Artificial Intelligence as a Tool for Academic Fraud: Legal and Ethical Aspects

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Abstract

In recent years, there has been a rapid development of artificial intelligence technologies, which has a noticeable impact on the field of education and science. On one hand, artificial intelligence facilitates accelerated data processing, increases the accuracy of analysis, and improves the quality of scientific work. On the other hand, the use of generative models (for example, algorithms capable of creating coherent texts) gives rise to new forms of academic fraud. The legal aspects of applying artificial intelligence in educational and scientific activities remain underdeveloped. The lack of clear regulations governing the use of artificial intelligence in the preparation of educational and scientific works creates legal uncertainty. The aim of this article is to explore the legal and ethical aspects of applying artificial intelligence in the preparation of educational and scientific works, as well as to assess the response of higher education institutions to emerging challenges. The methodological basis of the work consisted of scientific approaches to studying academic integrity and plagiarism, as well as concepts of digital transformation in education; analysis of regulatory and governing documents; and empirical research (survey methodology). The total number of participants in the study was 210 people (160 students and 50 teachers) from four Russian universities. The article examines the features of "AI plagiarism" in comparison with classical plagiarism, analyzes legal responsibility for the misuse of artificial intelligence, and provides examples of regulatory approaches from Russian and foreign universities. Particular attention is paid to moral dilemmas related to the line between the permissible "assistive" role of artificial intelligence and the complete substitution of the author's intellectual contribution. As illustrative materials, the results of a student audience survey are presented, as well as comparative data on the prevalence of AI fraud. The conclusions drawn may be useful in shaping institutional policies aimed at preserving academic integrity and quality of education in the context of digitalization. Higher education institutions must actively adapt to new realities by developing educational programs and rules that will help students and teachers use artificial intelligence responsibly and effectively. Further research in the field of legal regulation and ethics of AI use in education and science appears to be extremely important for ensuring sustainable development in these areas.

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