A Machine Learning Evaluation Framework for Place-based Algorithmic Patrol Management

83 Pages Posted: 12 Sep 2023

See all articles by Duncan Purves

Duncan Purves

University of Florida

Ryan Jenkins

California Polytechnic State University

Date Written: August 23, 2023


American law enforcement agencies are increasingly adopting data-driven technologies to combat crime, with the market for such technologies projected to grow significantly in the coming years. One prevalent approach, place-based algorithmic patrol management (PAPM), analyzes data on past crimes to optimize police patrols. These systems promise several benefits, including efficient resource allocation, reduced bias, and increased transparency. However, the adoption of these technologies has raised ethical and social concerns, particularly around privacy, bias, and community impact. This report aims to provide a comprehensive framework, including many concrete recommendations, for the ethical and responsible development and deployment of PAPM systems. Targeting developers, law enforcement agencies, policymakers, and community advocates, the recommendations emphasize collaboration among these stakeholders to address the complex challenges presented by PAPM. We suggest that failure to meet the proposed ethical guidelines might make the use of such technologies unacceptable. This report has been supported by National Science Foundation awards #1917707 and #1917712 and the Center for Advancing Safety of Machine Intelligence (CASMI).

Keywords: data-driven policing, predictive policing, police technology, responsible AI, machine learning

Suggested Citation

Purves, Duncan and Jenkins, Ryan, A Machine Learning Evaluation Framework for Place-based Algorithmic Patrol Management (August 23, 2023). Available at SSRN: https://ssrn.com/abstract=4549861 or http://dx.doi.org/10.2139/ssrn.4549861

Duncan Purves

University of Florida ( email )

PO Box 117165, 201 Stuzin Hall
Gainesville, FL 32610-0496
United States

Ryan Jenkins (Contact Author)

California Polytechnic State University ( email )

San Luis Obispo, CA 93407
United States

Do you have a job opening that you would like to promote on SSRN?

Paper statistics

Abstract Views
PlumX Metrics