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Cognitive Modeling Using Artificial Intelligence

Michael C. Frank & Noah D. Goodman

Annual Review of Psychology2025https://doi.org/10.1146/annurev-psych-030625-040748review
AJG 4ABDC A*
Weight
0.44

Abstract

Recent progress in artificial intelligence (AI) is exciting, but can AI models tell us about the human mind? AI models have a long history of being used as theoretical artifacts in cognitive science, but one key difference in the current generation of models is that they are stimulus computable, meaning that they can operate over stimuli that are similar to those experienced by people. This advance creates important opportunities for deepening our understanding of the human mind. We argue here that the most exciting of these is the use of AI models as cognitive models, wherein they are trained using human-scale input data and evaluated using careful experimental probes. Such cognitive models constitute a substantial advance that can inform theories of human intelligence by helping to explain and predict behavior.

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https://doi.org/https://doi.org/10.1146/annurev-psych-030625-040748

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@article{michael2025,
  title        = {{Cognitive Modeling Using Artificial Intelligence}},
  author       = {Michael C. Frank & Noah D. Goodman},
  journal      = {Annual Review of Psychology},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.1146/annurev-psych-030625-040748},
}

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Cognitive Modeling Using Artificial Intelligence

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Evidence weight

0.44

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.32 × 0.4 = 0.13
M · momentum0.57 × 0.15 = 0.09
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.