Dishonesty Norms in Bargaining - Paul Ohm

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Dishonesty Norms in Bargaining - Paul Ohmin,In,Paul,norms,NoRms,Ohm




    Forthcoming Northwestern University Law Review (2011).

     *By Scott R. Peppet

    As for privacy in general, it is difficult to see how a

    pooling equilibrium is avoided in which privacy is

    „voluntarily‟ surrendered, making the legal protection of

    privacy futile. 1 -- Richard Posner


     Every day that Tom Goodwin drives his Chevy Tahoe, his insurance company uses a small electronic monitor in his car to track his total driving time, speed, and driving habits. If he drives less than ten thousand hours a year, doesn‟t drive much after midnight, and avoids frequently slamming on

    the brakes, at the end of the year he receives up to twenty-five percent off his premiums. “There‟s this Big Brother thing, but it‟s good,” Goodwin says. 2“Since I know I‟m being watched, I‟m on my best behavior.” To date, 3Progressive Insurance‟s MyRate program is available in twenty states and

    has enrolled roughly ten thousand customers. Other insurance companies are 4following suit. Some carriers are going further, offering discounts for the use of more sophisticated devices that record geographical location, minute-5by-minute speeding violations, and whether seat belts are in use. Rental car

     * Associate Professor of Law, University of Colorado School of Law. I thank my colleagues at the University of Colorado Law School for their interest in and feedback on this project, particularly Paul Ohm, Vic Fleischer and Phil Weiser. I thank Mark Gibson and Matt Burns for their excellent research assistance. 1 Richard Posner, Privacy, in 3 THE NEW PALGRAVE DICTIONARY OF ECON. & THE LAW 103

    (1998) [hereinafter Posner, Privacy]. 2Bengt Halvorson, Car Insurance Savings Come With „Big Brother,‟ (last visited July 9, 2010). 3 See (last visited July 9, 2010). The program was recently renamed Snapshot and updated slightly. See id. (last visited August 3, 2010). 4 Many insurance providers offer similar discounts, sometimes of up to sixty percent off regular premiums. See Jilian Mincer, To Your Benefit, WALL ST. J. (Dec. 7, 2009) (discussing

    various plans). GMAC Insurance, for example, uses OnStar data to track total miles driven. See (last visited July 1, 2010). 5 See (last visited July 12, 2010). Intel is working on more sophisticated monitoring systems for cars akin to the “black boxes” in aircraft, capable of

    recording and transmitting basic vehicle telemetry, whether seat belts are in use, geographical location, mechanical malfunctions, and video of auto accidents, all of which would be of great interest to an insurance carrier. See John R. Quain, Intel Working on Black Box for Your


    companies have also experimented with using such monitors to incentivize safe driving.

     Similarly, every day the Mayo Clinic in Rochester, Minnesota uses remote monitoring devices to check up on the health of residents at the nearby Charter House senior living center. The devices transmit data about irregular heart rhythm, breathing rate, and the wearer‟s position and motion. “The goal,” says Dr. Charles Bruce, the lead investigator on the project, “is to have full remote monitoring of people, not patients, just like you measure 6the pressure of your tires today.” Medical device companies are racing to

    enter the remote monitoring space. Proteus Biomedical, for example, is testing a wearable electronic device that can sense when patients have taken 7their pills and transmit that information to the patients‟ doctors, and

    GlySens is working on an implantable subcutaneous blood sugar sensor for diabetics that uses the cellular network to constantly send real time results to 8one‟s doctor. Although today these devices do not report data to users‟

    health insurers, it would be a simple step for a patient to provide such access in return for a discount. Indeed, such “pervasive lifestyle incentive 9management” is already being discussed by those in the healthcare field.

     Finally, every day tenants, job applicants, and students voluntarily disclose verified personal information to their prospective landlords, employers, and safety-conscious universities using online services such as Rather than forcing these entities to run a

    background check, an applicant can digitally divulge pre-verified information such as criminal record, sex offender status, eviction history, and previous rental addresses. Moreover, these services allow an applicant to augment her resume by having verified drug testing done at a local collection site and added to her digital record. 11calls this “resume enhancement.”

Car, NEW YORK TIMES (July 7, 2010). Event recorders may become mandatory in new thvehicles. See Motor Vehicle Safety Act of 2010, S. 3302, 111 Cong. ?107 (2010). For

    discussion of the privacy implications of such technologies, see Patrick R. Mueller, Every

    Time You Brake, Every Turn You Make—I‟ll Be Watching You: Protecting Driver Privacy in

    Event Data Recorder Information, 2006 WIS. L. REV. 135 (2006). 6 (last visited July 1, 2010). 7 See Don Clark, Take Two Digital Pills and Call Me in the Morning, WALL ST. J. (Aug. 4,

    2009). 8 See (last visited August 1, 2010). Regular blood sugar monitors (which require pricking the finger) already exist to transmit such data electronically after each reading. See (last visited July 20, 2010). 9 See e.g., Upkar Varshney, Pervasive Healthcare and Wireless Health Monitoring, 12

    MOBILE NETW. APPL. 113, 115 (2007) (“Pervasive lifestyle incentive management could involve giving a small mobile micro-payment to a user device every time the user exercises or eats healthy food.”). 10 See (last visited July 11, 2010). 11 See (last visited July 11, 2010).


     This Article makes three claims. First, these examplesTom

    Goodwin‟s car insurance, pervasive health monitoring, and the

    incorporation of verified drug testing into one‟s “enhanced resume”—illustrate that rapidly changing information technologies are making possible the low-cost sharing of verified personal information for economic reward, or, put differently, the incentivized extraction of previously unavailable personal information from individuals by firms. In this new world, economic actors do not always need to “sort” or screen each other based on publicly available information, but can instead incentivize each other to “signal” their characteristics. For example, an insurance company

    does not need to do extensive data mining to determine whether a person is a risky driver or an unusual health riskit can extract that information from

    the insured directly. Second, this change towards a “signaling economy” (as

    opposed to the “sorting economy” in which we have lived since the late 1800s) poses a very different threat to privacy than the threat of data mining, aggregation and sorting that has preoccupied the burgeoning informational privacy field for the last decade. In a world of verifiable information and low-cost signaling, the game-theoretic “unraveling effect” kicks in, leading self-interested actors to disclose fully their personal information for economic gain. Although at first consumers may receive a discount for using a driving or health monitor, privacy may unravel as those who refuse to do so are assumed to be withholding negative information and therefore stigmatized and penalized. Third, privacy law and scholarship must reorient

    towards this unraveling threat to privacy. Privacy scholarship is unprepared for the possibility that when a few have the ability and incentive to disclose, all may ultimately be forced to do so. The field has had the luxury of ignoring unraveling because technologies did not exist to make a signaling economy possible. Those days are over. As the signaling economy evolves, privacy advocates must either concede defeat or focus on preventing unraveling. The latter will require both a theoretical shift in our conception of privacy harms and practical changes in privacy reform strategies.

     The Article‟s three Parts track these claims. Part I explores the

    emerging signaling economy.

    * * *

    Part II takes up the Article‟s second claim: that even the first steps

    we are now taking towards a signaling economysteps like those in the

    three examples abovepose a new set of privacy challenges previously

    largely ignored.

     Richard Posner first articulated these challenges decades ago, 12although at the time they were more theoretical than practical. Even with

    control over her personal information, he argued, an individual will often find it in her self interest to disclose such information to others for economic

     12 Posner‟s description of this problem is in Posner, Privacy, supra note __ at 105-107. He

    began to develop such themes in RICHARD A. POSNER, THE ECONOMICS OF JUSTICE 234 (1981).


    gain. If she can credibly signal to a health insurer that she does not smoke, she will pay lower premiums. If she can convince her employer that she is diligent, she will receive greater pay. As those with positive information about themselves choose to disclose, the economic “unraveling effect” will

    occur: in equilibrium, all will disclose their information, whether positive or negative, as disclosure by those with the best private information leads to disclosure even by those with the worst.

     The classic example of unraveling imagines a buyer inspecting a 13crate of oranges. The quantity of oranges in the crate is unknown and

    opening the crate before purchase is unwise because the oranges will rot before transport. There are stiff penalties for lying, but no duty on the part of the seller to disclose the number of oranges in the crate. The number of oranges will be easy to verify once the crate is delivered and opened. The buyer believes that there can‟t be more than one hundred oranges.

     The unraveling effect posits that all sellers will fully disclose the