Scenarios for the Transition to AGI

By Anton Korinek and Donghyun Suh, in a new NBER working paper:

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 automation proceeds sufficiently slowly, 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.

The best paper on these topics so far?  And here is a recent Noah Smith piece on employment as AI proceeds.  And a recent Belle Lin WSJ piece, via Frank Gullo, “Tech Job Seekers Without AI Skills Face a New Reality: Lower Salaries and Fewer Roles.”  And here is a proposal for free journalism school for everybody (NYT, okie-dokie!).