TLDR of Argmin's Summary of Half of the Meehl Lectures

Tags: ai, pompousness, Date: 2024-05-22

Over at, Ben Recht is reflecting on Meehl's lectures on the metatheory of science, which is about how science progresses. The original lectures are fascinating but also long as well as long-winded, and I found Ben's blog series a much better read (especially since the originals are video recordings). Still, at the time of writing, with 13 blog posts covering less than half of the lectures (5/12), no self-respecting 21st century scientist can risk the time investment (equivalent to publishing 0.25 papers in machine learning) or – even worse – getting slowed down by methodological considerations.

So, here is my TLDR for the busy professional: it's all Bayes and incentives. There is no silver bullet method, and while we do questionable things for all the wrong reasons, time will clean up any mess that we make anyway.

Expanding that for slightly longer attention spans:

At this point, the rest is somewhat predictable; my armchair is like any other. But if you can tolerate examples and spelling out implications, read on.

I believe improving the incentives is the most important contribution one can make in today's world. Now, go and read Ben's posts.