As we prepare for the start of the academic year, I write to share new resources designed to support you in establishing clear, effective Generative AI policies for your courses. The resources were developed by the GAITL Phase 2 Committee as part of its work this summer. As I wrote to the campus last month, the committee is charged with translating the recent Generative AI in Teaching and Learning report into resources for our campus for the fall semester. To address the report’s first near-term recommendation, this letter explains how to access examples of AI policies for course instructors, as well as an online tool to support faculty in developing their own syllabus statements outlining AI policies for their fall courses.

Our students are currently navigating a complex landscape where AI expectations vary significantly from one classroom to the next, and we need to provide them with unambiguous guidance. It is essential that every instructor at Brown sets a clear, explicit AI policy for their courses and takes the time as needed to discuss it with their students. When every course has clear expectations, our students can engage with academic integrity and confidence.

I encourage you not only to state what is permitted, but also to discuss the pedagogical “why” with your students. Reflecting on how AI tools interact with your course learning goals, and engaging openly with students about that rationale, is one of the most effective ways to build trust and foster meaningful learning.

To support your planning, the Sheridan Center has updated its Teaching with AI in Mind portal. Please use the portal to access the following key resources:

• Syllabus Policy Examples: A collection of sample course statements reflecting a full range of approaches, from a strict "No AI" policy to assignment-specific integration.
• AI Policy Explorer: An interactive web tool designed to help you consider and articulate permitted and prohibited AI uses based on your course learning outcomes. Based on your input, the tool will automatically generate a customizable syllabus statement that you can copy directly into your course materials.

These two new tools are the latest additions to the ongoing programming, course design workshops and one-on-one consultation resources provided by the Sheridan Center for Teaching and Learning on its webpage dedicated to helping instructors respond to the rise of generative AI, alongside the instruction, workshops and other resources available at the Library.

I want to thank co-chairs Michael Littman, associate provost for AI and university professor of computer science; Ravit Reichman, associate professor of English; and all of the members of the GAITL Phase 2 Committee for their work in developing these resources. 

I also continue to be grateful to the faculty, instructors and many others in the Brown community whose dedication supports teaching excellence and innovation at Brown.

Sincerely,

Francis J. Doyle III   

Provost