SaTC: CORE: Medium: Designing Privacy-Aware Social Companion Robots

社交伴侣机器人可以以类似人类的方式与人互动，使用语音，手势和物理存在。它们旨在帮助家庭进行膳食计划，儿童发展和沟通等活动。然而，它们先进的传感和推理能力可能会导致隐私问题，因为它们可以收集、推断和共享有关用户的个人信息。例如，当他们在家里走动和行动时，他们可以偷听到私人谈话。它们还可以访问敏感环境，如卧室，并且可以设计成看起来像熟悉的物体或人，这可能导致人们过度共享个人信息。他们也可能不适当地透露他们从其他住户或访客那里了解到的信息。因此，设计更多“隐私意识”的社交伴侣机器人至关重要，这些机器人可以推理何时收集和共享数据，何时不收集和共享数据，并以上下文适当的方式匹配人们对隐私的需求。这个跨学科项目旨在为具有隐私意识的社交机器人创建设计原则，以改善家庭环境中的人机交互。这些原则将告知机器人如何在家庭、工作场所、学校和医疗保健中设计、使用和接受。此外，该项目将通过媒体报道、研讨会和办公时间，通过外联活动提高家庭对智能环境中隐私的理解。该项目的教育活动将在隐私系统、家庭研究和人机交互方面对K-12和大学生进行培训。最后，项目团队将分享代码，出版物，原型和基于工作的数据集。该项目开发，实现和评估一个新的人机交互隐私框架，分为四个阶段。该框架模型用户的隐私期望，采用新的概念接地人机交互，开发新的方法来帮助用户管理自己的隐私，并使家庭内的隐私动态研究。具体来说，第一阶段对用户对社交机器人的隐私问题和期望进行建模，开发一个隐私框架，以确定隐私意识最重要的日常情况。第二阶段将框架实例化为用于捕获社会隐私动态的机器人动作的隐私控制器。隐私控制器的核心是一个可定制的架构，该架构基于从机器人环境中提取的高级上下文因素（例如房屋中的位置和在场的人数）生成隐私感知动作。第三阶段探索机器人如何利用隐私控制器架构向用户发出信号，演示或解释机器人的隐私感知行为。通过部署研究，第四阶段评估了隐私意识对机器人管理参与家庭生活的复杂隐私权衡的影响。这些研究的结果将为理解隐私感知社交机器人对家庭动态的好处、影响和限制提供实证基础。该奖项反映了NSF的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。

Social companion robots can interact with people in a human-like way, using speech, gestures, and physical presence. They are designed to help families with activities like meal planning, child development, and communication. However, their advanced sensing and reasoning capabilities can lead to privacy concerns, as they can collect, infer, and share personal information about their users. For instance, they can overhear private conversations as they move and act in the home. They also access sensitive environments, such as bedrooms, and can be designed to look like familiar objects or people, which can lead to people oversharing personal information. They might also inappropriately disclose information they learned with other home occupants or visitors. Therefore, it is crucial to design more “privacy-aware” social companion robots that can reason about when to collect and share data, and when not to, in ways that are context-appropriate and match people’s needs for privacy. This interdisciplinary project aims to create design principles for privacy-aware social robots to improve human-robot interactions in home environments. These principles will inform how robots are designed, used, and accepted in homes, workplaces, schools, and healthcare. Further, through outreach activities, the project will improve families’ understanding of privacy in smart environments through media coverage, workshops, and office hours. The educational activities of the project will train K-12 and college students in privacy systems, family studies, and human-computer interaction. Finally, the project team will share code, publications, prototypes, and datasets based on the work.This project develops, implements, and evaluates a novel privacy framework for human-robot interaction in four phases. This framework models users' privacy expectations, employs novel concepts grounded in human-robot interaction, develops new methods to help users manage their own privacy, and enables a study of privacy dynamics within families. Specifically, Phase I models users' privacy concerns and expectations regarding social robots, developing a privacy framework to identify everyday situations in which privacy awareness is most important. Phase II instantiates the framework as a privacy controller for the robot’s actions that captures the dynamics of social privacy. At the core of the privacy controller is a customizable architecture that generates privacy-aware actions based on extracted high-level contextual factors from the robot's environment, such as location in the house and number of people present. Phase III explores how the robot can leverage the privacy controller architecture to signal, demonstrate, or explain the robot's privacy-aware actions to users. Through deployment studies, phase IV assesses the impact of privacy awareness on the robot's management of the complex privacy trade-offs involved in participation in family life. The findings of these studies will provide an empirical basis for understanding a privacy-aware social robot's benefits, effects, and limitations on family dynamics.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.