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It does so by focusing on the proposed rules for the quality of the data and the models used, on biases, and on the human oversight. This article identifies and applies the relevant rules of the proposed AI Act in relation to quantitative recidivism risk assessment. This criticism becomes even more topical with the arrival of the Artificial Intelligence (AI) Act. It has been criticized for what is measured, whether the predictions are more accurate than those made by humans, whether it creates or increases inequality and discrimination, and whether it compromises or violates other aspects of fairness. Quantitative recidivism risk assessment can be used at the pretrial detention, trial, sentencing, and / or parole stage in the justice system. Data are more helpful than rhetoric if the goal is to improve practice at this opportune moment in history. Finally, criminal history is not a proxy for race, but instead it mediates the relationship between race and future arrest. Third, most (66 percent) of the racial difference in PCRA scores is attributable to criminal history-which is already embedded in sentencing guidelines. 34 13.5 percent nonoverlap in groups’ scores), so some applications could create disparate impact. Second, Black offenders obtain higher average PCRA scores than do White offenders (d =. First, application of well-established principles of psychological science revealed little evidence of test bias for the PCRA-the instrument strongly predicts arrest for both Black and White offenders, and a given score has essentially the same meaning-that is, the same probability of recidivism-across groups. Based on a sample of 34,794 federal offenders, we examine the relationships among race, risk assessment, and future arrest. Although these instruments figure prominently in current reforms, critics argue that benefits in crime control will be offset by an adverse effect on racial minorities. Now that the numbers of reported crimes that actually occur in each community are known, CrimeRisk can validate its models against the only comprehensive location-centric crime database in Canada with complete national coverage.One way to unwind mass incarceration without compromising public safety is to use risk assessment instruments in sentencing and corrections. with complete national coverage.ĬrimeRisk collects raw crime data from all 544 Canadian Police Service Areas, and uses a relational database built from the ground up to assign reported crimes from each agency to the city where it has law enforcement responsibility (Figure 2). This method provides an accurate representation of the complete number and types of crimes that are truly known to occur.Īfter establishing a comprehensive foundation of crime counts, CrimeRisk uses more than 15 proprietary models to statistically predict the rates for every major type of crime for every location in Canada. Now that the numbers of reported crimes that actually occur in each community are known, CrimeRisk can validate its models against the only comprehensive location-centric crime database in the U.S. is a proprietary solution that provides the most spatially-accurate crime data available today-at the policy address level.ĬrimeRisk collects raw crime data from all 18,000 law enforcement agencies in the U.S., and uses a relational database built from the ground up to assign reported crimes from each agency to the city where it has law enforcement responsibility (Figure 2). This method provides an accurate representation of the complete number and types of crimes that are truly known to occur.Īfter establishing a comprehensive foundation of crime counts, CrimeRisk uses more than 120 proprietary models to statistically predict the rates for every major type of crime for every location in the U.S. – Scout Vision® Appreciation Trends and ForecastsĬrimeRisk provides complete and accurate crime counts-at the policy address level.ĬrimeRisk by Location, Inc.