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Investigating Customers’ Perceived Sensitivity of Information Shared with a Robot Bartender

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Book cover Social Robotics (ICSR 2021)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 13086))

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Abstract

Personalised experiences with service robots positively affect people’s perception of the robot and, consequently, foster the success of the interaction. This implies that people need to share their personal information with the robot, which could let people feel uneasy when such interactions happen in public spaces or in the presence of strangers. Therefore, it is difficult for a service robot to personalise a human-robot interaction (HRI) when this can lead to a breach of privacy. As a first step, the current study investigated people’s perception of the sensitivity of various categories of potentially private personal information that are likely to be used by a service robot in a public business, such as a bar. We conducted a questionnaire-based study, where participants rated 15 personal information that they could share with either a human or robot bartender. The potentially private information was rated by participants according to their level of sensitivity. We analysed responses from 76 participants. We clearly identified information that are perceived as highly sensitive, such as those related to a person’s identity (e.g. sexual orientation, political beliefs), and as low in sensitivity, such as those related to personal interests (e.g. sports, TV shows). Our findings also showed that older people consider sharing their preference of drinks more sensitive than younger people, especially when the bartender is a robot. We did not find significant differences in users’ ratings due to their gender.

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Notes

  1. 1.

    Note that we did not ask participants to give us their personal information. We simply asked them to rate the sensitivity level of such information.

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Acknowledgements

This work has been supported by Italian PON I&C 2014-2020 within the BRILLO research project “Bartending Robot for Interactive Long-Lasting Operations”, no. F/190066/01-02/X44.

Author information

Authors and Affiliations

  1. ICAROS Center, University of Naples Federico II, Naples, Italy

    Alessandra Rossi & Silvia Rossi

  2. Department of Information Technology, Uppsala University, Uppsala, Sweden

    Giulia Perugia

  3. Human Technology Interaction Group, Department of Industrial Engineering and Innovation Sciences, Eindhoven University of Technology, Eindhoven, The Netherlands

    Giulia Perugia

  4. Department of Electrical Engineering and Information Technologies, University of Naples Federico II, Naples, Italy

    Silvia Rossi

Authors
  1. Alessandra Rossi
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  2. Giulia Perugia
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  3. Silvia Rossi
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Corresponding author

Correspondence to Alessandra Rossi .

Editor information

Editors and Affiliations

  1. Department of Electronic and Communication Engineering, National University of Singapore, Faculty of Engineering, Singapore, Singapore

    Haizhou Li

  2. The National University of Singapore, Singapore, Singapore

    Shuzhi Sam Ge

  3. A*STAR Institute for Infocomm Research, Singapore, Singapore

    Yan Wu

  4. Center for Human Technologies, Istituto Italiano Tecnologia, Genoa, Italy

    Agnieszka Wykowska

  5. Department of Electrical Engineering and Computer Science, Wichita State University, Wichita, KS, USA

    Hongsheng He

  6. Qingdao University, Qingdao, China

    Xiaorui Liu

  7. School of Cyber Science and Technology, Beihang University, Beijing, Beijing, China

    Dongyu Li

  8. Social Cognition Human-Robot Interaction, Istituto Italiano di Tecnologia, Genoa, Italy

    Jairo Perez-Osorio

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Rossi, A., Perugia, G., Rossi, S. (2021). Investigating Customers’ Perceived Sensitivity of Information Shared with a Robot Bartender. In: Li, H., et al. Social Robotics. ICSR 2021. Lecture Notes in Computer Science(), vol 13086. Springer, Cham. https://doi.org/10.1007/978-3-030-90525-5_11

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  • DOI: https://doi.org/10.1007/978-3-030-90525-5_11

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