Artificial Intelligence and Crime Detection: A Critical Review

Salehi, Karim; Habib Zadeh Khiyaban, Simin; Sabbar, Shoaib

doi:10.22059/jcss.2025.402206.1179

Artificial Intelligence and Crime Detection: A Critical Review

Articles in Press

Document Type : Original article

Authors

¹ Department of Law, Shahrekord Branch, Islamic Azad University, Shahrekord, Iran.

² Department of Public Administration, Faculty of Accounting and Management, Allameh Tabataba’i University, Tehran, Iran.

³ Department of International Commercial Law, Faculty of Law, Azad University, Tehran. Iran.

10.22059/jcss.2025.402206.1179

Abstract

Background: Since the advent of modern policing, technological innovations in communication and information management have significantly shaped investigative practices and crime detection strategies.
Aims: The current research study explores the transformative role of Artificial Intelligence in modern crime detection and prevention across diverse domains including cybercrime, environmental crime, financial fraud, and urban surveillance.
Methodology: Employing a qualitative meta-synthesis methodology, the research critically examines peer-reviewed literature published between the years 2015 and 2025 to identify emerging trends, technological innovations, and socio-legal implications associated with AI-driven policing.
Findings: The key findings highlight the integration of machine learning, computer vision, and natural language processing techniques into the predictive and real-time law enforcement systems. These technologies have demonstrably enhanced the accuracy, efficiency, and responsiveness of crime prevention strategies. However, the current study also reveals significant challenges, including algorithmic bias, lack of transparency, and inadequate regulatory oversight, particularly in socially stratified or underregulated contexts.
Conclusion: The current article underscores the necessity of embedding explainability, accountability, and human oversight into Artificial Intelligence systems to ensure the ethical and equitable implementation of AI-driven policing systems.

Keywords

Main Subjects

References

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