Task-interdependencies between Generative AI and Workers

Emmanuelle Walkowiak

Economics Letters, 2023, vol. 231, issue C

Abstract: Our paper formalizes a production function to give microeconomic foundations for the adoption of Generative AI (GAI) within workplaces. The production function accounts for task-interdependencies, the worker-GAI interaction and indistinguishability between human-created and AI-generated outputs. We show that workers and GAI represent two distinct but interdependent sides of the production, that jointly generate a network externality in learning that drives productivity. We find that in open learning organizations favoring the worker-GAI interaction, GAI should be matched to workers based on their ability to detect errors. We analyze configurations where the worker-GAI interaction is limited, referred as closed learning organizations, including firms banning the use of GAI, technological superclusters and emergence of small entrepreneurs innovating with GAI.

Keywords: Generative AI; Interdependencies; Interaction; O-ring; Matching; AI risks (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:ecolet:v:231:y:2023:i:c:s0165176523003403

DOI: 10.1016/j.econlet.2023.111315

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