Ethical Aspects of AI Regulation for Higher Education
Abstract
The article provides a comprehensive analysis of the AI Code of Ethics for education developed at the Tashkent State Law University. The AI Code ushers in a distinctive shift from prohibitive approaches to AI governance in higher education on the basis of the principle of precedence of education and mentorship over restrictive measures. By analyzing in detail the Code’s thirty-one articles contained in four parts (general provisions, AI usage in education, AI usage in research, governance and supervision) as supplemented by methodological framework for AI assessment and governance structures, this study showcases a comprehensive system introduced by the Code to establish precedence of education over prohibitions while maintaining academic integrity. The analysis flags innovative governance mechanisms (such as tripartite AI ethics councils including professors, technical specialists, students) and functions, all-around risk assessment protocols, adaptive phased introduction strategies and methodology for AI-assisted academic performance assessment based on a parallel system for analyzing the share of human involvement and AI. The Code integrates international standards (such as the UNESCO Recommendation on the Ethics of Artificial Intelligence, GDPR principles, International Center for Academic Integrity’ values) in adapting them to specific educational context. The authors examine both the Code’s potential benefits for education institutions (AI competency development, vocational preparedness, critical thinking skills) and implementation problems to be carefully considered (available resources, change management, methodological aspects of AI-assisted verification of outcomes). Much focus is made on the model’s scalability in view of variable budgeting levels and international cooperation mechanisms to achieve equitable access to technologies. The Code is important for showcasing a practicable model designed for education institutions worldwide to address the issues of responsible AI integration while maintaining academic standards and human-centered approach to education in the context of technological change.
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