Announcements

Updates on campus events, policies, construction and more.

close  

Information for Our Community

Whether you are part of our community or are interested in joining us, we welcome you to Washington University School of Medicine.

close  


Visit the News Hub

Payne named to national health care AI code of conduct steering committee

Data scientist to help lead National Academy of Medicine committee on equitable, responsible use of AI in health care

June 23, 2023

Philip R.O. Payne, PhD, the Janet and Bernard Becker Professor and director of the Institute for Informatics, Data Science & Biostatistics (I2DB) at Washington University School of Medicine in St. Louis, has joined the steering committee of a National Academy of Medicine working group to draft a code of conduct for artificial intelligence (AI) in health, medical care and health research.

The National Academy of Medicine announced June 20 that it is convening health, tech, research and bioethics leaders to develop an Artificial Intelligence Code of Conduct and describe the national architecture required to give rise to and support equitable and responsible use of AI in health, medical care, and health research. As AI is poised for a profound impact throughout the health field, the effort is a direct response to the growing call for a harmonized set of AI guidelines that can facilitate interoperable governance standards for its development and application.

Payne, also the associate dean for health information and data science and the chief data scientist for the School of Medicine, is an internationally recognized leader in the field of clinical research informatics and translational bioinformatics. As a member of the code of conduct steering committee, he will help develop a guiding framework to ensure that AI algorithms and their application in health, medical care, and health research perform accurately, safely, reliably and ethically in the service of better health for all. The code of conduct will be presented in a “best practice” framework that can be widely adopted, translated for implementation by various stakeholders and continuously improved to realize AI’s enormous promise.