Predictors of public support for AI in policing - Ahmet Guler; Sedat Kula; Kaan Boke (Policing: An International Journal, 2026)
Purpose This study examines factors shaping public support for AI in policing in the United States. Drawing on Rosenberg and Hovland’s tripartite model of attitudes, it investigates the effects of cognitive, affective and behavioral attitudes toward AI, alongside confidence in law enforcement, AI knowledge, police funding attitudes, media use and demographic characteristics. Design/methodology/approach Survey data from 583 respondents in three northeastern US states were analyzed using structural equation modeling (SEM). The model examined the effects of attitudes toward AI, AI knowledge, confidence in policing, police funding attitudes, media use and demographic variables on support for AI in policing. Findings Affective and behavioral attitudes, AI knowledge, confidence in law enforcement and support for police funding positively predicted support for AI in policing, whereas cognitive attitudes and media use did not. Several demographic characteristics were also significant, highlighting the importance of emotions, institutional trust and domain-specific knowledge in shaping public support. Research limitations/implications The cross-sectional design limits causal inference, and the sample from three northeastern states may restrict generalizability. Future research should use nationally representative, longitudinal or experimental designs, incorporate broader AI acceptance factors and examine attitudes toward specific AI applications in policing. Practical implications The findings suggest that public engagement addressing emotional responses and practical AI applications may be more effective than information alone. Transparent communication, public education and maintaining confidence in law enforcement may help foster informed public support. Social implications Public support for AI in policing depends on both attitudes toward AI and confidence in law enforcement. Promoting transparency, accountability and inclusive public engagement may strengthen trust and support equitable AI implementation. Originality/value This study integrates the tripartite model of attitudes with AI policing research using SEM. It provides one of the few US empirical studies showing that affective and behavioral attitudes are more influential than cognitive attitudes in shaping public support for AI in policing.