You vs. the Robot Factory: Some Principles for Understanding AI Hazards in the Workplace

Details

• Journal Article:
  The Synergist
• Personal Author:
  Sadowski, John P.
• Description:
  What might artificial intelligence (AI) in the workplace look like in the future? As an example, imagine an algorithmically controlled chemical factory. Perhaps it gathers data from distributed and wearable sensors and machine vision systems. Perhaps it controls chemical reaction parameters and hazardous machinery, operates the factory's ventilation system, and controls self-driving robotic vehicles. Perhaps it directs workers through messages on their smartphones to do certain tasks, and maybe even implements a chatbot to answer questions and issue clarifications to workers. How should an occupational and environmental health and safety (OEHS) professional go about hazard identification in this factory? What controls should they recommend implementing? As AI-enabled systems are increasingly adopted in the workplace, OEHS practitioners and researchers must be prepared to consider their effects on worker health and safety. While AI may at first seem radically different from other potentially hazardous aspects of the workplace, it can indeed be understood using established OEHS principles. Further, although people might not initially think to ask an OEHS professional about AI safety, their presence throughout all industrial sectors gives them a responsibility and an opportunity to have a significant impact through education and assessment activities. This would allow end-users to improve their own practices, as well as request that software vendors consider health and safety impacts in their software design, without requiring a wait for formal regulatory action. It would also foster the good governance and trust that would encourage adoption of AI in contexts where it is warranted. Nevertheless, OEHS research into AI is now in its infancy. A science of industrial hygiene for algorithms, which we might call "algorithmic hygiene," is needed, explicitly linking the characteristics of algorithmic systems to health and safety outcomes. This linking would guide research questions and provide a scientific basis for practical, actionable guidance for individual end-users, developers, and policymakers.
• Subjects:
  Artificial Intelligence Occupational Health Safety
• Keywords:
  Emerging technology; Artificial intelligence; Future of work; Algorithms; Exposure assessment; Risk management
• Source:
  Synergist 2025 Jun/Jul; 36(6/7):22-29
• ISSN:
  1066-7660
• Document Type:
  Text
• Funding:
  Contract
• Genre:
  Journal Article
• Place as Subject:
  Maryland ; Philadelphia Region [OSHA]
• CIO:
  National Institute for Occupational Safety and Health (NIOSH)
• Division:
  DFSE - Division of Field Studies and Engineering
• Topic:
  Workplace Safety & Health
• Location:
  North America
• Pages in Document:
  7 pdf pages
• Volume:
  36
• Issue:
  6
• NIOSHTIC Number:
  nn:20071265
• Federal Fiscal Year:
  2025
• Performing Organization:
  Advanced Technologies & Laboratories International Inc.
• Peer Reviewed:
  False
• Collection(s):
  National Institute for Occupational Safety and Health
• Main Document Checksum:
  urn:sha-512:371d571b90bfd3d8dfeafa28bac50fcae9149c78a3d84eed23cf84d61f6fd2c079fbce74adf4a462589d545ae00253b35eb7c414f23bdd1faa7d7dbaf6cd3504
• Download URL:
  https://stacks.cdc.gov/view/cdc/258743/cdc_258743_DS1.pdf
• File Type:
  [PDF - 540.74 KB ]