Princeton Scientist: We Don't Understand AI - Tom Griffiths - #553

About this episode

Tom Griffiths discusses the limitations of AI in understanding human cognition and the implications for artificial general intelligence.

A Princeton cognitive scientist says AI can't think like a child — and giving it more data won't fix that. If the field keeps scaling without solving what's actually missing, the gap between human and machine intelligence won't close. It'll just get more expensive. Tom Griffiths is a professor of psychology and computer science at Princeton, and one of the leading researchers working at the intersection of human cognition and AI. We cover: -why a child learns language from breadcrumbs while AI needs continents of data -the 250-year-old idea that quietly became the foundation of modern language models -what sycophantic AI actually does to your beliefs over time -why solving AGI might have less to do with scale and more to do with understanding what a child's mind really is. The hallucinations don't bother him — it's the sycophancy that should worry you. Key Takeaways: 00:00 The Math Behind How Minds Actually Work 00:30 Why Defining "Thought" Is Harder Than It Looks 04:30 What AI Gets Wrong About Consciousness 07:00 What ChatGPT Actually Revealed About the Field 08:10 Are Humans Really Irrational — Or Solving a Different Problem? 11:00 How Chomsky Turned Language Into a Math…

People in this episode

Guest: Tom Griffiths

Topics covered

• AI and cognition
• language learning
• human vs machine intelligence
• child development
• AGI challenges
• philosophy of mind

Keywords

• AI
• cognition
• language models
• human intelligence
• AGI
• child learning
• data scaling
• philosophy

Mentioned in this episode

Organizations: Princeton, Big Bang Productions Inc.

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