BI 107 Steve Fleming: Know Thyself

Steve and I discuss many topics from his new book Know Thyself: The Science of Self-Awareness. The book covers the full range of what we know about metacognition and self-awareness, including how brains might underlie metacognitive behavior, computational models to explain mechanisms of metacognition, how and why self-awareness evolved, which animals beyond humans harbor metacognition and how to test it, its role and potential origins in theory of mind and social interaction, how our metacognitive skills develop over our lifetimes, what our metacognitive skill tells us about our other psychological traits, and so on. We also discuss what it might look like when we are able to build metacognitive AI, and whether that's even a good idea. Steve's lab: The MetaLab.Twitter: @smfleming.Steve and Hakwan Lau on episode 99 about consciousness. Papers:Metacognitive training: Domain-General Enhancements of Metacognitive Ability Through Adaptive TrainingThe book:Know Thyself: The Science of Self-Awareness. Timestamps 0:00 - Intro 3:25 - Steve's Career 10:43 - Sub-personal vs. personal metacognition 17:55 - Meditation and metacognition 20:51 - Replay tools for mind-wandering 30:56 - Evolutionary cultural origins of self-awareness 45:02 - Animal metacognition 54:25 - Aging and self-awareness 58:32 - Is more always better? 1:00:41 - Political dogmatism and overconfidence 1:08:56 - Reliance on AI 1:15:15 - Building self-aware AI 1:23:20 - Future evolution of metacognition

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Neuroscience and artificial intelligence work better together. Brain inspired is a celebration and exploration of the ideas driving our progress to understand intelligence. I interview experts about their work at the interface of neuroscience, artificial intelligence, cognitive science, philosophy, psychology, and more: the symbiosis of these overlapping fields, how they inform each other, where they differ, what the past brought us, and what the future brings. Topics include computational neuroscience, supervised machine learning, unsupervised learning, reinforcement learning, deep learning, convolutional and recurrent neural networks, decision-making science, AI agents, backpropagation, credit assignment, neuroengineering, neuromorphics, emergence, philosophy of mind, consciousness, general AI, spiking neural networks, data science, and a lot more. The podcast is not produced for a general audience. Instead, it aims to educate, challenge, inspire, and hopefully entertain those interested in learning more about neuroscience and AI.