Scenarios for the Transition to AGI

Anton Korinek and Donghyun Suh

Papers from arXiv.org

Abstract: We analyze how output and wages behave under different scenarios for technological progress that may culminate in Artificial General Intelligence (AGI), defined as the ability of AI systems to perform all tasks that humans can perform. We assume that human work can be decomposed into atomistic tasks that differ in their complexity. Advances in technology make ever more complex tasks amenable to automation. The effects on wages depend on a race between automation and capital accumulation. If the distribution of task complexity exhibits a sufficiently thick infinite tail, then there is always enough work for humans, and wages may rise forever. By contrast, if the complexity of tasks that humans can perform is bounded and full automation is reached, then wages collapse. But declines may occur even before if large-scale automation outpaces capital accumulation and makes labor too abundant. Automating productivity growth may lead to broad-based gains in the returns to all factors. By contrast, bottlenecks to growth from irreproducible scarce factors may exacerbate the decline in wages.

Date: 2024-03
New Economics Papers: this item is included in nep-ain, nep-cmp, nep-gro and nep-tid
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Citations: View citations in EconPapers (2)

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Related works:
Working Paper: Scenarios for the Transition to AGI (2024)
Working Paper: Scenarios for the Transition to AGI (2024)
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Persistent link: https://EconPapers.repec.org/RePEc:arx:papers:2403.12107

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