Evaluating the ability of large language models to emulate personality.

ABSTRACT: For social sciences, recent advancements in Large Language Models (LLMs) have the potential to revolutionize the study of human behaviors by facilitating the creation of realistic agents characterized by a diverse range of individual differences. This research presents novel simulation studies assessing GPT-4's ability to role-play real-world individuals with diverse big five personality profiles. In simulation 1, emulated personality responses exhibited superior internal consistency, but also a more distinct and structured factor organization compared to the human counterparts they were based on. Furthermore, these emulated scores exhibited remarkably high convergent validity with the human self-reported personality scale scores. Simulation 2 replicated these findings but demonstrated tha

SUBMITTER: Wang Y 

PROVIDER: S-EPMC11695923 | biostudies-literature | 2025 Jan

REPOSITORIES: biostudies-literature