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Artificial intelligence and the work-health interface: A research agenda for a technologically transforming world of work.
Jetha, Arif; Bakhtari, Hela; Rosella, Laura C; Gignac, Monique A M; Biswas, Aviroop; Shahidi, Faraz V; Smith, Brendan T; Smith, Maxwell J; Mustard, Cameron; Khan, Naimul; Arrandale, Victoria H; Loewen, Peter J; Zuberi, Daniyal; Dennerlein, Jack T; Bonaccio, Silvia; Wu, Nicole; Irvin, Emma; Smith, Peter M.
Afiliación
  • Jetha A; Institute for Work & Health, Toronto, Ontario, Canada.
  • Bakhtari H; Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada.
  • Rosella LC; Institute for Work & Health, Toronto, Ontario, Canada.
  • Gignac MAM; Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada.
  • Biswas A; Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada.
  • Shahidi FV; Temerty Centre for Artificial Intelligence Research and Education in Medicine, University of Toronto, Toronto, Ontario, Canada.
  • Smith BT; Vector Institute, Toronto, Ontario, Canada.
  • Smith MJ; Institute for Clinical Evaluative Sciences, Toronto, Ontario, Canada.
  • Mustard C; Institute for Better Health, Trillium Health Partners, Mississauga, Ontario, Canada.
  • Khan N; Institute for Work & Health, Toronto, Ontario, Canada.
  • Arrandale VH; Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada.
  • Loewen PJ; Institute for Work & Health, Toronto, Ontario, Canada.
  • Zuberi D; Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada.
  • Dennerlein JT; Institute for Work & Health, Toronto, Ontario, Canada.
  • Bonaccio S; Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada.
  • Wu N; Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada.
  • Irvin E; Health Promotion, Chronic Disease, and Injury Prevention, Public Health Ontario, Toronto, Ontario, Canada.
  • Smith PM; School of Health Studies, Faculty of Health Sciences, Western University, London, Ontario, Canada.
Am J Ind Med ; 66(10): 815-830, 2023 10.
Article en En | MEDLINE | ID: mdl-37525007
ABSTRACT
The labor market is undergoing a rapid artificial intelligence (AI) revolution. There is currently limited empirical scholarship that focuses on how AI adoption affects employment opportunities and work environments in ways that shape worker health, safety, well-being and equity. In this article, we present an agenda to guide research examining the implications of AI on the intersection between work and health. To build the agenda, a full day meeting was organized and attended by 50 participants including researchers from diverse disciplines and applied stakeholders. Facilitated meeting discussions aimed to set research priorities related to workplace AI applications and its impact on the health of workers, including critical research questions, methodological approaches, data needs, and resource requirements. Discussions also aimed to identify groups of workers and working contexts that may benefit from AI adoption as well as those that may be disadvantaged by AI. Discussions were synthesized into four research agenda areas (1) examining the impact of stronger AI on human workers; (2) advancing responsible and healthy AI; (3) informing AI policy for worker health, safety, well-being, and equitable employment; and (4) understanding and addressing worker and employer knowledge needs regarding AI applications. The agenda provides a roadmap for researchers to build a critical evidence base on the impact of AI on workers and workplaces, and will ensure that worker health, safety, well-being, and equity are at the forefront of workplace AI system design and adoption.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Inteligencia Artificial / Lugar de Trabajo Tipo de estudio: Qualitative_research Límite: Humans Idioma: En Revista: Am J Ind Med Año: 2023 Tipo del documento: Article País de afiliación: Canadá

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Inteligencia Artificial / Lugar de Trabajo Tipo de estudio: Qualitative_research Límite: Humans Idioma: En Revista: Am J Ind Med Año: 2023 Tipo del documento: Article País de afiliación: Canadá
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