Tech & Health

September 22, 2022

VUMC to lead AI ethics core for NIH project

Vanderbilt researchers will lead and comprise the greater part of an artificial intelligence research ethics core for a National Institutes of Health (NIH) program called Bridge to Artificial Intelligence, or Bridge2AI.

Faculty members at Vanderbilt University Medical Center will have a central role in a National Institutes of Health (NIH) program called Bridge to Artificial Intelligence, or Bridge2AI.

Bradley Malin, PhD

The four-year, $104 million program is designed to accelerate use of machine learning (ML) and artificial intelligence (AI) in biomedical and behavioral research. VUMC researchers will lead and comprise the greater part of an AI research ethics core for Bridge2AI, with VUMC receiving $5.2 million over four years to support the work of the ethics core.

“Health and health care stand to benefit from advances in artificial intelligence, but those benefits will only be fully realized when the data utilized is collected in a societally responsible manner,” said Bradley Malin, Accenture Professor and professor of Biomedical Informatics. “The Bridge2AI program will work to ensure that ethical issues are front and center right from the outset of the program.”

Ellen Wright Clayton, MD, JD

Malin will lead the ethics core with Ellen Wright Clayton, MD, JD, the Craig-Weaver Professor Pediatrics and professor of Law; Xiaoqian Jiang, PhD, professor and director of the Center for Secure Artificial Intelligence for Healthcare at the University of Texas Health Sciences Center; and Camille Nebeker, EdD, MS, associate professor at the Wertheim School of Public Health at the University of California, San Diego.

Bridge2AI will generate several data sets for open-ended AI/ML research, which according to the NIH are to be “ethically sourced, trustworthy, well-defined and accessible.” Patricia Brennan, RN, PhD, director of the National Library of Medicine, said, “Rather than generating AI data sets under problem-inspired, or hypothesis-driven, research, we are proposing that by generating AI-ready data sets, we will accelerate our ability to be able to use AI techniques for discovery.”

The program is estimated to include $96 million for data generation projects on broad themes such as digital “twins” of patients as an aid to disease prevention and precision health care; expanding AI/ML in clinical care; functional genomics; body movement phenotyping; precision public health; and salutogenesis, or the general process of moving from a less healthy to a healthier state.

Along the way to generating these data sets, the program will seek to establish best practices for the collection and preparation of AI/ML-ready data for biomedical and behavioral health research.

Clayton noted that there are any number of established social, ethical and legal standards available to help focus the discussion of AI/ML for advancing biomedical research.

“Granted, so-called big data is a new phenomenon, but the issues it raises aren’t unfamiliar,” said Clayton, who helped establish VUMC’s Center for Biomedical Ethics and Society. “Under Bridge2AI, we look forward to engaging with scientists and data specialists on the leading edge of AI research, together developing and implementing ethical standards that can help see the field through to its next chapters. Engaging with and building trust among the public will be essential to this work.”

Other Bridge2AI cores will focus on program administration, data standards, tool optimization, “teaming,” and long-term AI workforce development. The six cores will comprise the Integration, Dissemination and Evaluation Center, otherwise known as the Bridge Center.

Laurie Novak, PhD, associate professor of Biomedical Informatics at VUMC, will serve as co-leader for two of the ethics core’s four planned buckets of work. Other VUMC faculty on tap for the ethics core include, from the Department of Biomedical Informatics, Toufeeq Ahmed, PhD, Daniel Fabbri, PhD, Paul Harris, PhD, Yaa Kumah-Crystal, MD, Michael Matheny, MD, Colin Walsh, MD, Martin Were, MD, and Zhijun Yin, PhD, and from the Department of Biostatistics, Chris Lindsell, PhD.

Bridge2AI is funded by the NIH Common Fund (HG012510).