Minds and Machines 30 (1):47-75 (2020)

Authors
Ryan Mark Nefdt
University of Cape Town
Abstract
This paper attempts to describe and address a specific puzzle related to compositionality in artificial networks such as Deep Neural Networks and machine learning in general. The puzzle identified here touches on a larger debate in Artificial Intelligence related to epistemic opacity but specifically focuses on computational applications of human level linguistic abilities or properties and a special difficulty with relation to these. Thus, the resulting issue is both general and unique. A partial solution is suggested.
Keywords compositionality  deep learning  linguistics  epistemic opacity
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DOI 10.1007/s11023-020-09519-6
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References found in this work BETA

The Modularity of Mind.Robert Cummins & Jerry Fodor - 1985 - Philosophical Review 94 (1):101.
Three Kinds of Idealization.Michael Weisberg - 2007 - Journal of Philosophy 104 (12):639-659.
Understanding From Machine Learning Models.Emily Sullivan - forthcoming - British Journal for the Philosophy of Science:axz035.

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