Douglas Guilbeault

Arianna Pera, Mauro Martino, Nima Dehmamy et al.

Claims about the universality of human concepts have been predominantly assessed through linguistic similarity across languages and cultures. However, words are effective as communication devices because they compress rich experiential variation into shared conventions, potentially obscuring hidden individual and cultural differences in how concepts are mentally represented. Here, we analyse 2.6 billion human-made sketches of common concepts from 236 countries and territories to examine conceptual structure through people's visual imagination. Consistent with recent work on image-based cognition, we find that single concepts unfold into multiple distinct visual exemplars, revealing latent information about similarities and differences in conceptual structure across cultures. This variation is strongest for concepts involving haptic interaction, suggesting that visual imagery reflects variation in embodied experience as much as conventional definitions. Comparing embedding models of sketches with word embedding models across languages, we find that their geometries diverge, with visual representations preserving rich semantic and cultural structure that language models compress. Cross-cultural similarities derived from sketches align 45% more closely with established cultural distances than do text-based measures. Together, these results suggest that patterns of human conceptual universality may depend critically on the modality through which concepts are measured, with large-scale sketching providing a direct, high-resolution probe of conceptual diversity across embodied and cultural dimensions of thought.

Xinrui Chloe Zhao, Douglas Guilbeault, Amir Goldberg

Recent studies argue that LLMs can predict human stereotypical judgments. Yet whether LLMs emulate the cognitive processes underlying human stereotypes, or merely retrieve learned associations to solve prediction tasks, remains unclear. Prior work examines LLMs' stereotypes in either (i) controlled judgment tasks like multiple choice surveys, or (ii) contexts constrained by conventionalized and predictable group biases. Here, we compare the structure of the stereotypes that humans and LLMs exhibit in the interpretation of free-form stimuli, namely abstract art and Rorschach blots, which lack pre-established cultural meanings. We recruit participants across five social domains (gender, partisanship, personality, urbanicity, and lifestyle) and elicit both first-order (direct personal interpretations) and second-order responses (predictions about how members of social groups will interpret the stimuli); we replicate this design with two multimodal models (GPT-4o mini and Llama-3.2-11B-Vision-Instruct). Humans and LLMs differ not only in magnitude but in the qualitative nature of their stereotypes. Human first-order responses display heterogeneity with minimal group structure. When predicting group responses, humans engage in "stereotype exaggeration" by moderately amplifying first-order tendencies while preserving diversity. By contrast, LLMs exhibit homogeneous first-order responses, and yet generate stark second-order stereotypes that neither amplify existing first-order tendencies nor reflect actual human group differences, a process we term "stereotype hallucination." LLMs continued to hallucinate stereotypes even when fine-tuned on the response data of actual participants. These findings suggest significant limitations in the use of LLMs to model and predict human behavior in novel contexts involving diverse interpretations.