Ep 248: AI and Philosophy of Science

whatshot 54 snips

Oct 13, 2025

The discussion dives into the misconceptions around AI and knowledge creation, challenging the predictive doom narratives that dominate current discourse. It critiques the reliance on Bayesian reasoning and highlights the philosophical blind spots in understanding AI's potential. The talk emphasizes that science isn't just data extrapolation, urging a reevaluation of personhood and creativity in the context of technology. It sheds light on the pitfalls of both AI doomers and accelerationists, advocating for a more nuanced understanding of how knowledge and science evolve.

01:25:39

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INSIGHT

AI Doom Is A New Priestly Prophecy

Hall frames AI debates as a clash of new priesthoods who prophesy futures people crave to hear.
He warns prophetic, sensational claims (e.g., 'If Anyone Builds It, Everyone Dies') distort policy and public perception.

insights

INSIGHT

Science Isn’t Mere Extrapolation

Hall argues many AI doom arguments assume science is curve-fitting or Bayesian extrapolation.
He counters that true scientific explanation requires theories (e.g., molecules, hydrogen bonding) not mere data extrapolation.

insights

INSIGHT

Philosophy Shapes How We View AI Futures

Major philosophy-of-science camps (Kuhn, Feyerabend, Lakatos) disagree on realism and method, often leaving confusion about how science creates explanations.
Hall prefers Popperian/Deutschian accounts that treat conjecture and explanation as central.

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Why Superintelligence Arguments Felt Wrong

00:54 • 2min

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Preparing a Response to AI Doomism

02:57 • 46sec

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Why Philosophy of Science Matters for AI

03:43 • 2min

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The New Priesthood: Physicists and Technologists

05:36 • 2min

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Personhood and the Limits of Physics

07:48 • 2min

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Big Questions Aren't Solved by Credentials

09:54 • 3min

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Life, Consciousness and the Missing Explanations

13:00 • 4min

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The New Priesthoods and Prophecy About the Future

17:00 • 2min

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Knowledge Creation Is Inherently Unpredictable

18:40 • 2min

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Early Critique of Bostrom and Bayesianism

20:19 • 5min

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Why Doomers Recycle the Same Arguments?

25:23 • 5min

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Publicity, Levity, and the Politics of Doom

30:14 • 6min

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Is Science Just Extrapolating Data?

35:49 • 3min

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Explanations Versus Data Extrapolation

38:37 • 34sec

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Doom Scenarios Depend on a False Model of Science

39:11 • 3min

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How Does Explanatory Knowledge Appear?

41:43 • 5min

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Survey of Philosophy of Science Positions

47:11 • 3min

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Popper, Deutsch and the Quest to Explain Creativity

49:59 • 50sec

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Transformers, Attention, and Limits of LLMs

50:49 • 3min

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Models, Understanding, and Scientific Insight

53:22 • 6min

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Could an LLM Solve Quantum Gravity?

58:54 • 2min

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Why There Can Be No Reliable Test for AGI

01:01:08 • 3min

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Doomers vs. Accelerationists: Both Misguided

01:04:00 • 4min

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Are Humans Just Prediction Engines?

01:07:53 • 4min

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Bad Philosophy Stymies Knowledge Growth

Will AI Make Students Stupid?

01:17:12 • 2min

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Are Current Gen AI Systems Truly Creative?

01:18:53 • 4min

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Practical Benefits and Real Risks of AI Tools

More Big Questions with Paul Davies

Paul Davies

Phillip Adams

#19992

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Science in a Free Society

Paul Feyerabend

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The Beginning of Infinity

Explanations That Transform the World

David Deutsch

In this groundbreaking book, David Deutsch argues that explanations have a fundamental place in the universe and that improving them is the basic regulating principle of all successful human endeavor. The book takes readers on a journey through various fields of science, history of civilization, art, moral values, and the theory of political institutions. Deutsch explains how we form new explanations and drop bad ones, and discusses the conditions under which progress, which he argues is potentially boundless, can and cannot happen. He emphasizes the importance of good explanations, which he defines as those that are 'hard to vary' and have 'reach', and argues that these explanations are central to the Enlightenment way of thinking and to all scientific and philosophical progress.

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Stephen Wolfram

In 'A New Kind of Science,' Stephen Wolfram presents a comprehensive study of computational systems, particularly cellular automata, and argues that the study of simple programs can revolutionize various fields of science. The book, which took over a decade to complete, introduces the Principle of Computational Equivalence and the concept of computational irreducibility. Wolfram demonstrates how simple rules can generate complex behavior, similar to patterns observed in nature, and discusses the implications of these findings for fields such as physics, biology, and mathematics. The book is known for its extensive use of computer graphics and its attempt to establish a new foundational science based on computational principles.

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Facing the Limits of Knowledge in the Twilight of the Scientific Age

John Horgan

In 'The End of Science,' John Horgan discusses the idea that science may be nearing its theoretical limits. He interviews various eminent scholars, including Fred Hoyle, Noam Chomsky, and John Wheeler, to explore topics such as God, superstrings, quarks, consciousness, and the Omega Point. Horgan argues that science is facing significant challenges, including the constraints imposed by special relativity, quantum mechanics, and chaos theory. He also critiques the trend of 'ironic science,' where theoreticians engage in speculative and often untestable theories, potentially reducing science to a status akin to literary criticism. The book presents a contrarian view on the future of scientific discovery and its place in the hierarchy of disciplines.

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David Deutsch

In 'The Fabric of Reality', David Deutsch explores a four-strand theory of everything, integrating Hugh Everett's many-worlds interpretation of quantum physics, Karl Popper's epistemology, Alan Turing's theory of computation, and Richard Dawkins's evolutionary theory. The book discusses the implications of these theories, including the concept of the multiverse, quantum computers, time travel, and the ultimate fate of the universe. Deutsch argues that these theories, when taken literally and jointly, reveal a unified, objective, and comprehensible fabric of reality.

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If Anyone Builds It, Everyone Dies

Eliezer Yudkowsky

Nate Soares

This book delves into the potential risks of advanced artificial intelligence, arguing that the development of superintelligence could lead to catastrophic consequences for humanity. The authors present a compelling case for the need for careful consideration and regulation of AI development. They explore various scenarios and potential outcomes, emphasizing the urgency of addressing the challenges posed by rapidly advancing AI capabilities. The book is written in an accessible style, making complex ideas understandable to a broad audience. It serves as a call to action, urging policymakers and researchers to prioritize AI safety and prevent potential existential threats.

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• Mentioned in 4 episodes

The big questions

Steven Landsburg

#103

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Superintelligence

Paths, Dangers, Strategies

Nick Bostrom

In this book, Nick Bostrom delves into the implications of creating superintelligence, which could surpass human intelligence in all domains. He discusses the potential dangers, such as the loss of human control over such powerful entities, and presents various strategies to ensure that superintelligences align with human values. The book examines the 'AI control problem' and the need to endow future machine intelligence with positive values to prevent existential risks.

This is the extended "director's cut" of a talk delivered for "RatFest 2025" (next year to be "Conjecture Con"). This also serves as a supplement to my "Doom Debates" interview which can be found here: https://youtu.be/koubXR0YL4A?si=483M6SPOKwbQYmzb

It is simply assumed some version of "Bayesian reasoning" is how AI will "create" knowledge. This misconception permeates the https://ai-2027.com paper, as well as Bostrom and Yudkowsky's work on this, as well as that of every other AI "Doomer" and even on the other extreme the so-called "AI-Accelerationists". All of that indicates a deep misconception about how new explanations are generated which comes from a deep misconception about how science works because almost no one in the field of AI seems to think the *philosophy of* science is even relevant. I explain what has gone wrong:

00:00 Introduction

09:14 The Big Questions and the new Priesthoods

18:40 Nick Bostrom and Superintelligence

25:10 If anyone builds it, everyone dies and Yudkowsky.

33:32 Prophecy, Inevitability, Induction and Bayesianism.

41:42 Popper, Kuhn, Feyerabend and Lakatos.

49:40 AI researchers ignore The Philosophy of Science.

58:46 A new test for AGI from Sam Altman and David Deutsch?

1:03:35 Accelerationists, Doomers and “Everyone dies”.

1:10:21 Conclusions

1:15:35 Audience Questions

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