Human and Artificial Intelligence Processing Animal Metaphors in English and Chinese

This study compares human and ChatGPT 4o processing of ox (“niu”, 牛) and dragon (“long”, 龍) metaphors in English and Chinese, exploring how cultural values and AI architecture influence interpretation. We used 30 corpus-derived sentences from Academia Sinica Balanced Corpus of Modern Chinese (ASBC) (Chinese Knowledge and Information Processing, 2010) and Corpus of Contemporary American English (COCA) (Davies, 2008), rated by 15 Chinese speakers, 15 English speakers, and ChatGPT 4o on a 5-point Likert scale. A key methodological step involved post-hoc categorization of sentences into daily, literary, and formal context types, which revealed significant quantitative divergence. Findings show statistically significant differences. Human participants demonstrated more context-sensitive and stable understanding; ChatGPT 4o showed high volatility (CV) with complex idioms like “having a cow.” For dragon metaphors, ChatGPT 4o systematically amplified cultural contrasts, leading to a strong cultural polarization effect, particularly in formal contexts. This suggests that while AI is a powerful linguistic tool, its statistical modeling architecture results in a statistically biased representation of cultural knowledge, lacking the nuance and stability of human cognition.