Harvard Law privacy symposium features big data


Big data sets off alarm bells for those concerned about its potential to abuse privacy, and for good reason. As with industry, government and people themselves have proved over time, where there is potential, privacy gets abused.  

Last week, the Harvard Law Review held "Symposium 2012: Privacy & Technology" at which experts from George Washington University, Harvard Law School, Berkeley Law School, The University of Chicago, The University of Maryland, Georgetown University, Fordham University and others spoke on various aspects of privacy, including big data.

FierceGovernmentIT provides coverage of the event, including audio recordings of presentations from Daniel Solove (George Washington University), Jonathan Zittrain (Harvard) and panel sessions.

In a paper called "A Positive Theory of Privacy", Lior Jacob Strahilevitz, a professor at The University of Chicago, included a section on big data's influence on consumer privacy. He said many privacy advocates delude themselves into believing that "all consumers and voters win" when privacy is enhanced, while at the same time, privacy skeptics score cheap rhetorical points by suggesting that only those with shameful secrets to hide benefit from privacy protections.

"Neither approach is appealing, and privacy scholars ought to be able to do better," Strahilevitz said in his paper.

The paper identifies a shift toward new forms of personality discrimination and analyzes the likely winners and losers among voters and industry groups, focusing its analysis on "personality cohorts characterized by high levels of extraversion and sophistication, whose preferences and propensities to influence political decisions should deviate from those of introverts and unsophisticated individuals in important ways."

Strahilevitz includes the following definition of big data: the [combination] of ... information processing hardware capable of sifting, sorting, and interrogating vast quantities of data [and the process of] mining the data for patterns, distilling the patterns into predictive analytics. He calls it the key privacy challenge of the 21st century.

He said big data creates clear winners and losers, and that "understanding the identities of winners and losers will help explain why the United States has taken a rather laissez faire attitude towards big data and why that lack of intervention is likely to continue."

The report showed that companies are already discriminating against online consumers based on the affluence of their neighborhoods and charging more or less accordingly, depending on both affluence and the level of brick and mortar competition in the area. Researchers also have recently determined that obese consumers are approximately 20 percent more likely to become delinquent on a mortgage than non-obese consumers and Strahilevitz said "lenders may (or already have) become avid purchasers of big databases that shed light on individuals' diet and exercise."

The bottom line, Strahilevitz said, is that "because consumption choices reveal personality attributes, the ability of big data to improve firms' bottom lines depends on those firms' abilities to engage in personality discrimination."

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