The Sexist Algorithm

Abstract

Algorithmic risk assessment tools are informed by scientific research concerning which factors are predictive of recidivism and thus support the evidence‐based practice movement in criminal justice. Automated assessments of individualized risk (low, medium, high) permit officials to make more effective management decisions. Computer‐generated algorithms appear to be objective and neutral. But are these algorithms actually fair? The focus herein is on gender equity. Studies confirm that women typically have far lower recidivism rates than men. This differential raises the question of how well algorithmic outcomes fare in terms of predictive parity by gender.