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  1. Throwing light on black boxes: emergence of visual categories from deep learning.Ezequiel López-Rubio - 2020 - Synthese 198 (10):10021-10041.
    One of the best known arguments against the connectionist approach to artificial intelligence and cognitive science is that neural networks are black boxes, i.e., there is no understandable account of their operation. This difficulty has impeded efforts to explain how categories arise from raw sensory data. Moreover, it has complicated investigation about the role of symbols and language in cognition. This state of things has been radically changed by recent experimental findings in artificial deep learning research. Two kinds of artificial (...)
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  • Empiricism in the foundations of cognition.Timothy Childers, Juraj Hvorecký & Ondrej Majer - 2023 - AI and Society 38 (1):67-87.
    This paper traces the empiricist program from early debates between nativism and behaviorism within philosophy, through debates about early connectionist approaches within the cognitive sciences, and up to their recent iterations within the domain of deep learning. We demonstrate how current debates on the nature of cognition via deep network architecture echo some of the core issues from the Chomsky/Quine debate and investigate the strength of support offered by these various lines of research to the empiricist standpoint. Referencing literature from (...)
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