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Molyneux’s question asks whether someone born blind, who could distinguish cubes from spheres using his tactile sensation, could recognize those objects if he received his sight. Locke says no: the newly sighted person would fail to point to the cube and call it a cube. Locke never provided a complete explanation for his negative response, and there are concerns of inconsistency with other important aspects of his theory of ideas. These charges of inconsistency rest upon an unrecognized and unfounded assumption (...) |
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Molyneux’s question asks whether someone born blind, who could distinguish cubes from spheres using his tactile sensation, could recognize those objects if he received his sight. Locke says no: the newly sighted person would fail to point to the cube and call it a cube. Locke never provided a complete explanation for his negative response, and there are concerns of inconsistency with other important aspects of his theory of ideas. These charges of inconsistency rest upon an unrecognized and unfounded assumption (...) |
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In recent years, many philosophers and scientists have argued or accepted that it is impossible to learn primitive sensory concepts like “blue” and “red”. This paper defends a more qualified picture. I try to show that some received characterisations of “learning” are nonequivalent and point towards different learning-nonlearning distinctions. And, on some ways of specifying such a distinction, it might be correct that we do not and cannot “learn” a concept of blue. But on other ways of specifying such a (...) No categories |
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This is the original, longer draft for my entry on Hume in the 'The Routledge Hand- book of Philosophy of Imagination', edited by Amy Kind and published by Routledge in 2016 (see the separate entry). — Please always cite the Routledge version, unless there are passages concerned that did not make it into the Handbook for reasons of length. — -/- This chapter overviews Hume’s thoughts on the nature and the role of imagining, with an almost exclusive focus on the (...) |
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In artificial intelligence, recent research has demonstrated the remarkable potential of Deep Convolutional Neural Networks (DCNNs), which seem to exceed state-of-the-art performance in new domains weekly, especially on the sorts of very difficult perceptual discrimination tasks that skeptics thought would remain beyond the reach of artificial intelligence. However, it has proven difficult to explain why DCNNs perform so well. In philosophy of mind, empiricists have long suggested that complex cognition is based on information derived from sensory experience, often appealing to (...) |