Cascading natural hazards are phenomena where each event affects the next, such as severe storms followed by flooding followed by landslides. Understanding these cascades requires that scientists from multiple disciplines work together. The goal of this joint meeting of the Board on Earth Sciences and Resources and the Water Science and Technology Board is to consider how machine learning can inform our understanding of cascading hazards. How has machine learning permeated the science behind natural hazard assessment? What data sets should be developed to be "AI-ready" and further advance the use of machine learning to help reveal the connections between hazards? What applications of AI and machine learning could be envisioned in the near future to better link natural hazards to socioeconomic and human health impacts? Join members of the two boards as they explore this topic with 6 national experts on cascading hazards and machine learning applications in weather prediction and hydrology.