The tldr from my reading is that Pearl thinks you can't ascend the "ladder of causality" with pure DL -- i.e. while you can make associations to answer simple p

The tldr from my reading is that Pearl thinks you can't ascend the "ladder of causality" with pure DL -- i.e. while you can make associations to answer simple probabilistic questions, you can't create a system that can answer questions like "if this intervention is made at t0, what is the likely outcome at t1?" or consider counterfactuals like "would my mother have lived longer if she didn't drink?" You'd probably be best served by reading Pearl himself, his recent Book of Why is good, this much earlier paper[0] kind of lays out a few things too as for his reasoning that causal inference needs different tools. There's also some stuff in the blogosphere about an earlier dispute you might find fun, i.e. the methods of using causal inference tools. Example[1]. [0] https://ftp.cs.ucla.edu/pub/stat_ser/r284-reprint.pdf https://ftp.cs.ucla.edu/pub/stat_ser/r284-reprint.pdf [1] https://statmodeling.stat.columbia.edu/2009/07/05/disputes_about/ https://statmodeling.stat.columbia.edu/2009/07/05/disputes_a...