[6gvONxR4sf7o]

I totally agree as causation as a sort of generalization enhancer akin to regularization. In stats, there's the notion of some "true" parameter that's trying to be estimated, but you get all sorts of systematic errors creeping in if you estimate it wrong. If you get a good estimate of it, though, you've learned something "true" and that generalizes much better than systematically wrong versions. Like, if you figure out F and m and that F=ma, you're going to make really good predictions, regardless of how far from your original training you are. Other truths are still pretty limited (like the example of a social study finding the true treatment effect of something on affluent white 20 year olds in LA), but the scientific ideas of internal and external validity still apply quite nicely.