OpenAI Proposes 'Reverse Federalism' for AI Safety, Pushing State-Federal Collaborative Governance

OpenAI today released a new AI governance policy paper outlining a 'reverse federalism' approach to AI safety regulation. The framework suggests that state-level AI legislation efforts can organically build up to form a coherent national governance system, rather than waiting for top-down federal mandates.

Unlike the traditional federal-led model, OpenAI advocates for states to experiment with AI regulation first, then consolidate those experiences into a unified national framework. This bottom-up path contrasts sharply with the conventional top-down approach where the federal government sets uniform standards for states to implement.

OpenAI emphasizes that this governance model can balance AI safety with democratic values. By involving more local stakeholders in rule-making, the approach aims to avoid concentration of AI governance power among a few elites or corporations, while allowing regions to calibrate regulatory intensity to local conditions.

The timing of this policy proposal is significant. Federal AI regulation has progressed slowly in the US Congress, while individual states have begun enacting their own AI safety laws. California and other states have introduced multiple AI safety bills, creating de facto regulatory momentum. OpenAI's proposal appears to be a policy response to this emerging reality.

As the world's leading AI company, OpenAI's policy stance carries substantial industry influence. The company previously called for a global AI regulatory body modeled on the IAEA. This latest state-federal framework focuses more specifically on US domestic governance pathways.

Critics may argue that fragmented state-level regulation creates compliance burdens that favor large companies with resources to navigate multiple regulatory regimes simultaneously, potentially excluding smaller players and open-source projects. OpenAI's paper counters that state-level experimentation allows testing different approaches, ultimately producing more scientifically grounded governance.

Regardless of perspective, this policy proposal signals that AI companies are evolving from regulated entities into active participants in regulatory framework design. The key question is whether this framework gains traction with lawmakers and how it might influence the multiple AI bills currently under Congressional consideration.