CHS: Small: Guiding future design of affect-aware cyber-human systems through the investigation of human reactions to machine errors

这个项目获得了关于人们如何对情感感知技术所产生的错误作出反应的新的基础知识。这些技术分析心率、大脑活动和身体姿势等测量数据，以获得对用户精神和情绪状态的估计；然后他们采取行动来改善用户的状态——例如，通过帮助完成任务。然而，由于测量结果通常很难解释，影响感知技术经常会犯错误。该项目由一个跨学科的工程和心理学研究小组领导，将研究用户如何对影响感知技术造成的不同类型的错误做出反应和补偿。这将有助于指导此类技术的未来设计，因为它将帮助研究人员和开发人员确定影响感知设备的最小可接受精度是多少，以及开发人员最需要减少哪些类型的错误。研究结果将在许多方面促进国民健康和福祉，因为情感感知技术在各种应用中变得越来越普遍，例如检测驾驶员的睡意、飞行和资源管理中的自适应自动化、适应学生的学习材料以及适应患者的康复练习。该团队将在人的因素和人机交互方面开发新的跨学科课程，并将向包括怀俄明州各地K-12和社区大学学生和教师在内的多个团体进行网络-人系统的推广。该项目由涉及人类受试者的一系列四个实验室研究组成，所有研究都使用一套生理传感器和NASA多属性任务电池。由于对影响感知网络-人类系统中用户对机器错误的反应知之甚少，前三个实验室研究将系统地改变四个关键特征：他们识别用户心理状态的准确性，系统采取的行动（任务难度的变化）的大小，错误对任务性能的影响，以及系统决策过程的透明度。这些错误将由《绿野仙踪》（Wizard of Oz）的实验设计引起，在实验中，在受试者不知道的情况下，机器的反应实际上是由人类操作员模拟的。在这个项目中，用户会被问及他们想要如何改变多属性任务电池的难度，如果做了与用户想要的相反的事情，就会产生错误。用户将不知道这种操作，并将被告知错误实际上是由于信号处理和模式识别不良。最后一项研究将检查系统的状态识别准确性和用户友好性之间的权衡，考虑到用户对系统的接受程度。在所有四项研究中，结果测量将是客观任务性能以及NASA任务负载指数和内在动机清单报告的主观用户体验。这将为研究界提供关于影响感知网络-人类系统的不同特征如何影响用户使用此类系统的客观和主观方面的详细信息。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

This project obtains new fundamental knowledge about how people react to errors made by affect-aware technologies. Such technologies analyze measurements such as heart rate, brain activity and body gestures to obtain an estimate of a user's mental and emotional state; they then take actions to improve the user's state - for example, by helping with a task. However, since the measurements are often hard to interpret, affect-aware technologies often make mistakes. Led by an interdisciplinary group of researchers in engineering and psychology, this project will examine how users react to and compensate for different types of errors made by affect-aware technologies. This will help guide future design of such technologies, as it will help researchers and developers identify what the minimal acceptable accuracy of an affect-aware device is and what types of errors most critically need to be reduced by developers. Results of the research will advance national health and well-being in many ways, as affect-aware technologies are becoming increasingly common for diverse applications such as detecting drowsiness in drivers, adaptive automation in flight and resource management, adaptation of learning material to students, and adaptation of rehabilitation exercises to patients. The team will develop new interdisciplinary courses in human factors and human-computer interaction, and will perform outreach about cyber-human systems to multiple groups including K-12 and community college students and teachers all around Wyoming.The project is structured as a series of four lab studies involving human subjects, all using a set of physiological sensors and the NASA Multi-Attribute Task Battery. As little is known about user reactions to machine errors in affect-aware cyber-human systems, the first three lab studies will systematically vary four critical characteristics: the accuracy with which they recognize the user's psychological state, the magnitude of the actions (changes to task difficulty) taken by the system, the impact that an error has on task performance, and the transparency of the system's decision-making process. The errors will be induced with a Wizard of Oz experiment design in which, unknown to the subject, the machine responses are actually simulated by a human operator. In this project, the user will be asked how they would like to change the difficulty of the Multi-Attribute Task Battery, and errors will be induced by doing the opposite of what the user wants. Users will be unaware of this manipulation, and will be told that the errors are actually due to poor signal processing and pattern recognition. The last study will then examine the trade-off between a system's state recognition accuracy and its user-friendliness with regard to user acceptance of the system. In all four studies, the outcome measures will be objective task performance as well as subjective user experience reported with the NASA Task Load Index and Intrinsic Motivation Inventory. This will provide the research community with detailed information about how different characteristics of affect-aware cyber-human systems influence both objective and subjective aspects of users' experiences with such systems.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.