Predictive Bias and Risk Assessment

Across the country, criminal justice institutions have turned to a data-driven movement to drive down inequities, squelch rising prison populations, reduce recidivism, save billions of dollars and reduce the crime rate. The criminal justice system has begun to utilize predictive assessments to allocate resources to likely crime hotspots and to predict the likelihood of reoffending. Reports have shown that the underlying algorithms of the predictive assessments are hampered by weak measures producing predictive inequities and bias. As such, the research projects will focus on determining predictive bias and developing a racial/ethnically equitable predictive instrument. Peer-Reviewed Journal Articles Differential Racial-Ethnic Predictive Validity The Predictive Utility of the Wisconsin Risk Needs Assessment Instrument The (Twice) Failure of the Wisconsin Risk Need Assessment in a Sample of Probationers The Influence of Race, Gender, and Offense Severity on Probation Outcomes Predicting Youth Assault and Institutional Danger in Juvenile Correctional Facilities Psychometric Racial and Ethnic Predictive Inequities Predicting Staff Assault in Juvenile Correctional Facilities Gender, Race/Ethnicity, and Prediction: Risk in Behavioral Assessment