Brown leaders discuss AI’s impact on learning and integrity

Faculty at Brown University are now offering courses dedicated to exploring the implications of artificial intelligence within their specific fields, responding to a technology rapidly reshaping how people learn and work. Recognizing the profound impact of generative AI, Brown leaders launched a multi-pronged approach including AI workshops and a learning community focused on emerging issues.

National discussions surrounding AI use are particularly focused on potential declines in fundamental academic skills; educators worry about reduced cognitive reasoning and problem solving skills, learning loss, and a reduction in quality human engagement. “There are reasons to be excited about the future of AI, but we also must grapple with new questions surrounding ethics, authorship, intellectual property and a host of other areas that overlap with teaching and learning,” says Brown University Provost Francis J. Doyle.

Brown’s GAITL Committee Examines AI’s Impact on Curriculum

Brown University’s commitment to proactively addressing artificial intelligence extends beyond policy creation to encompass comprehensive educational initiatives for both faculty and students. The Brown University Library launched a series of AI workshops and a dedicated learning community, recognizing the rapid evolution of generative AI. These programs aim to foster ongoing discussion and equip individuals with the skills to navigate this emerging technology. This approach signals a dedication to actively shaping AI’s integration into the academic environment, rather than simply reacting to its presence.

Faculty members are already integrating AI as a subject of study within their disciplines, moving beyond addressing it as a potential academic threat. The GAITL Committee, appointed by Provost Francis J. Doyle in early 2025, played a central role in charting a path forward, culminating in a July 2026 report detailing its findings and recommendations.

Michael Littman, the first associate provost for AI at Brown and co-chair of the committee, emphasized the importance of a campus-wide collaborative effort to fully tackle the challenges and opportunities presented by AI. Doyle said, “Our work has been focused on leveraging our entire academic community and all the expertise found within it to chart a path forward.” He continued, “There are exciting things ahead of us here, but we need to proceed thoughtfully and prudently.” The GAITL report revealed a nuanced perspective among students; while many are utilizing generative AI tools in their studies, a significant number express concern about its potential impact on their long-term cognitive abilities. Faculty members share these anxieties, and the report highlighted a need for clearer expectations and limitations regarding AI use within course syllabi.

This concern aligns with broader national discussions, which are increasingly focused on issues such as reduced cognitive reasoning and problem solving skills, learning loss, with a particular focus on concerns about writing skills, a reduction in quality human engagement, and a rise in academic dishonesty. Doyle noted the historical precedent for Brown’s proactive stance, referencing an article in the Brown Alumni Magazine from 43 years ago that addressed the integration of computers into education.

“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,” Doyle stated, quoting the decades-old publication.

The committee’s immediate recommendations center on publishing clear guidelines regarding AI expectations, while intermediate and long-term goals include updating academic codes and collaborating with peer institutions to establish standardized usage guidelines. Littman explained that a key realization during the committee’s deliberations was the need to tailor solutions to Brown’s unique academic environment. “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.” The University’s Open Curriculum, while fostering intellectual curiosity and student agency, presents a unique challenge in establishing consistent AI exposure checkpoints, requiring instructors to clearly articulate expectations and integrate AI thoughtfully into their courses. An expanded GAITL Phase 2 committee recently released sample generative AI syllabus statements to aid faculty, and Doyle has tasked the group with continuing to engage the campus community regarding the report’s broader recommendations.

Faculty & Student Concerns Regarding AI Cognition & Skills

Brown University expanded its commitment to understanding artificial intelligence’s influence on pedagogy with the launch of “Transcending Boundaries: AI + Science,” a new course series designed to integrate AI exploration across multiple disciplines. This initiative builds on earlier efforts, including seminars offered by the Sheridan Center for Teaching and Learning focused on adapting course design and assessment strategies for an era increasingly shaped by generative AI tools.

Concerns regarding the potential impact of AI on fundamental academic skills are prevalent among both students and faculty at Brown. The Generative AI in Teaching and Learning (GAITL) Committee’s report revealed that a significant number of students, while utilizing AI in their coursework, express worry about its long-term effects on their cognitive abilities.

This anxiety extends beyond general reasoning skills to encompass specific competencies, such as writing, as national discussions increasingly focus on potential loss of writing skills as a key consequence of widespread AI adoption. The University’s approach is deeply rooted in its history of proactively addressing technological advancements, as highlighted by Provost Francis J. Doyle. This historical precedent informs Brown’s current strategy of leveraging its academic community to chart a path forward for AI integration. Doyle acknowledged the unique challenges presented by the University’s Open Curriculum, which prioritizes student flexibility and intellectual curiosity.

While this approach allows students to intentionally engage with AI at varying depths, it also complicates the creation of consistent checkpoints for AI exposure. The committee’s recommendations emphasize the importance of developing markers or indicators that clarify AI expectations upfront, fostering a learning environment that balances innovation with academic integrity.

GAITL Report: Recommendations for AI Policy & Guidelines

This multifaceted approach extends beyond simply establishing policy, focusing instead on cultivating a community of practice around AI’s implications. Faculty members across disciplines at Brown have begun integrating explorations of AI directly into their coursework, moving beyond treating the technology as a problem to be solved and instead examining its impact on their respective fields. Provost Francis J. Doyle’s approach, informed by considering how the Open Curriculum influenced their approach, presents both opportunities and challenges in the context of AI integration.

This multifaceted approach extends beyond policy development, prioritizing practical education and sustained dialogue among faculty and students as AI tools rapidly evolve. This prompted the committee to prioritize publishing guidelines clarifying expectations around AI, alongside intermediate and long-term recommendations including updates to academic codes and collaborative standard-setting with peer institutions.

Michael Littman, in his role as Brown’s first associate provost for AI in July 2025, explained that the committee focused on defining what AI means for Brown specifically, rather than attempting a global solution. Doyle noted the potential to emphasize intrinsically human skills and to create opportunities for deeper immersion in AI development and evaluation, suggesting a spectrum of possibilities for instructors to explore.

Provost Doyle Advocates Proactive AI Shaping at Brown

Brown University is actively reshaping its approach to generative artificial intelligence, moving beyond reactive policy to foster a campus-wide understanding of its implications. Faculty members echoed these anxieties, prompting a need for clearer guidelines on appropriate AI use within coursework. This concern extends beyond simple academic integrity, as educators grapple with maintaining fairness in assessment when students have access to increasingly sophisticated AI assistance.

Addressing this complexity, the GAITL committee prioritized the publication of guidelines clarifying expectations around AI, and subsequently expanded into GAITL Phase 2 to further engage the campus community. The committee’s work continues a process begun earlier, with sample generative AI syllabus statements shared in August 2026 as a resource for faculty in their courses. This approach aims to balance innovation with the preservation of core academic values.