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Automation Surprise in the 21st Century: Culture, Collaborative Cognition, Complexity and Legacy Systems

机译:21世纪的自动化惊喜:文化,协作认知,复杂性和遗留系统

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Automation surprises continue to be a significant safety concern, and the system safety community's search for effective strategies to mitigate them are ongoing. The literature has offered two fundamentally divergent directions, based on different ideas about the nature of cognition and collaboration with automation: a normative individual-cognition model and a sensemaking model based on distributed cognition. In this talk, I will run through the human factors and system safety investigation of an accident that illustrates an undiscovered niche of catastrophic risk-even in an ultra-safe system. A combination of culture, buggy mental models and legacy systems contributed critically in this case, and there was no appropriate training, no written guidance, no documentation, and no likelihood of operational experience that would insulate people from the kind of automation surprise and accident that happened. The sensemaking model suggests that our understanding of the interaction between humans and automation in a case such as the one discussed can be improved by taking into account culture, collaborative cognition, complexity and legacy systems vis-a-vis the operational context, rather than focusing on suboptimal human performance.
机译:自动化惊喜继续成为一个重要的安全问题,系统安全社区的寻求减轻他们正在进行的有效策略。基于对自动化性质的不同思想,文献提供了两个根本不同的方向:一种基于分布式认知的规范性个人认知模型和一种敏感模型。在这次谈判中,我将贯穿于人类因素和系统安全调查的事故,说明灾难性风险的未被发现的利基 - 即使在超安全的系统中。在这种情况下,文化的组合,越野车模型和遗留系统批判性地贡献,并且没有适当的培训,没有书面指导,没有文件,也没有可能的操作经验,这些经验将使人们免受自动化的那种惊讶和事故发生了。传感模型表明,我们通过考虑文化,协作认知,复杂性和传统系统来改善在诸如讨论的案例中的人类和自动化之间的互动的理解,而不是关注的关注论次优人类绩效。

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