COMPAS has scales that measure both dynamic risk (criminogenic factors) and static risk (historical factors). Lock them up and throw away the key. We set out to assess one of the commercial tools made by Northpointe, Inc. to discover the underlying accuracy of their recidivism algorithm and to test whether the algorithm was biased against certain groups. While the COMPAS algorithm used to produce risk scores is proprietary, the output is not. The researchers were able to replicate … recidivism algorithm. Criminalizing algorithms include algorithms used in housing, credit determinations, healthcare, hiring, schooling, and more. COMPAS (Correctional Offender Management Profiling for Alternative Sanctions) is a popular commercial algorithm used by judges and parole officers for scoring criminal defendant’s likelihood of reoffending (recidivism). Compas and other products with similar algorithms play a role in many states’ criminal justice systems. Source document contributed to DocumentCloud by Julia Angwin (ProPublica). About COMPAS: COMPAS, an acronym for Correctional Offender Management Profiling for Alternative Sanctions, is an assistive software and support tool used to predict recidivism risk — the risk that a criminal defendant will re-offend. 1. Many of these have been shown to make recommendations and decisions that negatively affect marginalized communities, encoding systemic racism, and contribute to entry of the Criminal Justice system. COMPAS is an algorithm widely used in the US to guide sentencing by predicting the … found that the score correctly predicted an offender’s recidivism 61 percent of the time, but was only correct in its predictions of violent recidivism 20 percent of the Though COMPAS was fair in one respect, the algorithm was discriminatory under a different definition of fairness. COMPAS is helpful in ways that it provides scores from 1 (being lowest … Statistically based risk/needs assessments have become accepted as established and valid But even under a different measure that accounted for variations in the base recidivism rates, the algorithm still performed better than humans by achieving sixty-seven percent accuracy. And it was impossible to make the algorithm … Loomis’ COMPAS report indicated a high risk of recidivism. ... ProPublica: How we analyzed the COMPAS . The COMPAS algorithm’s accuracy rate of sixty-five percent matched the 2018 study exactly. Context. In a 2018 analysis, Stevenson and Vanderbilt’s Christopher Slobogin calculated that 58 percent of the widely used COMPAS algorithm’s violent recidivism risk score can be attributed to age. Strangely, both claims proved true. Algorithms, the logic at the heart of such programs, can replicate and even amplify the prejudices of those who create them. COMPAS refuted these allegations, arguing that their algorithm predicted recidivism accurately regardless of race. COMPAS has two primary risk models: General Recidivism Risk and Violent Recidivism Risk.