Diversity, Equity and Inclusion in Health Care
AMA PRA Category 1 Credits 1.25
CAMPEP Credits: 1.25
MDCB Credits: 1.25
Andrew Hope, MD
Princess Margaret Cancer Center / University of Toronto
Toronto, Ontario
Artificial intelligence (AI) and machine learning (ML) are beginning to have a dramatic impact on the field of medicine in the domains of clinical decision making, radiation planning and interactions between patients and their medical teams. Despite the power of this technology to improve cancer care, there are growing concerns that its deployment may exacerbate disparities and that its algorithms may create or amplify biases. This session will explore the technical pathways within AI model development that can perpetuate human bias and widen disparities in the health care setting depending on its application and implementation, including how AI interacts with gender, race and other socioeconomic factors. This session will also explore how AI can be used to correct disparities in medicine, the potential role and responsibility of industry, and opportunities to leverage AI in the global context, including in low- and middle-income countries. Finally, the session will discuss potential policy solutions to ensure the fair and ethical deployment of AI technologies, and the importance of ensuring that a diverse research community is included in the discussions of ensuring algorithmic fairness.
Speaker: Andrew Hope, MD – Princess Margaret Cancer Center / University of Toronto
Speaker: Andrew Hope, MD – Princess Margaret Cancer Center / University of Toronto
Speaker: Laleh Seyyed-Kalantari, PhD – York University
Speaker: Kingsley Ndoh, MD
Speaker: Ajay Aggarwal, MD, PhD – London School of Hygiene and Tropical Medicine
Speaker: Andrew Hope, MD – Princess Margaret Cancer Center / University of Toronto