Artificial Intelligence in the Workplace: A Living Systematic Review Protocol on Worker Safety, Health, and Well-Being Implications

Details

• Personal Author:
  Jetha, Arif ; Crouch, Meghan ; Vold, Karina ; Peters, Susan E. ; Vietas, Jay ; Sriharan, Abi ; Irvin, Emma
• Description:
  Background: Advancements in artificial intelligence (AI) are transforming employment and working conditions in ways that shape the safety, health, and well-being of workers. We describe a protocol for a living systematic review (LSR) that will examine the interrelationship between AI systems, employment and working conditions, and worker safety, health, and well-being. Research questions are: 1. What types of AI systems are being used within workplaces and how do their design and adoption impact worker safety, health, and well-being? 2. How do a worker's employment and working conditions affect the relationship between the adoption of AI systems and worker safety, health, and well-being? 3. How does a worker's social position (e.g., age, gender, race, disability) shape the interrelationship between AI systems at work, employment and working conditions, and their safety, health, and well-being? Methods: A comprehensive search of primary qualitative and quantitative research will be conducted. MEDLINE, Embase (OVID), PsycINFO (OVID), and Web of Science will be searched every six to twelve months using database-specific terms and keywords. Title/abstract and full-text screening will be completed independently by two reviewers. Relevant articles will be quality appraised using a mixed method assessment tool adapted for studies of AI. Medium and high-quality studies will be synthesized using a best evidence synthesis approach. To ensure relevancy, applied workplace and AI stakeholders will provide feedback at all stages of the LSR process through dissemination excluding quality appraisal. Annually, we will evaluate the appropriateness of the review process (e.g., frequency of searches, requirement to refine research questions, utility of continuing LSR). Any amendments to protocols will be documented. Discussion: This LSR will provide timely and evolving evidence on the implications of AI in the workplace that will be disseminated through a publicly available living review dashboard. We will capture the emerging impact AI has on workers. Findings can be used to develop strategies to minimize AI's potential workplace harms while amplifying its potential benefits, address emerging worker inequities, and inform ongoing discussions regarding responsible and safe AI adoption.
• Subjects:
  Artificial Intelligence Occupational Health Psychological Well-Being Safety Working Conditions
• Keywords:
  Author Keywords: Artificial Intelligence; Systematic Reviews; Occupational Health; Employment; Working Conditions Systematic Reviews; Artificial Intelligence; Wellbeing; Worker Safety; Worker Health; Occupational Health; Work Environment;
• ISSN:
  2046-4053
• Document Type:
  Text
• Funding:
  Cooperative Agreement
• Genre:
  Journal Article
• Place as Subject:
  Massachusetts ; Illinois ; Boston Region [OSHA] ; Chicago Region [OSHA]
• CIO:
  National Institute for Occupational Safety and Health (NIOSH)
• Topic:
  Workplace Safety & Health
• Location:
  North America
• Pages in Document:
  9 pdf pages
• Volume:
  14
• NIOSHTIC Number:
  nn:20071169
• Citation:
  Syst Rev 2025 Dec; 14:255
• Email:
  AJetha@iwh.on.ca
• Federal Fiscal Year:
  2026
• Performing Organization:
  Harvard University, Boston, Massachusetts
• Peer Reviewed:
  True
• Start Date:
  20070901
• Source Full Name:
  Systematic Reviews
• End Date:
  20260831
• Collection(s):
  National Institute for Occupational Safety and Health
• Main Document Checksum:
  urn:sha-512:5b303fd2458c298ddba5725bb3143b867e191e4d7417ec70020d5554b8728914ac221453f9ed728b146428faaa98163230abaf89abec9cb2437b71c60578d987
• Download URL:
  https://stacks.cdc.gov/view/cdc/257935/cdc_257935_DS1.pdf
• File Type:
  [PDF - 848.06 KB ]