AlanCrowe comments on Causal Diagrams and Causal Models - Less Wrong

61 Post author: Eliezer_Yudkowsky 12 October 2012 09:49PM

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Comment author: AlanCrowe 13 October 2012 10:05:33AM 0 points [-]

I think that one bootstraps the process with contrived situations designed to appeal to ones intuitions. For example, one attempts to obtain causal information through a randomised controlled trial. You mark the obverse face of a coin "treatment" and reverse face "control" and toss the coin to "randomly" assign your patients.

Let us briefly consider the absolute zero of no a priori knowledge at all. Perhaps the coin knows the prognosis of the patient and comes down "treatment" for patients with a good prognosis, intending to mislead you into believing that the treatment is the cause of good outcomes. Maybe, maybe not. Let's stop considering this because insanity is stalking us.

We are willing to take a stand. We know enough, a prior, to choose and operate a randomisation device and thus obtain a variable which is independent of all the others and causally connected to none of them. We don't prove this, we assume it. When we encounter a compulsive gambler, who believes in Lady Luck who is fickle and very likely is actually messing with us via the coin, we just dismiss his hypothesis. Life is short, one has to assume that certain obvious things are actually true in order to get started, and work up from there.