An impact assessment of machine learning risk forecasts on parole board decisions and recidivism

The Pennsylvania Board of Probation and Parole has begun using machine learning forecasts to help inform parole release decisions. In this paper, we evaluate the impact of the forecasts on those decisions and subsequent recidivism. A close approximation to a natural, randomized experiment is used to evaluate the impact of the forecasts on parole release decisions. A generalized regression discontinuity design is used to evaluate the impact of...