AI Governance in Higher Education: Case Studies of Guidance at Big Ten Universities
Project Overview
The document discusses the transformative role of generative AI in higher education, highlighting its potential to enhance personalized learning and tutoring while simultaneously raising significant challenges related to academic integrity and ethics. It examines AI governance strategies implemented by prominent universities, particularly their guidelines for responsible AI usage. The findings underscore the necessity for robust governance frameworks that consider the varied roles of faculty, students, and staff within educational settings. These frameworks emphasize the importance of education on AI, ethical usage, and effective communication to facilitate the integration of AI technologies. Overall, the study reveals that while generative AI can significantly benefit educational practices, careful consideration of ethical implications and governance is crucial for its successful implementation.
Key Applications
Guidelines and Policies for AI Usage in Education
Context: Higher education institutions (HEIs) targeting faculty, students, and researchers, including university IT departments providing guidance on responsible AI usage.
Implementation: Development of comprehensive guidelines and policies addressing the integration of AI in teaching practices and data-sharing practices. This includes recommendations on course design, assessment strategies, and restrictions on sensitive data input into AI tools.
Outcomes: Enhanced understanding of AI, responsible usage, promotion of academic integrity, increased awareness of data privacy and security risks, and guidance on ethical considerations.
Challenges: Complexity in accessing comprehensive guidelines due to overlapping content from multiple departments, and ensuring compliance with data-sharing restrictions among users.
Implementation Barriers
Organizational
Complexity in information structure due to multiple units involved in AI governance.
Proposed Solutions: Create a centralized AI Center to house all guidelines and simplify access for university members.
Workload
Increased workload for faculty due to the responsibility of guiding students in AI usage, along with managing AI-related academic integrity issues.
Proposed Solutions: Consider mechanisms to distribute the workload and support faculty in managing these responsibilities.
Knowledge and Skills
Lack of sound evidence on the pedagogical impact of AI technologies affecting faculty and student confidence, leading to a need for increased AI literacy.
Proposed Solutions: Enhance communication and educational opportunities to increase AI literacy among faculty and students.
Project Team
Chuhao Wu
Researcher
He Zhang
Researcher
John M. Carroll
Researcher
Contact Information
For information about the paper, please contact the authors.
Authors: Chuhao Wu, He Zhang, John M. Carroll
Source Publication: View Original PaperLink opens in a new window
Project Contact: Dr. Jianhua Yang
LLM Model Version: gpt-4o-mini-2024-07-18