Supervisor Learning
Today’s Learning: Trusting AI in Safety Training
- Automation bias: accepting AI advice without adequately checking it.
- Algorithm aversion: rejecting useful AI advice after seeing one mistake.
- Trust calibration: relying on AI only as much as its demonstrated competence justifies.
Practice Exercise
- Create a supervisor scenario involving production pressure and weakening safety boundaries.
- Have the chatbot provide a plausible but incomplete recommendation.
- Ask: What information is missing? What assumption is the AI making? What could happen if its advice is followed? What must be verified with a worker, procedure, or competent person?
- Ask the supervisor to explain and defend the final decision.
Key insight: The chatbot should develop judgment—not replace it.
“Use AI to stimulate judgment, not substitute for judgment.”
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Supervisor Learning
Short, scenario-based modules designed to enhance workplace safety awareness and leadership skills for supervisors.
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Comprehensive guides and institutional resources for students and researchers to navigate approved thesis research activities.
Research Summaries
Accessible summaries of occupational health and safety articles, thesis updates, and downloadable resources for students.
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We provide a clear distinction between institutionally approved research activities and public training. Our OHS Research Hub features accessible summaries, thesis updates, and downloadable resources designed specifically for students and researchers. This separation ensures that academic inquiry is conducted under institutional oversight while public training remains accessible to all supervisors and workers seeking foundational knowledge.