Nicoleta J. Economou-Zavlanos, PhD, has been named director of the newly established Duke Health AI Evaluation & Governance (E&G) Program. She will be charged with driving the trustworthy, responsible, and equitable integration of AI in health care.
The program operates under the leadership of Michael J. Pencina, PhD, chief data scientist at Duke Health and vice dean for data science at Duke University School of Medicine. Pencina directs Duke CTSI's Biomedical Informatics and Data Science Pillar, and CTSI will support E&G program operations.
Since 2022, Economou has served as the founding director of the Algorithm-Based Clinical Decision Support (ABCDS) Oversight initiative, which governs, evaluates, and monitors algorithmic solutions used at Duke Health. In this role, she leads the strategic direction and collaborates with Duke Health leaders and a wide spectrum of researchers to ensure algorithms are safe and meet best practices. Additionally, she oversees Duke Health initiatives related to the evaluation and governance of health AI technologies. Economou serves as the Chair of the Executive Advisory Board of the NIH Common Fund’s Bridge to Artificial Intelligence Program (Bridge2AI) and as Scientific Advisor for the Coalition for Health AI (CHAI), spearheading efforts to establish best practice guidance for trustworthy health AI.
Economou is a distinguished academic and researcher, recognized nationally for her contributions to the evaluation and governance of health AI, and is a newly appointed faculty member in the Department of Biostatistics and Bioinformatics. She has developed key frameworks, methodologies, and guidance for health AI governance, including systems for registration, review, and assurance. Her publications in NPJ Digital Medicine, JAMA, JAMA Health Forum, and JAMIA reflect her deep expertise and commitment to advancing the field.
In this new role, Economou will be responsible for leading programs and initiatives relevant to AI governance and evaluation at Duke Health. She will also be responsible for a portfolio of projects dedicated to framework development and advancing research in AI evaluation and governance, ensuring that AI technologies are trustworthy and aligned with high standards of quality, ethics, and fairness.