A multi-institutional collaborative advancing the thoughtful integration of artificial intelligence into medical education.
AI is transforming healthcare at a pace that mandates preparation of the next generation of physicians. However, medical educators face significant hurdles: governance frameworks that don't yet exist, faculty development that can't keep up, and the very real risk of "deskilling" or "never-skilling" our trainees. Meanwhile, every institution is writing the same policies from scratch, building the same curricula in parallel, and solving the same problems in isolation.
Together, we can do better.
This consortium brings together medical education leaders from major academic health systems to:
Share, don't duplicate. Policies, curricula, assessment tools, and faculty development resources — built once, adapted everywhere.
Move fast, stay grounded. Working groups focused on tangible outputs, not endless task forces.
Bridge education and operations. AI in the classroom must connect to AI in the clinic. We're building those bridges.
Partner with industry. Co-developing tools with the companies building them, not reacting after the fact.
| Group | Focus |
|---|---|
| Curriculum | Foundational and advanced AI education for learners at every stage |
| Faculty Development | Baseline to advanced AI knowledge and teaching skills for educators |
| Policy & Governance | Shared frameworks, infrastructure guidance, institutional adoption |
| Assessment | AI-powered evaluation, smarter feedback, freeing faculty for human interaction |
| Ethics & Equity | Responsible use, disclosure requirements, verification practices, professionalism |
| Research & Scholarship | Collaborative studies, validity evidence, dissemination |
Medical students are already using AI. Residents are dictating notes with ambient scribes. Attendings are getting diagnostic predictions they didn't ask for. The question isn't whether AI will transform medical education — it already is.
The question is whether we'll prepare our learners to use these tools wisely, critically, and ethically. Whether we'll develop faculty who can teach what they themselves are still learning. Whether we'll create policies that protect patients while enabling innovation.
This consortium exists because none of us can answer these questions alone.
We're actively recruiting faculty and trainees with expertise or interest in:
- Curriculum design and educational technology
- Clinical informatics and AI implementation
- Medical education research and assessment
- Health equity and AI ethics
- Faculty development and change management
To join: Contact any steering committee member or open an issue in this repository.
Jump straight to what you need:
| I want to... | Go to |
|---|---|
| Use AI in my own clinical or scholarly work | Faculty Development Repository — step-by-step workflows with prompts and guardrails |
| Write or update an AI policy | Composite GenAI Policy Guide — synthesized best practices, syllabus language, quick-reference tables |
| Teach learners about AI | Curricula & Learning Materials |
| Browse everything | Full Resource Library |
Have a time-saving AI workflow to share? Open a Pull Request or an issue in this repository — a two-sentence description is enough to start.
Consortium members contribute curricula, videos, policies, and tools for AI in medical education.
Highlights:
- Faculty Workflows: Omission Scanning for med/problem list reconciliation, pre-submission manuscript review, and more
- Curricula: AI clinical practice modules (Stanford), data science notebooks (Northwestern)
- Videos: AI in Med Ed Symposium recordings (Stanford), Clinical Informatics lectures (Penn)
- Policies: Generative AI guidance and governance frameworks
- Partners: Bridge2AI, Stanford HAI, AIMI, and more
├── RESOURCES.md # Main resource catalog (curricula, policies, videos, etc.)
└── resources/
├── Composite-GenAI-Policy-Guide.md # Synthesized best practices from all member institutions
├── Faculty-Development-Workflows.md # AI workflows for faculty clinical & administrative work
└── penn/ # Penn-specific documents (PDFs, reports)
Resources in RESOURCES.md are organized by type: Faculty Workflows, Curricula, Frameworks, Policies, Videos, and Partners. Institution-specific documents are stored in subfolders under resources/.
- Fork this repository
- Create a feature branch (
git checkout -b feature/new-resource) - Commit your changes (
git commit -m 'Add curriculum module on prompt engineering') - Push to the branch (
git push origin feature/new-resource) - Open a Pull Request
Not ready for a full PR? Open an issue describing the resource or workflow and it will be incorporated for you.
All contributions should include source attribution and respect institutional IP policies.
Educational materials in this repository are shared under CC BY-NC-SA 4.0 unless otherwise noted. Code is released under MIT License.
"The best time to prepare medical education for AI was five years ago. The second best time is now."