EP 1383
1383. AI Expert Says: Humans Are Just Mystical Meat Robots
In this episode of The Human Upgrade, Host Dave Asprey sits down with Tom Griffiths, Henry R. Luce Professor of Information Technology, Consciousness, and Culture at Princeton University, to explore what artificial intelligence reveals about the hidden algorithms running your brain. From mitochondria pre-processing reality before your conscious mind ever gets involved, to why emotions like anger, love, and remorse are computational survival tools built by evolution, this conversation goes deep on the mathematics of human cognition. They unpack why the success of large language models should make us reconsider what is truly special about human intelligence, how low energy and blood sugar degrade your decision-making at a hardware level, and why resource rationality explains the choices you make when your cognitive tank is running low. Griffiths also breaks down how his lab runs psychology experiments on AI models to measure bias and personality differences across systems, and Dave shares why he would choose the least psychologically toxic AI if forced to pick just one. Whether you are obsessed with brain optimization, biohacking your decision-making, or just want to understand the code your biology is running, this episode delivers the kind of insight that changes how you see your own mind.
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In this Episode of The Human Upgrade™...
What if understanding how AI thinks could reveal uncomfortable truths about how your own brain works, and give you powerful tools to make smarter decisions, resist manipulation, and upgrade your cognition at the root level?
Host Dave Asprey sits down with Tom Griffiths, the Henry R. Luce Professor of Information Technology, Consciousness, and Culture in the Departments of Psychology and Computer Science at Princeton University. Griffiths directs Princeton’s Computational Cognitive Science Lab, a research group focused on understanding the mathematical foundations of human cognition, and the Princeton Laboratory for Artificial Intelligence. He is the coauthor of Algorithms to Live By and the author of the new book The Laws of Thought, and his award-winning research has appeared in Science, Nature, and the Proceedings of the National Academy of Sciences.
Together, Dave and Tom go deep on the cognitive science behind human performance, brain optimization, and the surprising overlap between biohacking and artificial intelligence. They explore why your body filters reality before your conscious brain ever sees it, how your mitochondria function as a distributed cognitive network, and what that means for longevity, decision-making, and neuroplasticity.
You’ll Learn:
- Why AI models reveal that humans may be more “stochastic parrots” than we’d like to admit
- How your mitochondria pre-process sensory reality before your auditory cortex even fires
- Why emotions like anger, love, and remorse are computational tools evolution built into your reward function
- How low energy and blood sugar directly degrade your decision-making at a hardware level
- What “resource rationality” means and how to use it to make better decisions under constraint
- Why AI systems have measurable psychological personalities, and which ones are least likely to mess with your head
- How neuroplasticity can eliminate the inner critic and reshape your mental operating system
- Why two-process cognition (fast and slow thinking) is a feature, not a bug, of human intelligence
Keywords: AI, cognitive science, Tom Griffiths, The Laws of Thought, Princeton, brain optimization, neuroplasticity, mitochondria, decision-making, biohacking, Dave Asprey, human performance, longevity, anti-aging, consciousness, large language models, dopamine, reward function, resource rationality, emotions, game theory, altered states, chronic fatigue, dual process theory, Danger Coffee, Smarter Not Harder, cognitive biases, memory, AI bias, neurofeedback, Algorithms to Live By
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"I actually think one of the reasonable reactions that you can have to our current AI systems is to decrease your estimation of humanity."
Tom Griffiths
00:00 – Introduction: AI and Humanity
Opening teaser on what AI reveals about human cognition, followed by Host Dave Asprey introducing Princeton professor and cognitive scientist Tom Griffiths.
07:54 – Tom’s Background & Chronic Fatigue
Tom shares how a years-long post-viral illness as a teenager, similar to long COVID, redirected him from math and computer science toward the mysteries of the human mind.
10:22 – Mathematics of Mind
Tom outlines the three mathematical frameworks used to understand cognition: logic and symbols, neural networks and spatial representations, and probability theory.
12:43 – Memory and Emotion
Dave and Tom explore how memories are indexed by emotion, and how neural networks model the associations that move us from one thought to the next.
15:29 – Decision Making Under Constraints
Why resource rationality explains how humans make decisions under limited energy, time, and compute, and how AI can help fill those gaps without replacing human judgment.
21:10 – Computational Problems of Consciousness
Tom breaks down the three levels of analysis in cognitive science and why asking what problem consciousness solves is more useful than asking whether AI is conscious.
24:18 – Reality Pre-Processing
Dave presents his theory that mitochondria filter and pre-process sensory reality before the brain ever receives it, and what that means for cognition and bias.
26:14 – Meat Robots vs Stochastic Parrots
Tom explains how large language models work and why their success should make us reconsider what is truly unique about human intelligence.
29:21 – Emotions: Game Theory
Tom walks through the computational purpose of anger, love, and remorse using game theory, and why Waymo cars might need a rage light to survive city traffic.
35:39 – Dual Systems: Model-Based vs Model-Free
Why having both a fast instinctive system and a slow deliberate system is a feature of intelligent design, and how remorse bridges the two.
39:22 – Mitochondria and Consciousness
Dave builds a case for mitochondria as the lowest cognitive node in biology, running a fear, food, fertility, and friend algorithm across trillions of networked cells.
50:00 – Testing AI Like Humans
Tom’s lab runs the same experiments on AI models that they run on humans to measure bias, personality, and reasoning differences across systems.
52:11 – Choosing AI Models
Dave and Tom debate which AI model they would choose if limited to one, and why psychological toxicity matters as much as raw capability.
57:14 – AI Research Questions
How AI models succeed and fail at generating genuinely novel research questions, and why sycophancy remains one of the hardest problems to solve.
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