Interdisciplinary Workshop Forging a Path Between Causal Inference and Policy
Workshop co-organized by FOS, brought together data scientists, experts in the causal inference literature, and applied researchers, fostering collaborative exploration and amplifying the impact of causal inference and data science research on real-world policy challenges.
The difficulty of causal inference is not a matter of methodological rigour or reporting. The difficulty comes from the interdisciplinary nature of the process. Krishnan reminded those present that the community doing causal inference is not one community. Rather, causal inference is a process that engages different communities: biostatisticians, economists, epidemiologists, computer scientists, and data scientists, among others, making decisions that can inform policies.