.L. & TECH. 1, 3-4 (2011) (asserting that the dangers of de-anonymization are overstated, and the benefits of data mining understated).
155. See Richards, supra note 11, at 1935 (discussing the public-private divide in digital surveillance); cf. Robert M. Cover, Violence and the Word, 95 YALE L.J. 1601, 1601 (1986) ("Legal interpretation takes place in a field of pain and death." (footnote omitted)).
156. See, e.g., JULIE E. COHEN, CONFIGURING THE NETWORKED SELF: LAW, CODE, AND THE PLAY OF EVERYDAY PRACTICE 57 (2012) (describing how increased surveillance can lead to coordinated behavior that bends to the digital gaze instead of eliciting resistance)).
157. See John Christman, Autonomy in Moral and Political Philosophy, STAN. ENCYCLOPEDIA PHIL., http://plato.stanford.edu/entries/autonomy-moral/ (last updated Feb. 25, 2011) ("The variety of contexts in which the concept of autonomy functions has suggested to many that there are simply a number of different conceptions of autonomy, and that the word simply refers to different elements in each such of contexts.").
158. See, e.g., J.B. SCHNEEWIND, THE INVENTION OF AUTONOMY: A HISTORY OF MODERN MORAL PHILOSOPHY 3-5 (8th prtg. 2008) (arguing that Immanuel Kant "invented" rather than "discovered" the concept of autonomy in political philosophy from disparate, constituent parts)).
159. Others question autonomy as a subordinating value. See, e.g., Marina Oshana, How Much Should We Value Autonomy?, SOC. PHIL. & POL'Y, July 2003, at 99, 99, available at http://journals.cambridge.org/action/displayFulltext?type=1&pdftype=1&fid=191526&jid=SOY&volumeId=20&issueId=02&aid=191525 ("[T]he focus of this essay is on the phenomenon⋯ of being 'blinded' by the ideal of autonomy. What happens if we value autonomy too much?").
160. See, e.g., Craswell, Interpreting Deceptive Advertising, supra note 13, at 665-80.
161. For example, Florencia Luna defends "layers" of vulnerability over labels: "[A] way of understanding this proposal is not by thinking that someone is vulnerable, but by considering a particular situation that makes or renders someone vulnerable." See Florencia Luna, Elucidating the Concept of Vulnerability: Layers Not Labels, INT'L J. FEMINIST APPROACHES TO BIOETHICS, Spring 2009, at 121, 129.
162. See, e.g., BAUMEISTER & TIERNEY, supra note 3, at 1-5 (describing vulnerability studies).
163. See generally, e.g., Jim Rutenberg, Data You Can Believe In: How The Precision Targeting of "Persuadable" Voters That Put Obama Over the Top in 2012 Could Revolutionize the Advertising Industry, N.Y. TIMES MAG., June 23, 2013, at 22 (chronicling the rise of data-driven campaigning and the migration of campaign staffers to advertising firms following the election).
164. See Cent. Hudson Gas & Elec. Corp v Pub. Serv. Comm'n of N.Y., 447 U.S. 557, 561-64 (1980) (distinguishing commercial from political speech and laying out the standard of review).
165. The Supreme Court had the chance to expand or narrow the definition of commercial speech in Nike, Inc v Kasky, a case involving a corporation coming to its own defense against allegations of labor abuse. Nike, Inc v Kasky, 539 U.S. 654, 656-58 (2003). The Court declined to implement such an expansion over several dissents. Id. at 665-84.
166. Cf. Steven Shavell, Strict Liability Versus Negligence, 9 J. LEGAL STUD. 1, 1-2 (1980) (providing a classic discussion of the role of "activity level" in tort).
167. Neil M. Richards, Reconciling Data Privacy and the First Amendment, 52 UCLA L. REV. 1149, 1182 (2005).
168. Bartnicki v. Vopper, 532 U.S. 514, 517-18 (2001).
169. See ROBERT M. O'NEIL, THE FIRST AMENDMENT AND CIVIL LIABILITY 74-90 (2001)
170. See generally Jane Bambauer, Is Data Speech?, 66 STAN. L. REV. 57 (2014).
171. See id. at 58-64. Bambauer also engages with First Amendment theory more generally, and her stated aim is to create "a satisfying analytical framework for the variety of data collection practices that will give rise to First Amendment questions." Id. at 63. She goes on, however, to adopt Seana Shiffrin's "thinker-based" approach for triggering free speech scrutiny nearly verbatim and declines to comment on the level of scrutiny that should apply to data as speech. See id. at 83, 88, 104-106 (citing Seana Valentine Shiffrin, A Thinker-Based Approach to Freedom of Speech, 27 CONST. COMMENT. 283 (2011)).
172. Dietemann v. Time, Inc., 449 F. 2d 245 (9th Cir. 1971).
173. U.S. West, Inc v FCC, 182 F. 3d 1224 (10th Cir. 1999).
174. Sorrell v. IMS Health Inc., 131 S. Ct. 2653 (2011).
175. See Jack K. Levin & Lucas Martin, Scope of Consent, 75 AM. JUR. 2D Trespass § 75 (2007) ("One may become a trespasser by exceeding the scope of the consent, such as by intentionally conducting oneself in a manner differing from that allowed." (footnote omitted).
176. See id. Alternatively, one might say that society is prepared to accept Dietemann's expectation of privacy against recording technology as reasonable and compensate him accordingly. Bambauer seems to acknowledge as much in other work. See Jane Yakowitz Bambauer, The New Intrusion, 88 NOTRE DAME L. REV. 205, 235 (2012) ("The tort of intrusion reinforces norms by tracking social consensus, which means that most people will recognize what is and is not seclusion, even in new contexts. This makes the tort especially flexible and appropriate for application to new technologies.")).
177. Florida v. Jardines, 133 S. Ct. 1409 (2013).
178. U.S. West, Inc v FCC, 182 F. 3d 1224, 1229 (10th Cir. 1999).
179. Sorrell v. IMS Health Inc., 131 S. Ct. 2653, 2663-64 (2011) ("Given the legislature's expressed statement of purpose, it is apparent that [the law] imposes burdens that are based on the content of speech and that are aimed at a particular viewpoint⋯. It follows that heightened judicial scrutiny is warranted.")
180. see also R.A.V v City of St. Paul, 505 U.S. 377, 382-85 (1992) (prohibiting viewpoint discrimination even for otherwise proscribable categories of speech such as "fighting words")).
181. See, e.g., Glik v. Cunniffe, 655 F. 3d 78, 79 (1st Cir. 2011) (videotaping the police in public)
182. Pomykacz v. Borough of W. Wildwood, 438 F. Supp. 2d 504, 510-13 (D.N.J. 2006) (photographing the mayor in public).
183. See ROBERT C. POST, DEMOCRACY, EXPERTISE, AND ACADEMIC FREEDOM: A FIRST AMENDMENT JURISPRUDENCE FOR THE MODERN STATE 1 (2012) (distinguishing "coverage," whether the First Amendment applies at all, from "protection," the level of scrutiny free speech then requires)).
184. See, e.g., Cent. Hudson Gas & Elec. Corp v Pub. Serv. Comm'n of N.Y., 447 U.S. 557, 566 (1980).
185. See Robert Post, The Constitutional Status of Commercial Speech, 48 UCLA L. REV. 1, 38-40 (2000).
186. Ohralik v. Ohio State Bar Ass'n, 436 U.S. 447 (1978).
187. Bates v. State Bar of Ariz., 433 U.S. 350, 383-84 (1977).
188. See Shapero v. Ky. Bar Ass'n, 486 U.S. 466, 475 (1988) ("In assessing the potential for overreaching and undue influence, the mode of communication makes all the difference.")).
189. See, e.g., Tanzina Vega, Ad Texts, Tailored to Location, N.Y. TIMES, Feb. 28, 2011, at B6.
190. See Bill Wasik, Try It On, WIRED, Jan. 2014, at 90
191. Mark Prigg, Samsung Confirms It Is 'Investing Heavily' in Wearable Computers to Take on Google Glass and Apple's Rumoured iWatch, DAILY MAIL ONLINE (July 9, 2013, 11:40 AM), http://www.dailymail.co.uk/sciencetech/article-2358924/Samsung-confirms-investing-heavily-wearable-computers-takes-Google-Glass-Apples-rumoured-iWatch.html.
192. Citizens United v. FEC, 558 U.S. 310 (2010). In Citizens United v. FEC, the Court found inter alia that corporations constitute associations of individuals for purposes of the First Amendment. Id. at 342-65.
193. B.J. FOGG, PERSUASIVE TECHNOLOGY: USING COMPUTERS TO CHANGE WHAT WE THINK AND DO 103-05 (2003).
194. For a definition of neuromarketing, as well as a clever discussion of its intersection with commercial speech doctrine, see generally Marisa E. Main, Simply Irresistible: Neuromarketing and the Commercial Speech Doctrine, 50 DUQ. L. REV. 605 (2012).
195. Roman law imposed wide-ranging duties of good faith (bonae fidei). See BARRY NICHOLAS, AN INTRODUCTION TO ROMAN LAW 176 (1962). Signs of duress (metus) and or bad faith, broadly defined (dolus), could negate a transaction. Id. Even the failure of one party to correct a misapprehension of the other party constituted bad faith. Id. I have Hugh Spitzer to thank for this point.
196. The 2013 Edelman Trust Barometer shows that of more than 31,000 respondents, only nineteen percent trust business leaders to make ethical and moral decisions. Edelman Trustbarometer: 2013 Annual Global Study, EDELMAN (Jan. 20, 2013), http://www.edelman.com/trust-downloads/global-results-2/ (showing results on slide 30 of the presentation). Twenty-three percent of respondents cited "wrong incentives for driving business decisions" as a reason for trusting business less (second only to "corruption or fraud" at twenty-seven percent). Id. at slide 12.
197. See Kenneth A. Bamberger & Deirdre K. Mulligan, Privacy on the Books and on the Ground, 63 STAN. L. REV. 247, 303 (2011) ("The shortcomings of command-and-control governance⋯ are well recognized.")
198. Dennis D. Hirsch, Protecting the Inner Environment: What Privacy Regulation Can Learn from Environmental Law, 41 GA. L. REV. 1, 9, 10-11, 33-37 (2006) (arguing that "command-and-control type regulations would not be a good fit for the highly diverse and dynamic digital economy" due to the expense and threat to innovation)
199. Cass R. Sunstein, Administrative Substance, 1991 DUKE L.J. 607, 627 (critiquing command-and-control regulation).
200. See generally Woodrow Hartzog & Frederic Stutzman, The Case for Online Obscurity, 101 CAL. L. REV. 1 (2013) (formalizing the concept of obscurity as a means to minimize the risk that information will find its way to unintended recipients)).
201. See FED. TRADE COMM'N, PRIVACY ONLINE: FAIR INFORMATION PRACTICES IN THE ELECTRONIC MARKETPLACE 27-28 (2000), available at http://www.ftc.gov/sites/default/files/documents/reports/privacy-online-fair-information-practices-electronic-marketplace-federal-trade-commission-report/privacy2000text.pdf.
202. See, e.g., Privacy Policy, GOOGLE (Mar. 31, 2014), http://www.google.com/policies/privacy/ (stating data collection is necessary because it enables Google to develop new and improve existing products).
203. For instance, the online auction website eBay uses data to police against shill bidding, i.e., where an auctioneer bids on his own items in order to drive up other bids. Shill Bidding Policy, EBAY, http://pages.ebay.com/help/policies/seller-shill-bidding.html (last visited Aug. 22, 2014).
204. See generally Matthew A. Edwards, The FTC and New Paternalism, 60 ADMIN. L. REV. 323, 324-25 (2008) (illustrating the various challenges the FTC would encounter were it to try to bring claims based on behavioral economics)).
205. Cliffdale Assocs., Inc. 103 F.T.C. 110 app. at 174 (1984) (FTC Policy Statement on Deception) (defining deception).
206. Int'l Harvester Co., 104 F.T.C. 949 app. at 1070, 1073 (1984) (FTC Policy Statement on Unfairness) (defining unfairness).
207. Peter Swire has helpfully distinguished between "elephants," i.e., companies too big to avoid scrutiny, and "mice," who can hope to ignore the law. Peter P. Swire, Elephants and Mice Revisited: Law and Choice of Law on the Internet, 153 U. PA. L. REV. 1975, 1978-79 (2005).
208. Indeed, the FTC tends to seek consent orders with large companies with arguably mild privacy or security infractions, and smaller companies engaged in more flagrant behavior. See Marcia Hofmann, Federal Trade Commission Enforcement of Privacy, in Proskauer on Privacy § 4:1 (Kristen J. Mathews ed., 2013) (regularly updated summary of FTC privacy enforcement).
209. See Richard Craswell, Static Versus Dynamic Disclosures, and How Not to Judge Their Success or Failure, 88 WASH. L. REV. 333, 347-48 (2013).
210. Arguably notice is about conveying information, whereas nudging is about changing behavior. See Ryan Calo, Code, Nudge, or Notice?, 99 IOWA L. REV. 773, 775-78 (2014).
211. For instance, patients might be reticent to ignore the advice of doctors who have disclosed a conflict of interest for fear of insinuating corruption. See George Loewenstein et al., The Limits of Transparency: Pitfalls and Potential of Disclosing Conflicts of Interest, 101 AM. ECON. REV. (PAPERS & PROC.) 423, 424 (2011).
212. EVGENY MOROZOV, TO SAVE EVERYTHING, CLICK HERE: THE FOLLY OF TECHNOLOGICAL SOLUTIONISM 148 (2013). There are several flaws with technology critic Evgeny Morozov's analogy as presented. There is little evidence, for instance, to suggest that Google recorded personal WiFi data on purpose, and ample evidence that the company routinely thinks through ethical dilemmas such as when and how to report government requests for censorship or user data. The problem with Google Buzz - a social network that lead to a privacy law suit - was not enough consumer testing. But analyze the observation from a different direction. When firms study consumers scientifically for gain, why should scientific norms not apply?
213. NAT'L COMM'N FOR THE PROTECTION OF HUMAN SUBJECTS OF BIOMEDICAL & BEHAVIORAL RESEARCH, THE BELMONT REPORT: ETHICAL PRINCIPLES AND GUIDELINES FOR THE PROTECTION OF HUMAN SUBJECTS OF RESEARCH (1978) [hereinafter BELMONT REPORT].
214. See Charles W. Lidz & Suzanne Garverich, What the ANPRM Missed: Additional Needs for IRB Reform, 41 J.L. MED. & ETHICS 390, 390 (2013) ("IRBs have always come under considerable criticism. Some have critiqued IRBs for using important resources inefficiently⋯. Others have critiqued the inconsistency of review of multisite projects.")).
215. Of course, these companies have other problems. See Anupam Chander, How Censorship Hurts Chinese Internet Companies, ATLANTIC (Aug. 12, 2013, 12:21 PM), http://www.theatlantic.com/china/archive/13/08/how-censorship-hurts-chinese-internet-companies/278587/.
216. Cf. Webster, supra note 44, at 598 (citing PHILIP M. NAPOLI, AUDIENCE ECONOMICS: MEDIA INSTITUTIONS AND THE AUDIENCE MARKETPLACE 2-3 (2003)) (distinguishing between markets in which media is sold to audiences and markets where audiences are sold to advertisers). A recent study by Juniper Networks found that free apps were between 300 and 400 percent more likely to track users than paid ones.
217. See Daniel Hoffman, Exposing Your Personal Information - There's an App for That, JUNIPER NETWORKS (Oct. 30, 2012, 2:54 PM), http://forums.juniper.net/t5/Security-Mobility-Now/Exposing-Your-Personal-Information-There-s-An-App-for-That/ba-p/166058.
218. See, e.g., Mary Ellen Gordon, The History of App Pricing, and Why Most Apps Are Free, FLURRY (July 18, 2013), http://www.flurry.com/bid/99013/The-History-of-App-Pricing-And-Why-Most-Apps-Are-Free (noting that when consumers are given a choice between an advertisement free app or an app with even a nominal onetime fee, consumers overwhelmingly choose the advertisement infused free version).
219. See, e.g., JAN A.G.M. VAN DIJK, THE DEEPENING DIVIDE: INEQUALITY IN THE INFORMATION SOCIETY 1 (2005).
220. See THALER & SUNSTEIN, supra note 22, at 244-45 (citing JOHN RAWLS, A THEORY OF JUSTICE (1971)).
221. See Luc Bovens, The Ethics of Nudge, in PREFERENCE CHANGE: APPROACHES FROM PHILOSOPHY, ECONOMICS AND PSYCHOLOGY 207, 207-20 (Till Grüne-Yanoff & Sven Ove Hansson eds., 2009).
222. See, e.g., Richard A. Epstein, Behavioral Economics: Human Errors and Market Corrections, 73 U. CHI. L. REV. 111, 114-16 (2006) (restricting analysis of irrationality to decisions made by children and specific cases of force, fraud, or mistake)
223. Richard A. Posner, Rational Choice, Behavioral Economics, and the Law, 50 STAN. L. REV. 1551, 1552 (1998).