Intelligent machines and human worker inequities: examining the implications of AI in the workplace

Reasons for the study

There is a critical need for transdisciplinary and partnered research to unpack how workplace AI (artificial Intelligence) applications can contribute to worker inequities and to innovate strategies that protect vulnerable workers.

AI is rapidly transforming all aspects of work. However, it is unclear in what ways AI will impact existing worker inequities. It is estimated that, compared to past periods of technological change (for example, the industrial revolution), advanced technologies like AI are disrupting work at a rate that is ten times faster rate and 300 times greater in scale.

This study applies an equity lens to the analysis of this technological and socio-economic development. It aims to iIlluminate the impact of AI on both working conditions and workers, estimate the reach of these impacts on occupations and populations, and determine the extent to which existing workers' supports address these disparities. 

Objectives of the study

  • Examine and synthesize diverse evidence sources to build a framework showing how workplace AI applications affect working conditions in ways that contribute to worker inequities
  • Develop an analytical process to estimate the proportion of Canadian occupations and industry sectors affected by AI and identify groups of vulnerable workers
  • Review existing public policies and programs to determine the extent to which supports for workers address the growing application of AI and its impact on vulnerable workers
  • Build research and stakeholder capacity at the intersection of work, equity and AI

Target audience

Diverse academic and non-academic audiences, the latter including labour market policy-makers, employers, workers and their representatives

Related research summaries

Related scientific publications

Project status

Ongoing

Research team

  • Arif Jetha, Institute for Work & Health (PI)
  • Hela Bakhtari, Institute for Work & Health
  • Aviroop Biswas, Institute for Work & Health
  • Monique Gignac, Institute for Work & Health
  • Emma Irvin, Institute for Work & Health
  • Peter Smith, Institute for Work & Health
  • Faraz Vahid Shahidi, Institute for Work & Health
  • Silvia Bonaccio, University of Ottawa
  • Jack Dennerlein, Northeastern University
  • Marc Frenette, Statistics Canada
  • Marlène Koffi, University of Toronto
  • Peter Loewen, University of Toronto
  • Naimul Mefraz Khan, Toronto Metropolitan University
  • Laura Rosella, University of Toronto
  • Brendan Smith, Public Health Ontario
  • Maxwell Smith, Western University
  • Nicole Wu, University of Toronto
  • Daniyal Zuberi, University of Toronto

Collaborators and partners

Blueprint-ADE
Brookfield Institute for Innovation + Entrepreneurship
Canadian Manufacturers & Exporters
Center for Work, Health, and Well-being (Harvard T.H. Chan School of Public Health)
Future Skills Centre
Labour Market Information Council
Ontario Agency for Health Protection and Promotion (Public Health Ontario)
Responsible Artificial Intelligence (Toronto Metropolitan University)
Schwartz Reisman Institute for Technology and Society
Statistics Canada
Unifor
United Steelworkers 

Funded by

Social Sciences and Humanities Research Council (SSHRC); Future Skills Centre