When Can Digital Personas Reliably Approximate Human Survey Findings?

Excerpt

arXiv:2605.10659v2 Announce Type: replace-cross Abstract: Digital personas powered by Large Language Models (LLMs) are increasingly proposed as substitutes for human survey respondents, yet it remains unclear when they can reliably approximate human survey findings. We answer this question using the LISS panel, constructing personas from respondents' background variables and pre-2023 survey histories, then testing them against the same respondents' held-out post-cutoff answers. Across four perso