Hostname: page-component-848d4c4894-4rdrl Total loading time: 0 Render date: 2024-06-20T12:26:26.206Z Has data issue: false hasContentIssue false

Neural networks, AI, and the goals of modeling

Published online by Cambridge University Press:  06 December 2023

Walter Veit
Affiliation:
Department of Philosophy, University of Bristol, Bristol, UK wrwveit@gmail.com https://walterveit.com/
Heather Browning
Affiliation:
Department of Philosophy, University of Southampton, Southampton, UK DrHeatherBrowning@gmail.com https://www.heatherbrowning.net/

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.

Type
Open Peer Commentary
Copyright
Copyright © The Author(s), 2023. Published by Cambridge University Press

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Psillos, S. (2005). Scientific realism: How science tracks truth. Routledge.CrossRefGoogle Scholar
Rescher, N. (1958). On prediction and explanation. The British Journal for the Philosophy of Science, 8(32), 281290.CrossRefGoogle Scholar
Ross, L. N. (2020). Multiple realizability from a causal perspective. Philosophy of Science, 87(4), 640662.CrossRefGoogle Scholar
Saxe, A., Nelli, S., & Summerfield, C. (2021). If deep learning is the answer, what is the question? Nature Reviews Neuroscience, 22(1), 5567.CrossRefGoogle ScholarPubMed
Schaeffer, R., Khona, M., & Fiete, I. (2022). No free lunch from deep learning in neuroscience: A case study through models of the entorhinal-hippocampal circuit. bioRxiv, 2022-08.Google Scholar
Schickore, J. (2019). The structure and function of experimental control in the life sciences. Philosophy of Science, 86(2), 203218.CrossRefGoogle Scholar
Sober, E. (1999). The multiple realizability argument against reductionism. Philosophy of Science, 66(4), 542564.CrossRefGoogle Scholar
Veit, W. (2019). Model pluralism. Philosophy of the Social Sciences, 50(2), 91114.CrossRefGoogle Scholar