I have “faith” in things like Occam’s razor and hope it helps get toward objective truth, but there’s no way to know for sure. Without constraints on the prior, we can’t say much of anything beyond the data we have.
choosing an appropriate algorithm requires making assumptions about the kinds of target functions the algorithm is being used for. With no assumptions, no “meta-algorithm”, such as the scientific method, performs better than random choice.
For example, without an assumption that nature is regular, a million observations of the sun having risen on past days would tell us nothing about whether it will rise again tomorrow.
My comment about Occam’s razor was in reply to “the idea that all rational agents should be able to converge on objective truth.” I was pointing out that even if you agree on the data, you still may not agree on the conclusions if you have different priors. But yes, you’re right that you may not agree on how to characterize the data either.
I have “faith” in things like Occam’s razor and hope it helps get toward objective truth, but there’s no way to know for sure. Without constraints on the prior, we can’t say much of anything beyond the data we have.
https://en.wikipedia.org/wiki/No_free_lunch_theorem#Implications_for_computing_and_for_the_scientific_method
For example, without an assumption that nature is regular, a million observations of the sun having risen on past days would tell us nothing about whether it will rise again tomorrow.
Occam’s razor tells you to find the simplest explanation for the evidence,so it is downstream of the question of what constitutes evidence.
My comment about Occam’s razor was in reply to “the idea that all rational agents should be able to converge on objective truth.” I was pointing out that even if you agree on the data, you still may not agree on the conclusions if you have different priors. But yes, you’re right that you may not agree on how to characterize the data either.