Zoning
The prior conditions that determine what can be built where — not regulations on what buildings do, but architectural constraints on what buildings can be.
Building permit issuance rates, setback and height variance requests, environmental impact statement findings, and land use litigation outcomes — all of which measure what individual structures are permitted to do, not whether the prior architectural constraints on AI systems have been set in the public interest.
The degree to which pre-commitment constraints on AI system architecture — computational resource ceilings, training data provenance requirements, capability thresholds triggering mandatory review before deployment, and interoperability mandates as a condition of operating at scale — have been established by accountable public bodies before systems are built.
Direct NIST, in coordination with sector-specific regulators, to establish a digital zoning framework: a tiered capability-threshold map specifying which AI system architectures require pre-deployment review, what substrate conditions are mandatory by tier, and which architectural combinations are prohibited absent a demonstrated safety case.
Municipalities and state governments seeking to apply local governance norms to AI systems operating in their jurisdictions; smaller AI developers who benefit from clear pre-commitment rules over incumbents' ability to set de facto standards post-deployment; workers in regulated industries subject to AI decision systems.
Frontier AI developers whose competitive advantage depends on architectural decisions made in advance of any regulatory constraint, and who would face mandatory pre-deployment review at capability thresholds they currently self-certify; hyperscale cloud providers whose infrastructure-layer choices would become subject to zoning-equivalent review.
Direct NIST to publish a capability-tiered AI architectural constraint framework — specifying mandatory substrate conditions by deployment tier as a condition of federal procurement eligibility — updated on a two-year notice-and-comment cycle.
NIST is developing sector-specific profiles of the AI RMF that function as voluntary pre-commitment constraint frameworks. Public workshops and comment periods are announced at nist.gov/artificial-intelligence.
Over 60 U.S. municipalities have adopted or are developing AI procurement ordinances that function as local zoning rules for government AI use. Contact your city council's technology or public safety committee to advocate for pre-deployment review requirements.
The European AI Office is finalizing the classification criteria that determine which AI systems fall under the Act's most stringent pre-deployment requirements — the functional equivalent of zoning designation. Non-EU stakeholders may comment at digital-strategy.ec.europa.eu.
California, Colorado, and Texas have active legislative proceedings on pre-deployment AI review requirements. State commerce and judiciary committees accept written testimony from residents; hearing schedules are posted on state legislature websites.