“Towards a Formal Scientific Epistemology” by Richard_Ngo

In my post “Why I’m not a Bayesian”, I argued that the Bayesian approach of assigning credences to propositions with binary truth values only works in simple and restricted domains. Instead, I claimed, a better approach to epistemology is to assign degrees of truth to models of the world. This approach is broadly inspired by science, which is the domain from which we have the most evidence about which epistemological practices allow us to solve very hard problems. We don’t currently have a complete theory of scientific epistemology, but we can identify some important differences between scientific epistemology and Bayesian epistemology. Central examples of Bayesian epistemology (such as Solomonoff induction) assume that the truth lies within the class of hypotheses being considered. Conversely, in central examples of scientific research, the truth is definitely not already under consideration: the main problem is to come up with any hypothesis that explains existing data. Another way of putting this point: Bayesian epistemology is entirely about empirical updates, whereas science is mostly about the process of constructing new theories. In some cases, once you’ve constructed a theory, you can be confident that it's close to the truth merely from how well it fits [...] The original text contained 1 footnote which was omitted from this narration. --- First published: June 9th, 2026 Source: https://www.lesswrong.com/posts/NKFtDgSH7iZo8skTK/towards-a-formal-scientific-epistemology --- Narrated by TYPE III AUDIO.