To cite one field that I'm especially familiar with, consider probability and decision theory, where we went from having no concept of probability, to studies involving gambles and expected value, to subjective probability, Bayesian updating, expected utility maximization, and the Turing-machine-based universal prior, to the recent realizations that EU maximization with Bayesian updating and the universal prior are both likely to be wrong or incomplete.

I don't see how bayesian utility maximizers lack the "philosophical abilities" to discover these ideas. Also, the last one is only half true. The "wrong" link is about decision theory paradoxes, but a bayesian utility maximizer would overcome these with practice.