Machine learning has the potential to transform aspects of how healthcare and medicine are delivered, yet we know these technologies have the capacity to exacerbate existing inequalities (or introduce new ones). 

This webinar will discuss what it means for machine learning algorithms to be fair, explore potential issues, and share concrete steps for creating fair algorithms, as part of our larger goal of promoting equity in health systems. Special attention will be paid to fairness and bias considerations for large language models (e.g., ChatGPT/GPT-4, Bard/LaMDA).