Artificial intelligence, jobs, inequality and productivity: Does aggregate demand matter?
Thomas Gries & Wim Naudé
#2018-047
Rapid technological progress in artificial intelligence (AI) has been
predicted to lead to mass unemployment, rising inequality, and higher
productivity growth through automation. In this paper we critically
re-assess these predictions by (i) surveying the recent literature and
(ii) incorporating AI-facilitated automation into a product
variety-model, frequently used in endogenous growth theory, but modified
to allow for demand-side constraints. This is a novel approach, given
that endogenous growth models, and including most recent work on AI in
economic growth, are largely supply-driven. Our contribution is
motivated by two reasons. One is that there are still only very few
theoretical models of economic growth that incorporate AI, and moreover
an absence of growth models with AI that takes into consideration growth
constraints due to insuficient aggregate demand. A second is that the
predictions of AI causing massive job losses and faster growth in
productivity and GDP are at odds with reality so far: if anything,
unemployment in many advanced economies is historically low. However,
wage growth and productivity is stagnating and inequality is rising. Our
paper provides a theoretical explanation of this in the context of rapid
progress in AI.
JEL Classification: O47, O33, J24, E21, E25
Keywords: Technology, artificial intelligence, productivity, labour
demand, innovation, growth theory