*crossposted on LessWrong*

I'm interested in questions of the form, "I have a bit of metadata/structure to the question, but I know very little about the content of the question (or alternatively, I'm too worried about biases/hacks to how I think about the problem or what pieces of information to pay attention to). In those situations, what prior should I start with?"

I'm not sure if there is a more technical term than "low-information prior."

Some examples of what I found useful recently:

1. Laplace's Rule of Succession, for when the underlying mechanism is unknown.

2. Percentage of binary questions that resolves as "yes" on Metaculus. It turns out that of all binary (Yes-No) questions asked on the prediction platform Metaculus, ~29% of them resolved yes. This means that even if you know *nothing* about the *content* of a Metaculus question, a reasonable starting point for answering a randomly selected binary Metaculus question is 29%.

In both cases, obviously there are reasons to override the prior in both practice and theory (for example, you can arbitrarily add a "not" to all questions on Metaculus such that your prior is now 71%). However (I claim), having a decent prior is nonetheless useful in practice, even if it's theoretically unprincipled.

I'd be interested in seeing something like 5-10 examples of low-information priors as useful as the rule of succession or the Metaculus binary prior.