The Use of AI in Predicting Crime: A Legal Analysis of Predictive Policing and Profiling

Abstract

The integration of artificial intelligence (AI) in predictive policing and profiling represents a transformative shift in law enforcement strategies, enabling data-driven forecasts of criminal activities through algorithms analyzing vast datasets on demographics, historical crimes and social behaviors. This research article conducts a comprehensive legal analysis of these practices, examining their implications under constitutional frameworks, international human rights standards and data protection laws such as the GDPR and U.S. Fourth Amendment protections. Key concerns include algorithmic bias, which disproportionately impacts marginalized communities, leading to discriminatory profiling and perpetuating systemic inequalities. The study evaluates case studies from implementations in cities like Chicago and London, highlighting successes in resource allocation and crime reduction alongside risks of privacy erosion, false positives and due process violations. It argues for robust regulatory oversight, including transparency mandates, bias audits and ethical guidelines to mitigate harms while harnessing AI's potential for public safety. Ultimately, the analysis underscores the need for a balanced approach that prioritizes civil liberties in the era of algorithmic governance, proposing reforms to ensure equitable and accountable use of predictive technologies.