Large language models can replicate cross-cultural differences in personality
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arXiv
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| Main Authors: | , , |
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| Format: | Preprint |
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2023
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| _version_ | 1866912540103016448 |
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| author | Niszczota, Paweł Janczak, Mateusz Misiak, Michał |
| author_facet | Niszczota, Paweł Janczak, Mateusz Misiak, Michał |
| contents | We use a large-scale experiment (N=8000) to determine whether GPT-4 can replicate cross-cultural differences in the Big Five, measured using the Ten-Item Personality Inventory. We used the US and South Korea as the cultural pair, given that prior research suggests substantial personality differences between people from these two countries. We manipulated the target of the simulation (US vs. Korean), the language of the inventory (English vs. Korean), and the language model (GPT-4 vs. GPT-3.5). Our results show that GPT-4 replicated the cross-cultural differences for each factor. However, mean ratings had an upward bias and exhibited lower variation than in the human samples, as well as lower structural validity. We provide preliminary evidence that LLMs can aid cross-cultural researchers and practitioners. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2310_10679 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | Large language models can replicate cross-cultural differences in personality Niszczota, Paweł Janczak, Mateusz Misiak, Michał Computation and Language Artificial Intelligence Computers and Society I.2.7; K.4.2; J.4 We use a large-scale experiment (N=8000) to determine whether GPT-4 can replicate cross-cultural differences in the Big Five, measured using the Ten-Item Personality Inventory. We used the US and South Korea as the cultural pair, given that prior research suggests substantial personality differences between people from these two countries. We manipulated the target of the simulation (US vs. Korean), the language of the inventory (English vs. Korean), and the language model (GPT-4 vs. GPT-3.5). Our results show that GPT-4 replicated the cross-cultural differences for each factor. However, mean ratings had an upward bias and exhibited lower variation than in the human samples, as well as lower structural validity. We provide preliminary evidence that LLMs can aid cross-cultural researchers and practitioners. |
| title | Large language models can replicate cross-cultural differences in personality |
| topic | Computation and Language Artificial Intelligence Computers and Society I.2.7; K.4.2; J.4 |
| url | https://arxiv.org/abs/2310.10679 |