AI Regulation & Compliance
The EU AI Act risk tiers, sectoral rules, transparency obligations and evidence a regulator will accept.
7concepts
66flashcards
52minutes of reading
- 01 The AI Act Compliance Timeline as It Now Stands The phased application dates, the deferral of high-risk obligations agreed in 2026, and what remained on the original schedule when the rest moved.
- 02 The EU AI Act Risk Tiers How the Act classifies systems into prohibited, high-risk, transparency-obligated and minimal, why the classification turns on use rather than technology, and where the boundaries are genuinely unclear.
- 03 US State and Local AI Laws How New York City's bias-audit law, Colorado's rewritten AI Act and California's frontier-model and automated-decision rules create a moving patchwork, and why federal preemption pressure makes the effective dates less stable than the statutes suggest.
- 04 Evidence a Regulator Will Accept The difference between a policy and evidence of its operation, what an assessor actually asks for, and how to instrument a system so compliance artefacts are produced automatically rather than assembled retrospectively.
- 05 General-Purpose AI Model Obligations and the Code of Practice The two-tier regime the EU AI Act applies to general-purpose AI models, how a training-compute number triggers the systemic-risk tier, and what signing the July 2025 Code of Practice does and does not buy a provider now that enforcement has begun.
- 06 Provider and Deployer Obligations Why the same system carries different duties depending on your role, the actions that turn a deployer into a provider, and how the split shapes contracts between the two.
- 07 Sectoral Rules and Overlapping Regimes Why the AI Act is rarely the only regime applying, how data protection, sector rules and product safety interact with it, and the practical approach to satisfying several at once.