{"ID":2840855,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2511.13979","arxiv_id":"2511.13979","title":"Personality Pairing Improves Human-AI Collaboration","abstract":"Here we examine how AI agent \"personalities\" interact with human personalities to shape human-AI collaboration and performance. In a large-scale, preregistered randomized experiment, we paired 1,258 participants with AI agents prompted to exhibit varying levels of the Big Five personality traits. These human-AI teams produced 7,266 display ads for a real think tank, which we evaluated using 1,995 independent human raters and a field experiment on X that generated nearly 5 million impressions. We found that human and AI personalities individually shaped ad quality and teamwork. When examined together, human-AI personality pairings directly effected ad quality outcomes. For example, extraverted humans paired with conscientious AI produced the lowest-quality ads, followed by conscientious humans paired with agreeable AI and neurotic humans paired with conscientious AI. In the field experiment, ad quality significantly influenced ad performance, measured by click-through rates and cost-per-click, and neurotic humans paired with neurotic AI achieved higher click-through rates, even after controlling for ad quality. Together, these results provide the first large-scale causal experimental evidence that specific personality pairings can improve human-AI collaboration and motivate future research on the implications of AI personalization for performance and teamwork dynamics in human-AI teams.","short_abstract":"Here we examine how AI agent \"personalities\" interact with human personalities to shape human-AI collaboration and performance. In a large-scale, preregistered randomized experiment, we paired 1,258 participants with AI agents prompted to exhibit varying levels of the Big Five personality traits. These human-AI teams p...","url_abs":"https://arxiv.org/abs/2511.13979","url_pdf":"https://arxiv.org/pdf/2511.13979v2","authors":"[\"Harang Ju\",\"Sinan Aral\"]","published":"2025-11-17T23:15:50Z","proceeding":"cs.HC","tasks":"[\"cs.HC\"]","methods":"[]","has_code":false}