情况意识的评估 冲突风险 在过程中人类和人工智能之间的冲突风险 系统运行 系统运行
He Wen1, Md Tanjin Amin2, Faisal Khan1,2
1Centre for Risk, Integrity and Safety Engineering (C-RISE), Faculty of Engineering & Applied ScienceMemorial University, St. John's, NL A1B 3X5, Canada.
Industrial & engineering chemistry research
|February 9, 2024
概括
解释冲突,一个关键的人类-AI问题在工艺安全,是通过一种新的方法量化. 这项研究解决了由各种故障引发的隐藏解释冲突,为更好的AI安全管理提供了一条道路.
科学领域:
- 过程工程系统工程系统工程
- 人与人工智能的互动
- 过程安全 过程安全 过程安全
背景情况:
- 人与人工智能之间的冲突在工艺系统工程中越来越令人担忧,包括观察,行动和解释冲突.
- 与情境意识相关的解释冲突通常被认为是混乱或错误,但缺乏足够的研究重点.
- 现有的研究主要集中在观察和行动冲突上,忽视了解释冲突的关键方面.
研究的目的:
- 引入一种新的方法来量化解释冲突的概率和风险.
- 解决人类-人工智能系统中解释冲突的研究不足的领域.
- 为理解和管理过程安全中的解释冲突提供一个框架.
主要方法:
- 开发一种新的方法来量化解释冲突的概率和风险.
- 在双相分离器系统上演示,测试和验证方法.
- 分析诸如传感器故障,网络攻击和人为错误等各种因素如何导致解释冲突.
主要成果:
- 解释冲突往往是隐藏的,被传统的缺陷掩盖,或被观察和解释中的噪音所掩盖.
- 传感器故障,逻辑错误,网络攻击,人类错误和误解被确定为解释冲突的常见触发因素.
- 提出的方法论成功地量化了在实际过程系统中的解释冲突.
结论:
- 解释冲突对过程安全构成了重大,但往往被低估的风险.
- 开发的方法论为识别和评估解释冲突提供了至关重要的工具.
- 这项工作奠定了开发有效策略的基础,以管理解释冲突并提高整体系统安全.
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