Legal Risks of the Use of Synthetic Data in the Activities of Executive Authorities

The emergence of synthetic data marks a significant stage in the development of generative artificial intelligence. Synthetic data is a rapidly evolving field that offers both solutions to a wide range of problems associated with data scarcity and potential technical, organizational, and economic risks. Of particular importance are the legal risks associated with the use of synthetic data in the activities of executive authorities, since such bodies are responsible for implementing public policy in socially significant areas, protecting individual rights and freedoms, and safeguarding national and information security. Based on an analysis of both foreign and Russian scholarly literature, the study identifies the principal legal risks arising from the use of synthetic data in the work of executive authorities. These risks include the evasion of official accountability where decisions are made on the basis of «low-quality» synthetic data; the falsification of documents through the use of synthetic data; the dissemination of misinformation to the public; and violations of information protection legislation. The article argues that the principal means of mitigating these risks lies in the adoption of a regulatory framework governing the generation and use of synthetic data in the activities of executive authorities through the establishment of a legal regime for synthetic data, including the mandatory specification of liability measures applicable to officials authorized to work with such data.

1. Alekseev AO, Mironova ES. On the Ethical Risks of Artificial Intelligence Technologies and Their «Cognitive Biases». Technologos. 2025;3:67-76. DOI: 10.15593/perm.kipf/2025.3.06.

2. Apostolova NN. Making Legally Significant Decisions Using Artificial Intelligence. Bulletin of the Law Faculty, Southern Federal University. 2025;1(12):13-17. (In Russ.).

3. Bashina OE, Matraeva LV, Vasyutina ES. Artificial intelligence technologies in official statistics: opportunities for use and risks. Voprosy statistiki. 2025;2:5-14. (In Russ.).

4. Calcraft P, Thomas I, Maglicic M., Sutherland A. Accelerating public policy research with synthetic data. ADR UK: Economic and Social Research Council; 2021.

5. Gal MS, Lynskey O. Synthetic Data: Legal Implications of the Data-Generation Revolution. Iowa Law Review. 2024;109:1087-1156.

6. Jenkins K. Synthetic Data and Public Policy. Supporting real-world policymakers with algorithmically generated data. Policy Quarterly. 2023;19(2):29-39.

7. Jordon J, Szpruch L, Houssiau F, Bottarelli M, Cherubin G, Maple C, Cohen CN, Weller A. Synthetic Data — what, why and how? DOI: 10.48550/arXiv.2205.03257.

8. Lapina MA. Risk Management in Public Law: Posing a Problem. Rossiyskaya Justitsia. 2015;3:47-50. (In Russ.).

9. Laptev VA. The concept of artificial intelligence and legal responsibility for its work. Law. Journal of the Higher School of Economics. 2019;2:79-102. (In Russ.).

10. Lee P. Synthetic Data and the Future of AI. Cornell Law Review. 2025;110:1.

11. Martynov AV, Shireeva AV. The Concept and Types of Synthetic Data: On the Issue of the Necessity of Legal Regulation in Russian Legislation. Journal of Russian Law. 2025;29(11):135-148. (In Russ.).

12. Martynov AV, Shireeva EV. Legal and Practical Issues of Synthetic Data Use for Public Administration. Perm University Herald. Juridical Sciences. 2025;4(70):526-538. (In Russ.).

13. Mellouli S, Janssen M, Ojo A. Introduction to the Issue on Artificial Intelligence in the Public Sector: Risks and Benefits of AI for Governments. Digital Government Research and Practice. 2024;5:1-6.

14. Mittelstadt B. Principles alone cannot guarantee ethical AI. Nature machine intelligence. 2019;1:501-507.

15. Rabchevskiy AN. Overview of Synthetic Training Data Generation Methods and Systems. Applied Mathematics and Control Sciences. 2023;4:6-45. (In Russ.).

16. Risks in public and private law: based on the materials of the round table held at the Higher School of Economics on April 29, 2014. Public Administration Issues. 2014;2:110-119. (In Russ.).

17. Saleh FS, Aliakbarian MS, Salzmann M, Petersson L, Alvarez JM. Effective Use of Synthetic Data for Urban Scene Semantic Segmentation. Proceedings of the 15th European Conference on Computer Vision (ECCV). Munich, Germany, 8–14 September. 2018;84-100. Available at: https://openaccess.thecvf.com/content_ECCV_2018/papers/Fatemeh_Sadat_Saleh_Effective_Use_of_ECCV_2018_paper.pdf.

18. Salova TL, Suvorov IS. Syntetic Data: Problems and Solutions. Mathematical Structures and Modeling. 2025;3(75):116-121. (In Russ.).

19. Sharma AK, Sharma R. Generative Artificial Intelligence and Legal Frameworks: Identifying Challenges and Proposing Regulatory Reforms. Kutafin Law Review. 2024;3(11):415-451.

20. Shumailov I, Shumaylov Z, Zhao Y, Papernot N, Anderson R, Gal Y. The Curse of Recursion: Training on Generated Data Makes Models Forget. DOI: arXiv:2305.17493v3.

21. Solomonov EV. Legal Responsibility of Artificial Intelligence. Herald of Omsk University. Series «Law». 2025;22(2):62-71. (In Russ.).

22. Thomas JA, Foraker RE, Zamstein N, et al. Demonstrating an approach for evaluating synthetic geospatial and temporal epidemiologic data utility: results from analyzing 1.8 million SARS-CoV-2 tests in the United States National COVID Cohort Collaborative (№ 3C). Journal of the American Medical Informatics Association. 2022;8:1350-1365.

23. Tikhomirov YuA. Risks in Law: Nature and Causes. Law and Modern States. 2016;6:9-19. (In Russ.).

24. Tomlinson B. Turning Fake Data into Fake News: The AI Training Set as a Trojan Horse of Misinformation. San Diego Law Review. 2023;60:641-670.

25. Volodenkov SV, Fedorchenko SN, Pechenkin NM. Risks, Threats, and Challenges of Introducing Artificial Intelligence and Neural Network Algorithms into the Contemporary System of Socio-Political Communications: The Results of Expert Study. RUDN Journal of Political Studies. 2024;2:406-424. (In Russ.).

26. Zecca PA, Marcella R, Andrea B, et al. The Dark Side of Artificial Intelligence: The Possible Risk of Falsifying Images for Scientific Articles. Microscopy and Microanalysis. 2023;29:1688-1693.