From Academic Integrity to Institutional Stewardship: A Reflexive and Responsible Innovation Paradigm for Generative AI in Higher Education

Generative artificial intelligence (GenAI) has diffused through higher education faster than institutions have been able to govern it, reshaping the conditions under which universities produce knowledge, judgement, credentials, and public trust. Current responses (prohibition, detection, and accommodation) fall short of a settled governance posture, and existing frameworks, from AI ethics principles to standard Responsible Research and Innovation (RRI) models, are not calibrated to higher education’s distinctive epistemic, formative, and public-good missions. This article addresses that gap through a disciplined conceptual synthesis drawing on RRI, reflexive governance, and higher education theory. The synthesis develops a Reflexive and Responsible Innovation Paradigm (RRIP): a six-dimensional framework that re-specifies RRI’s canonical dimensions (anticipation, reflexivity, inclusion, responsiveness) for the university context and adds two higher-education-specific dimensions: epistemic stewardship and distributive justice. Epistemic stewardship, the article’s central theoretical contribution, names the institutional obligation to protect the conditions under which knowledge claims are formed, warranted, assessed, and trusted under AI mediation. RRIP is operationalized through a multi-level architecture of institutional mechanisms (deliberative AI councils, transparency registers, and reflexive assessment redesign) with a tiered implementation pathway calibrated to institutions of varying capacity. Institutional leaders, program directors, policymakers, and accreditation bodies will find in RRIP a theoretically grounded and practically applicable guide for assessment redesign, curriculum decisions, procurement governance, and sectoral coordination.