Oct 17, 2022
by Dr. Sophia Fantus
Assistant Professor, School of Social Work
University of Texas at Arlington
Bio
Dr. Sophia Fantus is an assistant professor in the School of Social Work at the University of Texas at Arlington. She has a B.A. in Religion and Bioethics from the University of Toronto, an MSW from New York University, and a PhD in Social Work and Bioethics from the University of Toronto. She is also a certified healthcare ethics consultant, having completed a two-year clinical ethics fellowship with Baylor College of Medicine’s Center for Medical Ethics and Health Policy. Dr. Fantus’ research interests focus on the integration of social work and bioethics. Her primary work is on moral distress of healthcare social workers and chaplains and is currently working on projects examining ethical decision-making and moral distress among informal family caregivers for persons living with Dementia and Alzheimer’s Disease. She also has interest in the ethics of medical AI/ML and how it connects to ethical practice and wellbeing among patients and providers.
Abstract
Artificial intelligence and machine learning (AI/ML) have transformed healthcare research and practice. The development of AI/ML in health has aimed to facilitate earlier and more accurate medical diagnoses, novel treatment and long-term care interventions, and ease workflow and administrative tasks. In research, advances in AI/ML have been used to examine genetics and neuroimaging using large datasets with the intention to treat degenerative illness, such as Alzheimer’s, Huntington’s, and Parkinson’s diseases. Yet, along with the expansion of AI/ML, there have been a wave of ethical and legal stipulations that have caused obstacles in how to justify AI/ML research and practice. Issues related to autonomy, bias, fairness, privacy and confidentiality, and trust have dominated theoretical scholarship. Yet, there is a gap in how these higher-level ethical principles and values may ultimately influence education, practice, and scholarship. The purpose of this talk is to describe these ethical considerations and explore ways in which to mitigate these risks and produce ethically informed medical AI/ML for patients, providers, and researchers.
Date: Monday, October 17, 2022
Time: 2:00 – 3:00 p.m. US Central Time
Location: Blocker 220 (in person)
Zoom: 998 4499 3279 (ID) & 724615 (PWD)
[Presentation slides]
https://tamids.tamu.edu/wp-content/uploads/2022/10/Slides-Sofia-Fantus.pdf
[Video]
https://www.youtube.com/watch?v=ggObicU3wc4