Algorithmic Policing, Fairness, & Structural Contingency: Does Police Organizational Structure Relate to Predictive Policing Technology Use?

• In Event: Police Organizations

Abstract

Adoption of algorithmic policing technologies have an impact on the communities served. For example, they can create feedback loops that result in over-policing minority communities or put policing decisions in an algorithmic “black box,” where practitioners, leaders, and citizens cannot understand, evaluate, or amend them. Recent sociotechnical systems research discusses the impacts of these technologies, but there is relatively less work in the criminal justice literature. We also have little insight into which departments use them and why. The current study uses 2020 LEMAS data and structural contingency theory to identify structural correlates of the use of predictive policing algorithms in large, municipal police departments. Results have implications for the adoption and use of these technologies by police departments and algorithmic fairness, accountability and transparency.

Authors

• Alicia L. Jurek, San Diego Regional Policy & Innovation Center

• Karen L. Boyd, San Diego Regional Policy & Innovation Center