AuthorHoffman, Sharona
PositionJournal of Law and Health's Digital Health & Technology Symposium

The Journal of Law and Health's Digital Health & Technology Symposium


The following is a transcription from The Digital Health and Technology Symposium presented at Cleveland-Marshall College of Law by The Journal of Law & Health on Friday, April 8, 2022. This transcript has been lightly edited for clarity.

Tigan Woolson:

First today, presenting on Artificial Intelligence (AI) and discrimination in healthcare, we have Professor Sharona Hoffman. Professor Sharona Hoffman is the Edgar A. Hahn Professor of Law, a professor of bioethics, and Co-Director of the Case Western Reserve University Law School's Law and Medicine Center. She has her J.D. from Harvard Law School, an L.L.M. in Health Law from the University of Houston, and an S.J.D. in Health Law from Case Western Reserve University. (2)

In 2017, Professor Hoffman was elected to the prestigious American Law Institute. She is one of the most cited health law scholars in the United States and received the 2021 Case Western Reserve University "Faculty Distinguished Research Award." She has also served twice as a visiting scholar at the Centers for Disease Control and Prevention. Professor Hoffman has published over 60 articles and book chapters on artificial intelligence, health information technology, big data, emergency preparedness, and many other health law topics. She has developed particular expertise and a national reputation in the area of health law and information technology. Her work has appeared in the Georgetown Law Journal, among many other prestigious journals. Professor Hoffman is currently working as a visiting scholar at the National Institute of Health in the Bioethics Department.

Sharona Hoffman:

Great! Thank you so much, it is a pleasure to be here. I am going to be talking about AI and discrimination in healthcare, and this is based on an article by the same title that appeared in the Yale Journal of Health Policy, Law, and Ethics a couple of years ago. (3)

I am going to be focusing on concerns, but we do have to acknowledge that AI is actually very promising. It can improve treatment outcomes in a lot of ways. It can help doctors identify patients who are at risk of complications and hospital readmissions. There is a lot of work being done here in Cleveland on images. First, you can use AI to analyze images to help you determine with greater certainty which ones [tumors] are malignant, which ones are aggressive and which ones [tumors] will and will not require chemotherapy. (4) That can spare patients a lot of uncomfortable and problematic treatments. It also can help identify candidates for clinical studies, and of course, it's been used a lot with COVID-19. (5) There were studies that used AI to try to predict patients' disease courses to predict which patients are going to get sick or very sick and need hospitalization, and which are not, and it was also used to analyze patient records to identify effective treatments. (6)

Now first looking at the privacy concerns we have. When you have AI, you are looking through a lot of patients' records and you are handling a lot of information, so you have to be concerned about whether it's going to be stored and handled securely and if privacy will be maintained. There are questions about the physician-patient relationship; will physicians become redundant and unnecessary, eventually? Will we have medicine by computer? You'll go in, you'll describe your symptoms to the computer, and it will spit out a diagnosis and treatment course. Will that be the new reality?

Second, the other very real problem is whether doctors are going to trust AI suggestions if those suggestions are not what they would naturally be inclined to do. For...

To continue reading

Request your trial

VLEX uses login cookies to provide you with a better browsing experience. If you click on 'Accept' or continue browsing this site we consider that you accept our cookie policy. ACCEPT