Regulatory pressure, group identity, and attribution of responsibility as factors in the acceptance of artificial intelligence by university teachers

Abstract

This article presents a theoretical analysis of the key socio-psychological barriers and resources influencing the acceptance of artificial intelligence (AI) technologies by university teachers. The digital transformation of education is often viewed as a purely technological process. However, it is essential to understand that it constitutes a social and psychological phenomenon that affects the deep foundations of the professional academic community. The discussion focuses on three interrelated constructs: regulatory pressure within the academic environment, the dynamics of professional group identity, and the mechanisms of responsibility attribution in the human–algorithm system. The study integrates the social influence theory (S. Asch, S. Moscovici), social identity theory (A. Tajfel, J. Turner), attribution theory, and moral responsibility theory to demonstrate that resistance to AI integration often stems not from individual lack of competence, but from a perceived threat to group identity based on the exclusivity of expert knowledge. Regulatory pressure from administrative institutions (university administration, relevant ministry) generally leads to conformist yet rigid acceptance, whereas informational influence from referent groups of innovative colleagues promotes genuine technology integration. Particular attention is given to analyzing the issue of responsibility distribution, where a key condition for acceptance is preserving the university teacher’s role of a moral agent. The problem of attributing responsibility is not technical, but existentially-psychological. Its resolution requires not so much training in working with AI as developing new models of professional identity and creating clear ethical frameworks. The article concludes that managerial and educational focus should shift from technical training to addressing group dynamics, developing a new ‘hybrid’ professional identity, and establishing clear ethical guidelines that eliminate the burden of moral uncertainty. Promising directions for further research include the empirical verification of the proposed theoretical model, the development of methods for diagnosing the type of teachers' professional identity, and the piloting of psychological support programs aimed at forming readiness for digital transformation.