Using data science to confront policing challenges

Increasing calls for changes in policing have departments across the country searching for new ways to build trust and protect citizens and officers alike. In response, police in Charlotte, N.C. and Nashville, Tenn. police have turned to a White House-backed project at the University of Chicago that uses advanced data analytics to predict and prevent adverse incidents, ranging from excessive force to officer injury. Led by the Center for Data Science and Public Policy at the Computation Institute and Harris School of Public Policy, the initiative applies machine-learning methods to police department data to identify officers and police calls at a higher risk of producing adverse events, such as the use of excessive force or a sustained citizen complaint. The predictive models can be used to guide personalized interventions for…


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