缺失的变量：风险评估中的社会技术对齐
The Missing Variable: Socio-Technical Alignment in Risk Evaluation
AI总结：
本文提出社会技术对齐STA变量，用于改进AI安全关键系统风险评估，通过案例研究展示其在捕捉社会技术安全影响方面的贡献。
摘要：
本文针对AI赋能的安全关键系统风险评估中存在的重要缺口进行了研究。尽管这些系统在AI系统辅助人类操作员的情况下，作为复杂的社会技术系统运作，现有的风险评估方法未能考虑人类、技术及组织元素之间的复杂交互。通过比较社会技术系统和AI赋能系统属性，并回顾当前的风险评估方法，我们确认标准风险表达中缺乏社会技术考虑。为弥合这一差距，我们引入了一个新的社会技术对齐STA变量，旨在整合到基础风险方程中。该变量估计AI系统、人类操作员和组织流程之间和谐互动的程度。对一个AI赋能的液氢加注系统的案例研究展示了该变量的相关性。通过比较一种朴素和受保护的系统设计，我们展示了STA增强的表达式如何捕捉传统风险评估所忽视的社会技术安全影响，从而提供更全面的风险评估基础。
英文摘要：
This paper addresses a critical gap in the risk assessment of AI-enabled safety-critical systems. While these systems, where AI systems assist human operators, function as complex socio-technical systems, existing risk evaluation methods fail to account for the associated complex interaction between human, technical, and organizational components. Through a comparative analysis of system attributes from both socio-technical and AI-enabled systems and a review of current risk evaluation methods, we confirm the absence of explicit socio-technical considerations in standard risk expressions. To bridge this gap, we introduce a novel socio-technical alignment ($STA$) variable designed to be integrated into the traditional risk equation. This variable estimates the degree of harmonious interaction between the AI systems, human operators, and organizational processes. A case study on an AI-enabled liquid hydrogen ($LH_2$) bunkering system demonstrates the variable's relevance. By comparing a naive and a safeguarded system design, we illustrate how the $STA$-augmented expression captures socio-technical safety implications that traditional risk evaluation overlooks, providing a more system-theoretic basis for risk evaluation.
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。
