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  1. Ethan Mollick

    Ethan Mollick on DeepMind's intelligence economics research: agent coordination capability is the key to economic transformation

    Ethan Mollick commented on Google DeepMind's "The Economics of Intelligence" research, pointing out that an organization is not merely the sum of its best individuals, so a single agent becoming stronger will not change the economy on its own; only agents that can work in coordination may bring about transformation. The research, released by Alex Imas, Andrew Koh, and Shane Legg, proposes two thresholds of economic capability—capability and coordination—and argues that economic transformation depends on whether AI becomes a super-strong individual, super-strong collaboration, or both.

    Ethan Mollick commented on Google DeepMind's "The Economics of Intelligence" research, pointing out that an organization is not merely the sum of its best individuals, so a single agent becoming stronger will not change the economy on its own; only agents that can work in coordination may bring about transformation. The research, released by Alex Imas, Andrew Koh, and Shane Legg, proposes two thresholds of economic capability—capability and coordination—and argues that economic transformation de

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    #hot-signal#English text is being prepared.#Agents#Papers/Research
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    Google DeepMind paper proposes that AI's economic impact depends on agents' coordination capabilities

    On October 30, 2026, Google DeepMind published the paper "The Economics of Intelligence," proposing that the economic impact of AGI be characterized by two thresholds—competence (single-task capability) and coordination (agents' ability to collaborate)—and arguing that the economic impact depends on agents' coordination capabilities rather than on individual models becoming stronger. The paper states that AI has already shown changes in lean startups, flattened organizational structures, and a slowdown in hiring for some entry-level positions, but that large-scale unemployment has not yet occurred; most benchmarks test only a single model, whereas firms compete as teams. The paper cites a 100-person test in which groups with complementary pairings performed 32% better than randomly paired groups. On the same day, Ethan Mollick commented on the research, pointing out that an organization is not merely the sum of its best individuals, that a single agent becoming stronger will not change the economy on its own, and that only agents capable of working in coordination may bring about transformation.

    On October 30, 2026, Google DeepMind published the paper "The Economics of Intelligence," proposing that the economic impact of AGI be characterized by two thresholds—competence (single-task capability) and coordination (agents' ability to collaborate)—and arguing that the economic impact depends on agents' coordination capabilities rather than on individual models becoming stronger. The paper states that AI has already shown changes in lean startups, flattened organizational structures, and a s

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