Status: Completed

Algorithmic bias is often described as “systemic and repeatable errors in a computer system that create unfair outcomes.” It had real-world implications that manifested broadly in areas such as employment, housing, and healthcare. Many emerging methods were utilized to mitigate algorithmic bias, and ultimately reduce health inequities, yet gaps remained in development and implementation. This project brought together Duke faculty colleagues and other experts from different disciplines to discuss harmful bias and created innovative training programs to eliminate bias in algorithms that were used to make decisions and target resources that affected patient care.

2023-2024 Awardee, Duke Faculty Advancement Seed Grants

This initiative was anchored in the Duke University School of Nursing’s mission to lead with equity and innovation, and it was conducted in strategic partnership with Duke AI Health.

The following Duke University School of Nursing faculty nurses have expertise in AI:

• Dr. Michael Cary – Principal Investigator
• Dr. Kais Gadhoumi – Assistant Research Professor in the School of Nursing
• Dr. Jennie De Gagne –  Clinical Professor in the School of Nursing
• Dr. Elaine Kauschinger – Assistant Clinical Professor in the School of Nursing
• Dr. Allison Lewinski – Associate Research Professor in the School of Nursing
• Dr. Kay Lytle – Chief Nursing Information Officer, Duke Health System
• Dr. Jacqui McMillian-Bohler – Associate Dean of Innovation and Evaluation
• Dr. Michael Zychowicz – Clinical Professor in the School of Nursing