tech_data · EU AI Act Article 10 · FTC AI guidance · FTC Act §5
Model Collapse / Verified Data
Model collapse from synthetic data — prove training data provenance or copyright defeat
—EU AI Act Art 10 training data governance
Regulatory exposure — commonly overlooked:
Model trained on AI-generated data — vendor owns collapse risk, deployer owns downstream harm. · Federal agencies disagree on AI approach — but examiners agree internal logs are insufficient.
TAM / Exposure
Foundation model training · copyright litigation $10B+ exposure
Insurance lines
IP defense · E&O · D&O
Exhibit authority
US Federal Exhibit — Training Data Provenance + Collapse Detection Pack
Global leaders
OpenAI · Anthropic · EU Commission · NYT v OpenAI · Authors Guild · NAIC · FTC · EEOC
NYT litigation
Prove what data model saw — receipt at training decision point.
Art 10 EU
Training data governance mandatory — provenance receipt satisfies documentation.
Quality degradation
Collapse detection requires baseline receipt — compare model version decisions.
[United States (Federal)] Agency pincer
FTC, CFPB, EEOC, and DOJ all active on AI — one receipt chain satisfies cross-agency discovery.
[United States (Federal)] Federal preemption fight
State laws filling void — multistate operators need jurisdiction-tagged receipts.
[Text / Chat] Modality hook
Baseline — all frameworks apply to text decisions.
7 mandate layers (live)
Regulatory ClockCountdown to operative regulatory deadline — NAIC adoption, GSE mandate, EU transposition.Open →
Domain ClassifierIndustry-specific SAFE/CRISIS/VIOLATION with regulatory framework mapping.Open →
Exhibit / Filing PackRegulator-ready external validation — NAIC Exhibit D, Fannie QC, EU FRIA, FDA Part 11.Open →
Mandate RegistryEnroll deployers/insureds under vertical-specific governance mandate.Open →