Enhancing Human-Robot Collaboration through Existing Guidelines: A Case Study Approach
Yutaka Matsubara, Akihisa Morikawa, Daichi Mizuguchi, Kiyoshi Fujiwara
- Year
- 2025
- Access
- Open access
Abstract
As AI systems become more prevalent, concerns about their development, operation, and societal impact intensify. Establishing ethical, social, and safety standards amidst evolving AI capabilities poses significant challenges. Global initiatives are underway to establish guidelines for AI system development and operation. With the increasing use of collaborative human-AI task execution, it's vital to continuously adapt AI systems to meet user and environmental needs. Failure to synchronize AI evolution with changes in users and the environment could result in ethical and safety issues. This paper evaluates the applicability of existing guidelines in human-robot collaborative systems, assesses their effectiveness, and discusses limitations. Through a case study, we examine whether our target system meets requirements outlined in existing guidelines and propose improvements to enhance human-robot interactions. Our contributions provide insights into interpreting and applying guidelines, offer concrete examples of system enhancement, and highlight their applicability and limitations. We believe these contributions will stimulate discussions and influence system assurance and certification in future AI-infused critical systems.
Keywords
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