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The risk of re-offense is considered in decision-making at many stages of thecriminal justice system, from pre-trial, to sentencing, to parole. To aiddecision makers in their assessments, institutions increasingly rely onalgorithmic risk assessment instruments (RAIs). These tools assess thelikelihood that an individual will be arrested for a new criminal offensewithin some time window following their release. However, since not all crimesresult in arrest, RAIs do not directly assess the risk of re-offense.Furthermore, disparities in the likelihood of arrest can potentially lead tobiases in the resulting risk scores. Several recent validations of RAIs havetherefore focused on arrests for violent offenses, which are viewed as beingmore accurate reflections of offending behavior. In this paper, we investigatebiases in violent arrest data by analysing racial disparities in the likelihoodof arrest for White and Black violent offenders. We focus our study on2007--2016 incident-level data of violent offenses from 16 US states asrecorded in the National Incident Based Reporting System (NIBRS). Our analysisshows that the magnitude and direction of the racial disparities depend onvarious characteristics of the crimes. In addition, our investigation revealslarge variations in arrest rates across geographical locations and offensetypes. We discuss the implications of the observed disconnect between re-arrestand re-offense in the context of RAIs and the challenges around the use of datafrom NIBRS to correct for the sampling bias.

On the Validity of Arrest as a Proxy for Offense: Race and the Likelihood of Arrest for Violent Crimes