Policing with AI: Navigating the Balance Between Enhanced Security and Civil Liberties

Abstract

This article examines the complex intersection of artificial intelligence and law enforcement in the United States, highlighting both the transformative potential and significant concerns associated with these technologies. It explores how police departments are increasingly deploying AI-driven systems, including predictive algorithms, facial recognition, automated license plate readers, and gunshot detection sensors, fundamentally altering traditional policing practices. Through a comprehensive review of empirical research, the article investigates how these technologies promise enhanced efficiency through resource optimization, rapid response capabilities, and potentially more objective analysis, while simultaneously raising profound concerns about perpetuating systemic bias, identification errors with serious consequences, privacy erosion, and diminished public trust. The article extends to emerging governance frameworks, emphasizing the importance of regulatory oversight, community involvement, and technical safeguards. By drawing on diverse scholarly perspectives, this article provides a balanced assessment of AI's role in modern policing while acknowledging the complex interplay between technological capabilities, institutional practices, and societal values that will ultimately determine these systems' impact on justice and public safety in American communities.