Dennis Hirsch Paper on Big Data and the FTC’s Unfairness Authority

Dennis D. Hirsch of Capital has written That's Unfair! Or Is It? Big Data, Discrimination and the FTC's Unfairness Authority, 103 Kentucky Law Journal (2015). Here is the abstract:

Big data and data analytics (“big data”) can produce many social and economic benefits.  But they can also generate privacy injuries and harmful discrimination.  The governance of big data should, accordingly, focus on balancing benefits and risks.  Where the potential benefits outweigh the risks, the big data application should be seen as appropriate.  Where the risks outweigh the benefits, it should be seen as inappropriate.  This provides a framework for sorting beneficial from harmful uses of big data, and so for figuring out which big data applications are in bounds, and which are not.

Others have advocated a risk-benefit approach to big data.  However, the scholarly literature has not yet identified a legal basis on which to ground such an approach.  This Article does.  It argues that the FTC could use its Section 5 “unfairness authority” to draw the line between those big data uses that are appropriate and fair, and those that are inappropriate and unfair. In this way, it could provide guidance to big data businesses that are struggling to find a coherent, legally-grounded framework for making such calls.  It could also take an important step towards protecting privacy and civil rights in the era of big data.

This raises an important legal question. Does the Commission’s unfairness authority encompass the governance of big data?  Or does this task lie outside the scope of the FTC's  statutory jurisdiction?  Here, the essay offers an original reading of FTC v. Wyndham Worldwide Corp., a district court decision (on appeal at the time of this writing) that provides the latest word on the scope of the FTC’s unfairness jurisdiction.  It shows that the Wyndham decision both supports the FTC’s authority to govern big data practices and provides guidance on how the Commission could go about doing so.

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