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Despite the risk of a fragmented legal landscape, the slow pace of federal AI legislation makes state-level action essential. States are acting as "laboratories of democracy," pioneering regulatory approaches that can later inform a much-needed national framework.

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In China, mayors and governors are promoted based on their ability to meet national priorities. As AI safety becomes a central government goal, these local leaders are now incentivized to create experimental zones and novel regulatory approaches, driving bottom-up policy innovation that can later be adopted nationally.

The absence of a comprehensive federal AI law has spurred states like California and Colorado to experiment with unique regulatory approaches. This state-level action, while creating a "patchwork," allows for testing different governance models to see what works best before potential federal adoption.

By aligning its RAISE Act with California's SB 53, New York is helping create a powerful, bi-coastal regulatory consensus. This convergence counters the industry's argument against a "chaotic patchwork" of state laws and establishes a baseline for AI transparency that other states may adopt, effectively setting a national standard in the absence of federal action.

A16z proposes a federalist approach to AI governance. The federal government, under the Commerce Clause, should regulate AI *development* to create a single national market. States should focus on regulating the harmful *use* of AI, which aligns with their traditional role in areas like criminal law.

Contrary to their current stance, major AI labs will pivot to support national-level regulation. The motivation is strategic: a single, predictable federal framework is preferable to navigating an increasingly complex and contradictory patchwork of state-by-state AI laws, which stifles innovation and increases compliance costs.

While seemingly promoting local control, a fragmented state-level approach to AI regulation creates significant compliance friction. This environment disproportionately harms early-stage companies, as only large incumbents can afford to navigate 50 different legal frameworks, stifling innovation.

The idea of individual states creating their own AI regulations is fundamentally flawed. AI operates across state lines, making it a clear case of interstate commerce that demands a unified federal approach. A 50-state regulatory framework would create chaos and hinder the country's ability to compete globally in AI development.

California's push for aggressive AI regulation is not primarily driven by voter demand. Instead, Sacramento lawmakers see themselves as a de facto national regulator, filling a perceived federal vacuum. They are actively coordinating with the European Union, aiming to set standards for the entire U.S. and control a nascent multi-trillion-dollar industry.

Facing a federal vacuum on AI policy, major players like OpenAI and Google are surprisingly endorsing state-level regulations in California and New York. This counter-intuitive move serves two purposes: it creates a manageable, de facto national standard they can influence, and it pressures a gridlocked Congress to finally act to avoid a messy patchwork of state laws.

Instead of a single, premature federal AI mandate, a patchwork of state-level regulations creates a portfolio of experiments. This allows policymakers to learn what works in different populations (e.g., rural vs. urban) before establishing a more informed national framework.