Abstract
ABSTRACTRacial bias in predictive policing algorithms has been the focus of a number of recent news articles, statements of concern by several national organizations (e.g., the ACLU and NAACP), and simulation-based research. There is reasonable concern that predictive algorithms encourage directed police patrols to target minority communities with discriminatory consequences for minority individuals. However, to date there have been no empirical studies on the bias of predictive algorithms used for police patrol. Here, we test for such biases using arrest data from the Los Angeles predictive policing experiments. We find that there were no significant differences in the proportion of arrests by racial-ethnic group between control and treatment conditions. We find that the total numbers of arrests at the division level declined or remained unchanged during predictive policing deployments. Arrests were numerically higher at the algorithmically predicted locations. When adjusted for the higher overall crime rate at algorithmically predicted locations, however, arrests were lower or unchanged.
Highlights
Place-based predictive policing is based on two core ideas: (1) mathematical forecasting methods can be used to anticipate future crime risk in narrowly prescribed geographic areas; and (2) the delivery of police resources to those prediction locations disrupts the opportunity for crime (Bowers, Johnson, and Pease 2004; Mohler et al 2011)
We ask three related questions: (1) Did arrest of minority individuals differ between control and treatment conditions in test divisions? (2) Did arrest rates overall differ between control and treatment conditions in test divisions? and (3) Did the rate of arrests per crime differ across treatment and control conditions
We test three null hypotheses: (1) arrest of minority individuals did not differ between control and treatment conditions in test divisions; (2) arrest rates overall did not differ between control and treatment conditions in test divisions; (3) the rate of arrests per crime was unchanged across treatment and control conditions
Summary
Place-based predictive policing is based on two core ideas: (1) mathematical forecasting methods can be used to anticipate future crime risk in narrowly prescribed geographic areas; and (2) the delivery of police resources to those prediction locations disrupts the opportunity for crime (Bowers, Johnson, and Pease 2004; Mohler et al 2011). The prevailing view, derived from experiments in hot spot policing (Sherman and Eck 2002; Braga and Bond 2008), is that the presence of police in a given place removes opportunities for crime even without any direct contact with potential offenders (Sherman and Weisburd 1995; Weisburd 2008; Loughran et al 2011) This general deterrent effect persists for some time after police have departed (Koper 1995; Sherman and Weisburd 1995) and appears to diffuse into nearby areas, where the police were not concentrating their efforts (Clarke and Weisburd 1994; Weisburd et al 2006; Telep et al 2014). We seek to evaluate whether predictive policing leads to patterns of arrest biased against minority individuals
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