Abstraction & Idealization: AI's Plato Problem [Mazviita Chirimuuta]
Machine Learning Street Talk (MLST)
The podcast explores the philosophy of science, particularly focusing on abstraction, idealization, and the limitations of mechanistic explanations in understanding the brain and cognition. Mazviita Chirimuuta, author of "The Brain Abstracted," discusses how scientific models often simplify or misrepresent reality due to cognitive limitations and the pursuit of mathematical neatness. The conversation challenges the assumption that mathematical representations necessarily reveal a deeper truth about the universe, suggesting instead that they are tools shaped by human perspectives and goals. Chirimuuta introduces the concept of "haptic realism," emphasizing that knowledge is acquired through active engagement and manipulation rather than passive observation. The discussion also touches on the implications of technology and AI, questioning whether non-embodied AI can truly replicate human understanding, given the importance of embodiment and situatedness in biological cognition.
Part 1: Philosophy, Neuroscience, and Abstraction
Part 2: Scientific Models and Knowledge Frameworks
Part 3: Computation and Biological Reality
Part 4: Agency, Intentionality, and Causation
Part 5: AI, Embodiment, and Meaning
Part 6: Digital Impact and Social Ethics
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