The traditional government model of setting a regulation and waiting years to assess it is obsolete for AI. A new approach is needed: a dynamic board of government, industry, and academic leaders collaborating to make and update rules in real-time.

Major government action on AI is unlikely to be driven by political shifts like midterm elections. Historical precedent suggests a high-salience incident will be the necessary trigger for significant, bipartisan regulatory intervention, regardless of which party controls the government.

Historically, effective regulation for technologies like cars and aviation came decades after their invention, once failure patterns were understood. Regulating AI before we know how it will fail is likely to be useless and stifle innovation, as we can't create rules for unknown problems.

Major AI companies are not solely seeking to stifle competition with regulation. They are also signaling an inability to self-regulate amidst intense competitive pressure, effectively asking external bodies to impose a mandatory safety floor that applies to everyone.

The debate over AI regulation often gets bogged down in technical complexity. A simpler, powerful argument is that nearly every other impactful technology—from cars and planes to food and medicine—requires pre-market safety validation. AI, with its greater potential risks, should be no different.

Major technological shifts like electricity, cars, and nuclear power all created significant new risks. In each case, the market developed standards and insurance to build confidence and drive adoption long before government regulation was established. AIUC is applying this historical blueprint to AI.

The Y2K crisis was averted not by top-down legislation but because professionals worried, took responsibility, and implemented solutions like creating secure bunkers. This direct causal relationship—proactive, industry-led action preventing catastrophe—serves as a model for how the AI industry should address its own systemic risks without waiting for government mandates.

The argument that the U.S. must avoid AI regulation to compete with China is fragile. Once a significant negative event occurs—like widespread job loss or a major accident—domestic concerns will overwhelm geopolitical competition, making immediate regulation the primary political focus.

An anonymous CEO of a leading AI company told Stuart Russell that a massive disaster is the *best* possible outcome. They believe it is the only event shocking enough to force governments to finally implement meaningful safety regulations, which they currently refuse to do despite private warnings.