Bayesian "Epistemology"

• Bayes theorem cannot possibly assign a probability to the truth of a theory we do not yet have. And theories we do not yet have are actually the very business of scientists to create.
• You might have 10 possible diseases. We do a test. We rule out 9. We treat what’s left. Does that mean you as the patient are certainly suffering from “what’s left”? No!
• We have 3 diseases a patient might possibly have that we cannot distinguish between given the symptoms. We treat the most dangerous first. […] Probability need not enter into it. It’s not what the patient most likely has, but also what the patient is most threatened by.
• What Bayes Theorem cannot do is actually perform the function that scientists and philosophers who call themselves Bayesian say it can: to be a philosophy of inferring the best explanation. It cannot possibly create new explanations (which is, and should be the focus of science as much as gathering new evidence) and nor can it tell us what we should do. If we have a problem and we have no actual solution to it, Bayes' theorem cannot possibly help. All it can do is assign probabilities to existing ideas (none of which are regarded as actual solutions).
• When we have actual solutions in science they go by a generic honorific title. We call them “The scientific theory of…”. […] We don’t need to assign a probability to it being true. We regard it as provisionally true knowing it is superior to all rivals (insofar as there are any (and there are not!)) and we use it as if it’s true (this is pragmatic). But actually we expect that one day we will find it false.