标题： 人工智能人类监督的设计考虑：来自协同设计研讨会和工作设计理论的见解 显示英文标题

标题： Design Considerations for Human Oversight of AI: Insights from Co-Design Workshops and Work Design Theory

摘要： 随着人工智能系统变得越来越强大和自主，领域专家的角色正在从亲自执行任务转向监督人工智能生成的输出。 这种监督至关重要，因为未被发现的错误可能会造成严重后果或削弱人工智能的优势。 然而，有效的监督不仅取决于检测和纠正人工智能的错误，还取决于监督人员的动机和参与度，以及他们对自己工作的意义感。 然而，关于领域专家如何对待和体验监督任务，以及在设计有效的、有激励性的界面时应考虑什么，了解甚少。 为了解决这些问题，我们与心理学和计算机科学领域的领域专家进行了四次共同设计工作坊。 我们让他们首先监督一个基于人工智能的评分系统，然后讨论他们在监督过程中的体验和需求。 最后，他们共同设计了可以支持他们完成监督任务的界面原型。 我们的主题分析揭示了四个关键的用户需求：理解任务和职责、深入了解人工智能的决策过程、对过程做出有意义的贡献，以及与同事和人工智能进行协作。 我们将这些实证见解与工作设计的SMART模型相结合，开发了一个可推广的十二项设计考虑框架。 我们的框架将界面特征和用户需求与有效且令人满意的工作的心理过程联系起来。 基于工作设计理论，我们期望这些考虑因素适用于各个领域，并讨论了它们如何通过提供关于设计吸引人且有意义的界面的具体指导，扩展现有的人机交互指南和有效的人类监督理论框架，以支持对人工智能系统的监督。 显示英文摘要

摘要： As AI systems become increasingly capable and autonomous, domain experts' roles are shifting from performing tasks themselves to overseeing AI-generated outputs. Such oversight is critical, as undetected errors can have serious consequences or undermine the benefits of AI. Effective oversight, however, depends not only on detecting and correcting AI errors but also on the motivation and engagement of the oversight personnel and the meaningfulness they see in their work. Yet little is known about how domain experts approach and experience the oversight task and what should be considered to design effective and motivational interfaces that support human oversight. To address these questions, we conducted four co-design workshops with domain experts from psychology and computer science. We asked them to first oversee an AI-based grading system, and then discuss their experiences and needs during oversight. Finally, they collaboratively prototyped interfaces that could support them in their oversight task. Our thematic analysis revealed four key user requirements: understanding tasks and responsibilities, gaining insight into the AI's decision-making, contributing meaningfully to the process, and collaborating with peers and the AI. We integrated these empirical insights with the SMART model of work design to develop a generalizable framework of twelve design considerations. Our framework links interface characteristics and user requirements to the psychological processes underlying effective and satisfying work. Being grounded in work design theory, we expect these considerations to be applicable across domains and discuss how they extend existing guidelines for human-AI interaction and theoretical frameworks for effective human oversight by providing concrete guidance on the design of engaging and meaningful interfaces that support human oversight of AI systems.