为航海人员设计可解释AI，提升人机协作中的信任与透明度。
From Sea to System: Exploring User-Centered Explainable AI for Maritime Decision Support
- 针对海事场景设计用户中心的可解释AI评估问卷。
- 发现透明性比性能更影响航海人员对AI的信任度。
- 适合参与海上智能系统开发与人机协作研究的团队。
随着自主技术日益影响海事操作，理解AI决策的原因与决策本身同样关键。在复杂动态的海事环境中，对AI的信任不仅取决于性能，还依赖于透明度和可解释性。本文强调可解释AI（XAI）是实现海事领域有效人机协同的基础，其中知情监督与共同理解至关重要。为此，我们提出一项面向海事领域的特定调查，旨在捕捉航海专业人士对信任、可用性和可解释性的感知。我们的目标是提高意识，并指导以用户为中心的XAI系统开发，使其更好地满足船员与海事团队的需求。
原文摘要 · Abstract (English)
As autonomous technologies increasingly shape maritime operations, understanding why an AI system makes a decision becomes as crucial as what it decides. In complex and dynamic maritime environments, trust in AI depends not only on performance but also on transparency and interpretability. This paper highlights the importance of Explainable AI (XAI) as a foundation for effective human-machine teaming in the maritime domain, where informed oversight and shared understanding are essential. To support the user-centered integration of XAI, we propose a domain-specific survey designed to capture maritime professionals' perceptions of trust, usability, and explainability. Our aim is to foster awareness and guide the development of user-centric XAI systems tailored to the needs of seafarers and maritime teams.
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