Artificial Intelligence and Occupational Health: Global Umbrella Review of Applications and Limitations

IF 3.2 3区医学 Q1 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH

Safety and Health at Work Pub Date : 2026-06-01 Epub Date: 2026-02-24 DOI:10.1016/j.shaw.2026.02.004

Alexis Descatha, Devan Hawkins, Grace Sembajwe, Saber Aloui, Eric Fadel, Diana Gagliardi, Francesco S. Violante, Malcom R. Sim, Marc Fadel, Seong-Kyu Kang

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引用次数: 0

Abstract

Background

Artificial Intelligence (AI) and information processing are technologies that will likely be the transformational for Occupational Health and Safety (OHS). We aim to provide a global umbrella review of the application of AI in occupational health, highlighting its strengths, limitations, and perspectives regarding its application.

Methods

In PubMed, Web of Science, and Scopus, we identified reviews published in peer-reviewed journals, as well as reports in the gray literature, dealing with the application of AI in OHS. Data extraction from these publications focused on applications of the technologies, strengths, and limitations of their utilization.

Results

From 1,884 initial hits, 33 reviews were included in this review, with only 4 systematic and 12 other systematized reviews. Many diverse AI applications in occupational health were found. Studies were identified from all continents and were mostly published in the last 15 years. The findings suggested that AI might have positive applications (risk prevention and monitoring, diagnosis, health, and well-being, training and skills development, automation and robotics, sector-specific applications, and organizational efficiency). Data and security, reliability, and limitations of AI systems, impacts on workers, governance and ethics, and scientific and methodological limitations were noted. However, the level of evidence is low and further specific studies will be needed, especially worker-centered studies with a health equity perspective.

Conclusion

The application of AI to OHS requires proactive policy, worker participation, and evidence-informed risk management, with rigorous impact assessments and ongoing research.

查看原文本刊更多论文

人工智能与职业健康：全球应用与局限性综述。

背景：人工智能（AI）和信息处理技术可能会成为职业健康与安全（OHS）的变革。我们的目标是对人工智能在职业健康中的应用进行全球概括性回顾，突出其优势、局限性和应用前景。方法：在PubMed、Web of Science和Scopus中，我们找到同行评议期刊上发表的评论，以及灰色文献中的报告，这些报告涉及人工智能在OHS中的应用。从这些出版物中提取的数据侧重于技术的应用、优势和使用的局限性。结果：从1884个初始点击中，33个评论被纳入本综述，只有4个系统评论和12个其他系统评论。发现人工智能在职业卫生领域有许多不同的应用。这些研究来自各大洲，大多是在过去15年里发表的。研究结果表明，人工智能可能具有积极的应用（风险预防和监测、诊断、健康和福祉、培训和技能开发、自动化和机器人、特定部门应用以及组织效率）。指出了人工智能系统的数据和安全性、可靠性和局限性、对工人的影响、治理和道德以及科学和方法的局限性。然而，证据水平很低，需要进一步的具体研究，特别是以工人为中心的健康公平观点的研究。结论：人工智能在职业健康安全中的应用需要积极的政策、员工参与和循证风险管理，并进行严格的影响评估和持续的研究。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Safety and Health at Work Social Sciences-Safety Research

CiteScore

6.40

自引率

5.70%

发文量

1080

审稿时长

38 days

期刊介绍： Safety and Health at Work (SH@W) is an international, peer-reviewed, interdisciplinary journal published quarterly in English beginning in 2010. The journal is aimed at providing grounds for the exchange of ideas and data developed through research experience in the broad field of occupational health and safety. Articles may deal with scientific research to improve workers'' health and safety by eliminating occupational accidents and diseases, pursuing a better working life, and creating a safe and comfortable working environment. The journal focuses primarily on original articles across the whole scope of occupational health and safety, but also welcomes up-to-date review papers and short communications and commentaries on urgent issues and case studies on unique epidemiological survey, methods of accident investigation, and analysis. High priority will be given to articles on occupational epidemiology, medicine, hygiene, toxicology, nursing and health services, work safety, ergonomics, work organization, engineering of safety (mechanical, electrical, chemical, and construction), safety management and policy, and studies related to economic evaluation and its social policy and organizational aspects. Its abbreviated title is Saf Health Work.