Our Research

The accountability of police to the public is imperative for a functioning democracy. The opinions of police executives—pivotal actors for implementing oversight policies—are an understudied, critical component of successful reform efforts. We use a pre-registered survey experiment administered to all U.S. municipal police chiefs and county sheriffs to assess whether police executives’ attitudes towards civilian oversight regimes are responsive to 1) state-level public opinion (drawing on an original n=16,840 survey) and 2) prior adoption of civilian review boards in large agencies. Results from over 1,300 police executives reveal that law enforcement leaders are responsive to elite peer adoption but much less to public opinion, despite overwhelming public support. Elected sheriffs are less likely to support any civilian oversight. Our findings hold implications for reformers: We find that existing civilian oversight regimes are largely popular, and that it is possible to move police executive opinion towards support for civilian oversight.

This study investigates how information about public opinion and peer practices influences police executives’ views on civilian review boards. We applied structural topic modeling in an experimental paradigm, a novel approach diverging from traditional experimental survey methods, to the open-ended responses of 1331 police executives collected in an original survey experiment. This technique enables the capture of subtle shifts in belief directly from the executives’ own words. The experiment systematically varied the information provided to police executives, including state-level public opinion data from a representative sample of 16,840 U.S. residents, and peer practices in major city police agencies. Our findings reveal that police executives, although generally aligned in their views, demonstrate a readiness to update their beliefs when presented with cohesive local public opinion and information about peer practices in policing.

Law enforcement agencies are increasingly adopting AI-powered tools. While prior work emphasizes the technological features driving public opinion, we investigate how public trust and support for AI in government vary with the institutional context. We administer a pre-registered survey experiment to 4,200 respondents about AI use cases in policing to measure responsiveness to three key institutional factors: bureaucratic proximity (i.e., local sheriff versus national FBI), algorithmic targets (i.e., public targets via predictive policing versus detecting officer misconduct through automated case review), and agency capacity (i.e., necessary resources and expertise). We find that the public clearly prefers local over national law enforcement use of AI, while reactions to different algorithmic targets are more limited and politicized. However, we find no responsiveness to agency capacity or lack thereof. The findings suggest the need for greater scholarly, practitioner, and public attention to organizational, not only technical, prerequisites for successful government implementation of AI.