Shaping Artificial Intelligence Regulatory Model: International and Domestic Experience

The article contains an analysis of AI regulatory models in Russia and other countries. The authors discuss key regulatory trends, principles and mechanisms with a special focus on balancing the incentives for technological development and the minimization of AI-related risks. The attention is cente...

Full description

Saved in:
Bibliographic Details
Published inLegal Issues in the Digital Age Vol. 6; no. 2; pp. 50 - 68
Main Authors Buryaga, Vladimir, Djuzhoma, Veronika, Artemenko, Egor
Format Journal Article
LanguageEnglish
Published 02.07.2025
Online AccessGet full text

Cover

Loading…
More Information
Summary:The article contains an analysis of AI regulatory models in Russia and other countries. The authors discuss key regulatory trends, principles and mechanisms with a special focus on balancing the incentives for technological development and the minimization of AI-related risks. The attention is centered on three principal approaches: “soft law”, experimental legal regimes (ELR) and technical regulation. The methodology of research covers a comparative legal analysis of AI-related strategic documents and legislative initiatives such as the national strategies approved by the U.S., China, India, United Kingdom, Germany and Canada, as well as regulations and codes of conduct. The authors also explore domestic experience including the 2030 National AI Development Strategy and the AI Code of Conduct as well as the use of ELR under the Federal Law “On Experimental Legal Regimes for Digital Innovation in the Russian Federation”. The main conclusions can be summed up as follows. A vast majority of countries including Russian Federation has opted for “soft law” (codes of conduct, declarations) that provides a flexible regulation by avoiding excessive administrative barriers. Experimental legal regimes are crucial for validating AI applications by allowing to test technologies in a controlled environment. In Russia ELR are widely used in transportation, health and logistics. Technical regulation including standardization is helpful to foster security and confidence in AI. The article notes widespread development of national and international standards in this field. Special regulation (along the lines of the European Union AI Act) still has not become widespread. A draft law based on the risk-oriented approach is currently discussed in Russia. The authors of the article argue for the gradual, iterative development of legal framework for AI to avoid rigid regulatory barriers emerging too prematurely. They also note the importance of international cooperation and adaptation of the best practices to shape an efficient regulatory system.
ISSN:2713-2749
2713-2749
DOI:10.17323/2713-2749.2025.2.50.68