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

Author

Listed:
  • Jetha, Arif
  • Liao, Qing
  • Shahidi, Faraz Vahid
  • Vu, Viet
  • Biswas, Aviroop
  • Smith, Brendan
  • Smith, Peter

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.

Suggested Citation

  • Jetha, Arif & Liao, Qing & Shahidi, Faraz Vahid & Vu, Viet & Biswas, Aviroop & Smith, Brendan & Smith, Peter, 2025. "Machine learning and the labor market: A portrait of occupational and worker inequities in Canada," Social Science & Medicine, Elsevier, vol. 381(C).
    • Handle: RePEc:eee:socmed:v:381:y:2025:i:c:s0277953625006264
    DOI: 10.1016/j.socscimed.2025.118295
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    References listed on IDEAS

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