The future of criminal justice: the role of artificial intelligence in predictive analytics

Introduction. This article focuses on the importance and prospects for the use of artificial intelligence in predictive analytics in the criminal justice context. The research is motivated by the significant development of artificial intelligence and machine learning technologies, which are being used in a multitude of fields, including criminal justice. The authors detail the theoretical and practical aspects of predictive analytics, which makes it possible to predict future events based on statistical data and machine learning algorithms. Special attention is paid to the difference between artificial intelligence and predictive analytics. The effectiveness of the application of predictive analytics in criminal justice, including optimising preliminary investigations, improving criminal prosecution and predicting the outcome of criminal cases, is highlighted. Methods. The basis of the research methodology is dialectical materialism, applied general scientific (system-structural and formallogical, inductive and deductive, analysis and synthesis) and special (formal-legal, comparativelegal) methods. Results. The authors conclude that artificial intelligence spans a wider range of tasks requiring human intelligence, while predictive analytics concentrates on making predictions. Advanced technologies that are already in active use in various countries, improving and optimising the allocation of law enforcement and judicial resources, are described. The prospect of integrating virtual and augmented reality technologies into criminal justice is considered, which can radically change approaches to predictive analytics and criminal procedure in general, enriching visualisation and interactive cooperation between participants of legal relations.