Policy paper: Eric Schmidt, Scale AI CEO Alexandr Wang, and Center for AI Safety Director Dan Hendrycks argue the US shouldn't do a “Manhattan Project” for AGI
In a policy paper published Wednesday, former Google CEO Eric Schmidt, Scale AI CEO Alexandr Wang …
Context & Ripple Effects
The paper adds a constraint to a policy argument in which Eric Schmidt had recently urged Western investment in open-source models while also calling for cross-border AI-safety cooperation at the AI Action Summit. It distinguishes support for U.S. AI competitiveness from endorsement of a single, centrally organized AGI program.
It also lands against a longer-running scrutiny of Schmidt's overlap between AI investing and national-security policy work, including conflict-of-interest concerns about his AI investments. That makes the paper's institutional prescription—not only its safety framing—material to the debate.
First-order effects
- Schmidt, Wang, and Hendrycks put a prominent joint position into the U.S. AGI-policy debate: they oppose a Manhattan Project-style development effort.
- The paper immediately gives policymakers and AI organizations a clear distinction to test—supporting AI capacity or safety work does not necessarily mean supporting centralized AGI development.
Second-order effects
- Advocates of a government-led AGI effort will need to answer the paper's critique of the program's structure, rather than treating AI competitiveness as sufficient justification for that model.
- Companies and safety groups engaging government on frontier AI may face sharper questions about which responsibilities belong with the state and which should remain outside a single national program.
Third-order effects
- If this divide persists, AI industrial policy may be shaped less by a simple race-versus-safety framing and more by competing views of how directly the state should organize frontier-model development.
- The episode points toward a more contested model of state-mediated AI: prominent industry and safety figures can favor strategic capacity while resisting formal centralization of AGI work.
The trend: AI policy is increasingly separating the goal of national AI capability from the question of whether government should directly coordinate frontier development.