A research article published under the Criminal justice and Behavior (BSI) journal that focused on the debate around algorithm risk assessment in the Criminal Justice system. The article addressed layers of bias, challenges to fairness within the risk-assessment models themselves as they integrate statistical fairness and the tradeoffs between them. Using data from a racially biased criminal justice system can lead to unmeasurable biases in both risk scores and outcome measures analyzed a risk-assessment instrument- as proven in COMPAS, the Correctional Offender Management Profiling for Alternative Sanctions Tool, that detailed 45% of Black defendants being flagged as high risk. By comparison, only 23% of White defendants who were not rearrested were flagged as high risk. The overall article calls for predictive accuracy, integrated fairness among judges, defense lawyer model fairness access to address the overall equalizing false positive/negatives amongst groups. An ultimate call to  develop legal frameworks that promote transparency, accurate measurement, and just decision-making.

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^{Keywords: Risk assessment, race, algorithms, sentencing, crime prevention, decision-making, prediction, violence risk assessment}

• Recidivism