Vaden Masrani and Ben Chugg, hosts of the Increments Podcast, are joining me to debate Bayesian vs. Popperian epistemology.
I’m on the Bayesian side, heavily influenced by the writings of Eliezer Yudkowsky. Vaden and Ben are on the Popperian side, heavily influenced by David Deutsch and the writings of Popper himself.
We dive into the theoretical underpinnings of Bayesian reasoning and Solomonoff induction, contrasting them with the Popperian perspective, and explore real-world applications such as predicting elections and economic policy outcomes.
The debate highlights key philosophical differences between our two epistemological frameworks, and sets the stage for further discussions on superintelligence and AI doom scenarios in an upcoming Part II.
00:00 Introducing Vaden and Ben
02:51 Setting the Stage: Epistemology and AI Doom
04:50 What’s Your P(Doom)™
13:29 Popperian vs. Bayesian Epistemology
31:09 Engineering and Hypotheses
38:01 Solomonoff Induction
45:21 Analogy to Mathematical Proofs
48:42 Popperian Reasoning and Explanations
54:35 Arguments Against Bayesianism
58:33 Against Probability Assignments
01:21:49 Popper’s Definition of “Content”
01:31:22 Heliocentric Theory Example
01:31:34 “Hard to Vary” Explanations
01:44:42 Coin Flipping Example
01:57:37 Expected Value
02:12:14 Prediction Market Calibration
02:19:07 Futarchy
02:29:14 Prediction Markets as AI Lower Bound
02:39:07 A Test for Prediction Markets
2:45:54 Closing Thoughts
Show Notes
Vaden & Ben’s Podcast: https://www.youtube.com/@incrementspod
Vaden’s Twitter: https://x.com/vadenmasrani
Ben’s Twitter: https://x.com/BennyChugg
Bayesian reasoning: https://en.wikipedia.org/wiki/Bayesian_inference
Karl Popper: https://en.wikipedia.org/wiki/Karl_Popper
Vaden's blog post on Cox's Theorem and Yudkowsky's claims of "Laws of Rationality": https://vmasrani.github.io/blog/2021/the_credence_assumption/
Vaden’s disproof of probabilistic induction (including Solomonoff Induction): https://arxiv.org/abs/2107.00749
Vaden’s referenced post about predictions being uncalibrated > 1yr out: https://forum.effectivealtruism.org/posts/hqkyaHLQhzuREcXSX/data-on-forecasting-accuracy-across-different-time-horizons#Calibrations
Article by Gavin Leech and Misha Yagudin on the reliability of forecasters: https://ifp.org/can-policymakers-trust-forecasters/
Sources for claim that superforecasters gave a P(doom) below 1%: https://80000hours.org/2024/09/why-experts-and-forecasters-disagree-about-ai-risk/
https://www.astralcodexten.com/p/the-extinction-tournament
Vaden’s Slides on Content vs Probability: https://vmasrani.github.io/assets/pdf/popper_good.pdf
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