Ethical Challenges From Medical Big Data and AI

Big data and artificial intelligence are revolutionizing most areas of society, and are poised to make a similar impact on health care and medicine. Like all new powerful technologies, AI has risks as well as benefits. If not carefully managed, AI can contribute to serious harm to patients in areas including privacy and nosocomial injury. This presentation will describe the nature of these risks along with potential approaches to reduce harm.

Originally published on January 8, 2020.

Lecture Presenter
Brian R. Jackson, MD, MS
Brian R. Jackson, MD, MS
Medical Director, Business Development, IT and Support Services, ARUP Laboratories
Associate Professor of Clinical Pathology; Adjunct Associate Professor of Biomedical Informatics, University of Utah School of Medicine

Dr. Jackson is the medical director for Business Development, Support Services and IT at ARUP and an associate professor of pathology (clinical) at the University of Utah School of Medicine. He received his BA in mathematics, his MS in medical informatics, and his MD from the University of Utah, and completed a clinical pathology residency at Dartmouth-Hitchcock Medical Center. Prior to his employment at ARUP, Dr. Jackson was a staff clinical pathologist and informaticist at Dartmouth-Hitchcock Medical Center, a product manager for a Belgium-based medical software firm, and a National Library of Medicine informatics fellow at the University of Utah. Dr. Jackson’s research interests include economic analysis of diagnostic testing, physician utilization of laboratory tests, and corporate social responsibility in healthcare. He is certified in clinical pathology by the American Board of Pathology.

Objectives

After this presentation, participants will be able to:

Identify key limitations of HIPAA in the big data/AI era
Identify mechanisms of bias in black box algorithms
Describe mechanisms for AI risk reduction through both public policy and academic research