USE OF ARTIFICIAL INTELLIGENCE AND ACADEMIC INTEGRITY: THE PRIVATE-LAW ASPECT

Abstract

Introduction. The global process of digitalization has led to the widespread use of artificial intelligence (AI) across various spheres of human life. Its application in the academic environment must be combined with the assurance of trust and the need for reliability in scientific works. This explains the necessity of establishing clear rules for the use of AI in education and science. On this basis, it is essential to develop a well-reasoned framework for the proper application of AI in scholarly and educational activities.

The  purpose of the article is to develop a scientific approach to the use of artificial intelligence in compliance with the principles of academic integrity. The following research methods were employed: the formal-logical method—to identify manifestations of AI use in scientific and educational activities; the systemic-structural method—to clarify the specific features of ensuring compliance with academic integrity by means of technological advancements; and the dialectical method—to compare compliance and violation of academic integrity in the context of AI use.

Summary of key research results. It is demonstrated that presenting information generated by AI as one’s own original work constitutes a violation of copyright and academic integrity. It is emphasized that information obtained with the help of AI requires mandatory verification against primary sources. Unlike a library, which contains verified materials, AI outputs may include both accurate and misleading data. It is highlighted that AI was created as an auxiliary tool and cannot replace human authorship. The results of AI use directly depend on its input sources, which may include both scientific and dubious materials. Even accurate data may be reproduced without proper attribution, thereby raising copyright concerns. In law and legislation, a universal AI is incapable of ensuring compliance with the rules of legal drafting, as well as accounting for mental and national particularities. Hence, human creativity remains indispensable in these processes. The problems associated with AI use encompass both academic ethics and legal risks, including plagiarism and the dissemination of inaccurate information. The use of AI in scientific research is permissible only with proper referencing, critical analysis, and creative interpretation. For Ukraine, an urgent task is the improvement of legislation concerning digital objects of civil rights and the development of an ethical code for the use of AI in education and science. Academic culture must be based on openness, respect for copyright, and integrity in scientific research.

Conclusions. When using AI in scientific activity, it is necessary to comply with the requirements of current legislation on intellectual property protection. The principles of handling AI-generated information should include: (a) respect for copyright in relation to the results of human creative activity, fair use of sources and proper citation; (b) prevention of unlawful appropriation of information not belonging to human authorship by falsely attributing it as one’s own; (c) verification of authorship in respect of information provided by AI (since AI processes input data that may itself be subject to intellectual property rights); (d) maintenance of a high level of legal culture, social awareness, and scientific ethics; (e) human oversight of AI-generated information, including verification against primary sources, editing, and proper attribution of authorship.