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Algorithmic prediction in policing: assumptions, evaluations and accountability

4th March 2016

The goal of predictive policing is to forecast where and when crimes will take place in the future. In less than a decade since its inception, the idea has captured the imagination of police agencies around the world. An increasing number of agencies are purchasing software tools that claim to help reduce crime by mapping the likely locations of future crime to guide the deployment of police resources. Yet the claims and promises of predictive policing have not been subject to critical examination. This paper will provide a long overdue review of the available literature on the theories, techniques and assumptions embedded in various predictive tools. Specifically, it highlights three key issues about the use of algorithmic prediction in policing that researchers and practitioners should be aware of: Assumptions, evaluation and accountability.

Hosted by CGHR, the Ethics of Big Data Research Group, and the Technology and Democracy Project.