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Survival Analysis of a Criminal Justice Decision Algorithm

Presented by:
Hope Johnson

Risk assessment algorithms are increasingly common in the criminal justice process to predict the chance that an individual convicted of a crime will commit another crime, or recidivate. Recent studies have sparked interest in verifying that such assessment tools predict the risk of recidivism with equal accuracy across races. Using methods from survival analysis, this research finds that one risk assessment instrument commonly used in the United States significantly over-predicts the risk of recidivism for Hispanics and African-Americans, and under-predicts the risk of recidivism for Caucasians, Asians, and Native Americans.