LEGAL RESPONSIBILITY FOR SPREADING FAKES: THE LIMITS OF ACCEPTABLE REGULATION IN A DEMOCRATIC SOCIETY
Abstract and keywords
Abstract:
Is devoted to the need to establish legal liability for the dissemination of fake information, as modern technologies based on artificial intelligence are capable of creating extremely realistic video recordings, audio files, and handwritten documents, which casts doubt on the authenticity of the presented evidence, poses a threat to the hacking of banking systems, the compromise of individuals or companies, the manipulation of public opinion, and the creation of fake news, as well as being used for the purposes of blackmail and extortion. With the growing popularity of fakes, the risks of their use in fraud, libel, and other criminal offenses have also increased

Keywords:
information law, information security, artificial intelligence, fake news, digitalization, digital transformation. socially dangerous activities, the penetration of crime into the field of information technology
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References

1. Criminal Code of the Russian Federation No. 63‑FZ dated June 13, 1996 (as amended on December 25, 2025).

2. Novoselov I. E., Smirnov A. A. Generation of biomedical images for data augmentation using generative-adversarial networks // MNIZH. 2024. No. 5 (143)

3. Frolova M. Under the video of a friend: scammers began to fake «circles» in Telegram // URL: https://iz.ru /

4. Ivanov V. G. Deepfakes: prospects for application in politics and threats to personality and national security / V. G. Ivanov, Ya. R. Ignatovsky // Bulletin of the Peoples' Friendship University of Russia. Series: State and Municipal Administration. 2020. No. 4. P. 379–386.

5. Goodfellow Ya., Bendjio I., Courville A. Deep learning / translated from English by A. A. Slinkin. 2nd ed., ispr. M. : DMK Press, 2018.

6. Choi Y., Choi M., Kim M., Ha J. W., Kim S., & Choo J. Stargan: Unified generative adversarial networks for multi-domain image-to-image translation. In Proceedings of the IEEE conference on computer vision and pattern recognition. 2018. P. 8789–8797.

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