Thanks for this! Apparently, among many economists Occam's Razor is viewed as just a modelling trick, judging from the conversations on Reddit I've had recently. I'd felt that perspective was incorrect for a while, but after encountering it so many times, and then later on being directed to this paper, I'd begun to fear my epistemology was built on shaky foundations. It's relieving to see that's not the case.
It turns out there's an extremely straightforward mathematical reason why simplicity is to some extent an indicator of high probability.
Is there anything ruling out a bias towards simplicity that is extremely small, or are there good reasons to think the bias would be rather large? Figuring out how much predictive accuracy to exchange for theory conciseness seems like a tough problem, possibly requiring some arbitrariness.
This essay claims to refute a popularized understanding of Occam's Razor that I myself adhere to. It is confusing me, since I hold this belief at a very deep level that it's difficult for me to examine. Does anyone see any problems in its argument, or does it seem compelling? I specifically feel as though it might be summarizing the relevant Machine Learning research badly, but I'm not very familiar with the field. It also might be failing to give any credit to simplicity as a general heuristic when simplicity succeeds in a specific field, and it's unclear whether such credit would be justified. Finally, my intuition is that situations in nature where there is a steady bias towards growing complexity are more common than the author claims, and that such tendencies are stronger for longer. However, for all of this, I have no clear evidence to back up the ideas in my head, just vague notions that are difficult to examine. I'd appreciate someone else's perspective on this, as mine seems to be distorted.
Essay: http://bruce.edmonds.name/sinti/