Scenarios for the Transition to Artificial General Intelligence (AGI)

A recent working paper by Anton Korinek and Donghyun Su explores different scenarios for the transition to Artificial General Intelligence (AGI). The article analyzes the impact of technological progress on production and wages, considering the possibility of full automation and its implications for the labor market. The authors discuss the race between automation and capital accumulation, the effects on wage dynamics, and the potential for wide-ranging productivity gains. The research provides valuable insight into the economic implications of AGI development.

The transition to artificial general intelligence (AGI) has been a topic of great interest and speculation in recent years. Many researchers and industry leaders believe that AGI, which refers to AI systems that can perform all human-level tasks, may soon become a reality. In a working paper titled “Scenarios for AGI Transition,” economists Anton Korinek and Donghyun Suh delve into the economic implications of AGI development.

The paper begins by examining the relationship between technological progress, production and wages. The authors propose a framework that decomposes human work into atomistic tasks of varying levels of complexity. They argue that progress in technology enable the automation of increasingly complex tasks, potentially leading to the automation of all tasks with the advent of AGI.

One crucial aspect analyzed in the article is the race between automation and capital accumulation. If automation progresses slowly enough, there will always be enough work for humans and wages may continue to rise. However, if the complexity of the tasks that humans can perform is limited and full automation is achieved, wages may collapse. The authors also consider the possibility of wage declines before full automation occurs if large-scale automation outpaces capital accumulation, leading to an oversupply of labor.

The research suggests that automating productivity growth can lead to wide-ranging gains in returns to all factors of production. On the other hand, bottlenecks to growth caused by scarce, nonreproducible factors can exacerbate wage declines. The authors emphasize the importance of understanding the distribution of tasks in the complexity space and its impact on economic performance.

While the paper provides valuable insight into the potential implications of AGI development, it also acknowledges the uncertainties surrounding the transition. The authors emphasize that the distribution of tasks in the complexity space plays a crucial role in determining economic outcomes. They consider both unbounded and bounded distributions, the latter reflecting the finite computational capabilities of the human brain.

Overall, Korinek and Suh’s research contributes to the ongoing discussion about the future of work in the age of AI and automation. Analyzing different scenarios for the transition to AGI, the paper sheds light on the possible effects on output, wages and human welfare. It serves as a valuable resource for policymakers, researchers, and industry leaders seeking to understand the economic implications of AGI development.

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