用户更看重对机器人如何使用数据的控制权，而非透明度或主动服务。
Privacy Perceptions in Robot-Assisted Well-Being Coaching: Examining the Roles of Information Transparency, User Control, and Proactivity
- 通过实验测试信息透明度、用户控制权和机器人主动性对隐私感知的影响。
- 有具体控制权时，用户对隐私保护的满意度和信任感显著提升。
- 在社交机器人辅助健康辅导中，控制权比透明度和主动性更重要。
社交机器人在心理健康辅导中日益发挥重要作用，可独立或协同人类教练提供支持。由于涉及用户敏感信息，隐私问题备受关注。然而，影响用户隐私感知的关键因素仍不明确。本研究系统考察了三个因素：（1）信息使用透明度，（2）用户对信息处理的具体控制权，（3）机器人行为模式——主动型或被动响应型。基于200名参与者在线实验的结果显示，即使用户已授权机器人访问个人数据，仍期望能明确控制信息在会话中的解读与共享方式。提供此类控制权的条件，显著提升了用户对隐私恰当性的感知和信任度。相比之下，透明度和主动性对隐私感知的影响较小且不显著。结果表明，仅告知用户或主动提供服务不足以保障隐私感受，必须配合用户控制机制。该发现强调了未来需进一步探索用户管理机器人信息处理与共享的机制，尤其当机器人承担更主动角色时。
原文摘要 · Abstract (English)
Social robots are increasingly recognized as valuable supporters in the field of well-being coaching. They can function as independent coaches or provide support alongside human coaches, and healthcare professionals. In coaching interactions, these robots often handle sensitive information shared by users, making privacy a relevant issue. Despite this, little is known about the factors that shape users' privacy perceptions. This research aims to examine three key factors systematically: (1) the transparency about information usage, (2) the level of specific user control over how the robot uses their information, and (3) the robot's behavioral approach - whether it acts proactively or only responds on demand. Our results from an online study (N = 200) show that even when users grant the robot general access to personal data, they additionally expect the ability to explicitly control how that information is interpreted and shared during sessions. Experimental conditions that provided such control received significantly higher ratings for perceived privacy appropriateness and trust. Compared to user control, the effects of transparency and proactivity on privacy appropriateness perception were low, and we found no significant impact. The results suggest that merely informing users or proactive sharing is insufficient without accompanying user control. These insights underscore the need for further research on mechanisms that allow users to manage robots' information processing and sharing, especially when social robots take on more proactive roles alongside humans.
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