Conveying human goals to autonomous systems (AS) occurs both when the system is being designed and when it is being operated. The design-step conveyance is typically mediated by robotics and AI engineers, who must appropriately capture end-user requirements and concepts of operations, while the operation-step conveyance is mediated by the design, interfaces, and behavior of the AI. However, communication can be difficult during both these periods because of mismatches in the expectations and expertise of the end-user and the roboticist, necessitating more design cycles to resolve. We examine some of the barriers in communicating system design requirements, and develop an augmentation for applied cognitive task analysis (ACTA) methods, that we call robot task analysis (RTA), pertaining specifically to the development of autonomous systems. Further, we introduce a top-down view of an underexplored area of friction between requirements communication -- implied human expectations -- utilizing a collection of work primarily from experimental psychology and social sciences. We show how such expectations can be used in conjunction with task-specific expectations and the system design process for AS to improve design team communication, alleviate barriers to user rejection, and reduce the number of design cycles.

翻译：将人类目标传达给自主系统（AS）的过程发生在系统设计阶段和运行阶段。设计阶段的传达通常由机器人学和人工智能工程师中介，他们必须恰当地捕获最终用户的需求和操作概念，而运行阶段的传达则由人工智能的设计、接口和行为中介。然而，由于最终用户与机器人专家的期望和专业知识不匹配，这两个阶段的沟通都可能存在困难，需要更多的设计周期来解决。我们研究了传达系统设计需求中的一些障碍，并针对认知任务分析（ACTA）方法开发了一种改进方案，称为机器人任务分析（RTA），专门针对自主系统的开发。此外，我们利用主要来自实验心理学和社会科学领域的研究成果，从自上而下的视角探讨了一个尚未充分研究的需求沟通摩擦领域——隐含的人类期望。我们展示了如何将这些期望与任务特定期望及自主系统设计过程相结合，以改善设计团队的沟通，缓解用户拒绝的障碍，并减少设计周期的数量。