Chicago Researchers Test Data to Predict Police Misconduct

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A pair of University of Chicago research teams are analyzing big data to answer a thorny question that has become especially charged in recent months: Will a police officer have an adverse interaction with a citizen? The Chicago Tribune reports that the team from the university’s Crime Lab is in the first stages of working with the Chicago Police Department to build a predictive data program to improve the department’s Early Intervention System, which is designed to determine if an officer is likely to engage in aggressive, improper conduct with a civilian.

The other team, part of the university’s Center for Data Science & Public Policy, is expected to launch a data-driven pilot of an Early Intervention System with the Charlotte-Mecklenburg, N.C., Police Department this summer. The center is working on similar efforts with the Los Angeles County sheriff’s office and the Nashville and Knoxville police departments in Tennessee. Data crunching has been used in policing since the late 1970s. Applying this level of big-data processing to predict police misconduct is new. “The thing we’re finding is that using it (big data) to predict officer adverse incidents is just one use,” said Rayid Ghani, director of the Center for Data Science & Public Policy and previously chief data scientist for President Obama’s 2012 campaign. “Inside police departments, they are doing a lot of other things — performance management, other safety things, training. This is easily extensible to all those things.”

 

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