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Repurposing recidivism models for forecasting police officer use of force

2020-12-10IEEE International Conference on Big Data (Big Data) 2020Code Available0· sign in to hype

Samira Khorshidi, George Mohler, Jeremy G. Carter

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Abstract

We review several concepts and modeling techniques from statistical and machine learning that have been developed to forecast recidivism. We show how these methods might be repurposed for forecasting police officer use of force. Using open Chicago police department use-of-force complaint data for illustration, we discuss feature engineering, construction of black-box models, interpretable forecasts, and fairness.

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