Neural networks, AI, and the goals of modeling

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Behavioral and Brain Sciences 46:e411 (2023)
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Abstract

Deep neural networks (DNNs) have found many useful applications in recent years. Of particular interest have been those instances where their successes imitate human cognition and many consider artificial intelligences to offer a lens for understanding human intelligence. Here, we criticize the underlying conflation between the predictive and explanatory power of DNNs by examining the goals of modeling.

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10.1017/s0140525x23001681

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Author Profiles

Walter Veit
University of Reading
Heather Browning
University of Southampton

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References found in this work

Model Pluralism.Walter Veit - 2019 - Philosophy of the Social Sciences 50 (2):91-114.
The multiple realizability argument against reductionism.Elliott Sober - 1999 - Philosophy of Science 66 (4):542-564.
Multiple Realizability from a Causal Perspective.Lauren N. Ross - 2020 - Philosophy of Science 87 (4):640-662.
On prediction and explanation.Nicholas Rescher - 1957 - British Journal for the Philosophy of Science 8 (29):281.

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