Forms of explanation and understanding for neuroscience and artificial intelligence

Much of the controversy evoked by the use of deep neural networks as models of biological neural systems amount to debates over what constitutes scientific progress in neuroscience. To discuss what constitutes scientific progress, one must have a goal in mind (progress toward what?). One such long-t...

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Bibliographic Details
Published inJournal of neurophysiology Vol. 126; no. 6; pp. 1860 - 1874
Main Author Thompson, Jessica A F
Format Journal Article
LanguageEnglish
Published United States 01.12.2021
Subjects
Artificial Intelligence
Deep Learning
Humans
Neurosciences
deep learning
understanding
intelligibility
explanation
causality
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Summary:Much of the controversy evoked by the use of deep neural networks as models of biological neural systems amount to debates over what constitutes scientific progress in neuroscience. To discuss what constitutes scientific progress, one must have a goal in mind (progress toward what?). One such long-term goal is to produce scientific explanations of intelligent capacities (e.g., object recognition, relational reasoning). I argue that the most pressing philosophical questions at the intersection of neuroscience and artificial intelligence are ultimately concerned with defining the phenomena to be explained and with what constitute valid explanations of such phenomena. I propose that a foundation in the philosophy of scientific explanation and understanding can scaffold future discussions about how an integrated science of intelligence might progress. Toward this vision, I review relevant theories of scientific explanation and discuss strategies for unifying the scientific goals of neuroscience and AI.
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ISSN:0022-3077
1522-1598
DOI:10.1152/jn.00195.2021