Abstract:

This work presents a review of the applications of Artificial Intelligence (AI) in educational and workplace safety, exploring current implementations, potential future developments, and the associated challenges and opportunities. As learning environments and workplaces become increasingly complex, the integration of AI technologies offers promising solutions to enhance safety measures, predict potential hazards, and optimize risk management strategies, while improving educational outcomes.

We identify and categorize key areas where AI is making significant contributions to both safety and learning:
(1) Adaptive safety training: AI-powered platforms that personalize safety education based on individual learning styles and prior knowledge, enhancing retention and application of safety protocols.
(2) Immersive learning experiences: Virtual and augmented reality systems enhanced by AI for creating realistic, risk-free environments to practice safety procedures and decision-making.
(3) Cognitive load management: AI algorithms that optimize the presentation of safety information to reduce cognitive overload and improve learning efficiency.
(4) Real-time feedback and assessment: AI-driven systems that provide immediate feedback on safety practices, facilitating continuous learning and improvement.
(5) Predictive analytics for risk prevention: Machine learning models that analyze patterns in educational and workplace data to forecast potential safety risks and tailor preventive measures.
(6) Adaptive emergency response training: AI simulations that adjust scenario complexity based on learner performance, enhancing preparedness for emergency situations.
(7) Collaborative learning in safety education: AI-facilitated peer-to-peer learning platforms that encourage knowledge sharing and collective problem-solving in safety-related topics.

Our analysis reveals that the integration of AI in safety education and workplace practices has led to significant improvements in both incident prevention and learning outcomes. We explore how AI-enhanced safety training translates to improved situational awareness, decision-making skills, and overall safety culture in real-world environments. The paper then discusses emerging trends and future directions in AI for safety education, including the potential for AI to bridge the gap between theoretical safety knowledge and practical application.

We also address the ethical implications of AI in safety education and workplace implementation, including issues of data privacy, the digital divide, and the need for human oversight in AI-assisted safety systems.

The review concludes by outlining a research agenda for advancing AI applications in safety education and workplace implementation.

In conclusion, this review demonstrates the transformative potential of AI in enhancing safety education and implementation across diverse learning and working environments. While challenges remain, the continued advancement of AI technologies, coupled with responsible implementation strategies, promises to significantly improve safety knowledge, skills, and attitudes, leading to safer and more productive educational and professional settings. As AI continues to evolve, its integration into safety education and workplace practices will likely become an essential component of comprehensive occupational health and safety management systems and educational curricula, fostering a culture of continuous learning and safety awareness.

Keywords:

AI, Safety, Workplace.