Data Mining and the Security-Liberty Debate
I’ve written a short essay (about 20 pages), entitled Data Mining and the Security-Liberty Debate, for an upcoming symposium on surveillance for the U. Chicago Law Review. The symposium website is here. The symposium looks to be a terrific event. The event will be held on June 15-16, 2007 (registration information is available at the symposium website). Besides myself, participants include Julie Cohen, Ronald Lee, Ira Rubenstein, Ken Bamberger, Deirdre Mulligan, Timothy Muris, Lior Strahilevitz, Anita Allen, Thomas Brown , Richard A. Epstein , Orin Kerr, Patricia Bellia, Richard A. Posner, Paul Schwartz, and Chris Slogobin.
My paper can be downloaded at the symposium website or at this SSRN link. In the essay, I take on some common arguments about data mining and the debate between security and liberty.
In particular, I critique arguments by Richard Posner, William Stuntz, and a provocative new book by Eric Posner and Adrian Vermeule called Terror in the Balance: Security, Liberty, and the Courts. Posner and Vermeule argue tthat in times of crisis, courts and legislatures should defer to the executive on issues of national security. I spend a considerable part of my essay critiquing their argument.
The essay’s abstract:
In this essay, written for a symposium on surveillance for the University of Chicago Law Review, I examine some common difficulties in the way that liberty is balanced against security in the context of data mining. Countless discussions about the trade-offs between security and liberty begin by taking a security proposal and then weighing it against what it would cost our civil liberties. Often, the liberty interests are cast as individual rights and balanced against the security interests, which are cast in terms of the safety of society as a whole. Courts and commentators defer to the government’s assertions about the effectiveness of the security interest. In the context of data mining, the liberty interest is limited by narrow understandings of privacy that neglect to account for many privacy problems. As a result, the balancing concludes with a victory in favor of the security interest. But as I argue, important dimensions of data mining’s security benefits require more scrutiny, and the privacy concerns are significantly greater than currently acknowledged. These problems have undermined the balancing process and skewed the results toward the security side of the scale.