Hal Varian (Google) (Mar 2017)
Causal inference is challenging due to confounding variables and the need to distinguish correlation from causation, but methods like randomized experiments, natural experiments, instrumental variables, regression discontinuity design, and difference-in-differences can help establish causal relationships. Machine learning can enhance causal analysis but requires careful consideration of selection bias and other challenges.