This post is about the distinctions between Traditional and Bayesian Rationality, specifically the difference between refusing to hold a position on an idea until a burden of proof is met versus Bayesian updating.

Good quality government policy is an important issue to me (it's my Something to Protect, or the closest I have to one), and I tend to approach rationality from that perspective. This gives me a different perspective from many of my fellow aspiring rationalists here at Less Wrong.

There are two major epistemological challenges in policy advice, in addition to the normal difficulties we all have to deal with: 1) Policy questions fall almost entirely within the social sciences. That means the quality of evidence is much lower than it is in the physical sciences. Uncontrolled observations, analysed with statistical techniques, are generally the strongest possible evidence, and sometimes you have nothing but theory or professional instinct to work with.
2) You have a very limited time in which to find an answer. Cabinet Ministers often want an answer within weeks, a timeframe measured in months is luxurious. And often a policy proposal is too sensitive to discuss with the general public, or sometimes with anyone outside your team.

By the standards of Traditional Rationality, policy advice is often made without meeting a burden of proof. Best guesses and theoretical considerations are too weak to reach conclusions. A proper practitioner of Traditional Rationality wouldn't be able to make any kind of recommendation, one could identify some promising initial hypotheses, but that's it.

But Just because you didn't have time to come up with a good answer doesn't mean that Ministers don't expect an answer. And a practitioner of Bayesian Rationality always has a best guess as to what is true, even if the evidence base is non-existent you can fall back on your prior. You don't want to be overconfident in stating your position, assumptions must be outlined and sensitivities should be explored. But you still need to give an answer and that's what attracts me to Bayesian approaches: you don't have to be officially agnostic until being presented with a level of evidence that is unrealistically high for policy work.

It seems to me that if you have very good quality evidence then Bayesian and Traditional Rationality are very similar. Good evidence either proves or disproves a proposition for a Traditional Rationalist, and for a Bayesian Rationalist it will shift their probability estimate, as well as increasing their confidence a lot. The biggest difference seem to me to be that Bayesian Rationality seems is able to make use of weak evidence in a way Traditional Rationality can't.