Understanding human interaction with automated and algorithmic systems

了解人类与自动化和算法系统的交互

• 批准号: RGPIN-2020-07026
• 负责人: Burns, Catherine
• 金额: $ 5.32万
• 依托单位: University of Waterloo
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2020
• 资助国家: 加拿大
• 起止时间: 2020-01-01 至 2021-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=718653
• 关键词: Understanding; human; interaction; automated; algorithmic

Autonomous systems, advanced algorithms, and artificial intelligence are emerging technologies. While these technologies aim to reduce human mental workload, if they are not designed with the user in mind these technologies can increase workload and decrease situation awareness. This proposal explores using a method from human factors engineering, Cognitive Work Analysis (CWA), to define the requirements for autonomous, algorithmic or artificially intelligent systems in ways that they assist human operators and improve human decision making. CWA is well-suited for this problem as CWA was developed to help people work better with complex system like the ones proposed here. In particular, CWA takes advantage of a strong reasoning structure and models of human information processing that advance current approaches to human interaction. Dr. Burns, as a world leader in CWA has developed the method in new directions and applied it successfully to many different domains. The research proposed here is novel and innovative, and this is the first time Cognitive Work Analysis will be applied to generate explanations from AI to operators, to directly predict how trust will change with system transparency, to predict how human operator workload will change, and to communicate intention to human operators. Dr. Burns proposes to develop and demonstrate whether CWA can achieve the following in AI, autonomous or algorithmic systems: O1)Provide a framework for improving the explanations provided to operators. O2) Predict how human operator performance changes with system transparency. O3) Improve the recognition of system intent. This research is applied in several different contexts, from financial systems, to defence systems to autonomous vehicles. The application in different contexts increases the ability of the work to have impact to industry and to the methods of human factors engineering. This work is important and will influence all new applications of advanced technology, that use algorithms or AI to make decisions. This work builds on Dr. Burns' world leading program in human factors engineering and advances Canada's position as a leader in highly effective advanced technologies.

自主系统、先进算法和人工智能都是新兴技术。虽然这些技术旨在减少人类的精神工作量，但如果它们在设计时没有考虑到用户，这些技术可能会增加工作量并降低情况感知能力。本提案探讨了使用人因工程的一种方法，即认知工作分析（CWA），来定义自主、算法或人工智能系统的需求，以帮助人类操作员并改善人类决策。