构建人机协同的智能决策框架，提升关键基础设施安全与可信度。
A Conceptual Framework for AI-based Decision Systems in Critical Infrastructures
- 融合多学科理论，建立人机协作的综合性决策框架
- 通过电网管理案例验证框架在真实场景中的可行性
- 适合关注安全系统设计与人机信任机制的研究者
人机在安全关键系统中的交互带来独特挑战，现有框架未能充分解决透明性、信任与可解释性需求，以及稳健安全决策的矛盾。亟需一个整合人类与人工智能能力、兼顾上述关切的综合性框架，以填补关键基础设施系统设计、部署与维护中的重要空白。本文提出一种跨学科概念框架，融合数学、决策理论、计算机科学、哲学、心理学及认知工程等传统领域，并结合能源、交通与航空等专业工程领域。其灵活性通过电力系统管理案例得以验证。
原文摘要 · Abstract (English)
The interaction between humans and AI in safety-critical systems presents a unique set of challenges that remain partially addressed by existing frameworks. These challenges stem from the complex interplay of requirements for transparency, trust, and explainability, coupled with the necessity for robust and safe decision-making. A framework that holistically integrates human and AI capabilities while addressing these concerns is notably required, bridging the critical gaps in designing, deploying, and maintaining safe and effective systems. This paper proposes a holistic conceptual framework for critical infrastructures by adopting an interdisciplinary approach. It integrates traditionally distinct fields such as mathematics, decision theory, computer science, philosophy, psychology, and cognitive engineering and draws on specialized engineering domains, particularly energy, mobility, and aeronautics. Its flexibility is further demonstrated through a case study on power grid management.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。