Data Mining and the Security-Liberty Debate
posted by Daniel Solove
My short essay, Data Mining and the Security-Liberty Debate, 74 U. Chi. L. Rev. 343 (2008) has just been published. I’ve posted the final version on SSRN. Here’s the 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.
The essay critiques arguments by Richard Posner and William Stuntz, as well as Eric Posner and Adrian Vermeule’s Terror in the Balance: Security, Liberty, and the Courts
April 7, 2008 at 12:51 am
Posted in: Articles and Books, Privacy, Privacy (Electronic Surveillance), Privacy (Law Enforcement), Privacy (National Security)
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Responses (1)
Jardine Barrington-Cook - July 1, 2008 at 5:48 pm
Hi,
I came here after reading “I’ve got nothing to hide”. I believe that there is one crucial argument against data mining (and “stop and search”) which has been missed and is widely misunderstood. It is based on the same piece of mathematics which makes universal health screening a bad idea WHEN YOUR TEST ISN’T VERY GOOD. Basically – let’s assume 1 in a million people is an active terrorist (or has some rare condition), and that your technique is good enough to spot 80% of these people. That sounds like you should do it! However if 0.1% of the population are picked up as “potential terrorists” (or false positive to have the desease) then applying this data minimg will cause about 1000 innocent people to be arrested for every terrorist spotted (or patient unnecessarily treated). Not only is this a bad use of resources, it potentially radicalises and recruits for the terrorists. So if 1% of those falsely accused now believe they HAVE to take up arms against the government you just made the problem 10 times worse. In the clinical case if treatment side effects occur in 1% of cases you have a similar result of decreasing overall health.
Ah – if only we could increase mathematical literacy, perhaps we could avoid each generation of politicans and policemen thinking this was a good idea, until the public backlash they don’t understand forces them to abandon it as impractical.
Regards
JIBC
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