Talk:Workplace impact of artificial intelligence

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Ideal sources for Wikipedia's health content are defined in the guideline Wikipedia:Identifying reliable sources (medicine) and are typically review articles. Here are links to possibly useful sources of information about Workplace impact of artificial intelligence.

PubMed provides review articles from the past five years (limit to free review articles)
The TRIP database provides clinical publications about evidence-based medicine.
Other potential sources include: Centre for Reviews and Dissemination and CDC

A fact from Workplace impact of artificial intelligence appeared on Wikipedia's Main Page in the Did you know column on 8 September 2020 (check views). The text of the entry was as follows:

Did you know... that the hazards of artificial intelligence include algorithmic bias, blaming humans for machine errors, and human–robot collisions?

A record of the entry may be seen at Wikipedia:Recent additions/2020/September. The nomination discussion and review may be seen at Template:Did you know nominations/Workplace impact of artificial intelligence.

Wikipedia

Did you know nomination

The following is an archived discussion of the DYK nomination of the article below. Please do not modify this page. Subsequent comments should be made on the appropriate discussion page (such as this nomination's talk page, the article's talk page or Wikipedia talk:Did you know), unless there is consensus to re-open the discussion at this page. No further edits should be made to this page.

The result was: promoted by Amkgp (talk) 05:20, 2 September 2020 (UTC)[reply]

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Comment or view
Article history

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... that the hazards of artificial intelligence include algorithmic bias, blaming humans for machine errors, and human–robot collisions?

Reviewed: Julián Podoba

Moved to mainspace by John P. Sadowski (NIOSH) (talk). Self-nominated at 02:00, 20 August 2020 (UTC).[reply]

Interesting article, long enough, new enough, well-written and well-referenced. Hook is interesting, largely due to the topic itself being very catchy. QPQ done. AGF on some sources, since they are paywalled, but those available online check out, and no copyvio problems found. Good to go! Constantine ✍ 06:22, 24 August 2020 (UTC)[reply]

Focus of the article

I think this article should focus more on the automation potential of AI and the associated question regarding the future of the necessity of work.-- Maxeto0910 (talk) 22:26, 20 March 2024 (UTC)[reply]

That sounds more like an essay than part of this article in particular. Some of this is already included, e.g., call center automation. If you have specific additions and sources to improve the article it would help to make the changes you suggest. Recon rabbit 23:49, 20 March 2024 (UTC)[reply]

It's not essay-like at all to focus more on the anticipated future developments of AI regarding the need to work. It receives broad media coverage and I think should make up a larger part of this article to give due weight to this often discussed aspect. Maxeto0910 (talk) 23:41, 2 February 2025 (UTC)[reply]

Wiki Education assignment: Research Process and Methodology - FA24 - Sect 200 - Thu

This article was the subject of a Wiki Education Foundation-supported course assignment, between 5 September 2024 and 13 December 2024. Further details are available on the course page. Student editor(s): Nyn218 (article contribs).

— Assignment last updated by Nyn218 (talk) 22:09, 9 November 2024 (UTC)[reply]

Add references

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In order for any potential AI health and safety application to be adopted, it requires acceptance by both managers and workers.

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A comprehensive literature review published in Occupational and Environmental Medicine emphasizes that successful adoption of AI-based health and safety systems in the workplace fundamentally depends on acceptance by both managers and frontline workers. It argues that workers’ concerns—ranging from privacy and trust issues to insufficient training—must be addressed, while managers need to balance productivity goals with genuine safety outcomes. The study draws on organizational behavior and occupational safety research to demonstrate that this dual-level acceptance is a critical facilitator of AI deployment in safety-sensitive contexts.

URL: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11855051/

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AI may increase the scope of work tasks where a worker can be removed from a situation that carries risk.

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A peer-reviewed article published in the International Journal of Environmental Research and Public Health (2023) highlights that AI-powered robotics and sensor technologies are instrumental in removing workers from hazardous environments. The study explains that AI systems—such as autonomous robots and automated guided vehicles—are increasingly deployed to perform tasks in physically dangerous or high-exposure settings, effectively reducing direct human involvement in injury-prone work. These findings are grounded in robust environmental health and occupational safety research, offering a credible and academically authoritative foundation for your statement.

URL: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1006221/

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AI can also be used to make the workplace safety and health workflow more efficient.

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An article from Occupational Health & Safety Online (OH&S) discusses how predictive analytics, a form of AI, is transforming health and safety workflows. It explains that by analyzing incident reports, equipment data, and environmental inputs, AI systems enable employers to optimize safety protocols proactively, anticipate injuries, ensure compliance, and streamline operations. This integration of AI into workplace safety tools not only helps prevent accidents before they occur but also enhances administrative efficiency—making safety and health workflows faster and more effective. As a professional industry publication focused on occupational safety, this source provides adaptable, real-world insight that supports your statement with practical relevance and sector authority.

URL: https://ohsonline.com/articles/2025/06/05/the-role-of-predictive-analytics-in-optimizing-health-and-safety-workflows.aspx

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Einola and Khoreva explore how different organizational groups perceive and interact with AI technologies.

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This peer-reviewed article—Best Friend or Broken Tool? Exploring the Co-existence of Humans and Artificial Intelligence in the Workplace Ecosystem by Katja Einola and Violetta Khoreva (2022), published in the journal Human Resource Management—investigates how various organizational members interpret AI differently. The study finds that distinct groups within organizations develop unique sensemaking strategies regarding AI solutions, as AI becomes embedded in workflows. This nuanced insight emphasizes that successful AI implementation relies on understanding and engaging the varied perceptions across organizational roles, reinforcing the importance of context-aware integration strategies.

URL: https://onlinelibrary.wiley.com/doi/10.1002/hrm.22147

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Increased monitoring may lead to micromanagement and thus to stress and anxiety.

Source:

A comprehensive report from the U.S. Government Accountability Office (GAO) highlights that the increasing use of digital surveillance tools in the workplace often leaves employees “on edge,” negatively impacting mental health, morale, and productivity. It notes that constant tracking can make workers feel scrutinized, undermining trust and contributing to stress and anxiety—effects characteristic of micromanagement. This institutional analysis underscores the psychological costs of pervasive employee monitoring, grounding your statement in a trusted government authority.

URL: https://www.gao.gov/blog/why-do-i-feel-somebodys-watching-me-workplace-surveillance-can-impact-more-just-productivity Jaroslav Radomír (talk) 06:12, 7 September 2025 (UTC)[reply]