Modelling Artificial Intelligence in Economics

Thomas Gries and Wim Naudé

No 14171, IZA Discussion Papers from IZA Network @ LISER

Abstract: Economists' two main theoretical approaches to understanding Artificial Intelligence (AI) impacts have been the task-approach to labor markets and endogenous growth theory. Therefore, the recent integration of the task-approach into an endogenous growth model by Acemoglu and Restrepo (AR) is a useful advance. However, it is subject to the shortcoming that it does not explicitly model AI and its technological feasibility. The AR model focuses on tasks and skills but not on abilities, while abilities better characterize AI services' nature. This paper addresses this shortcoming by elaborating the task-approach with AI abilities for use within endogenous growth models. This more ability-sensitive specification of the task-approach allows for more nuanced and realistic impacts of progress in artificial intelligence (AI) on the economy to be captured.

Keywords: labor economics; endogenous growth theory; Artificial Intelligence; mathematical models (search for similar items in EconPapers)
JEL-codes: E21 E25 J24 O33 O47 (search for similar items in EconPapers)
Pages: 23 pages
Date: 2021-03
New Economics Papers: this item is included in nep-cmp, nep-mac and nep-ore
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Published - published in: Journal for Labour Market Research, 2022, 56, 12 (2022)

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Journal Article: Modelling artificial intelligence in economics (2022)
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