Artificial Intelligence, Growth, and Inequality

Cambridge University Press eBooks, pp. 107–172

Abstract

In this chapter, we take the production function enriched with AI abilities from Chapter 4, and apply it to study the implications for progress in AI on growth and inequality. The crucial finding we discuss in this chapter is that understanding the nature of AI as narrow ML and its effect on key macroeconomic outcomes depends on having appropriate assumptions in growth models. In particular, we discuss the appropriateness of assuming, as most standard endogenous growth models today do, that economies are supply driven. If they are not supply driven, then demand constraints, which can arise from the diffusion of AI, may restrict growth. Through this, we show why expectations that AI will may lead to “explosive” economic growth is unlikely to materialize. We show that by considering the nature of AI as specific (and not general) AI and making appropriate assumptions that reflect the digital AI economy better, economic outcomes may be characterized by slow growth, rising inequality, and rather full employment – conditions that rather well describe economies in the West.

Authors 3

1. Wim A. Naudé Aachen

   RWTH Aachen University

   Affiliation as printed

   Rheinisch-Westfälische Technische Hochschule, Aachen, Germany

2. Thomas Gries

   Paderborn University

   Affiliation as printed

   Universität Paderborn, Germany

3. Nicola Dimitri

   University of Siena

   Affiliation as printed

   Università degli Studi, Siena