Scenarios for the Transition to AGI
Anton Korinek, Donghyun Suh
TL;DR
This paper develops a compute-centric framework to study the economic transition to Artificial General Intelligence (AGI) by modeling human work as atomistic tasks organized in compute space and automated via an exogenous frontier $I$. It shows that the distribution of task complexity—whether bounded or unbounded—crucially determines whether wages collapse or can rise indefinitely, with a sharp region-based dynamic governed by a threshold $\hat{I}$ and a factor-price frontier $FPF$. Through dynamic analyses and four automation scenarios, the authors show that wage trajectories depend on the race between automation and capital accumulation, with outcomes ranging from wage growth to rapid collapse, and scenarios such as bout of automation potentially restoring labor scarcity later. Extensions incorporating fixed factors, automation of R&D, nostalgic jobs, and heterogeneous workers reveal richer, sometimes non-monotonic, wage paths and highlight policy levers like delaying automation or investing in capital accumulation to sustain wage growth. Overall, the study quantifies how compute-driven automation can reshape growth, wages, and distribution under different plausible futures, informing policymakers and researchers about potential risk and resilience pathways in the AGI era.
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.