Date
Publisher
arXiv
Generative AI has drawn significant attention from stakeholders in higher education. As it introduces new opportunities for personalized learning and tutoring support, it simultaneously poses challenges to academic integrity and leads to ethical issues. Consequently, governing responsible AI usage within higher education institutions (HEIs) becomes increasingly important. Leading universities have already published guidelines on Generative AI, with most attempting to embrace this technology responsibly. This study provides a new perspective by focusing on strategies for responsible AI governance as demonstrated in these guidelines. Through a case study of 14 prestigious universities in the United States, we identified the multi-unit governance of AI, the role-specific governance of AI, and the academic characteristics of AI governance from their AI guidelines. The strengths and potential limitations of these strategies and characteristics are discussed. The findings offer practical implications for guiding responsible AI usage in HEIs and beyond.
Study at a glance
- Question: How do leading universities guide and govern the responsible use of generative AI?
- Setting and data: AI guidelines from 14 prestigious universities in the United States
- Method: Case study of institutional guidelines
Why it matters
While generative AI introduces opportunities for personalized learning and tutoring support, it simultaneously poses challenges to academic integrity and ethical issues. Governing responsible AI usage is therefore increasingly important as institutions attempt to embrace the technology.
Key findings
- Across 14 prestigious U.S. universities, most institutional guidelines focused on embracing generative artificial intelligence responsibly.
- University guidance featured multi-unit collaboration and role-specific policies to manage generative artificial intelligence use.
- Campus artificial intelligence governance exhibited distinct academic characteristics with identifiable strengths and potential limitations.
Summary drafted with AI from the paper’s abstract and may contain errors. See the full paper for details.
What is the application?
Who age?
Why use AI?
Study design
