Your Brain vs. AI: What Makes Human Thinking Unique

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Dr. Perlmutter’s groundbreaking new book, Brain Defenders, is now available for pre-order. Discover how to protect your brain and future health – reserve your copy today at https://www.braindefenders.com.

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What if AI isn’t on a path to become a better human — but a fundamentally different kind of mind altogether? In this episode, Tom Griffiths joins me to challenge how we think about intelligence itself — and to make a compelling case that AI systems are best understood not as smarter or dumber than humans, but as “alien organisms” solving problems in ways our brains never could.

Tom Griffiths is a cognitive scientist, the Henry R. Luce Professor of Psychology and Computer Science at Princeton University, and head of Princeton’s AI Lab. He is the co-author of the international bestseller Algorithms to Live By and author of the new book The Laws of Thought — an ambitious survey of three centuries of attempts to capture human thinking in mathematics.

We dig into the three mathematical frameworks scientists use to model thought, why a human toddler can learn language from a fraction of the data a large language model requires, what “resource rationality” reveals about mental health and decision-making, and what we stand to lose — and gain — as we increasingly outsource our thinking to machines.

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00:00 – Introduction
00:46 – A New Way to Think About Brain Health: Brain Defenders
05:27 – Welcoming Cognitive Scientist Tom Griffiths
06:04 – The Great Mystery: Can Math Explain How We Think?
08:23 – Three Threads of Cognitive Science: Rules, Networks, Probability
10:17 – Why AI Needs 10,000x More Data Than a Child
12:27 – Intuition Decoded: How Neural Networks Mirror Implicit Learning
15:03 – The Creativity Gap: Why AI Can’t Think Outside the Box
18:06 – 40 Hz Light Therapy and Cognitive Decline
20:07 – Inductive Bias: The Evolutionary Head Start of the Human Brain
22:41 – Mental Health Through Three Levels of Analysis
25:25 – Resource Rationality: Why Humans Aren’t Actually Irrational
29:33 – Free Will Through the Lens of the Laws of Thought
31:35 – Rethinking Education With Cognitive Science
34:33 – Evolutionary Mismatch: The Mind Meets Modern Technology
37:23 – AI as Alien Intelligence: A New Mental Model
38:04 – Personalized Brain Health: 3X4 Genetics
39:55 – Uncertainty: The Hidden Engine of Human Cognition
43:34 – Bayesian Inference: The Math of “Best Guessing”
44:37 – The Biggest Misconceptions About Intelligence
47:14 – Algorithms to Live By: Optimizing Daily Decisions
49:22 – Five Years From Now: The AI Forecast
51:33 – The Calculator Effect: What Happens When We Outsource Thinking
53:56 – Metacognition: Becoming the Manager of AI
55:34 – Closing Thoughts

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Dr. Tom Griffiths, PhD is a cognitive scientist and computational psychologist whose research has shaped how scientists understand human decision-making under uncertainty and how artificial intelligence differs from biological intelligence. He earned his PhD in psychology from Stanford University in 2005, along with master’s degrees in psychology and statistics, with doctoral exchange work at MIT’s Brain and Cognitive Sciences Department and CSAIL. He holds a Bachelor of Arts with Honours in Psychology from the University of Western Australia.

Dr. Griffiths is the Henry R. Luce Professor of Information Technology, Consciousness, and Culture at Princeton University, with appointments in Psychology and Computer Science. He directs both the Computational Cognitive Science Laboratory and the Princeton Laboratory for Artificial Intelligence. Before joining Princeton in 2018, he held faculty positions at Brown University and UC Berkeley.

He is a Fellow of the Association for Psychological Science, a recipient of awards from the American Psychological Association and the National Academy of Sciences, co-author of the international bestseller Algorithms to Live By: The Computer Science of Human Decisions, and author of The Laws of Thought: The Quest for a Mathematical Theory of the Mind. His work has appeared in Science, Nature, and PNAS.

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