Modelling artificial intelligence in economics

Thomas Gries and Wim Naudé

Journal for Labour Market Research, 2022, vol. 56, issue 1, 1-13

Abstract: Abstract We provide a partial equilibrium model wherein AI provides abilities combined with human skills to provide an aggregate intermediate service good. We use the model to find that the extent of automation through AI will be greater if (a) the economy is relatively abundant in sophisticated programs and machine abilities compared to human skills; (b) the economy hosts a relatively large number of AI-providing firms and experts; and (c) the task-specific productivity of AI services is relatively high compared to the task-specific productivity of general labor and labor skills. We also illustrate that the contribution of AI to aggregate productive labor service depends not only on the amount of AI services available but on the endogenous number of automated tasks, the relative productivity of standard and IT-related labor, and the substitutability of tasks. These determinants also affect the income distribution between the two kinds of labor. We derive several empirical implications and identify possible future extensions.

Keywords: Artificial intelligence; Automation; Labor economics; Mathematical models (search for similar items in EconPapers)
JEL-codes: E21 E25 J24 O33 O47 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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Journal Article: Modelling artificial intelligence in economics (2022)
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DOI: 10.1186/s12651-022-00319-2

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