Predictive Policing and the Ethics of Preemption

Abstract

The American justice system, from police departments to the courts, is increasingly turning to information technology for help identifying potential offenders, determining where, geographically, to allocate enforcement resources, assessing flight risk and the potential for recidivism amongst arrestees, and making other judgments about when, where, and how to manage crime. In particular, there is a focus on machine learning and other data analytics tools, which promise to accurately predict where crime will occur and who will perpetrate it. Activists and academics have begun to raise critical questions about the use of these tools in policing contexts. In this chapter, I review the emerging critical literature on predictive policing and contribute to it by raising ethical questions about the use of predictive analytics tools to identify potential offenders. Drawing from work on the ethics of profiling, I argue that the much-lauded move from reactive to preemptive policing can mean wrongfully generalizing about individuals, making harmful assumptions about them, instrumentalizing them, and failing to respect them as full ethical persons. I suggest that these problems stem both from the nature of predictive policing tools and from the sociotechnical contexts in which they are implemented. Which is to say, the set of ethical issues I describe arises not only from the fact that these tools are predictive, but also from the fact that they are situated in the hands of police. To mitigate these problems, I suggest we place predictive policing tools in the hands of those whose ultimate responsibility is to individuals (such as counselors and social workers), rather than in the hands of those, like the police, whose ultimate duty is to protect the public at large.

Keywords: predictive policing, ethics of policing, AI ethics, profiling