Paper Number

ICIS2025-1463

Paper Type

Complete

Abstract

This study examines the impact of artificial intelligence (AI) adoption on organizational performance and societal outcomes in U.S. police departments. Using panel data from 3,270 municipal departments from 2016 to 2022, we distinguish between analytical AI tools (predictive policing, crime pattern analysis) and surveillance technologies (facial recognition, automated license plate readers). Fixed-effects regression analyses reveal that analytical AI reduces total arrests by 9.1% and Black arrest proportions by 3.1% without compromising crime clearance rates. In comparison, general IT increases both clearance efficiency (3.6%) and enforcement intensity. The effects vary significantly by organizational context; AI benefits concentrate in technologically limited departments (15.2% arrest reduction) versus minimal effects in IT-mature agencies (3.6%). Surveillance AI exacerbates racial disparities by 7.6% in homogeneous departments (>83% White officers) but remains neutral in diverse agencies. Findings demonstrate that AI reshapes decision-making toward selective enforcement and highlight the implementation context's critical role in determining equity outcomes.

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Dec 14th, 12:00 AM

AI Adoption in U.S. Police Departments: Impacts on Enforcement Outcomes and Arrest Disparities

This study examines the impact of artificial intelligence (AI) adoption on organizational performance and societal outcomes in U.S. police departments. Using panel data from 3,270 municipal departments from 2016 to 2022, we distinguish between analytical AI tools (predictive policing, crime pattern analysis) and surveillance technologies (facial recognition, automated license plate readers). Fixed-effects regression analyses reveal that analytical AI reduces total arrests by 9.1% and Black arrest proportions by 3.1% without compromising crime clearance rates. In comparison, general IT increases both clearance efficiency (3.6%) and enforcement intensity. The effects vary significantly by organizational context; AI benefits concentrate in technologically limited departments (15.2% arrest reduction) versus minimal effects in IT-mature agencies (3.6%). Surveillance AI exacerbates racial disparities by 7.6% in homogeneous departments (>83% White officers) but remains neutral in diverse agencies. Findings demonstrate that AI reshapes decision-making toward selective enforcement and highlight the implementation context's critical role in determining equity outcomes.

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