The Role of Artificial Intelligence in Situational Crime Prevention with an Emphasis on Privacy Challenges

Abstract

This article examines the role of artificial intelligence in situational crime prevention with particular emphasis on privacy challenges. Situational crime prevention focuses on reducing criminal opportunities by modifying environmental, technological, and organizational conditions that facilitate crime. Artificial intelligence has expanded this preventive model through predictive analytics, smart surveillance, biometric identification, cyber threat detection, automated risk assessment, and data-driven criminal justice management. These technologies can improve the speed, accuracy, and efficiency of preventive interventions by identifying crime patterns, detecting suspicious behavior, supporting resource allocation, and strengthening responses to both physical and cybercrime. However, the use of artificial intelligence in crime prevention also creates serious legal and ethical concerns. Because AI systems depend on extensive data collection and algorithmic processing, they may threaten informational privacy, increase mass surveillance, enable discriminatory profiling, reduce transparency, and weaken accountability. The article argues that the preventive benefits of AI cannot justify unrestricted monitoring or automated suspicion. Instead, AI-based situational prevention must be governed by legality, necessity, proportionality, transparency, explainability, human oversight, data minimization, purpose limitation, independent auditing, and effective remedies. The study concludes that artificial intelligence should function as a supportive tool for human decision-making rather than a substitute for legal judgment. A legitimate model of AI-based crime prevention must reduce criminal opportunities while preserving privacy, dignity, equality, and the rule of law.