Summary: Mazviita and I discuss the growing divide between prediction and understanding as neuroscience models and deep learning networks become bigger and more complex. She describes her non-factive account of understanding, which among other things suggests that the best predictive models may deliver less understanding. We also discuss the brain as a computer metaphor, and whether it's really possible to ignore all the traditionally "non-computational" parts of the brain like metabolism and other life processes. Show notes: Her website.Outside color website (with links to more of her publications)Her book Outside Color: Perceptual Science and the Puzzle of Color in Philosophy.Papers we discuss or mention:Prediction Versus Understanding in Computationally Enhanced Neuroscience.Your brain is like a computer: function, analogy, simplification.Charting the Heraclitean Brain: Perspectivism and Simplification in Models of the Motor Cortex.
