Clarifying status of DNNs as models of human vision

Jeffrey S. Bowers, Gaurav Malhotra, Marin Dujmović, Milton L. Montero, Christian Tsvetkov, Valerio Biscione, Guillermo Puebla, Federico Adolfi, John E. Hummel, Rachel F. Heaton, Benjamin D. Evans, Jeffrey Mitchell, Ryan Blything

Research output: Contribution to journalReview articlepeer-review

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.

Original languageEnglish (US)
Article numbere415
JournalBehavioral and Brain Sciences
Volume46
DOIs
StatePublished - Dec 6 2023

ASJC Scopus subject areas

  • Neuropsychology and Physiological Psychology
  • Physiology
  • Behavioral Neuroscience

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