Emerging Technologies in Workplace Safety and Health (HFS208)

HFS208 equips WSH practitioners, managers, and human factors professionals to understand, evaluate, and make informed adoption decisions about emerging AI and intelligent systems in safety-critical workplaces. Structured as six interactive seminars, the course uses an information systems lens to examine how AI-augmented workflows reshape safety information management at personal, team, and organisational levels. Students then explore vision-based systems, embodied autonomous systems, and real-time sensing and simulation technologies, examining each through the dual lens of WSH application potential and human factors risk. Rather than training students to become technologists, the course develops confident, critical practitioners who can review vendors, evaluate evidence, and lead responsible technology adoption in their organisations.

• How Large Language Models Work and its Applications in WSH
• Prompting as Professional Practice
• AI and Personal Safety Information
• AI and Team Information Flows
• AI and Organisational Knowledge at Scale
• Agentic Systems and Orchestration
• Computer Vision for Safety
• VR/AR/XR for Safety Training and Simulation
• Collaborative Robots and Human-Robot Interaction
• Drones and Autonomous Mobile Systems
• Wearables and Real-Time Physiological and Environmental Sensing
• Digital Twins and Predictive Safety Systems

• Explain how large language models, multimodal AI, and agentic systems function at a conceptual level, including the failure modes and limitations most relevant to WSH decision-making.
• Describe how AI-augmented information workflows operate across personal, team, and organisational levels within a WSH context, using an information systems framework.
• Identify the capabilities and inherent limitations of vision-based systems, embodied autonomous systems, and real-time sensing and digital twin technologies in safety-critical environments.
• Evaluate technology claims against practical WSH deployment realities, distinguishing evidence-based capability from vendor hype and deployment optimism.
• Appraise the human factors, ethical, privacy, and governance implications of deploying intelligent systems in WSH contexts,and articulate the conditions under which adoption is and is not appropriate.
• Formulate a human-centred, evidence-informed technology adoption position for a real WSH challenge, integrating technical understanding, systems thinking, and multi technology perspectives.