AI-DRIVEN PREDICTIVE POLICING AND EMERGING SECURITY CHALLENGES IN NIGERIA

Abstract

Nigeria continues to experience severe insecurity, including insurgency, banditry, kidnapping, and urban violence, which have overwhelmed traditional policing approaches. In response, there is growing interest in the use of Artificial Intelligence (AI)-driven predictive policing as a technological tool to enhance crime prevention and security management. However, its applicability, effectiveness, and governance implications in the Nigerian context remain underexplored. This study examines the role of AI-driven predictive policing in addressing insecurity in Nigeria. It adopts a qualitative research design based on a systematic review of academic literature, policy documents, and comparative analysis of predictive policing practices in selected countries, including the United States, the United Kingdom, China, and African states such as Kenya, Rwanda, and South Africa. The findings reveal that predictive policing can enhance security operations by improving crime mapping, early warning systems, and resource allocation. However, its implementation also raises significant concerns, including algorithmic bias, weak regulatory frameworks, privacy violations, and limited public trust in law enforcement institutions. The study further shows that Nigeria's current legal and institutional structures, including the Nigerian Data Protection Act and constitutional privacy provisions, are not adequately prepared for the large-scale deployment of AI-based policing systems. It concludes that predictive policing should be adopted as a supportive tool within a strongly regulated framework that ensures transparency, accountability, and protection of fundamental human rights.