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The Robot Privacy Paradox: Understanding How Privacy Concerns Shape Intentions to Use Social Robots

Christoph Lutz, Aurelia Tamò‐Larrieux

Year
2020
Citations
127
Access
Open access

Abstract

Conceptual research on robots and privacy has increased but we lack empirical evidence about the prevalence, antecedents, and outcomes of different privacy concerns about social robots. To fill this gap, we present a survey, testing a variety of antecedents from trust, technology adoption, and robotics scholarship. Respondents are most concerned about data protection on the manufacturer side, followed by social privacy concerns and physical concerns. Using structural equation modeling, we find a privacy paradox, where the perceived benefits of social robots override privacy concerns.

Keywords

RobotInformation privacyInternet privacyVariety (cybernetics)ScholarshipPrivacy by DesignStructural equation modelingEmpirical researchSocial robotRobotics

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