Big Data and Racial Bias: Can That Ghost Be Removed from the Machine?

Discrimination in the U.S. credit market is well documented. Historically, minorities have disproportionately been denied loans, mortgages, and credit cards, or charged higher rates than other customers. Now that artificial intelligence is taking over many credit decisions -- and taking human bias out of the equation -- it'll be easy to enforce laws against discrimination in lending, right? Not necessarily, argues Jann Spiess, an assistant professor of operations, information, and technology at Stanford Graduate School of Business. In a recent paper in The University of Chicago Law Review, he and Talia Gillis, a doctoral student at Harvard Business School and Harvard Law School, examined what happens when existing anti-discrimination rules are applied to choices made by machines.