Ranae Jabri, University of Sydney - Algorithmic Policing

Title: Algorithmic Policing

Abstract: Predictive policing algorithms are increasingly used by law enforcement agencies in the United States. These algorithms use past crime data to generate predictive policing boxes, specifically the highest crime risk areas where law enforcement is instructed to patrol every shift. However, the trade-offs involved in the effects of local police presence remain open for investigation. I collect a novel dataset on predictive policing box locations, crime incidents, and arrests from a major urban jurisdiction where predictive policing is used. This paper uses a natural experiment research design to examine the impacts of police presence induced by predictive policing algorithms on crime and racial disparities in arrests. I estimate that algorithm-induced police presence decreases serious violent and property crimes, but exacerbates racial disparities in arrests in traffic incidents and serious violent crimes. The evidence suggests a threefold increase in arrests of Black motorists when the neighbourhood is targeted with algorithm-induced police presence in comparison to when it is not.

Presenter: Ranae Jabri, University of Sydney

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