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To Thine Own Self Be True? Incentive Problems In Personalized Law, Jordan M. Barry, John William Hatfield, Scott Duke Kominers

William & Mary Law Review

Recent years have seen an explosion of scholarship on “personalized law.” Commentators foresee a world in which regulators armed with big data and machine learning techniques determine the optimal legal rule for every regulated party, then instantaneously disseminate their decisions via smartphones and other “smart” devices. They envision a legal utopia in which every fact pattern is assigned society’s preferred legal treatment in real time.

But regulation is a dynamic process; regulated parties react to law. They change their behavior to pursue their preferred outcomes— which often diverge from society’s—and they will continue to do so under personalized law: They …