I think another important part of Pearl’s journey was that during his transition from Bayesian networks to causal inference, he was very frustrated with the correlational turn in early 1900s statistics. Because causality is so philosophically fraught and often intractable, statisticians shifted to regressions and other acausal models. Pearl sees that as throwing out the baby (important causal questions and answers) with the bathwater (messy empirics and a lack of mathematical language for causality, which is why he coined the do operator).
Pearl discusses this at length in The Book of Why, particularly the Chapter 2 sections on “Galton and the Abandoned Quest” and “Pearson: The Wrath of the Zealot.” My guess is that Pearl’s frustration with statisticians’ focus on correlation was immediate upon getting to know the field, but I don’t think he’s publicly said how his frustration began.
I think another important part of Pearl’s journey was that during his transition from Bayesian networks to causal inference, he was very frustrated with the correlational turn in early 1900s statistics. Because causality is so philosophically fraught and often intractable, statisticians shifted to regressions and other acausal models. Pearl sees that as throwing out the baby (important causal questions and answers) with the bathwater (messy empirics and a lack of mathematical language for causality, which is why he coined the do operator).
Pearl discusses this at length in The Book of Why, particularly the Chapter 2 sections on “Galton and the Abandoned Quest” and “Pearson: The Wrath of the Zealot.” My guess is that Pearl’s frustration with statisticians’ focus on correlation was immediate upon getting to know the field, but I don’t think he’s publicly said how his frustration began.