Leveraging Artificial Intelligence to Enhance Safety Standards Education

Abstract

The growing complexity of contemporary safety standards poses challenges for education, interpretation, and practical application, particularly in socio-technical systems where technical, human, and organisational dimensions must be integrated. At the same time, recent advances in generative Artificial Intelligence (AI) offer new opportunities to support learning, sense-making, and engagement with normative frameworks.

This paper explores how generative AI can be used to support the education and understanding of safety standards without reducing them to procedural checklists or automated compliance tools. The study focuses on the Dutch National Norm NEN-NTA 8287:2021, which adopts a safety-by-design perspective and explicitly emphasises system integration across the lifecycle. We describe an AI-assisted educational approach in which large language models are used to support interpretation of standard requirements, exploration of relationships between safety domains, and reflection on integration challenges. Rather than replacing expert judgement, AI is positioned as an interactive support that facilitates structured dialogue, comparative reasoning, and contextual explanation.

The paper reflects on experiences from applying this approach in a safety education context and discusses its implications for safety learning, standards comprehension, and integration-oriented thinking. Benefits, limitations, and ethical considerations are examined, including risks of over-reliance, misinterpretation, and authority displacement. The results suggest that, when used critically and transparently, generative AI can enhance engagement with complex safety standards and support integrative understanding. The paper contributes to ongoing discussions on safety education, safety-by-design, and the responsible use of AI in safety-critical domains.

Keywords: NTA 8287; AI; safety; standard; education