Rethinking Bias in AI – Why Algorithmic Bias is Only the Tip of the Iceberg
February 4, 2026: 10 am PT / 11 am MT / 12 pm CT / 1 pm ET
Presenters: Steven Lin, MD, and Tricia Elliott, MD
This 60-minute conversational session will feature STFM President Steven Lin, MD, and STFM Past President Tricia Elliott, MD. The conversation will begin with a discussion about how biased data leads to skewed AI outputs and touch on strategies for mitigation, such as de-biasing data and fairness audits. The conversation will then pivot to a broader view: participation bias (how limited voices shape AI priorities) and implementation bias (how deployment can exclude marginalized communities). The speakers will offer ideas for equity-centered policies and practices, and describe how STFM’s National Family Medicine AI Centers of Excellence can build capacity and skills.
Participants will get practical tips on:
- Talking the AI talk
- Having relevant conversations in their institutions
- Making the business case for equitable AI integration
- AI practices that promote health equity
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Integrity, Identity, and Inclusion: Reframing Professionalism for a New Era
March 31, 2026: 10 am PT / 11 am MT / 12 pm CT / 1 pm ET
Presenters: Andrea Anderson, MD, MEd
This 60-minute presentation by Immediate Past ABFM Chair Andrea Anderson, MD, will invite family medicine educators to reexamine how professionalism is defined and taught amid rapidly evolving social and cultural contexts. This session will explore emerging frameworks that integrate integrity, self-awareness, and inclusion as core dimensions of physician identity. Participants will discuss how traditional professionalism standards can unintentionally reinforce bias and exclusion, and how to reframe them toward equity and belonging. Practical strategies for teaching, assessing, and modeling professionalism in diverse learning environments will also be highlighted.
Learning Objectives:
Following this presentations, participants will be able to:
- Examine evolving definitions of medical professionalism that address modern challenges in healthcare and education.
- Identify best practices for teaching and assessing professionalism in diverse, inclusive learning environments.
- Analyze how health equity and bias considerations intersect with traditional professionalism standards.
- Discuss generational variations in perspectives on professionalism and their implications for mentoring and role modeling.
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