Artificial intelligence in crime prevention and combating: opportunities and challenges

This paper explores the intertwined yet distinct roles of crime prevention and crime control in ensuring societal safety and reducing crime rates. Crime prevention focuses on proactively mitigating the factors that contribute to criminal behavior before offenses occur, encompassing a multifaceted approach to address underlying social and environmental conditions. The study argues that effective crime control is inextricably linked to robust crime prevention strategies; neglecting the root causes of crime renders even the strictest punitive measures ineffective. While prevention cannot eliminate crime entirely, its absence leads to a perpetual cycle of criminal activity. The research highlights the increasing integration of artificial intelligence (AI) and machine learning (ML) in crime prediction and resource allocation. The paper details the key stages of crime prediction using AI: data collection from diverse sources (past crime records, socio-economic data, social media, CCTV footage), data preprocessing, model selection (regression, classification, neural networks), model training, evaluation, prediction, and result interpretation.