American Research Journal of Humanities and Social Sciences

Artificial intelligence is becoming an important analytical resource in criminology and contemporary policing, particularly in situations where large and complex datasets exceed the practical limits of conventional analysis. This review examines the growing use of artificial intelligence in crime prediction, criminal investigation, forensic data analysis, and police decision-making. The discussion covers machine learning, neural networks, computer vision, automated language analysis, data visualization, and conversational systems that support the identification of patterns, anomalies, threats, and relationships within criminal information. These technologies can assist investigators in processing digital evidence, examining multimedia material, identifying emerging criminal patterns, and improving the allocation of police resources. The review also examines concerns surrounding data quality, privacy, algorithmic bias, explainability, reliability, security, and accountability. The evidence indicates that artificial intelligence can strengthen investigative capacity when its outputs are appropriately validated and combined with professional judgment. Its practical value depends on transparent data practices, continuous evaluation, human oversight, and safeguards that protect individual rights. Responsible and context-sensitive implementation remains essential for achieving reliable applications of artificial intelligence across criminology and police sciences.

Keywords: Artificial Intelligence; Criminology; Intelligent Policing; Crime Prediction; Criminal Investigation; Forensic Data Analysis; Machine Learning; Predictive Analytics; Police Technology; Algorithmic Bias; Data Privacy; AI Ethics.