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An Overview of Ethics and Equity of Artificial Intelligence in Healthcare

April 3 @ 9:30 am 10:30 am

Part of the Planning Workshop #1

Speaker:
Benjamin Collins, M.D.
Vanderbilt University Medical Center

Abstract: The use of artificial intelligence and machine learning tools in healthcare raises questions of the ethics and equity regarding such tools. A wide variety of possible issues have been identified and strategies for how to address many of these issues are deliberated among experts. The use of AI in other fields potentially previews some of the problems that we may encounter in healthcare as well. This presentation will focus on a broad overview of the issues of ethics and equity with AI/ML in healthcare and possible strategies to address them, including brief contextualization using both actual cases and hypothetical cases modeled on real AI/ML tools. Several key concepts will be the focus: technology is not neutral, patient engagement and community engagement are essential, trust and trustworthiness of AI/ML, principles of ethics and equity, and ethical issues of AI/ML from an AI lifecycle perspective. Attendees will be able to recognize ethics and equity issues of AI/ML in healthcare; to employ principles of ethics and equity when thinking about those issues; and to contrast AI tools and the contexts in which they are developed, implemented, and used with reference to an AI lifecycle. 

Bio: Benjamin Collins is a physician and postdoctoral research fellow in ethics, legal, and social issues of artificial intelligence (AI) in healthcare with the Department of Biomedical Informatics and the Center for Biomedical Ethics and Society. Clinically he works as a hospitalist with the Department of Medicine. He completed medical school at Virginia Commonwealth University School of Medicine in Richmond, VA and internal medicine residency at Temple University Hospital in Philadelphia, PA. During residency, he also earned an MA degree in Urban Bioethics from Temple with a thesis on, “A Theory of Sociotechnical Justice in Healthcare.” He then completed a clinical informatics fellowship at Oregon Health & Science University along with an MS degree in biomedical informatics, finishing a capstone project by developing an online training module for clinicians on algorithmic bias in healthcare. He received the 2022 American Medical Informatics Association (AMIA) Academic Forum Best Paper Award for his work on, “Development of an Online Training Module on Algorithmic Bias in Health Care for Clinicians.” He volunteers as a member of the Diversity, Equity, and Inclusion Committee in AMIA and serves as the 2023-2024 education co-chair for their education, governance, and policy subcommittee.