Responsible Adoption of Generative AI in Higher Education: Developing a "Points to Consider" Approach Based on Faculty Perspectives

TL;DR

This paper develops a set of normative points to guide the responsible and context-sensitive adoption of generative AI in higher education, emphasizing faculty perspectives and institutional values.

Contribution

It introduces a 'points to consider' framework based on faculty insights, addressing the unique goals and governance structures of higher education.

Findings

Six normative points for AI adoption in higher education

Insights into benefits and risks of generative AI in academia

Barriers to AI integration identified and discussed

Abstract

This paper proposes an approach to the responsible adoption of generative AI in higher education, employing a ''points to consider'' approach that is sensitive to the goals, values, and structural features of higher education. Higher education's ethos of collaborative faculty governance, pedagogical and research goals, and embrace of academic freedom conflict, the paper argues, with centralized top down approaches to governing AI that are common in the private sector. The paper is based on a semester long effort at the University of Pittsburgh which gathered and organized perspectives on generative AI in higher education through a collaborative, iterative, interdisciplinary process that included recurring group discussions, three standalone focus groups, and an informal survey. The paper presents insights drawn from this effort that give rise to the ''points to consider'' approach the paper develops. These insights include the benefits and risks of potential uses of generative AI In higher education, as well as barriers to its adoption, and culminate in the six normative points to consider when adopting and governing generative AI in institutions of higher education.