Human Decisions and Machine Predictions

We examine how machine learning can be used to improve and understand human decisionmaking. In particular, we focus on a decision that has important policy consequences. Millions of times each year, judges must decide where defendants will await trial-at home or in jail. By law, this decision hinges on the judge's prediction of what the defendant would do if released. This is a promising machine learning application because it is a concrete prediction task for which there is a large volume of data available. Yet comparing the algorithm to the judge proves complicated. First, the data are themselves generated by prior judge decisions. We only observe crime outcomes for released defendants, not for those judges…

• SF
  Simons Foundation
• UO
  University of Chicago
• UO
  University of Michigan