Household robots boasting mobility, more sophisticated sensors, and powerful processing models have become increasingly prevalent in the commercial market. However, these features may expose users to unwanted privacy risks, including unsolicited data collection and unauthorized data sharing. While security and privacy researchers thus far have explored people's privacy concerns around household robots, literature investigating people's preferred privacy designs and mitigation strategies is still limited. Additionally, the existing literature has not yet accounted for multi-user perspectives on privacy design and household robots. We aimed to fill this gap by conducting in-person participatory design sessions with 15 households to explore how they would design a privacy-aware household robot based on their concerns and expectations. We found that participants did not trust that robots, or their respective manufacturers, would respect the data privacy of household members or operate in a multi-user ecosystem without jeopardizing users' personal data. Based on these concerns, they generated designs that gave them authority over their data, contained accessible controls and notification systems, and could be customized and tailored to suit the needs and preferences of each user over time. We synthesize our findings into actionable design recommendations for robot manufacturers and developers.

翻译：家用机器人凭借其移动性、更精密的传感器和强大的处理模型，在商业市场上日益普及。然而，这些特性可能使用户面临不必要的隐私风险，包括未经请求的数据收集和未经授权的数据共享。尽管安全与隐私研究人员已探讨了人们对家用机器人的隐私担忧，但关于人们偏好的隐私设计和缓解策略的研究仍较为有限。此外，现有文献尚未充分考虑多用户视角下的隐私设计与家用机器人。为填补这一空白，我们与15个家庭进行了面对面的参与式设计讨论，探究他们如何基于自身担忧和期望来设计具备隐私意识的家用机器人。研究发现，参与者不信任机器人或其制造商能够尊重家庭成员的隐私数据，也不相信它们能在多用户生态系统中运行而不危及用户的个人数据。基于这些担忧，他们提出了赋予用户数据自主权、包含易用控制与通知系统、并能随时间推移定制化以适应每位用户需求和偏好的设计方案。我们将研究发现整合为对机器人制造商和开发者的可操作设计建议。