I mostly liked the post. In Pearl's book, the example of whether smoking causes cancer worked pretty well for me despite being potentially controversial, and was more engaging for being on a controversial topic. Part of that is he kept his example fairly cleanly hypothetical. Eliezer's "I didn't really start believing that the virtue theory of metabolism was wrong" in a footnote, and "as common sense would have it" in the main text, both were suggesting it was about the real world. I think in Pearl's example, he may have even made his hypothetical data give the opposite result to the real world.

This post I also thought was more engaging due to the controversial topic, so if you can keep that while reducing the "mind-killer politics" potential I'd encourage that.

I was fine with the model he was falsifying being simple and easily disproved - that's great for an example.

I'm kind of confused and skeptical at the bit at the end: we've ruled out all the models except one. From Pearl's book I'd somehow picked up that we need to make some causal assumption, statistical data wasn't enough to get all the way from ignorance to knowing the causal model.

Is assuming "causation would imply correlation" and "the model will have only these three variables" enough in this case?