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This work presents a personalised AI coaching system to enhance occupational health and safety using a bottom-up design approach inspired by Lean UX and Agile principles. Leveraging Large Language Models and Computer Vision, the pilot integrated automated reporting and role-playing simulations to address safety challenges. Prototyping with existing and adapted AI tools demonstrated feasibility, with positive feedback from managers highlighting its potential to improve compliance and the need for staff involvement. The study underscores AI’s role as a collaborative coaching mediator and the effectiveness of bottom-up design in aligning solutions with user needs, while naturally integrating persuasive technology principles.

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Design of a Personalised AI Coaching Assistant for Occupational Health and Safety

  • 会议论文

  • 发表日期：

    2025年

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  • Jonathan Vitale,
  • Shlomo Berkovsky,
  • Shun Takeuchi,
  • Amin Beheshti,
  • Kexuan Xin,
  • Junya Saito,
  • Sosuke Yamao

摘要

This work presents a personalised AI coaching system to enhance occupational health and safety using a bottom-up design approach inspired by Lean UX and Agile principles. Leveraging Large Language Models and Computer Vision, the pilot integrated automated reporting and role-playing simulations to address safety challenges. Prototyping with existing and adapted AI tools demonstrated feasibility, with positive feedback from managers highlighting its potential to improve compliance and the need for staff involvement. The study underscores AI’s role as a collaborative coaching mediator and the effectiveness of bottom-up design in aligning solutions with user needs, while naturally integrating persuasive technology principles.