AI policy is the deliberate set of governmental and institutional decisions about whether, when, where, and how AI is developed, deployed, constrained, taxed, subsidized, and integrated into existing law. It is distinct in scope from AI governance, which is the taxonomy of governance modes: AI policy is what specific actors do, while AI governance describes how their actions are structured. Coverage of specific instruments and jurisdictions is split across legislation/, government/, entities/ (regulators), analysis/, and many concepts/ pages, indexed below.
Organization by instrument type
Organization by jurisdictional layer
Organization by substantive issue
Substantive issues are indexed through the concepts/ folder. The umbrella concept page AI Governance (umbrella) enumerates 11 governance modes.
Institutional-design debate: "fail gracefully"
In a May 12, 2026 essay in Asterisk Magazine (the "Dagger" column), the author argues that AI policy must "fail gracefully" — that it should be designed to survive an unaligned executive branch rather than depending on one. The essay cites the Trump administration's reported retaliation against Anthropic over autonomous-weapons and surveillance guardrails as evidence that executive-dependent AI governance is, in the author's terms, brittle, and proposes three structural design principles:
- Statutory whistleblower protections with a 180-day federal-court kick-out, so that courts, not the executive, decide whether a whistleblower retaliation claim moves forward, foreclosing pocket-veto-by-delay.
- Revival of the Office of Technology Assessment (OTA), restoring the legislative-branch technical-assessment capacity Congress eliminated in 1995, so that policymaking does not depend solely on executive-branch evaluations.
- Federally funded technical assistance for state attorneys general, anchored at the FTC's Office of Technology, to distribute enforcement capacity across multiple jurisdictions so that an executive-branch retreat does not collapse all enforcement.
(Source: asteriskmag.substack.com)
The essay advances an institutional-design counter-position to the procurement-driven and pre-release-vetting frames the author describes as dominant in US AI policy. It characterizes both as brittle relative to political risk and argues for structural redundancy as the binding governance design principle.
Relationships
- depends-on: AI Governance (umbrella) (the taxonomy), all specific governance-mode concept pages.
- related: US AI Regulatory Approaches Compared, EU vs. US AI Regulation: A Deep Comparison, US-China AI Competition: Different Races, Different Metrics.
Sources
Umbrella page; sources live on the linked pages. Created 2026-05-11 during the v4.0 backlog-close pass.