Clarifying status of DNNs as models of human vision

Abstract

On several key issues we agree with the commentators. Perhaps most importantly, everyone seems to agree that psychology has an important role to play in building better models of human vision, and (most) everyone agrees (including us) that deep neural networks (DNNs) will play an important role in modelling human vision going forward. But there are also disagreements about what models are for, how DNN-human correspondences should be evaluated, the value of alternative modelling approaches, and impact of marketing hype in the literature. In our view, these latter issues are contributing to many unjustified claims regarding DNN-human correspondences in vision and other domains of cognition. We explore all these issues in this response.

Publication DOI: https://doi.org/10.1017/S0140525X23002777
Divisions: College of Health & Life Sciences > School of Psychology
College of Health & Life Sciences
Additional Information: © 2023 The Authors. CC BY 4.0
Uncontrolled Keywords: Neural Networks, Computer,Humans,Cognition
Publication ISSN: 1469-1825
Last Modified: 16 Dec 2024 09:01
Date Deposited: 07 Feb 2024 14:31
Full Text Link:
Related URLs: https://www.cam ... 505B6EB48A8FC95 (Publisher URL)
http://www.scop ... tnerID=8YFLogxK (Scopus URL)
PURE Output Type: Letter
Published Date: 2023-12-06
Accepted Date: 2023-12-01
Authors: Bowers, Jeffrey S
Malhotra, Gaurav
Dujmović, Marin
Montero, Milton L
Tsvetkov, Christian
Biscione, Valerio
Puebla, Guillermo
Adolfi, Federico
Hummel, John E
Heaton, Rachel F
Evans, Benjamin D
Mitchell, Jeffrey
Blything, Ryan (ORCID Profile 0000-0003-2285-7219)

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