Machine learning and the labor market: A portrait of occupational and worker inequities in Canada

Arif Jetha, Qing Liao, Faraz Vahid Shahidi, Viet Vu, Aviroop Biswas, Brendan Smith and Peter Smith

Social Science & Medicine, 2025, vol. 381, issue C

Abstract: Machine learning (ML), an artificial intelligence (AI) subfield, is increasingly used by Canadian workplaces. Concerningly, the impact of ML may be inequitable and contribute to social and health inequities in the working population. The aim of this study is to estimate the number of workers in occupations with high, medium, and low ML exposure and describe differences in exposure according to occupational and worker sociodemographic factors.

Keywords: Artificial intelligence; Machine learning; Labor market data analysis; Worker inequities; Occupational exposure; Future of work; Gender differences (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:socmed:v:381:y:2025:i:c:s0277953625006264

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DOI: 10.1016/j.socscimed.2025.118295

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