Q&A: How Brown University is navigating the rise of generative AI use in the classroom
In just a few short years, generative artificial intelligence tools have made a leap from novelties that produce stilted text to genuine societal disruptors that may alter the way people learn, work and even think.
Generative artificial intelligence (AI) tools have rapidly evolved from simple text generators to powerful societal disruptors that could reshape learning, work, and thought. At Brown University, leaders and faculty immediately understood the profound impact AI would have on teaching and learning. The university's Sheridan Center for Teaching and Learning initiated seminars on course design and learning assessment in the age of AI, while the library launched AI workshops and a learning community to discuss emerging issues.
National conversations about AI use in classrooms center on AI literacy and the risks of misuse, including reduced cognitive skills, learning loss, diminished human engagement, and increased academic dishonesty. Brown's Provost Francis J. Doyle III emphasized the university's commitment to maintaining academic excellence while leveraging AI's benefits and mitigating its risks.
Doyle stressed the importance of collective action, noting that the entire academic community must work together to address the multifaceted challenges and opportunities presented by AI.
The university's Generative AI in Teaching and Learning (GAITL) committee, formed in spring 2025, aimed to understand how AI influenced teaching and learning, identify campus and global trends, and examine the research on AI. The committee's goal was to align Brown's approach with its institutional values, focusing on shaping the future of AI rather than simply reacting to it.
This approach echoed the university's proactive stance in the 1980s when it integrated computers into education, as exemplified by a 1980s Brown Alumni Magazine article.
The GAITL report, released in August 2026, provided recommendations such as publishing guidelines for AI expectations and updating academic codes to address generative AI. The committee also developed sample syllabus statements to help faculty navigate AI use. Doyle charged the committee with engaging the campus community on the report's longer-term recommendations.
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