But it is not clear at all why stories do not approximate Bayesian updating. Stories do allow us to reach far into the void of space which cannot be mapped immediately from sensory data, but stories also mutate and get forgotten based how useful they are which at least resembles Bayesian updating. The question is whether this kind of filtering throws off the approximation so far that it is qualitatively a different computation.
I don't think we can say that the mutation or loss of stories is very close to Bayesian updating. It may be a form of natural selection, and maybe sometimes the trait being selected for is "truth", but very often it's going to be something other than truth. Memes mutate in order to be more viral, and may lose truth on the way.
Stories about big, shocking, horrible events are more memetically contagious and will thus look more probable, if you're assuming that their memetic availability reflects their likelihood.