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Published on: August 17, 2018
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Colour/shape-taste correspondences across three languages in ChatGPT
Kosuke Motoki1, Charles Spence2, Carlos Velasco3
1Department of Management, The University of Tokyo, Tokyo, Japan.
Cognition
|September 1, 2024
Summary
This study shows that large language models like ChatGPT capture crossmodal correspondences between shapes, colors, and tastes, with variations based on GPT version and language. ChatGPT-4o better replicates human associations than ChatGPT-3.5, though nuances differ.
Area of Science:
- Cognitive Science
- Artificial Intelligence
- Psychology
Background:
- Crossmodal correspondences link sensory features (e.g., sweet taste with pink color).
- These associations are consistent across cultures and languages.
- Investigating AI's ability to replicate human sensory perception is crucial.
Purpose of the Study:
- To determine if ChatGPT (versions 3.5 and 4o) captures crossmodal correspondences.
- To examine shape-taste and color-taste associations in ChatGPT across English, Japanese, and Spanish.
- To compare AI's correspondences with established human patterns.
Main Methods:
- Twelve studies using ChatGPT-3.5 and -4o with prompts in three languages.
- Assessed taste-shape associations (round/angular shapes with five basic tastes).
- Assessed color-taste associations (eleven colors with five basic tastes).
Main Results:
- ChatGPT demonstrated consistent shape-taste associations (round=sweet/umami, angular=bitter/salty/sour).
- ChatGPT-4o, unlike 3.5, replicated human color-taste patterns (e.g., sweet=pink, sour=yellow).
- AI's associations were sometimes more pronounced than subtle human nuances, with language/version variations.
Conclusions:
- ChatGPT models exhibit crossmodal correspondences, influenced by GPT version and language.
- ChatGPT-4o shows greater alignment with human sensory associations than ChatGPT-3.5.
- Findings advance understanding of AI's perceptual capabilities and human-like cognition.
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