Cognitive automation: implications for occupational safety and health
This report examines the impact of cognitive automation and artificial intelligence on occupational safety and health (OSH). It utilizes a systematic literature review methodology to categorize AI-based systems into full and semi-automation tasks across person-related, information-related, and object-related domains. Furthermore, it identifies key OSH implications, focusing heavily on psychosocial effects such as workload, job transformation, deskilling, trust, loss of autonomy, and privacy concerns.
Summary and content fields are drawn from the document text and are pending editorial review.
Who issued it
Who it governs
Researchers, policy-makers, and occupational safety and health professionals seeking to understand the implications of cognitive automation on workers.
What the document contains
The report addresses the application of AI-based systems and advanced robotics for the automation of cognitive tasks, analyzing task characteristics (routine vs non-routine, semi- vs full automation) across person-, information-, and object-related domains, and evaluates their psychosocial, organizational, and physical implications for occupational safety and health.
The report does not provide legally binding compliance directives, explicit technological codes of practice, or definitive enforcement mechanisms for managing workplace AI systems.
- AI-based automation tends to substitute or transform specific tasks rather than entire jobs outright.
- Cognitive task automation impacts information-related, person-related, and object-related tasks across various sectors.
- The integration of AI systems generates significant psychosocial OSH effects, including changes in workload, job insecurity, and loss of privacy.
- Deskilling and loss of worker autonomy are notable risks associated with algorithmic management and automated decision support systems.
- Cybersecurity and formal risk assessment tools specifically tailored for AI-based workplace systems currently exhibit notable gaps in availability.
1 Introduction and objectives 2 Methodology 3 AI-based systems and types of tasks 4 OSH implications 5 Summary and Conclusion
How it scores
Each score is backed by a quote verified against the document text. Editorial review has not yet confirmed them.
Accountability
3/5Clear responsibility for AI outcomes
While the final responsibility for diagnosing the patient and assigning them to a treatment plan is still performed by a medical professional, the surrounding tasks to arrive at these decisions can be automated.
3.2.1 Information-related tasks
screening score · 2026-10-25
Fairness
2/5Non-discrimination and equitable treatment
If, unbeknownst to them, these algorithms are biased or discriminatory, then managers are being manipulated into propagating an act of discrimination without knowing it
4.1.3 Job transformation
screening score · 2026-10-25
Privacy
3/5Protection of personal data and private life
A central OSH concern associated with the spread of AI is the potential loss of privacy in the workplace.
4.1.6 Loss of privacy
screening score · 2026-10-25
Transparency
3/5Openness about how AI systems work and are used
This from of transparency can help in discovering hidden biases and reduce unintentional discrimination.
4.1.3 Job transformation
screening score · 2026-10-25
Enforcement
0/5Consequences and compliance mechanisms with real force
N/A
screening score · 2026-10-25
Impact Assessment
3/5Required assessment of an AI system's risks/impacts before or during use
Risk assessment could help gage the possible consequences of a breach in that area.
4.2.2 Cybersecurity
screening score · 2026-10-25