From Permissive Practices to Institutional Norms: Ethical Regulation of Artificial Intelligence in Russian Higher Education

Abstract

The relevance of this study stems from a contradiction between the widespread de facto use of artificial intelligence (AI) in Russian universities and the lack of formal rules governing this process. The aim of this work is to comprehensively analyze official documents from Russian universities that regulate the use of AI in education, including ethical aspects and risks. The methodology is based on a two-stage content analysis of publicly available university policy documents. The theoretical framework draws on neo-institutional theory, particularly the concepts of institutional isomorphism and the stages of institutionalization. The scientific novelty of the study lies not only in expanding the geography of AI policy research by including the Russian case but also in advancing neo-institutional analysis of regulation under conditions of technological uncertainty. The Russian material allows us to refine the dynamics of early-stage institutionalization: we show that the formation of AI policies is nonlinear, combining the borrowing of discursive formulas with the persistence of an "institutional vacuum" at the procedural level. We introduce a typology of adaptive and restrictive regulatory modes, interpreted as two stable patterns of institutional response to digital innovation, and demonstrate their simultaneous coexistence within a single national system. Ethical principles are interpreted as a specific mechanism for the symbolic legitimation of universities in the absence of detailed regulations. This complements existing approaches to analyzing institutional isomorphism and competitive differentiation among universities. Future research directions include analyzing how participants in the educational process internalize these rules and conducting longitudinal observations of the evolution of institutional forms.