Fighting Bias from Bias: Robust Natural Language Techniques to Promote Health Equity

Explore the intersection of artificial intelligence and healthcare equity in this 38-minute talk from the Center for Language & Speech Processing at Johns Hopkins University. Delve into the potential of AI to address health-related disparities while examining the challenges of identifying systemic inequality and translating it into machine-learnable tasks. Discover recent progress in clinical phenotyping and its implications for language model robustness in medical applications. Learn about ongoing efforts to combat systemic inequality in healthcare by identifying and characterizing stigmatizing language in medical records. Gain insights into the broader purpose of AI in healthcare infrastructure and its role in improving health outcomes for diverse populations.