According to DeepMind Institute, Google DeepMind researchers Alex Imas and Andrew Koh, together with co-founder Shane Legg, argued that stronger AI capabilities at the individual level would affect wages and prices only gradually. In their view, sharper shifts in market concentration, employment, and wages would emerge only after multi-agent coordination passes a "super-cooperation" threshold. The article divides AI development into four stages: minimal AGI, super-competent AI, super-cooperative AI, and ASI. It also says current AI systems show strong individual capabilities but weak coordination, which means changes in jobs and wages are likely to appear before changes in firm structure. The authors called for benchmarks to measure the organizational capacity of multi-agent systems.
ChainCatcher, citing DeepMind Institute, said Google DeepMind researchers Alex Imas and Andrew Koh, together with co-founder Shane Legg, argued that better AI at the individual level would change wages and prices slowly, not all at once.
The piece said sharp shifts in market concentration, employment, and wages would happen only once multi-agent coordination gets beyond a "super-cooperation" threshold.
The authors split AI development into four stages: minimal AGI, super-competent AI, super-cooperative AI, and ASI. And they said current AI systems look strong individually but weak at coordination, which means changes in wages and job roles are more likely to arrive before any change in corporate structure. They also said benchmarks are needed to measure the organizational capacity of multi-agent systems.
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