Learning Objectives
Understand key opportunities and challenges for AI governance in healthcare, particularly in regard to rapidly emerging generative AI applications
Discuss various responsible AI and AI governance frameworks that seek to ensure safety and efficacy in AI adoption
Explore the role of government, legislation, and regulators in supporting safe and equitable adoption of AI in healthcare
Explore opportunities for government, industry, and academic partnerships to accelerate AI validation, development, and adoption of safety standards
Consider the potential impact of AI on the healthcare workforce and provider and patient experiences
Identify the risks we should be most concerned with and what approaches can we take to mitigate those risks?
By the end of the presentation, participants should have a sense of the opportunities and challenges of adopting AI in healthcare, key risks and frameworks for mitigating them, and the potential role of government, academia, and industry in addressing these issues.
Calvin Lawrence, Distinguished Engineer – Responsible AI , Member of AI Ethics Board and Academy of Technology, IBM
Seth Dobrin, PhD, Founder and CEO, Qantm AI
Gil Alterovitz, PhD, Director, Biomedical Cybernetics Laboratory Harvard Medical School, Member of CHAI
Yoav Schlesinger Architect, Ethical AI Practice, Healthcare Salesforce
Dennis Chornenky, Chief AI Advisor UC Davis Health and CEO, Domelabs AI, Moderator