Analyzing and Ameliorating the Risks of AI in Policing

Dear Colleagues,

The use of artificial intelligence (AI) to forecast the timing and location of crime—often called “predictive policing” or algorithmic patrol management—has been on the rise in recent years, with many police forces embracing the technology as an efficient solution to distributing patrol resources and deterring crime. Predictive policing uses a variety of AI-driven algorithms to detect patterns in historical data, analyze current and past criminal activity, and provide information to law enforcement that can help predict where and when crimes are likely to occur. Several studies suggest that predictive policing can be successful in tamping down crime.

However, the ethical implications of using predictive policing are still coming into focus. While it has the potential to improve public safety, it also has the possibility of infringing on civil rights and creating a world of digital surveillance and discrimination. As such, it is important to consider the ethical implications of AI-driven policing.

This Special Issue will consider the ethical implications of AI-driven predictive policing from a variety of perspectives, including (but not limited to) legal, ethical, philosophical, and sociological perspectives. We invite papers that focus on the ethical implications of predictive policing, including issues related to privacy, autonomy, and control, as well as the potential for algorithmic bias and discrimination. We are also interested in papers that address the implications of predictive policing for criminal justice systems, police use of force, and research ethics.

Predictive policing has been roundly criticized in academic circles and the public sphere. Because of this, we especially encourage submissions that offer practical (and, ideally, empirically validated) approaches for ameliorating the concerns raised thus far about predictive policing.

• Potential topics include, but are not limited to:
• Methods to operationalize the values of AI ethics into the design and deployment of predictive policing technologies;
• Data use, privacy and fairness concerns in predictive policing;
• Impact of predictive policing on law enforcement organizational behavior and dynamics;
• Over-criminalization, the social construction of crime, and racial profiling in predictive policing;
• Results of predictive policing on civil liberties and public safety;
• The prospects for explainable and transparent predictive policing algorithms;
• Ethical frameworks to evaluate predictive policing technologies;
• Challenges with implementing predictive policing in diverse social, cultural, or geographic contexts;
• Role of the public in regulating predictive policing technologies, including frameworks and models for legislation or governance.

We welcome papers from researchers and practitioners, including legal scholars, ethicists, philosophers, social scientists, law enforcement officials, public policy experts, and computer scientists. We also encourage papers that engage with interdisciplinary perspectives and include empirical, theoretical, or policy-oriented research.

Dr. Ryan Jenkins
Guest Editor

Manuscript Submission Information

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• predictive policing
• artificial intelligence ethics
• patrol management
• algorithmic justice
• feedback loops
• civil liberties
• criminal justice
• algorithmic bias
• police ethics