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BI 128 Hakwan Lau: In Consciousness We Trust

BI 128 Hakwan Lau: In Consciousness We Trust

FromBrain Inspired


BI 128 Hakwan Lau: In Consciousness We Trust

FromBrain Inspired

ratings:
Length:
86 minutes
Released:
Feb 20, 2022
Format:
Podcast episode

Description

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Hakwan and I discuss many of the topics in his new book, In Consciousness we Trust: The Cognitive Neuroscience of Subjective Experience. Hakwan describes his perceptual reality monitoring theory of consciousness, which suggests consciousness may act as a systems check between our sensory perceptions and higher cognitive functions. We also discuss his latest thoughts on mental quality space and how it relates to perceptual reality monitoring. Among many other topics, we chat about the many confounds and challenges to empirically studying consciousness, a topic featured heavily in the first half of his book. Hakwan was on a previous episode with Steve Fleming, BI 099 Hakwan Lau and Steve Fleming: Neuro-AI Consciousness.





Hakwan's lab: Consciousness and Metacognition Lab.Twitter: @hakwanlau.Book:In Consciousness we Trust: The Cognitive Neuroscience of Subjective Experience.





0:00 - Intro
4:37 - In Consciousness We Trust
12:19 - Too many consciousness theories?
19:26 - Philosophy and neuroscience of consciousness
29:00 - Local vs. global theories
31:20 - Perceptual reality monitoring and GANs
42:43 - Functions of consciousness
47:17 - Mental quality space
56:44 - Cognitive maps
1:06:28 - Performance capacity confounds
1:12:28 - Blindsight
1:19:11 - Philosophy vs. empirical work
Released:
Feb 20, 2022
Format:
Podcast episode

Titles in the series (99)

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.