Artificial Intelligence and Preventive Criminal Policy in Dealing with Urban Violent Crimes

The expansion of data driven technologies and advances in artificial intelligence have created new opportunities for criminal policymaking, particularly in crime prevention. In many criminal justice systems, data analysis algorithms and crime prediction tools are increasingly used to identify crime patterns and improve the allocation of security resources. Urban violent crimes, because of their serious social and security consequences, have become a key area for applying these technologies. This study examines the capacities and challenges of using artificial intelligence in preventive criminal policy to address urban violent crimes and explores the legal and policy requirements for its responsible application. The research adopts a descriptive analytical approach based on documentary and library sources in criminology, criminal law, and artificial intelligence. The findings indicate that artificial intelligence can strengthen preventive criminal policy by analyzing large datasets, identifying spatial and temporal crime patterns, and predicting high risk areas, which may help improve the efficiency of security resource allocation. However, the use of predictive algorithms also raises important challenges, including the risk of data bias, limited algorithmic transparency, accountability concerns, and gaps in existing legal frameworks. The study concludes that the effective use of artificial intelligence in crime prevention requires clear legal regulations, appropriate oversight mechanisms, and careful attention to principles of algorithmic fairness and the protection of fundamental rights.

کلیدواژه ها:

artificial intelligence ، preventive criminal policy ، urban violent crimes ، predictive policing ، algorithmic justice