Integrating Artificial Intelligence into Law Enforcement: Socioeconomic and Ethical Challenges

Abstract

The contemporary legitimacy crisis in American policing, amplified by high-profile incidents of misconduct and long-standing racial and socioeconomic inequities, has spurred urgent demands for structural reform. Central to these reforms is the adoption of artificial intelligence (AI) and surveillance technologies, such as body-worn cameras and predictive analytics, which are increasingly framed as solutions to institutional opacity and public distrust. However, this article critically interrogates the ethical and equity implications of integrating AI into law enforcement, particularly when such tools are deployed within cultures of impunity and without community oversight. Through a rapid literature review of interdisciplinary research across criminal justice, ethics, and information systems, this study examines how the convergence of historical bias, algorithmic opacity, and organizational inertia risks reinforcing rather than redressing systemic harm and socioeconomic challenges. The absence of participatory governance and transparency in AI deployment further marginalizes the very communities these reforms purport to serve. This article contends that technological innovation, when divorced from ethical governance and equity-centered design, functions less as a corrective mechanism and more as a force multiplier for entrenched injustice and a means to an end. A reimagined framework for AI in policing must prioritize democratic accountability, community engagement, and the recalibration of organizational culture to ensure that digital reform does not become a proxy for deepening inequity, amplified and unchecked. This research contributes to the growing discourse on algorithmic justice by foregrounding the socio-technical dynamics at play and advancing normative principles for ethically aligned policing in the digital age.