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Deep Neural Networks as Scientific Models.

Authors :
Cichy RM
Kaiser D
Source :
Trends in cognitive sciences [Trends Cogn Sci] 2019 Apr; Vol. 23 (4), pp. 305-317. Date of Electronic Publication: 2019 Feb 19.
Publication Year :
2019

Abstract

Artificial deep neural networks (DNNs) initially inspired by the brain enable computers to solve cognitive tasks at which humans excel. In the absence of explanations for such cognitive phenomena, in turn cognitive scientists have started using DNNs as models to investigate biological cognition and its neural basis, creating heated debate. Here, we reflect on the case from the perspective of philosophy of science. After putting DNNs as scientific models into context, we discuss how DNNs can fruitfully contribute to cognitive science. We claim that beyond their power to provide predictions and explanations of cognitive phenomena, DNNs have the potential to contribute to an often overlooked but ubiquitous and fundamental use of scientific models: exploration.<br /> (Copyright © 2019 Elsevier Ltd. All rights reserved.)

Details

Language :
English
ISSN :
1879-307X
Volume :
23
Issue :
4
Database :
MEDLINE
Journal :
Trends in cognitive sciences
Publication Type :
Academic Journal
Accession number :
30795896
Full Text :
https://doi.org/10.1016/j.tics.2019.01.009