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Algorithmic Predictions in Policing: Assumptions, Evaluation and Accountability

When Mar 04, 2016
from 11:00 AM to 12:00 PM
Where S3, Alison Richard Building
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Predictive Policing Poster
Lyria Bennett Moses
Associate Professor, Faculty of Law, University of New South Wales
 
4th March, 11-12, S3, Alison Richard Building
Co-sponsored by CGHR, Ethics of Big Data Research Group, and the Technology and Democracy Project
 
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.

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This is the website for Ella McPherson's work related to her 2014-17 ESRC-funded research project, Social Media, Human Rights NGOs, and the Potential for Governmental Accountability.