Communications
I am writing to share the final report and recommendations of the Generative AI in Teaching and Learning (GAITL) Committee.
Over the past several years, generative artificial intelligence (GenAI) has moved from a novel tech disruption to an active part of our daily academic operations. To understand exactly how these tools are altering the academic landscape, in March 2025 I charged the GAITL Committee with mapping our campus usage, understanding how our peer institutions are responding to these new technologies and recommending an ethical path forward in using GenAI to support innovative and equitable teaching and learning.
Guided by Brown's core mission to advance free inquiry and our community’s ongoing commitment to academic excellence, the committee — co-chaired by Michael L. Littman, associate provost for artificial intelligence, and Eric Kaldor, director of assessment and transformational programs at the Sheridan Center — undertook an extensive, data-driven assessment of GenAI use at Brown. The committee analyzed community feedback collected from nearly 700 faculty, students and staff and benchmarked practices among a number of our peers, including Ivy Plus universities. In addition, the committee partnered with our Data Science Institute to review nearly 3,000 Brown course syllabi from the 2023-24 and 2024-25 academic years.
Findings
The report highlights a striking, asymmetric pattern of AI adoption across our campus, alongside some shared cultural anxieties. I urge all faculty, students and staff to read the full report, but I will share key findings here and summarize next steps.
- Classroom Disconnect: While a large majority of student respondents are actively using GenAI to support their learning of new concepts, faculty are primarily leveraging these tools in their research.
- Shared Concerns: Despite using the technology differently, both faculty and students express similar concerns. Both groups worry that over-reliance on AI may reduce long-term critical thinking, have negative cognitive consequences and undermine academic integrity.
- Uneven Syllabus Landscape: The audit of nearly 3,000 syllabi revealed that more than half did not state a policy around GenAI use in teaching and learning. Those syllabi that did state a policy varied widely in their guidance — ranging from complete integration to total prohibition — creating an urgent need for institutional clarity.
- Need for Literacy: Notably, the feedback the committee received from Brown students did not indicate a desire for an unregulated digital environment. Rather, student respondents expressed a desire for structured institutional policies and training to develop AI literacy.
The Strategic Roadmap
To protect the integrity of the learning experience at Brown while leveraging the opportunities presented by GenAI technology, the committee made six core recommendations, structured across three operational phases:
Phase 1: Baseline Rules and Access (Near-Term Recommendations). The report shares the recommendation that Brown should establish university-wide baseline policies for GenAI use in order to promote a common understanding across the Brown community of what constitutes acceptable and unacceptable use. At the same time, the report conveys the importance of preserving departmental and faculty autonomy to set localized standards for their specific courses. In addition, the recommendations call for expanding secure, enterprise-level AI tools through the Office of Information Technology to guarantee data privacy and ensure equitable access for all students.
Phase 2: Literacy and Policy Integration (Medium-Term Recommendations). For the medium-term, the committee proposes that the Sheridan Center for Teaching and Learning and University Library develop and administer additional specialized training to support faculty and staff AI literacy. It also recommends initiating the governance process to formally update the College and Graduate School academic codes to explicitly address boundaries of AI assistance.
Phase 3: National Leadership and Curriculum (Long-Term Recommendations). Looking further ahead, the committee’s long-term recommendations include exploring a coalition of peer higher education institutions to help set national standards for AI in teaching and learning. They also include investigating a formal “AI Literacy” undergraduate course designation.
Next Steps
Addressing these recommendations requires that our community work together deliberately and intentionally to identify solutions that align with our values and our commitment to academic excellence. As noted in my cover letter for the report, this summer a reconstituted and expanded GAITL Committee will propose and draft potential syllabi templates to be discussed with faculty, students and staff in the fall through a university-wide community engagement process. In parallel, the Office of the Provost is developing a comprehensive plan to address medium- and long-term recommendations in the committee’s report.
Given the rapid pace of GenAI development, any plan must be viewed as a living document that we will continually refine. We are committed to doing so with ongoing input from the community.
The rapid and pervasive adoption of GenAI requires us to re-examine what a world-class education looks like in a digital age. I want to thank the members of the GAITL Committee and the many other faculty, staff and students who have contributed to this vital project, and I look forward to the ongoing engagement with our community. Again, I encourage you to read the full report, and I look forward to our campus discussions.
Sincerely,
Francis J. Doyle III
Provost