Key Initiatives

Artificial Intelligence in Medical Education Initiative

The STFM Artificial Intelligence in Medical Education Initiative

An STFM Artificial Intelligence in Medical Education Task Force, chaired by STFM President Steven Lin, MD, is working on the following tactics to advance responsible, outcome-driven, and people-centered artificial intelligence:

  • Identify and act on opportunities for collaborative work around AI within STFM (e.g. the AI in Education Collaborative and other Collaboratives)
  • Identify and act on opportunities to collaborate around AI with the larger family of family medicine organizations
  • Forge new partnerships with other professional societies, health systems, industry, payers, and government around AI
  • Identify and promote foundational AI use cases that help the family medicine workforce 
  • Identify opportunities to develop datasets that catalyze family medicine R&D and attract industry
  • Identify and promote opportunities to apply AI to support core values such as equity and community
  • Support the work of family medicine AI pioneers, disseminate learnings, and promote the development of new centers of excellence 
  • Provide members with opportunities to practice with exemplar AI-based tools that can be applied to a wide range of clinical, educational, and research settings\
  • Address key limitations to the use of AI including unintended, harmful consequences
  • Identify and promote opportunities for AI to personalize the learning journey for learners (“precision medical education”)
  • Identify and promote opportunities for AI to lower the burden of education administration and curriculum development for faculty
  • Identify and promote opportunities to elevate members to leadership roles in AI
  • Identify or create new opportunities to incorporate AI content/training into existing STFM programs and offerings for medical students, residents, and faculty
  • Explore the feasibility of an AI certificate program for STFM members
  • Inspire and mobilize STFM members and more broadly, frontline primary care clinicians, scholars, educators, and learners around AI

STFM Artificial Intelligence in Medical Education Task Force

  • Steven Lin, MD, Stanford University School of Medicine
  • Rika Bajra, MD, Stanford University School of Medicine
  • Ian Bennett MD, PhD, University of Washington School of Medicine
  • Linda Chang, PharmD, MPH, BCPS, University of Illinois College of Medicine at Rockford
  • John Hayes DO, MCW-Prevea Green Bay Family Medicine Residency Program
  • Enitza George, MD, MBA, MSAI, SUNY Downstate Health Sciences University
  • Karim Hanna, MD, USF TGH Family Medicine Residency Program
  • Misbah Keen, MD, MBI, MPH, University of Washington School of Medicine
  • Winston Liaw, MD, MPH, University of Houston
  • May Lin, DO, Touro University
  • Yun Shi, MD, PhD, UT Health San Antonio
  • Margaret Ann Smith, Stanford School of Medicine
  • Brent Sugimoto, MD, MPH, LifeLong Medical Care Family Medicine Residency Program
  • Mary Theobald, MBA, Society of Teachers of Family Medicine
  • Timothy Tsai, DO MMCi, Stanford University School of Medicine
  • Steven Waldren, MD, MS, American Academy of Family Physicians
  • Yun Liu, Google Research

     

Quick Links

Contact Us

11400 Tomahawk Creek Parkway

Leawood, KS 66211

(800) 274-7928

stfmoffice@stfm.org 

 

 

Events

October 27, 2025, 6 pm Eastern: Bishop Society Webinar: Learning From Adversity—Lessons for the Future

November 14, 2025 8:30 am–5:30 pm Central: POCUS Launchpad: Navigating Logistics of Implementing Ultrasound in Residency Training

November 19, 2025, 1 pm Eastern: GME Leadership Webinar Series: “Soft Power, Strong Purpose: Navigating Institutional Realities”

January 29–February 1, 2026: The 2026 STFM Conference on Medical Student Education

February 4, 2026, 1 pm Eastern: Webinar: Integrity, Identity, and Inclusion: Reframing Professionalism for a New Era

May 2–6, 2026: The 2026 STFM Annual Spring Conference

Due Dates

October 28, 2025: Apply for the STFM Foundation Faculty for Tomorrow Resident Scholarship

November 1, 2025: Apply for Behavioral Science/Family Systems Educator Fellowship

November 8, 2025: Nominations for the following awards: Curtis G. Hames Research Award and STFM Research Paper of the Year Award

November 14, 2025: Apply for Emerging Leaders Fellowship

November 17, 2025: Apply for Faculty Development Delivered Chair

December 1, 2025: Apply for Deputy Editor for DEIA of Family Medicine Journal

December 15, 2025: Apply for CERA Clerkship Survey Director

December 15, 2025: Apply for CERA Mentor Director

January 15, 2026: Family Medicine Call for Papers: Theme Issue on Point-of-Care Ultrasound (POCUS) in Family Medicine Education

March 1, 2026: Family Medicine Call for Papers: Theme Issue on Scope of Practice in Family Medicine

Useful Links

Ask a Question
AI Chatbot Tips

Tips for Using STFM's AI Assistant

STFM's AI Assistant is designed to help you find information and answers about Family Medicine education. While it's a powerful tool, getting the best results depends on how you phrase your questions. Here's how to make the most of your interactions:

1. Avoid Ambiguous Language

Be Clear and Specific: Use precise terms and avoid vague words like "it" or "that" without clear references.

Example:

Instead of: "Can you help me with that?"
Try: "Can you help me update our Family Medicine clerkship curriculum?"
Why this is important: Ambiguous language can confuse the AI, leading to irrelevant or unclear responses. Clear references help the chatbot understand exactly what you're asking.

2. Use Specific Terms

Identify the Subject Clearly: Clearly state the subject or area you need information about.

Example:

Instead of: "What resources does STFM provide?"
Try: "I'm a new program coordinator for a Family Medicine clerkship. What STFM resources are available to help me design or update clerkship curricula?"
Why this is better: Providing details about your role ("program coordinator") and your goal ("design or update clerkship curricula") gives the chatbot enough context to offer more targeted information.

3. Don't Assume the AI Knows Everything

Provide Necessary Details:The STFM AI Assistant has been trained on STFM's business and resources. The AI can only use the information you provide or that it has been trained on.

Example:

Instead of: "How can I improve my program?"
Try: "As a program coordinator for a Family Medicine clerkship, what resources does STFM provide to help me improve student engagement and learning outcomes?"
Why this is important: Including relevant details helps the AI understand your specific situation, leading to more accurate and useful responses.

4. Reset if You Change Topics

Clear Chat History When Switching Topics:

If you move to a completely new topic and the chatbot doesn't recognize the change, click the Clear Chat History button and restate your question.
Note: Clearing your chat history removes all previous context from the chatbot's memory.
Why this is important: Resetting ensures the AI does not carry over irrelevant information, which could lead to confusion or inaccurate answers.

5. Provide Enough Context

Include Background Information: The more context you provide, the better the chatbot can understand and respond to your question.

Example:

Instead of: "What are the best practices?"
Try: "In the context of Family Medicine education, what are the best practices for integrating clinical simulations into the curriculum?"
Why this is important: Specific goals, constraints, or preferences allow the AI to tailor its responses to your unique needs.

6. Ask One Question at a Time

Break Down Complex Queries: If you have multiple questions, ask them separately.

Example:

Instead of: "What are the requirements for faculty development, how do I register for conferences, and what grants are available?"
Try: Start with "What are the faculty development requirements for Family Medicine educators?" Then follow up with your other questions after receiving the response.
Why this is important: This approach ensures each question gets full attention and a complete answer.

Examples of Good vs. Bad Prompts

Bad Prompt

"What type of membership is best for me?"

Why it's bad: The AI Chat Assistant has no information about your background or needs.

Good Prompt

"I'm the chair of the Department of Family Medicine at a major university, and I plan to retire next year. I'd like to stay involved with Family Medicine education. What type of membership is best for me?"

Why it's good: The AI Chat Assistant knows your role, your future plans, and your interest in staying involved, enabling it to provide more relevant advice.

Double Check Important Information

While the AI Chat Assistant is a helpful tool, it can still produce inaccurate or incomplete responses. Always verify critical information with reliable sources or colleagues before taking action.

Technical Limitations

The Chat Assistant:

  • Cannot access external websites or open links
  • Cannot process or view images
  • Cannot make changes to STFM systems or process transactions
  • Cannot access real-time information (like your STFM Member Profile information)

STFM AI Assistant
Disclaimer: The STFM Assistant can make mistakes. Check important information.