Mitigating Bias in Feedback: Strategic Use of AI to Improve Learner Assessment

Saturday, April 26, 2025

10:00am – 11:30am HST

Location: Convention Center: 304

CE: 1.5

Leader(s)

Rebecca Carter, MD (she/her/hers)

Associate Professor of Pediatrics
University of Maryland School of Medicine
Baltimore, Maryland, United States

Co-Leader(s)

Esther Chung, MD, MPH (she/her/hers)

Professor of Pediatrics
Pediatrics
University of Washington
Seattle, Washington, United States
HB

Heather Burrows, MD PhD

Professor
University of Michigan
Ann arbor, Michigan, United States
SM

Sanghamitra Misra, MD, MEd (she/her/hers)

Professor
Baylor College of Medicine
Houston, Texas, United States
Maria Demma Cabral, MD (she/her/hers)

Faculty
Cottage Children's Medical Center
Santa Barbara, California, United States
JD

Jocelyn Deleon, MD (she/her/hers)

Assistant Professor
Western Michigan University Homer Stryker M.D. School of Medicine
Portage, Michigan, United States

Disclosure(s):

Rebecca Carter, MD: I do not have any relevant financial / non-financial relationships with any proprietary interests.

Esther K. Chung, MD, MPH: GlaxoSmithKline (Ongoing) (Products/Services: Ownership Interest including individual stocks, stock options, excluding diversified mutual funds); Pfizer (Ongoing) (Products/Services: Ownership Interest including individual stocks, stock options, excluding diversified mutual funds)

Heather Burrows, MD PhD: I do not have any relevant financial / non-financial relationships with any proprietary interests.

Sanghamitra M. Misra, MD, MEd: I do not have any relevant financial / non-financial relationships with any proprietary interests.

Maria Demma Cabral, MD: I do not have any relevant financial / non-financial relationships with any proprietary interests.

Jocelyn Deleon, MD: I do not have any relevant financial / non-financial relationships with any proprietary interests.

Workshop Description: Increasingly, medical educators are identifying ways to recognize and reduce bias in narrative feedback to learners. Despite concerns about bias and depersonalization of artificial intelligence (AI), AI may also provide a strategy to decrease bias and increase personalized feedback strategies for faculty delivering feedback to learners. In this interactive workshop, educators explore an innovative approach to feedback using AI. By leveraging AI algorithms, participants will learn how to mitigate bias in narrative assessments and tailor feedback to individual resident and medical student learners. The workshop emphasizes personalized guidance, ensuring that learners receive constructive and fair evaluations. Through hands-on activities, educators discover practical ways to harness AI’s potential for enhancing medical education, practicing prompts, and understanding how the common language pitfalls can be avoided in generating meaningful, actionable feedback to learners.

Learning Objectives:

Describe the current state of feedback in medical education and common pitfalls introducing bias in narrative and verbal feedback.
Recognize how generative AI can identify potential explicit and subtle bias in feedback language.
Collaborate in the creation of best practices for balancing personalized educator input and designing AI algorithms to promote fairness and inclusivity.