EPISODE · Sep 25, 2024 · 43 MIN
Nature of Intelligence, Ep. 1: What is Intelligence
from COMPLEXITY · host Santa Fe Institute
Guests: Alison Gopnik, SFI External Faculty; Professor of Psychology and Affiliate Professor of Philosophy at University of California, Berkeley; Member of Berkeley AI Research GroupJohn Krakauer, SFI External Faculty; John C. Malone Professor of Neurology, Neuroscience, and Physical Medicine & Rehabilitation, Johns Hopkins UniversityHosts: Abha Eli Phoboo & Melanie MitchellProducer: Katherine MoncurePodcast theme music by: Mitch MignanoPodcast logo by Nicholas GrahamFollow us on:Twitter • YouTube • Facebook • Instagram • LinkedIn • BlueskyMore info:Complexity Explorer: Tutorial: Fundamentals of Machine LearningLecture: Artificial IntelligenceSFI programs: EducationBooks: Artificial Intelligence: A Guide for Thinking Humans by Melanie MitchellWords, Thoughts and Theories by Alison Gopnik and Andrew N. MeltzoffThe Scientist in the Crib: Minds, Brains, and How Children Learn by Alison Gopnik, Andrew N. Meltzoff, and Patricia K. KuhlThe Philosophical Baby: What Children's Minds Tell Us About Truth, Love, and the Meaning of Life by Alison GopnikThe Gardener and the Carpenter: What the New Science of Child Development Tells Us About the Relationship Between Parents and Children by Alison GopnikTalks: The Future of Artificial Intelligence by Melanie MitchellImitation Versus Innovation: What Children Can Do That Large Langauge Models’ Can’t by Alison GopnikThe Minds of Children by Alison GopnikWhat Understanding Adds to Cambrian Intelligence: A Taxonomy by John KrakauerPapers & Articles:“Why you can’t make a computer that feels pain,” by Daniel C. Dennett“Transmission versus truth, imitation versus innovation: What children can do that Large Language and Language-and-Vision models cannot (yet),” in Perspectives on Psychological Science (October 26, 2023), doi.org/10.1177/17456916231201401“Empowerment as Causal Learning, Causal Learning as Empowerment: A bridge between Bayesian causal hypothesis testing and reinforcement learning,” by Alison Gopnik“What can AI Learn from Human Exploration? Intrinsically-Motivated Humans and Agents in Open-World Exploration” by Yuqing Du et al, for Workshop: Agent Learning in Open-Endedness Workshop, NeurIPS 2024 conference“Two views on the cognitive brain,” by David L. Barack & John W. Krakauer, Perspectives in Nature Reviews Neuroscience Vol 22 (April 15, 2021)“The intelligent reflex,” by John W. Krakauer, Philosophical Psychology (May 23, 2019), doi.org/10.1080/09515089.2019.1607281“Representation in Cognitive Science by Nicholas Shea: But Is It Thinking? The Philosophy of Representation Meets Systems Neuroscience” by John W. Krakauer
What this episode covers
Depending on whom you ask, artificial intelligence is either going to solve all humanity’s problems, or it’s going to kill us. Business leaders are getting ready for it to “disrupt” entire industries, and educators are re-thinking how to teach in the age of ChatGPT. It can feel like artificial intelligence is going to transform everything about the way we live. But in order to understand how to think about AI, it’s useful to take a step back. In today’s episode, we’re asking what it means to call anything "intelligent". What makes humans intelligent? And how do machines compare? Guests: John Krakauer and Alison Gopnik
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Nature of Intelligence, Ep. 1: What is Intelligence
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