Self-Surveillance Privacy

39 Pages Posted: 22 Dec 2010 Last revised: 17 Aug 2014

Jerry Kang

University of California, Los Angeles (UCLA) - School of Law

Katie Shilton

University of Maryland, College Park - College of Information Studies

Deborah Estrin

University of California, Los Angeles (UCLA)

Jeff Burke

University of California, Los Angeles (UCLA)

Mark Hansen

University of California, Los Angeles - Department of Statistics

Date Written: December 21, 2010

Abstract

It has become cliché to observe that new information technologies endanger privacy. Typically, the threat is viewed as coming from Big Brother (the government) or Company Man (the firm). But for a nascent data practice we call "self-surveillance," the threat may actually come from ourselves. Using various existing and emerging technologies, such as GPS-enabled smartphones, we are beginning to measure ourselves in granular detail - how long we sleep, where we drive, what we breathe, what we eat, how we spend our time. And we are storing these data casually, perhaps promiscuously, somewhere in the "cloud," and giving third-parties broad access. This data practice of self-surveillance will decrease information privacy in troubling ways. To counter this trend, we recommend the creation of the Privacy Data Guardian, a new profession that manages Privacy Data Vaults, which are repositories for self-surveillance data.

In Part I, we describe the emerging data practice of self-surveillance, which has been enabled by various new measurement and communication technologies. We explain how self-surveillance can produce substantial benefits to both the individual and society, in both intrinsic and instrumental terms. Unfortunately, such benefits may never be achieved without substantial privacy costs.

Part II makes threshold clarifications about those privacy costs. It proffers two different metrics by which privacy might be measured and explains why the rise of self-surveillance will entail the net loss of privacy under either metric. We also point out that the problem of self-surveillance (our surveilling us) is, fortunately, more tractable than related privacy problems, such as third-party surveillance of us and our surveillance of third-parties.

Having cleared this brush, we turn to our central proposal - the creation of the Personal Data Guardian, a professional whose job it is to maintain a client’s self-surveillance data in a Personal Data Vault. In addition to providing technical specifications of this approach, we outline the specific legal relations, which include a fiduciary relationship, between client and Guardian. In addition, we recommend the creation of an evidentiary privilege, similar to a trade secret privilege, that protects self-surveillance data held by a licensed Guardian.

Finally, Part IV answers objections that our solution is implausible or useless. We conclude by pointing out that various legal, technological, and self-regulatory attempts at safeguarding privacy from new digital, interconnected technologies have not been particularly successful. Before self-surveillance becomes a widespread practice, some new innovation is needed. In our view, that innovation is a new "species," the Personal Data Guardian, created through a fusion of law and technology and released into the current information ecosystem.

Keywords: privacy, surveillance, personal data vault, personal data guardian, information flows, gps

Suggested Citation

Kang, Jerry and Shilton, Katie and Estrin, Deborah and Burke, Jeff and Hansen, Mark, Self-Surveillance Privacy (December 21, 2010). Iowa Law Review, Vol. 97, p. 809, 2012; UCLA School of Law Research Paper No. 11-01. Available at SSRN: https://ssrn.com/abstract=1729332 or http://dx.doi.org/10.2139/ssrn.1729332

Jerry Kang (Contact Author)

University of California, Los Angeles (UCLA) - School of Law ( email )

385 Charles E. Young Dr. East
Room 1242
Los Angeles, CA 90095-1476
United States
310-206-7298 (Phone)
310-206-7010 (Fax)

Katie Shilton

University of Maryland, College Park - College of Information Studies ( email )

College Park, MD
United States

Deborah Estrin

University of California, Los Angeles (UCLA) ( email )

405 Hilgard Avenue
Box 951361
Los Angeles, CA 90095
United States

Jeff Burke

University of California, Los Angeles (UCLA) ( email )

405 Hilgard Avenue
Box 951361
Los Angeles, CA 90095
United States

Mark Hansen

University of California, Los Angeles - Department of Statistics ( email )

8125 Math Sciences
UCLA
Los Angeles, CA 90095
United States

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