Artificial Intelligence in Higher Education: Examining the AI Policy Landscape at U.S. Institutions

Abstract

Addressing a critical need for comprehensive policy development in the area of Artificial Intelligence in Education (AIED), this exploratory study investigates the prevalence and characteristics of emerging AI policies across U.S. higher education institutions. Through a close review of AI policies from a stratified random sample of four-year institutions across the country, variations in policy adoption were examined across different institution types. Official online policy-related resources provided for campus-wide use were observable in less than half of U.S. institutions, and large discrepancies in the quality and quantity of policy guidance provided were found among existing policy resources. Significant disparities were most associated with institution type. Research-intensive universities were more likely to have provided significant AI policy resources compared to smaller institutions. The study identifies a range of policy providers and highlights diverse approaches to AI use, ethical guidelines, and target audiences, which reflect different combinations and degrees of leadership, institutional cultures, resources, and individual initiatives. Considering the social impacts of technologies, these varied results underscore the necessity for a standardized and well-structured policy framework to ensure effective and ethical AI integration in higher education. The lack of consistency in existing policy practices, especially in light of emerging ethical considerations, c…