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A comment on Understanding Causality Is the Next Challenge for Machine Learning. Parent comment

Re:Understanding Causality Is the Next Challenge for Machine... by zwaps on Thursday October 29, 2020 @05:24PM (#24936094)
DAGs are not the only valid approach to causality, nor do they subsume other approaches (I have previously commented on this during the Gelman&Pearl debates).

As you suggest, the treatment effect and econometrics literature currently is on a semi-parametric trend: Given that they don't believe that one can actually produce a believable complete causal model (or DAG), one tries to estimate a treatment effect that does not depend on parametric or functional assumptions.

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Re:Understanding Causality Is the Next Challenge for Machine... by a9h74j on Friday October 30, 2020 @12:06AM (#24939044)
> DAGs are not the only valid approach to causality

It has been a truism to some that "most efforts in policy are responses to previous efforts in policy." In SPC you can measure noise and overcontrol. With a long-lived policy-making institution [unusual?] honesty might admit to facing effects of previous well-intentioned policies.

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