It's a dichotomy in this specific case where science says "don't care, same math, same predictions" and EY's Bayes says "my model is simpler than yours, so it's better". The dichotomy disappears once the models are different experimentally, except that one should still strive to find the Kolmogorov-simplest model with the same predictive power. In any case, EY's point, the way I understood it, is that when the scientific method fails (different models are not easily testable, like in economics, for example), one should "fall back" on Bayes.
It is foolish to strive to find the Kolmogorov-simplest model, because that task is known to be impossible.
Today's post, The Dilemma: Science or Bayes? was originally published on 13 May 2008. A summary (taken from the LW wiki):
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