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Scenarios for the Transition to AGI

arXiv 2403.12107 ↗First posted 17 Mar 2024econ.GN cs.AI q-fin.ECcited by 13

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Abstract (arXiv)

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.

Key facts. Cited by 13 papers in the map (data through 14 Oct 2026). Builds on 3 of its 28 references that are in the map. First posted on arXiv 17 Mar 2024.

Builds on

3 of 28 references.

References · 3

  1. 2022Do As I Can, Not As I Say: Grounding Language in Robotic Affordancescited by 2,348
  2. 2023GPTs are GPTs: An Early Look at the Labor Market Impact Potential of Large Language Modelscited by 176
  3. 2022Compute Trends Across Three Eras of Machine Learningcited by 163

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 6; 2026: 7.

13 papers.

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