REGULATING THE USE OF GENERATIVE AI BY HIGHER EDUCATION STUDENTS: UKRAINIAN AND EUROPEAN EXPERIENCE

Abstract

The article analyses the policies regulating the use of generative artificial intelligence (AI) by higher education students in Ukrainian and European universities. In the context of the rapid integration of AI into educational processes, the article focuses on the permissions, prohibitions, and responsibilities defined in the relevant institutional regulations. Special attention is given to how generative artificial intelligence may be used by students in the learning process, the risks identified in institutional policies, and the measures envisaged in cases of non-compliance. A comparative analysis of policies adopted by leading universities reveals both common and distinctive features in the regulation of AI use. Common features include the unconditional prioritisation of academic integrity, recognition of the need for transparency in AI use, holding students accountable for AI application, and viewing AI as a supportive rather than a substitutive tool in learning. Issues such as data privacy, copyright, and potential bias are also recurring themes across most policies. Key differences include the degree of detail in disciplinary measures, the varying level of institutional support for AI services, and differing approaches to formulating prohibitions. While Ukrainian policies tend to set out sanctions more explicitly, European institutions usually rely on pre-existing academic integrity provisions. The authors emphasise the importance of balancing policy flexibility with the need for clear regulation of student–AI interaction and highlight the necessity of regularly reviewing and updating such policies. Most of the analysed policies focus not on reactive control but on proactive strategies that facilitate the shift from mere control to the strategic integration of AI as a transformative educational asset. This strategic shift is crucial for universities seeking to remain competitive in an AI-driven world.