This article provides a thorough analysis of the use of artificial intelligence   (AI) in criminal justice systems, with a particular emphasis on predictive policing, risk assessment approaches, and sentencing algorithms. The analysis weighs the implications of algorithmic decision-making in relation to issues of fairness, transparency, due process, and underlying prejudices by comparing the COMPAS system in the United States, the PredPol system in the United Kingdom, and AI-based policing technologies in China. Methodologically, this study employs doctrinal and comparative legal approaches, supplemented by inter-disciplinary ideas from technology and ethics. The findings highlight widespread challenges across jurisdictions, including racial discrimination, socioeconomic bias, a lack of transparency, and insufficient supervision measures. Furthermore, the research analyses the perceived potential and hazards of using these technologies in Bangladesh’s expanding legal infrastructure. Finally, the article recommends for the institutionalisation of regulatory measures, oversight bodies, and context-based adjustments that are essential to guarantee that the use of AI in criminal justice adheres to the principles of justice, human rights, and democratic accountability.

The importance of employees’ personal data, the protection of which is provided for by current legislation, is changing in the context of the current transformation of labour relations. This is due to the spread of digital technologies, primarily artificial intelligence technologies and products based on them, the efficiency of which directly depends on access to gigantic volumes of data. Employers are increasingly introducing digital technologies into the workplace, which means that the confidentiality of employees’ personal data is exposed to additional, previously absent risks, as evidenced by the increasingly extensive case law on this issue. One of the most significant changes made in recent years in the management of production processes is algorithmic management. It is built primarily on the work of artificial intelligence systems that collect numerous data, analyse it, and actually make many decisions for the employer or significantly facilitate their adoption with the intellectual support. Algorithmic management allows for the optimisation of management, including personnel management, but increases the risks of leakage or misuse of information required for the operation of artificial intelligence systems, threatening the privacy of employees, which in the long term may become a fairly common cause of labour disputes. A study of existing judicial practice makes it possible to more accurately identify gaps and shortcomings in legal regulation that need to be eliminated, including those that hinder the administration of justice in resolving disputes concerning the processing of employees’ personal data by employers.

The article is devoted to the outcomes of the 10th International Scientific and Practical Convention of Students and Postgraduates “Vector of Law: Global Challenges and the National Code”, held on November 28–29 at Kazan (Volga Region) Federal University. The key events, award ceremonies, opening and closing sessions are described in detail. The article analyzes the geography of the convention and the organizational process itself. The geographical representation of the participants is reviewed — it included more than 250 students from 20 leading law universities of Russia and neighboring countries. Special attention is given to the discussion of major issues in contemporary jurisprudence, the search for innovative approaches, and the development of proposals for transforming modern law. The significance of the convention as a platform that unites young scholars and experienced researchers is emphasized, providing a productive space for the exchange of knowledge and best practices in organizing similar events