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How does someone use do-calculus? It's a nice mathematization of Goodhart's law, https://en.wikipedia.org/wiki/Goodhart%27s_law

but how would help an algorithm make better predictions?

Sure, the reason a person turns on the heat affects our belief in the outside weather (were they feeling cold, or were they just trolling?), but how do you know the reason a person turned on the heat, and couldn't you learn which reason are predictive by measuring correlations with other observables? If you know the reason directly ("I'm just playing with the dial because I'm 4 years old") that's a data point you could throw into your ML model without explicitly knowing it's a reason.







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