Confidant: A Privacy Controller for Social Robots

Brian Tang, Dakota Sullivan, Bengisu Cagiltay, Varun Chandrasekaran, Kassem Fawaz, Bilge Mutlu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

As social robots become increasingly prevalent in day-to-day environments, they will participate in conversations and appropriately manage the information shared with them. However, little is known about how robots might appropriately discern the sensitivity of information, which has major implications for human-robot trust. As a first step to address a part of this issue, we designed a privacy controller, Confidant, for conversational social robots, capable of using contextual metadata (e.g., sentiment, relationships, topic) from conversations to model privacy boundaries. Afterwards, we conducted two crowdsourced user studies. The first study (n=174) focused on whether a variety of human-human interaction scenarios were perceived as either private/sensitive or non-private/non-sensitive. The findings from our first study were used to generate association rules. Our second study (n=95) evaluated the effectiveness and accuracy of the privacy controller in human-robot interaction scenarios by comparing a robot that used our privacy controller against a baseline robot with no privacy controls. Our results demonstrate that the robot with the privacy controller outperforms the robot without the privacy controller in privacy-awareness, trustworthiness, and social-awareness. We conclude that the integration of privacy controllers in authentic human-robot conversations can allow for more trustworthy robots. This initial privacy controller will serve as a foundation for more complex solutions.

Original languageEnglish (US)
Title of host publicationHRI 2022 - Proceedings of the 2022 ACM/IEEE International Conference on Human-Robot Interaction
PublisherIEEE Computer Society
Pages205-214
Number of pages10
ISBN (Electronic)9781538685549
DOIs
StatePublished - 2022
Externally publishedYes
Event17th Annual ACM/IEEE International Conference on Human-Robot Interaction, HRI 2022 - Sapporo, Japan
Duration: Mar 7 2022Mar 10 2022

Publication series

NameACM/IEEE International Conference on Human-Robot Interaction
Volume2022-March
ISSN (Electronic)2167-2148

Conference

Conference17th Annual ACM/IEEE International Conference on Human-Robot Interaction, HRI 2022
Country/TerritoryJapan
CitySapporo
Period3/7/223/10/22

Keywords

  • human-robot conversations
  • privacy
  • trust

ASJC Scopus subject areas

  • Artificial Intelligence
  • Human-Computer Interaction
  • Electrical and Electronic Engineering

Fingerprint

Dive into the research topics of 'Confidant: A Privacy Controller for Social Robots'. Together they form a unique fingerprint.

Cite this