Ethical Governance of Artificial Intelligence in Universities: A Framework for Educational Justice, Accountability, and Academic Autonomy within the Philosophy of Education

Abstract

This study aimed to develop a framework for the ethical governance of artificial intelligence in universities, emphasizing educational justice, accountability, and academic autonomy within the philosophy of education. This qualitative study employed thematic analysis. Participants consisted of 18 faculty members, experts in philosophy of education, artificial intelligence and educational technology, technology ethics, higher education management and policy, and university administrators in Tehran, selected through purposive criterion-based sampling. Data were collected through in-depth semi-structured interviews lasting approximately 45–75 minutes, and sampling continued until theoretical saturation was achieved. Interviews were transcribed verbatim and analyzed through iterative coding, categorization, and theme development. MAXQDA was used to organize and manage the qualitative data. Trustworthiness was enhanced through member checking, peer review, constant comparison, and systematic documentation of analytical decisions. The analysis identified one overarching theme, “human-centered and value-based governance of artificial intelligence in universities,” and seven major themes: educational justice; accountability and transparency; academic autonomy and human agency; data governance and privacy; AI literacy and ethical capacity; participatory regulation and institutional oversight; and preservation of the authenticity of education. The final framework was organized into three interrelated layers: normative and philosophical principles, procedural and operational requirements, and institutional and capacity-building mechanisms. Educational justice was found to include distributive, procedural, and restorative dimensions. The findings further indicated that responsibility for high-stakes academic decisions should remain with identifiable human and institutional actors, while AI should support rather than replace faculty judgment and students’ cognitive agency. Ethical governance of AI in universities requires moving beyond a purely technological approach toward a human-centered, accountable, and value-based governance model in which educational justice, human responsibility, academic freedom, meaningful oversight, and preservation of educational purposes constitute the principal criteria for legitimate AI use.