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5 - Artificial Intelligence, Growth, and Inequality

Published online by Cambridge University Press:  23 May 2024

Wim Naudé
Affiliation:
Rheinisch-Westfälische Technische Hochschule, Aachen, Germany
Thomas Gries
Affiliation:
Universität Paderborn, Germany
Nicola Dimitri
Affiliation:
Università degli Studi, Siena
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Summary

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.

Type
Chapter
Information
Artificial Intelligence
Economic Perspectives and Models
, pp. 107 - 172
Publisher: Cambridge University Press
Print publication year: 2024

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