Collaborative Research: The role of trust when learning from robots

协作研究：向机器人学习时信任的作用

• 批准号: 1955280
• 负责人: Tamar Kushnir
• 金额: $ 36.79万
• 依托单位: Cornell University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-09-15 至 2021-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1955280&HistoricalAwards=false
• 关键词: Collaborative; Research; role; trust; when

A decade ago, robots typically played the role of “tool” or “teammate”. Today, although there are some clear cases where the “tool” or “teammate” model is appropriate, most collaborative robots in long-term deployments in homes, workplaces, or schools readily switch back and forth between being an agentic “teammate” to an inanimate “tool”. While people tolerate this shift in perceived agency, it is unknown how this shift impacts interpersonal properties that are typically attributed only to agentic “teammate” robots. This project will evaluate factors that affect how people trust robots, recognizing that the way humans “trust” non-agentic automation is fundamentally different from the way that we “trust” agents and agentic robots. What happens to the trust formed while a robot is an agent when it becomes an inanimate tool? What happens when the inanimate tool returns to being an agentic teammate? The proposed research will fill a significant gap in our understanding of how young humans develop trust in robots. While trust in non-agentic robots is well understood, there has been little systematic study of trust in robots that function as collaborative tools. This work has broad applications to future deployment of robots as systems that vary over time between agentic (human-like) and non-agentic (object-like) behavior. The investigators will concentrate on the role of agency in establishing trust in human-robot interactions in an important application domain: children’s learning. Educational robots designed specifically for children are increasingly common, often replacing human channels of social information. However, these robots cannot be successful without trust; because children are inherently social and collaborative learners, trust is a prerequisite for successful learning. Integrating insights from interactive robot design into experiments with preschool and early school age children, the project will determine how shifts in perceived agency impact the formation, maintenance, and repair of trust: Study 1 investigates how variations of low-level perceptual cues over a single interaction influence trust and subsequent learning. Study 2 examines how variations of high-level social cues lead to differential trust and subsequent learning. For these experiments, a set of age-appropriate collaborative learning games were designed. The investigators also created a coding scheme for child behavior as well as a post-interaction child interview to assess children’s perceptions of the robots and to measure effectiveness of learning. Findings and activities of this project could have broad impacts in multiple arenas including: (1) design guidelines that will influence a broad range of application areas including healthcare, manufacturing, and education; (2) enhancement/augmentation of learning, education and training, including research offerings for graduate and undergraduate investigators; (3) broadening of participation in one area of computing, and (4) dissemination of science to the general public and to the research community.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.

十年前，机器人通常扮演“工具”或“队友”的角色。今天，虽然有一些“工具”或“队友”模型是合适的，但在家庭、工作场所或学校的长期部署中，大多数协作机器人很容易在一个有代理的“队友”和一个没有生命的“工具”之间来回切换。虽然人们可以容忍这种感知代理的转变，但尚不清楚这种转变如何影响通常只归因于代理“队友”机器人的人际关系属性。该项目将评估影响人们如何信任机器人的因素，认识到人类“信任”非代理自动化的方式与我们“信任”代理和代理机器人的方式有着根本的不同。当机器人成为一个没有生命的工具时，它作为代理人所形成的信任会发生什么？当这个无生命的工具重新成为一个真正的队友时会发生什么？这项拟议的研究将填补我们对年轻人如何对机器人产生信任的理解上的重大空白。虽然对非代理机器人的信任已经得到了很好的理解，但对作为协作工具的机器人的信任却很少有系统的研究。这项工作在未来的机器人部署中具有广泛的应用，作为在代理（类人）和非代理（类物体）行为之间随时间变化的系统。研究人员将集中在一个重要的应用领域：儿童学习中，代理在建立人机交互信任中的作用。专门为儿童设计的教育机器人越来越普遍，经常取代人类的社会信息渠道。然而，没有信任，这些机器人就无法成功；因为儿童天生是社会性和合作性的学习者，信任是成功学习的先决条件。将互动机器人设计的见解整合到学龄前和学龄前儿童的实验中，该项目将确定感知代理的变化如何影响信任的形成、维护和修复：研究1调查了单一互动中低级感知线索的变化如何影响信任和随后的学习。研究2探讨了不同的高层次社会线索如何导致不同的信任和随后的学习。在这些实验中，我们设计了一套适合年龄的协作学习游戏。研究人员还为儿童行为制定了一个编码方案，并对儿童进行了互动后的访谈，以评估儿童对机器人的看法，并衡量学习的有效性。该项目的研究结果和活动可能在多个领域产生广泛影响，包括：(1)将影响医疗保健、制造业和教育等广泛应用领域的设计指南；(2)加强学习、教育和培训，包括为研究生和本科生研究人员提供研究服务；(3)扩大在一个计算领域的参与；(4)向公众和研究界传播科学。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。