从海洋到系统：探索以用户为中心的可解释人工智能用于海事决策支持
From Sea to System: Exploring User-Centered Explainable AI for Maritime Decision Support
AI总结：
本文探讨海事决策支持中可解释人工智能的重要性，并提出面向海事专业人员的领域调查，以推动以用户为中心的XAI系统设计。
摘要：
随着自主技术日益塑造海事运营，理解人工智能系统为何做出某个决策变得与其做出什么决策同样重要。在复杂且动态的海事环境中，对人工智能的信任不仅取决于性能，还取决于透明度和可解释性。本文强调可解释人工智能（XAI）作为海事领域有效人机协作基础的重要性，在该领域中，知情的监督和共同理解至关重要。为支持以用户为中心的XAI集成，我们提出了一项面向特定领域的调查，旨在捕捉海事专业人员对信任、可用性和可解释性的看法。我们的目标是提升认知并指导以用户为中心的XAI系统开发，使其适应海员和海事团队的需求。
英文摘要：
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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
