Artificial Intelligence, Income Distribution and Economic Growth

Thomas Gries and Wim Naudé

No 13606, IZA Discussion Papers from Institute of Labor Economics (IZA)

Abstract: The economic impact of Articial Intelligence (AI) is studied using a (semi) endogenous growth model with two novel features. First, the task approach from labor economics is reformulated and integrated into a growth model. Second, the standard representative household assumption is rejected, so that aggregate demand restrictions can be introduced. With these novel features it is shown that (i) AI automation can decrease the share of labor income no matter the size of the elasticity of substitution between AI and labor, and (ii) when this elasticity is high, AI will unambiguously reduce aggregate demand and slow down GDP growth, even in the face of the positive technology shock that AI entails. If the elasticity of substitution is low, then GDP, productivity and wage growth may however still slow down, because the economy will then fail to benefit from the supply-side driven capacity expansion potential that AI can deliver. The model can thus explain why advanced countries tend to experience, despite much AI hype, the simultaneous existence of rather high employment with stagnating wages, productivity, and GDP.

Keywords: technology; artificial intelligence; productivity; labor demand; income distribution; growth theory (search for similar items in EconPapers)
JEL-codes: E21 E25 J24 O33 O47 (search for similar items in EconPapers)
Pages: 72 pages
Date: 2020-08
New Economics Papers: this item is included in nep-big, nep-gro, nep-lma and nep-mac
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (11)

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Related works:
Working Paper: Artificial Intelligence, Income Distribution and Economic Growth (2020)
Working Paper: Artificial Intelligence, Income Distribution and Economic Growth (2020)
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