Where synthetic fidelity comes from, and what to ask any provider
Synthetic respondents arrive in nearly every research platform now, usually as a toggle you can switch on. The output looks the same either way: smooth cross-tabs, tight intervals, and nothing on the screen to tell you whether the model tracked reality or missed it entirely.
This whitepaper works from one idea. Fidelity is inherited, so a model reproduces a real population only as faithfully as the real data underneath it allows. Judge that foundation and you can judge the layer built on top of it.
Where AI genuinely helps: knowledge management, transcript synthesis, draft scaffolding, pattern surfacing
How an answer can come back precise and still miss the truth, and why provenance is what separates two estimates that look identical in a deck
The four stages where quality gets built in before, during, and after fieldwork, each with a question to ask any supplier
