Times are displayed in (UTC-04:00) Eastern Time (US & Canada) Change
3/12/2025 |
3:30 PM – 5:00 PM |
Conference A
S32: Invited Session: Ethics in AI: Principles and Practices for Healthcare
Presentation Type: Panel
Session Credits: 1.5
Session Chair:
Peter Elkin, MD, MACP, FACMI, FNYAM, FAMIA, FIAHSI - University at Buffalo School of Medicine and Biomedical Sciences
Invited Session: Ethics in AI: Principles and Practices for Healthcare
Presentation Time: 03:30 PM - 05:00 PM
Abstract Keywords: Machine Learning, Generative AI, and Predictive Modeling, Ethical, Legal, and Social Issues, Reproducible Research Methods and Tools
Primary Track: Data Science/Artificial Intelligence
Programmatic Theme: Health Data Science and Artificial Intelligence Innovation: From Single-Center to Multi-Site
As artificial intelligence (AI) shapes society, scholars, practitioners, and the public need to address ethics of applications in healthcare. Panelists from settings ranging from healthcare organizations to universities to industry will describe progress and challenges in ethics for AI in healthcare. Topics for discussion include but are not limited to confabulation in large language models, bias and fairness for predictive analytics, organizational issues, scientific reproducibility, and emerging best practices for implementation of ethical AI in healthcare. By addressing ethical issues with respect to AI system developers, care team members, and patients among other groups, the panel will provide a comprehensive overview of progress and challenges in ethics in AI in healthcare.
Speaker(s):
Anthony Solomonides, PhD, MSc(Math), MSc(AI), FAMIA, FACMI
Research Institute, Endeavor Health
Rayid Ghani, MS
Carnegie Mellon Uniiversity
Laurie Novak, PhD, MHSA
Vanderbilt University Medical Center Dept of Biomedical Informatics
Sunyang Fu, PhD, MHI
UTHealth
Sabrina Hsueh, PhD
Pfizer
Author(s):
Presentation Time: 03:30 PM - 05:00 PM
Abstract Keywords: Machine Learning, Generative AI, and Predictive Modeling, Ethical, Legal, and Social Issues, Reproducible Research Methods and Tools
Primary Track: Data Science/Artificial Intelligence
Programmatic Theme: Health Data Science and Artificial Intelligence Innovation: From Single-Center to Multi-Site
As artificial intelligence (AI) shapes society, scholars, practitioners, and the public need to address ethics of applications in healthcare. Panelists from settings ranging from healthcare organizations to universities to industry will describe progress and challenges in ethics for AI in healthcare. Topics for discussion include but are not limited to confabulation in large language models, bias and fairness for predictive analytics, organizational issues, scientific reproducibility, and emerging best practices for implementation of ethical AI in healthcare. By addressing ethical issues with respect to AI system developers, care team members, and patients among other groups, the panel will provide a comprehensive overview of progress and challenges in ethics in AI in healthcare.
Speaker(s):
Anthony Solomonides, PhD, MSc(Math), MSc(AI), FAMIA, FACMI
Research Institute, Endeavor Health
Rayid Ghani, MS
Carnegie Mellon Uniiversity
Laurie Novak, PhD, MHSA
Vanderbilt University Medical Center Dept of Biomedical Informatics
Sunyang Fu, PhD, MHI
UTHealth
Sabrina Hsueh, PhD
Pfizer
Author(s):