Social Robots in Healthcare: Characterizing Privacy Considerations

被引：1

作者：

Jayaraman, Sandhya ^{[1
]}

Phillips, Elizabeth K. ^{[2
]}

Church, Daisy ^{[3
]}

Riek, Laurel D. ^{[1
]}

机构：

[1] Univ Calif San Diego, San Diego, CA 92093 USA

[2] George Mason Univ, Fairfax, VA USA

[3] Acad Art Univ, San Francisco, CA USA

来源：

COMPANION OF THE 2024 ACM/IEEE INTERNATIONAL CONFERENCE ON HUMAN-ROBOT INTERACTION, HRI 2024 COMPANION | 2024年

关键词：

Human robot interaction; Robotics; Healthcare robotics; Privacy; Utility; Design fictions; Robot humanlikeness; APPEARANCE; HOME;

D O I：

10.1145/3610978.3640713

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

As healthcare robots gain traction, human-robot interaction (HRI) researchers are exploring the factors that impact user adoption and trust in these robots. Due to the sensitive nature of care, privacy concerns play a significant role in determining robot utility, usefulness, and adoption. In our work, we conducted a 3x3x3 online study (N = 239) to explore peoples' perceptions of privacy and utility of 3 robots at varying levels of Human-Likeness (HL) across 3 realistic healthcare contexts. The results show that the context of care delivery is a key driver of perceptions of privacy and acceptable privacy-utility trade-offs. Interestingly, the HL of robot design may not significantly impact peoples' privacy perceptions of healthcare robots. We plan to leverage these key findings to develop privacy-aware robot behaviors that are context adaptable in order to improve privacy outcomes for healthcare robots.

引用

页码：568 / 572

页数：5

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