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Hofstede's Cultural Dimensions and the Choice of AI Regulatory Approaches by University Staff
The rapid integration of artificial intelligence (AI) into higher education has intensified the need for regulatory frameworks that balance innovation with risk mitigation. This chapter examines regulatory preferences regarding AI among staff members of higher education institutions. The analysis is based on Hofstede's cultural dimensions framework to explore how individual cultural orientations influence attitudes toward AI regulation. The empirical sample includes 363 employees from higher education institutions across 37 regions of the Russian Federation. Data were collected through a survey. The results show that power distance is associated with support for stricter regulatory measures, including formalized rules and potential bans on AI use. Uncertainty avoidance correlates with preferences for centralized, rule-based governance aimed at reducing technological uncertainty. Collectivism is linked to give support for regulatory approaches emphasizing collective decision-making rather than individual discretion. Descriptive analysis indicates moderate levels of power distance and collectivism, relatively low uncertainty avoidance, and relatively high long-term orientation. Overall, respondents tend to favor the development of clear and centralized rules for AI use in higher education while demonstrating a willingness to invest in learning and adopting AI technologies. The findings highlight the importance of understanding cultural characteristics when implementing AI technologies in education. They also provide insights for educational policymakers, university administrators, and other key participants in the educational process. Furthermore, the study opens opportunities for future cross-cultural research on AI governance in higher education.