Automation and artificial intelligence in police body-worn cameras: Experimental evidence of impact on perceptions of fairness among officers

Abstract

Explore officers' perceptions of the fairness of monitoring with systematic variations in activation (manual/automatic) and auditing (on-demand/supervisor random/artificial intelligence) policy regimes for body-worn cameras (BWCs). This study uses a 2 × 3 survey experiment in a sample of officers wearing BWCs ( n = 258) to assess the perceived fairness of BWC monitoring under varying activation and audit policies. Participants were randomly assigned one of six vignettes, each incorporating one of two BWC activation policies (manual vs. automatic) and one of three BWC footage review policies (complaint-based, random supervisor, random AI). Automatic BWC activation and artificial intelligence auditing of footage cause declines in perceived fairness of monitoring. Further, officers perceive the most unfairness in monitoring when they lack control over the initiation of recording and when the resultant footage is outside of their supervisors' immediate control. The findings underscore potential adverse effects on officers' perceptions of monitoring fairness under varying BWC policy conditions. As artificial intelligence technology gains traction in policing, the potential impact of officers' concerns on program implementation and fidelity should be considered. • This study uses an experimental design to examine how different body-worn camera (BWC) policies shape officers' perceptions of monitoring fairness. • Automatic camera activation reduces perceived fairness relative to manual activation, underscoring the importance of officer control. • Proactive, random footage review—especially when performed by artificial intelligence—further lowers perceptions of fairness. • High-ranking personnel rate BWC policies as fairer than front-line officers, highlighting potential perceptual gaps within agencies.