thomblake comments on Causal Diagrams and Causal Models - Less Wrong
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I suspect this depends on the handling of the issue. Eliezer presenting his model of the world as "common sense," straw manning the alternative, and then using fake data that backs up his preferences is, frankly, embarrassing.
This is especially troublesome because this is an introductory explanation to a technical topic- something Eliezer has done well before- and introductory explanations are great ways to introduce people to Less Wrong. But how can I send this to people I know who will notice the bias in the second paragraph and stop reading because that's negative evidence about the quality of the article? How can I send this to people I know who will ask why he's using two time-variant variables as single acyclic nodes, rather than a ladder (where exercise and weight at t-1 both cause exercise at t and weight at t)?
What would it look like to steel man the alternative? One of my physics professors called 'calories in-calories out=change in fat' the "physics diet," since it was rooted in conservation of energy; that seems like a far better name. Like many things in physics, it's a good first order approximation to the engineering reality, but there are meaningful second order terms to consider. "Calories in" is properly "calories absorbed" not "calories put into your mouth"- though we'll note it's difficult to absorb more calories than you put into your mouth. Similarly, calories out is non-trivial to measure- current weight and activity level can give you a broad guess, but it can be complicated by many things, like ambient temperature! Any attempt we make to control calories in and calories out will have to be passed through the psychology and physiology of the person in question, making them even more difficult to control in the field.
Compare the volume of discussion of the method and the overweight-exercise link in the comments.
Why do you need to send this article to people who could ask that? If you're saying "Oh, this should actually be modeled using causal markov chains..." then this is probably too basic for you.
Because I'm still a grad student, most of those people that I know are routinely engaged in teaching these sorts of concepts, and so will find articles like this useful for pedagogical reasons.