UVA School of Medicine (SOM) MD Program Policy on Generative AI

UVA SOM supports medical students to use generative AI and large language models to augment learning with appropriate educational use defined by faculty. Specific policy points are described below.

This document was created to define acceptable student use of generative AI software, including but not limited to ChatGPT, CoPilot, Gemini, Claude, DeepSeek, and Dall-E, etc.

We acknowledge there are many potential benefits of AI software as well as inherent risks (e.g., bias, limited contextual understanding, plagiarism, ethics and academic integrity, inappropriate language, errors in referencing, etc).

• Faculty will set expectations for the use of AI in their specific assignments including explicit direction as to when students cannot use AI. In general, students may utilize generative AI as a tool, resource, or consultant and not as a replacement for their own knowledge synthesis, reasoning, or self-reflection.
• If generative AI is used for an assignment, it must be appropriately cited.
• Students are responsible for any inaccurate, biased, offensive, or otherwise unethical content they submit regardless of whether they personally authored it or used AI software to generate the content.
• Students may not create H&Ps or patient care documentation within the authentic clinical environment using artificial intelligence applications outside of those supported by the EHR (e.g., Dax CoPilot).
• Consistent with copyright and intellectual property rights, students may not copy and paste system or course session materials, presentation slides, or practice exam questions into AI systems that do not offer contractual data protection of university information. See examples of acceptable use below.
• When submitting scholarly work for publication or presentation, students must adhere to generative AI policies set forth by journals and organizations and disclose when and how these tools have been used.
• If a student is found to have inappropriately utilized generative AI, the student will be subject to the UVA SOM Code of Conduct and greater University Honor Code.

Reviewing Recorded Course Content
A student uses Microsoft Copilot to summarize and highlight key concepts from the transcript of a recorded lecture in Panopto. Because this content is under UVA copyright, Copilot is the preferred tool, as it operates within a UVA-specific tenant that ensures contractual data protection—no data leaves the institution, and no prompts are used for AI model training.

Creating Study Aids with UVA-Owned Content
A student uploads UVA course slides and faculty-generated notes from an immunology session to Microsoft Copilot to generate Anki flashcards. Copilot is used because the materials are UVA intellectual property.

Generating Differential Diagnoses from a Classroom Case
During a small-group session in the Foundations of Clinical Medicine (FCM) course, students are presented with a fictional patient case. During and after class, a student uses ChatGPT to explore potential differential diagnoses and management plans based on the case. Since the case is simulated and contains no real patient information or proprietary UVA content, using ChatGPT is acceptable.

Using Public or Student-Created Content with External Tools
To prepare for an upcoming exam, a student uses ChatGPT to generate quiz questions from publicly available online resources and personally written summaries of course topics (e.g., mechanisms of the adaptive immune response). Since these inputs are not UVA-owned or sensitive, ChatGPT is permitted.

Using Generative AI to Understand Learning Objectives
A student copies a course learning objective into NotebookLM to generate a visual concept map and simplified explanation. Because learning objectives are general and not proprietary or sensitive, this use of NotebookLM is allowed.

This Student Policy on Generative AI is subject to change to ensure alignment with UVA SOM, UVAHealth, and University of Virginia policies.

The Medical Education Management Committee has oversight and approval for this policy.

• Next scheduled review January 2027
• Revised May 2025
• Developed by the UVA SOM Generative AI Advisory Team and reviewed and approved by the Medical Education Management Committee November 2023