Collaborative Research: The role of trust when learning from robots

十年前，机器人通常扮演“工具”或“队友”的角色。今天，尽管有一些明显的情况下，“工具”或“队友”模式是合适的，但大多数长期部署在家庭、工作场所或学校的协作机器人很容易在代理的“队友”和无生命的“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，但这种转变对人际关系属性的影响尚不清楚，这些属性通常只被归因于具有代理能力的“队友”机器人。这个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根本不同。当机器人变成一个无生命的工具时，当它成为一个代理时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有代理能力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培养对机器人的信任的理解方面的一个重大空白。虽然对非智能型机器人的信任是众所周知的，但对作为协作工具的机器人的信任却很少有系统的研究。这项工作在未来机器人系统的部署中具有广泛的应用，这些系统在代理(类人类)和非代理(类对象)行为之间随着时间的变化而变化。研究人员将集中在一个重要的应用领域：儿童学习中，机构在建立人与机器人互动中的信任方面所起的作用。专门为儿童设计的教育机器人越来越普遍，经常取代人类的社交信息渠道。然而，没有信任，这些机器人就不会成功；因为孩子天生就是社交和合作的学习者，信任是成功学习的先决条件。该项目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，将确定感知机构的变化如何影响信任的形成、维持和修复：研究1调查了低水平感知线索在单一互动中的变化如何影响信任和随后的学习。研究2考察了高层社交线索的变化如何导致不同的信任和随后的学习。针对这些实验，设计了一套适合年龄的协作学习游戏。研究人员还创建了儿童行为的编码方案，以及互动后的儿童访谈，以评估儿童对机器人的看法，并衡量学习的有效性。这个项目的发现和活动可能在多个领域产生广泛的影响，包括：(1)设计指导方针，将影响包括医疗保健、制造和教育在内的广泛应用领域；(2)加强/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)向公众和研究社区传播科学。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

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.