Donghyun Suh

This paper develops a model of hierarchical production organizations to study the effects of technological change on income distribution, with a focus on top labor incomes. The model features workers with different skill levels who interact with machines. The complexity of automated tasks determines whether machines augment or substitute for workers. Two main findings emerge: First, if machines only perform sufficiently simple tasks, they augment low-skilled workers. Consequently, technological advances decrease income concentration at the top by raising low-skill wages more than high-skill wages. Second, if the task complexity of machines surpasses a certain threshold, then machines substitute for low-skilled workers but augment high-skilled workers. As a result, income concentration rises as gains are greatest for the most skilled workers, amplifying the "superstar effect." Lastly, I examine the implications of future AI systems automating managerial functions performed by high-skilled workers. I find that AI managers can reduce income inequality by augmenting low-skilled workers and substituting for high-skilled workers, with the largest gains for the least skilled workers. Overall, the model shows how the complexity of automated tasks determines the effects of technology on income distribution. The results provide insights into diverging trends in top income shares before and after the 1980s, as well as implications of AI for future income inequality.

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.