Talia B. Gillis

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86.2
Big Data and Discrimination
Talia B. Gillis
Doctoral Student, Harvard Business School; John M. Olin Fellow in Empirical Law and Economics, Harvard Law School.

For helpful feedback, we thank Oren Bar-Gill, Netta Barak-Corren, Yochai Benkler, John Beshears, Alexandra Chouldechova, Ellora Derenoncourt, Noah Feldman, Deborah Hellman, Howell Jackson, Cass Sunstein, Justin Wolfers, the editors and the participants of The University of Chicago Law Review Symposium on Personalized Law, and participants of the Law and Economics Colloquium at the University of Toronto and the Business Law Workshop at Oxford University. Talia Gillis acknowledges support provided by the John M. Olin Center for Law, Economics, and Business at Harvard Law School.

Jann L. Spiess
Post-doctoral Researcher, Microsoft Research New England.

For many financial products, such as loans and insurance policies, companies distinguish between people based on their different risks and returns. However, the ability to distinguish between people by trying to predict future behavior or profitability of a contract is often restrained by legal rules that aim to prevent certain types of discrimination.