Why superintelligent AI trained alone won't cooperate with us

AI trained to maximize performance on fixed benchmarks faces a fatal flaw: deployment changes the world, breaking the assumptions the system learned from. The authors argue that building cooperative superintelligence requires abandoning the isolated optimization approach entirely—instead designing AI as a participant in multi-agent equilibrium from the start, with adaptive counterparties and institutions as core design features rather than afterthoughts.