Significant progress in artificial intelligence technologies expands development opportunities in many areas of public life, but at the same time creates security threats, including when AI processes personal data. The article examines the legal aspects of regulating the protection of personal data in the context of the development of artificial intelligence, analyzes foreign experience in ensuring confidentiality and assesses the current state of legal protection of personal data in the Republic of Kazakhstan. The study is based on a comparative legal analysis of the legislation of the EU, USA, China and Kazakhstan in the field of personal data protection and AI regulation, and analyzes the differences in law enforcement and the degree of recognition of the right to privacy in these jurisdictions. In the EU, personal data is regulated under the GDPR, which views its protection as an inalienable right of the individual. In the United States, the approach is less unified and is determined at the state level, which leads to fragmentation of legal regulation. China, by contrast, controls data processing from a national security perspective, which limits the scope of citizens' rights to protect their personal data. The article identifies key issues in law enforcement practice in the Republic of Kazakhstan, including the lack of constitutional recognition of the right to personal data protection, insufficient regulation of automated decision-making, and the lack of a mechanism for the “right to an explanation” of decisions made by AI. Measures are proposed to improve the legal regulation of privacy protection, including the introduction of legal norms that ensure the explainability of AI decisions, strengthening the protection of personal data in automated systems, and harmonizing national norms with international standards. The results obtained can be used to improve the legislation of Kazakhstan in the field of AI and personal data, as well as for further research in the field of legal regulation of digital technologies.
Umitchinova et al. (Tue,) studied this question.