ISCAP Proceedings: Abstract Presentation
Artificial Intelligence As A Governance Stressor In Higher Education
Heather Richards
Nichols College
Bryant Richards
Nichols College
Abstract
Generative AI is reshaping higher education, yet institutional governance has focused primarily on student learning, assessment, and academic integrity. Less attention has been given to how AI-related uncertainty affects faculty evaluation systems, including promotion, tenure, and rank review, where peer judgment, disciplinary standards, and academic freedom are institutionally enacted.
Drawing on threat-rigidity theory, this conceptual article argues that ambiguity surrounding AI-mediated authorship and intellectual labor may be appraised as a threat to evaluative reliability, academic integrity, and institutional legitimacy. In response, institutions may adopt procedural governance contraction: the increased use of disclosure mandates, documentation requirements, standardized rubrics, detection practices, and centralized interpretations of acceptable scholarly work. Although these mechanisms may be intended to reduce uncertainty, they can shift evaluative authority away from disciplinary peer judgment and toward compliance-oriented governance.
The article introduces evaluative authority as the discretionary capacity of disciplinary peer bodies to interpret scholarly contribution and legitimacy within faculty review systems. It argues that AI-related governance responses in faculty evaluation may mirror restrictive approaches already visible in student assessment, contributing to governance drift, inconsistent evaluation practices, chilling effects on innovation, weakened institutional trust, and academic freedom concerns.
Integrating threat-rigidity theory with adaptive leadership and established AI governance standards, the article proposes design principles for faculty AI governance. These principles emphasize transparency, proportionality, disclosure, human accountability, faculty capacity building, and discipline-sensitive professional judgment. Generative AI is positioned as a governance stressor that reveals how higher education institutions allocate evaluative authority when established norms of authorship and intellectual contribution become unstable.