Why the brain is not a computer

It's one of the most powerful ideas in the history of science. That a brain is, in essence, a computer. That we can look past its gelatinous flesh and see through to its underlying workings. That these workings are best described in the language of programs and computations, algorithms and representations. There's no question that this "brain as computer" analogy, has been—in many ways—enormously generative. But in other ways could it be leading us astray?  My guest today is Dr. Mazviita Chirimuuta. Mazviita is a Philosopher of Mind and Neuroscience at the University of Edinburgh, in Scotland. She's the author of the widely acclaimed and widely discussed 2024 book, The Brain Abstracted: Simplification in the History and Philosophy of Neuroscience.  Here, Mazviita and I talk about the early days of her career spent trying to build computational models of cells in the visual system—and how this informed her later philosophical work. We discuss how neuroscience—indeed all science—involves key simplifying strategies: analogy, mathematization, and reductionism. We talk about the history of the "brain as computer" analogy and the different ways of understanding its status. We consider how a computational understanding of the brain feeds directly into certain ideas about technology, for example the idea that machines are on the cusp of consciousness or the idea that we may one day soon upload our minds to the digital realm. Along the way, we touch on Marr's levels of analysis, maps and territories, biological naturalism, medium dependence and independence, analog vs digital computing, neuromorphic AI, Moravec's paradox, the lower bounds of cognition, and whether consciousness is more like the game of chess or more like soccer.  I learned a lot from this one, folks—and I think you will, too. On to my conversation with Dr. Mazviita Chirimuuta. Enjoy!   Notes 7:00 – Dr. Chirimuuta's book, again, is here. You can also read a précis of the book here, which was published along with commentaries here. 9:00 – Dr. Chirimuuta's paper, 'Prediction versus understanding in computationally enhanced neuroscience.' 12:30 – The (very) short Borges story, 'On Exactitude in Science.' 17:00 – The classic essay by Eugene Wigner, 'The unreasonable effectiveness of mathematics in the natural sciences.' 19:00 – For more on metaphor and analogy in science, see our earlier episode. For another perspective on the "brain as computer" analogy, see here. 27:00 – The classic article from 1943 by McCulloch and Pitts, one of the earliest articulations of the idea of computation in the brain. 30:00 – For a primer on Marr's levels of analysis, see here. 36:00 – For some perspectives on the controversial idea of "mind uploading," see here. 42:00 – For an articulation of biological naturalism, see, e.g., work by Anil Seth here and <a href= "https://www.cambridge.org/core/journals/behavioral-a