We Wont be Missed: Work and Growth in the Era of AGI

This chapter explores theoretically the long-run implications of Artificial General Intelligence (AGI) for economic growth and labor markets. AGI makes it feasible to perform all economically valuable work using compute. I distinguish between bottleneck and accessory work—tasks essential vs. non-essential for unhindered growth. As computational resources expand: (i) the economy automates all bottleneck work, (ii) some accessory work may be left untouched by AI and assigned exclusively to humans, (iii) output becomes linear in compute and labor and its growth is driven by the expansion of compute, (iv) wages converge to the opportunity cost of computational resources required to reproduce human work, and (v) the share of labor income in GDP converges to zero.

This chapter studies the long-run behavior of wages and growth in an economy where Artificial General Intelligence (AGI) is developed and computational resources increase over time. AGI allows the economy to complete all relevant work using computing systems. These systems consume computational resources but do not require human input, guidance, or effort to accomplish work. The key economic problem is how to allocate finite (but growing) computational resources and human labor to accomplishing the work needed to produce output. The chapter introduces a key distinction between bottleneck and accessory work.

• Bottleneck work comprises tasks essential for economic growth. Output cannot expand indefinitely unless inputs in bottleneck tasks also expand or become infinitely valuable.

• Accessory work is non-essential to growth. Output can expand indefinitely even if these tasks are discarded or limited in input.

My main theoretical result shows that all bottleneck work is eventually automated while some accessory work may be left untouched by AI. Once this occurs, output shifts from being multiplicative in compute and human effort to being additive, and the long-run growth rate of the economy is pinned by the growth rate of compute.

Despite AI completing all bottleneck tasks without human input, people still hold jobs. They can contribute by fulfilling bottleneck work. Human labor remains valuable because it saves scarce computational resources. Alternatively, workers may perform accessory work, where it is impractical to use compute since we already have too many workers. In the first case, wages are pinned by the value of computational resources saved. In the later, wages are bounded above by the value of computational resources it would cost to automate accessory work.

In sum, the advent of AGI changes the way labor is valued. Before AGI, wages reflected the importance of bottleneck work and the scarcity of labor with the requisite skill for this work. With AGI, wages reflect the computational cost of replicating the work produced by all human labor. Despite the fact that human labor retains some value, its contribution to GDP and growth becomes vanishingly small, with the share of labor in GDP converging to zero, and all income being eventually accruing to compute.

I then expand the analysis to an economy where AGI can be used to complete scientific work, accelerating the pace of technological progress. Without AGI for science, technological progress is constrained by population growth (as in the semi-endogenous growth models of Jones, 1995; Kortum, 1997; Segerstrom, 1998). With AGI, all scientific bottleneck work is automated and the rate of technological progress is determined by the growth rate of compute. This may generate sustained exponential growth despite shrinking population, but does not create a singularity or infinite growth explosion.