Among its key findings, the report revealed that while most students report using generative AI in the course of their studies, many of those same students worry that it is negatively affecting their long-term cognition. Faculty members shared these concerns, and while many faculty have begun using AI in some capacity in teaching or research, many course syllabi do not adequately establish clear expectations or limitations on AI use.
The GAITL committee’s immediate recommendations included publishing guidelines that help to clarify expectations around AI. Intermediate and longer-term recommendations include updating academic codes to address generative AI, and eventually partnering with peer institutions to set standards around its use in teaching and learning. In August 2026, an expanded committee, called GAITL Phase 2, shared sample generative AI syllabus statements to serve as a resource for faculty in their courses, and Doyle has charged the group with engaging with the campus community about the report’s longer-term recommendations.
In an interview, Doyle and Littman discussed the report, its development process, and next steps in Brown’s effort to incorporate AI in teaching and learning in a way that harnesses its positive potential and mitigates risks to academic integrity and the ability of faculty to assess learning and understanding.
Q: For universities, the proliferation of generative AI tools has raised clear challenges and presented new opportunities. How has Brown gone about confronting and considering those?
Doyle: Our approach has been to make sure we are taking this on in a way that is consistent with our institutional values. Brown has a long tradition of approaching challenges this way. I am going to take us back in time a bit. There is an article in the Brown Alumni Magazine from 43 years ago about how Brown should incorporate computers in education. It speaks to some of the same challenges and opportunities we face today, and there is a quote from an associate provost at the time that just screamed out at me: “If you accept that fact and realize that it has the potential for major social change — both positive and negative — and if you realize that many schools with different goals may be shaping the technology, you come to the conclusion that we have the opportunity to shape the new technology, too, and to do it in a way that is really appropriate to Brown.”
For me, there is a strong resonance with what we are seeing with AI. We cannot sit and wait for this to happen to us. Much like our very proactive mentality in the ’80s when it came to the computer and education, I think we are in a moment where Brown has a chance to seize this opportunity and leverage the Brown DNA. And that has been our approach. We created the associate provost for AI role, and we stood up the Generative AI in Teaching and Learning Committee so that we could engage the entire campus in this process of shaping an approach to AI that is consistent with our institutional values. And now we have the GAITL report that charts a way forward. Q: Could you talk a little about the report and how it came together?
Q: Could you talk a little about the report and how it came together?
Littman: We formed the committee in spring of 2025 with representatives from across campus with the goal to try to understand: Where were we in terms of how AI was influencing teaching and learning? What is happening on campus? What is happening on other campuses that we should know about? What is the research around this starting to look like? At one point, one of the committee members said, “Well, how should we be thinking of this in terms of the Open Curriculum?” That was a big frame shift. The whole committee clicked into place at that point. There was a realization that we’re not trying to solve this problem at a global scale. We’re trying to figure out what this means for Brown and how we can shape that future.
Q: I want to dig in a bit on the Open Curriculum. How does it influence Brown’s approach to understanding AI and incorporating it into how we teach and learn?
Doyle: We have great examples from across campus of faculty creating opportunities for students to explore AI in many different ways in the classroom, in the lab and out in the world. That is not just in computer science, engineering and applied math where Brown faculty are at the cutting edge of developing new AI tools that solve all kinds of real-world problems. We have also had classes that examine AI in the humanities, in law and public policy, education, healthcare and other areas. Those opportunities are there, and the Open Curriculum enables students to take full advantage of them.
In terms of top-down policy, however, the Open Curriculum is a bit of a double-edged sword when it comes to AI. On one hand, it offers students real flexibility to take ownership of how deeply they immerse themselves in AI. If we are able to provide clarity about the content of courses up front, students can be intentional about leaning in different directions in terms of AI engagement. But it also presents a challenge. By design, and to promote intellectual curiosity, we do not have narrow lanes that students need to pass through as they chart their intellectual paths, so it is challenging to create checkpoints in students’ exposure to AI.
I think we do have an opportunity to create areas in the curriculum that emphasize intrinsically human skills and veer away from reliance on AI tools. And in other areas, instructors may employ a deeper immersion into developing, using and evaluating AI tools. And there is a full spectrum of possibilities in between. The key is developing markers or indicators that make expectations surrounding AI clear to everyone up front. That is something in the report that grew out of the discussions we have been having over the past year.
Littman: I agree. I feel like the openness, the flexibility and the exploratory nature of the Brown education is kind of perfect for the kind of topics that we’re now dealing with. For example, we’re trying to re-envision education at some level — how we engage students and how we assess them, what material is central and what is just interesting — and it’s a long-standing cultural perspective at Brown for the students to be involved in that and not just subject to it.