位置：机器人隐私作为具身边界工作——连接日常机器人中的能力、情境与设计响应
Position: Robot Privacy as Embodied Boundary Work. Connecting Capabilities, Contexts, and Design Responses in Everyday Robotics
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- The Hong Kong University of Science and Technology (Guangzhou)（香港科技大学（广州））
- Tsinghua University（清华大学）
- Beijing Academy of Artificial Intelligence（北京智源人工智能研究院）
- The Hong Kong University of Science and Technology（香港科技大学）
机构由 AI 辅助整理，请以论文原文为准。
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中文总结 AI 辅助
本研究提出具身边界隐私框架，结合机器人7种能力与5种部署情境分析其隐私风险，给出具身隐私机制设计启示，呼吁HRI领域关注机器人具身行动的隐私意义。
中文摘要 AI 辅助
机器人正日益进入日常环境，隐私不仅由数据实践塑造，还受空间、身体、社会及关系边界的影响。它们的具身能力使其能通过情境化行动重塑这些边界，对以数据流、界面设置或一次性同意为核心的隐私框架提出挑战。现有研究已从传感、数据收集、远程临场感、透明度、同意、旁观者意识及多利益相关方治理等角度探讨机器人隐私。本研究在上述工作基础上，提出具身边界隐私作为一种“按能力-情境”框架，用于研究物理存在的机器人如何在情境化交互中重塑隐私边界。具体而言，该框架将隐私风险按机器人的7种能力和5种部署情境进行组织，探究具身能力如何实现边界跨越、情境如何决定受影响主体、这些跨越的解读方式以及何时引发争议。本研究运用该视角，概述具身隐私机制的设计与研究启示，包括边界检查点、视角感知传感控制、远程临场感披露、物体与身体层面的访问规则、对社会说服性隐私影响的约束以及本地中断权。本研究鼓励人机交互（HRI）领域的研究、设计与治理将机器人的移动、朝向、 proximity（接近度）、物体访问、远程临场感及社会表达视为与隐私相关的行动，其意义取决于具体情境。
英文摘要
Robots are increasingly entering everyday environments where privacy is shaped not only by data practices, but also by spatial, bodily, social, and relational boundaries. Their embodied capabilities allow them to reshape these boundaries through situated action, challenging privacy framings centered on data flows, interface settings, or one-time consent. Prior work has examined robot privacy through sensing, data collection, telepresence, transparency, consent, bystander awareness, and multi-stakeholder governance. Building on this work, we propose embodied boundary privacy as a capability-by-context framing for examining how physically present robots may reshape privacy boundaries in situated interaction. Specifically, this framing organizes privacy risks across seven robot capabilities and five deployment contexts, asking how embodied capabilities enable boundary crossings and how situated contexts shape who is affected, how these crossings are interpreted, and when they become contested. We use this perspective to outline design and research implications for embodied privacy mechanisms, including boundary checkpoints, viewpoint-aware sensing control, remote-presence disclosure, object- and body-level access rules, constraints on socially persuasive privacy influence, and local interruption rights. We encourage HRI research, design, and governance to treat robot movement, orientation, proximity, object access, remote presence, and social expression as privacy-relevant actions whose meaning depends on context.
