FROM INNOVATION TO REGULATION: ETHICAL GOVERNANCE OF AI IN TEACHING AND LEARNING

Abstract

This study examines the policy and ethical issues surrounding the implementation of Artificial Intelligence (AI) in higher education teaching and learning. With AI tools quickly finding their way into the classroom, which has been facilitated by AI in examining assessment, tutoring, feedback, and instructional design, they have also brought about the privacy, bias, transparency, academic integrity, and the changing role of educators. The aim of the study is to chart these ethical emerging issues and determine the strengths and weaknesses in the existing institutional and international policies regulating the utilization of AI in teaching. Peer-reviewed articles, institutional guidelines, and global policy documents published since 2020 to 2025 were used to carry out a qualitative scoping review. The PRISMA criteria were used to filter sources. Trends were classified by thematic analysis to categorize them into five areas, data governance, fairness and bias, pedagogical autonomy, student well-being, and accountability in AI-assisted decision-making. University and accreditation policy documents, as well as policy documents of various organizations like UNESCO, OECD, and EDUCAUSE, were compared in order to evaluate their coherence and readiness to implement. The findings suggest that although educational institutions of higher learning are becoming more responsive to the risks of ethical issues, policies are usually general, inconsistent, and responsive. The transparency of algorithms and their responsible use in grading and assessment is not well-advised, and there are no systems that can be used to track the long-term educational effect of AI. The faculty and students are not always clear on what they can do with the use, and this has resulted in uneven adoption. Better systems are required to provide responsible uses of AI that safeguard academic values and encourage equity and meaningful human supervision. The research identifies the necessity of standardized rules, policy creation, and constant training of teachers to make recommendation of ethical and sustainable integration of AI.

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