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Understanding users' perception of privacy in human-robot interaction

Min Kyung Lee, Karen Tang, Jodi Forlizzi, Sara Kiesler

Year
2011
Citations
82

Abstract

Previous research has shown that design features that support privacy are essential for new technologies looking to gain widespread adoption. As such, privacy-sensitive design will be important for the adoption of social robots, as they could introduce new types of privacy risks to users. In this paper, we report findings from our preliminary study on users' perceptions and attitudes toward privacy in human-robot interaction, based on interviews that we conducted about a workplace social robot.

Keywords

RobotPerceptionInternet privacyComputer scienceHuman–robot interactionPrivacy by DesignHuman–computer interactionInformation privacyPrivacy softwareArtificial intelligence

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