Economic growth under transformative AI
Philip Trammell (Global Priorities Institute, Oxford University) and Anton Korinek (University of Virginia, NBER and CEPR)
GPI Working Paper No. 8-2020, published in the National Bureau of Economic Research Working Paper series and forthcoming in the Annual Review of Economics
Industrialized countries have long seen relatively stable growth in output per capita and a stable labor share. AI may be transformative, in the sense that it may break one or both of these stylized facts. This review outlines the ways this may happen by placing several strands of the literature on AI and growth within a common framework. We first evaluate models in which AI increases output production, for example via increases in capital's substitutability for labor or task automation, capturing the notion that AI will let capital “self-replicate”. This typically speeds up growth and lowers the labor share. We then consider models in which AI increases knowledge production, capturing the notion that AI will let capital “self-improve”, speeding growth further. Taken as a whole, the literature suggests that sufficiently advanced AI is likely to deliver both effects.
Other working papers
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Consider a decision between: 1) a certainty of a moderately good outcome, such as one additional life saved; 2) a lottery which probably gives a worse outcome, but has a tiny probability of a far better outcome (perhaps trillions of blissful lives created). Which is morally better? Expected value theory (with a plausible axiology) judges (2) as better, no matter how tiny its probability of success. But this seems fanatical. So we may be tempted to abandon expected value theory…
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