research-article

The Robot Who Knew Too Much: Toward Understanding the Privacy/Personalization Trade-Off in Child-Robot Conversation

Authors:

Jill Fain LehmanAuthors Info & Claims

IDC '16: Proceedings of the The 15th International Conference on Interaction Design and Children

Pages 379 - 387

https://doi.org/10.1145/2930674.2930687

Published: 21 June 2016 Publication History

Abstract

In human-human conversation we elicit, share and use information as a way of defining and building relationships -- how information is revealed, and by whom, matters. A similar goal of using conversation as a relationship-building mechanism in human-robot interaction might or might not require the same degree of nuance. We explore what happens in the increasingly likely situation that a robot has sensed information about a child of which the child is unaware, then discloses that information in conversation in an effort to personalize the child's experience. In a pilot study, 28 children conversed with a social robot that either told a story with characters already introduced into the conversation by the child (control) or characters hidden by the child in a treasure chest that the child was holding (experimental). Cumulative evidence showed that all participants in the experimental condition noticed the robot's violation of expectations, but younger children (4 to 6 years) exhibited more contained emotional reactions than older children (7 to 10 years), and girls expressed more negative affect than boys. Despite the immediate response, post-conversation measures suggest that the single event did not have an impact on children's ratings of robot likeability or their willingness to interact with the robot again.

References

[1]

Samer Al Moubayed, Jonas Beskow, Gabriel Skantze, and Björn Granström. 2012. Furhat: A back-projected human-like robot head for multiparty human-machine interaction. In Cognitive Behavioural Systems. Springer, 114--130.

Digital Library

[2]

Luigi Atzori, Antonio Iera, and Giacomo Morabito. 2010. The internet of things: A survey. Computer networks 54, 15 (2010), 2787--2805.

Digital Library

[3]

Simon Baron-Cohen. 1997. Mindblindness: An essay on autism and theory of mind. MIT press.

[4]

Cindy L Bethel, Matthew R Stevenson, and Brian Scassellati. 2011. Secret-sharing: Interactions between a child, robot, and adult. In Proceedings of the IEEE International Conference on Systems, man, and cybernetics (SMC). IEEE, 2489--2494.

[5]

Nadia Chernyak and Heather E Gary. 2014. Autonomous Movement Predicts Children's Moral Regard and Prosocial Behavior Towards a Social Robot Dog. In Proceedings of 36th annual meeting of the Cognitive Science Society. 2032--2037.

[6]

H.H. Clark. 2006. Context and Common Ground. In Encyclopedia of Language & Linguistics (Second Edition) (second edition ed.), Keith Brown (Ed.). Elsevier, Oxford, 105--108. http://www.sciencedirect.com/science/article/pii/B0080448542010889

[7]

Alison Gopnik and Janet W Astington. 1988. Children's understanding of representational change and its relation to the understanding of false belief and the appearance-reality distinction. Child development (1988), 26--37.

[8]

Peter H Kahn, Heather E Gary, and Solace Shen. 2013. Children's Social Relationships With Current and Near-Future Robots. Child Development Perspectives 7, 1 (2013), 32--37.

[9]

Peter H Kahn Jr, Takayuki Kanda, Hiroshi Ishiguro, Nathan G Freier, Rachel L Severson, Brian T Gill, Jolina H Ruckert, and Solace Shen. 2012. "Robovie, you'll have to go into the closet now": Children's social and moral relationships with a humanoid robot. Developmental psychology 48, 2 (2012), 303.

[10]

Vera Khovanskaya, Eric P.S. Baumer, Dan Cosley, Stephen Voida, and Geri Gay. 2013. "Everybody Knows What You'Re Doing": A Critical Design Approach to Personal Informatics. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI '13). ACM, New York, NY, USA, 3403--3412.

Digital Library

[11]

Alfred Kobsa, Hichang Cho, and Bart P Knijnenburg. 2016. The effect of personalization provider characteristics on privacy attitudes and behaviors: An Elaboration Likelihood Model approach. Journal of the Association for Information Science and Technology (2016).

[12]

Séverin Lemaignan, Julia Fink, Francesco Mondada, and Piérre Dillenbourg. 2015. You're Doing It Wrong! Studying Unexpected Behaviors in Child-Robot Interaction. In Social Robotics, Adriana Tapus, Elisabeth André, Jean-Claude Martin, François Ferland, and Mehdi Ammi (Eds.). Lecture Notes in Computer Science, Vol. 9388. Springer International Publishing, 390--400. http://dx.doi.org/10.1007/978-3-319-25554-5_39

[13]

Vanessa LoBue, Tracy Nishida, Cynthia Chiong, Judy S DeLoache, and Jonathan Haidt. 2011. When getting something good is bad: Even three-year-olds react to inequality. Social Development 20, 1 (2011), 154--170.

[14]

Omar Mubin and Christoph Bartneck. 2015. Do as I say: Exploring human response to a predictable and unpredictable robot. In Proceedings of the 2015 British HCI Conference. ACM, 110--116.

Digital Library

[15]

Marina Nazario. 2015. This talking dinosaur for kids was named one of the best inventions of the year. (8 December 2015). Retrieved January 21, 2016 from http://www.businessinsider.com/cognitoys-talking-dinosaur-2015-12.

[16]

Jean Piaget. 1997. The moral judgement of the child. Simon and Schuster.

[17]

Janet C. Read and Stuart MacFarlane. 2006. Using the Fun Toolkit and Other Survey Methods to Gather Opinions in Child Computer Interaction. In Proceedings of the 2006 Conference on Interaction Design and Children (IDC '06). ACM, New York, NY, USA, 81--88. http://doi.acm.org/10.1145/1139073.1139096

Digital Library

[18]

Carolyn Saarni. 1988. Children's understanding of the interpersonal consequences of dissemblance of nonverbal emotional-expressive behavior. Journal of Nonverbal Behavior 12, 4 (1988), 275--294.

[19]

E. Short, J. Hart, M. Vu, and B. Scassellati. 2010. No fair!! An interaction with a cheating robot. In Proceedings of the 5th ACM/IEEE International Conference on Human-Robot Interaction (HRI). 219--226.

Digital Library

[20]

Juliana Sutanto, Elia Palme, Chuan-Hoo Tan, and Chee Wei Phang. 2013. Addressing the personalization-privacy paradox: an empirical assessment from a field experiment on smartphone users. Mis Quarterly 37, 4 (2013), 1141--1164.

Digital Library

[21]

Fumihide Tanaka, Aaron Cicourel, and Javier R Movellan. 2007. Socialization between toddlers and robots at an early childhood education center. Proceedings of the National Academy of Sciences 104, 46 (2007), 17954--17958.

[22]

Daniel Ullman, Iolanda Leite, Jonathan Phillips, Julia Kim-Cohen, and Brian Scassellati. 2014. Smart human, smarter robot: How cheating affects perceptions of social agency. In Proceedings of the 36th Annual Conference of the Cognitive Science Society (CogSci2014).

[23]

Marynel Vazquez, Alexander May, Aaron Steinfeld, and Wei-Hsuan Chen. 2011. A deceptive robot referee in a multiplayer gaming environment. In Proceedings of the 2011 International Conference on Collaboration Technologies and Systems (CTS). 204--211.

[24]

E Fosch Villaronga and J Albo-Canalsb. 2015. Boundaries in Play-based Cloud-companion-mediated Robotic Therapies: From Deception to Privacy Concerns. In Proceedings of the 1st International Conference on Social Robots in Therapy and Education (New Friends).

[25]

James Vlahos. 2015. Barbie Wants to Get to Know Your Child. (15 September 2015). Retrieved January 21, 2016 from http://www.nytimes.com/2015/09/20/magazine/barbie-wants-to-get-to-know-your-child.html?smtyp=cur&_r=1.

[26]

Jacqueline Kory Westlund and Cynthia Breazeal. 2015. Deception, Secrets, Children, and Robots: What's Acceptable? Workshop on The Emerging Policy and Ethics of Human-Robot Interaction (2015).

[27]

J.P. Whitney, T. Chen, J. Mars, and J.K. Hodgins. 2016. A hybrid hydrostatic transmission and human-safe haptic telepresence robot. In 2016 IEEE International Conference on Robotics and Automation (ICRA), Stockholm, Sweden (to appear). IEEE.

[28]

Janice Zeman and Judy Garber. 1996. Display rules for anger, sadness, and pain: It depends on who is watching. Child development 67, 3 (1996), 957--973.

Cited By

Dubois-Sage MJacquet BJamet FBaratgin J(2024)People with Autism Spectrum Disorder Could Interact More Easily with a Robot than with a Human: Reasons and LimitsBehavioral Sciences10.3390/bs1402013114:2(131)Online publication date: 12-Feb-2024
https://doi.org/10.3390/bs14020131
Chen YYeh SLin WYueh HFu L(2023)The Effects of Social Presence and Familiarity on Children–Robot InteractionsSensors10.3390/s2309423123:9(4231)Online publication date: 24-Apr-2023
https://doi.org/10.3390/s23094231
Dubois-Sage MJacquet BJamet FBaratgin J(2023)We Do Not Anthropomorphize a Robot Based Only on Its Cover: Context Matters too!Applied Sciences10.3390/app1315874313:15(8743)Online publication date: 28-Jul-2023
https://doi.org/10.3390/app13158743
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Index Terms

The Robot Who Knew Too Much: Toward Understanding the Privacy/Personalization Trade-Off in Child-Robot Conversation
1. Human-centered computing
  1. Human computer interaction (HCI)

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cover image ACM Conferences

IDC '16: Proceedings of the The 15th International Conference on Interaction Design and Children

June 2016

774 pages

ISBN:9781450343138

DOI:10.1145/2930674

Conference Chairs:
Janet C. Read
University of Central Lancashire, UK
,
Phil Stenton
BBC Research & Development, UK

Copyright © 2016 ACM.

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Published: 21 June 2016

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IDC '16

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SIGCHI

IDC '16: Interaction Design and Children

June 21 - 24, 2016

Manchester, United Kingdom

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IDC '16 Paper Acceptance Rate 36 of 77 submissions, 47%;

Overall Acceptance Rate 172 of 578 submissions, 30%

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Cited By

Dubois-Sage MJacquet BJamet FBaratgin J(2024)People with Autism Spectrum Disorder Could Interact More Easily with a Robot than with a Human: Reasons and LimitsBehavioral Sciences10.3390/bs1402013114:2(131)Online publication date: 12-Feb-2024
https://doi.org/10.3390/bs14020131
Chen YYeh SLin WYueh HFu L(2023)The Effects of Social Presence and Familiarity on Children–Robot InteractionsSensors10.3390/s2309423123:9(4231)Online publication date: 24-Apr-2023
https://doi.org/10.3390/s23094231
Dubois-Sage MJacquet BJamet FBaratgin J(2023)We Do Not Anthropomorphize a Robot Based Only on Its Cover: Context Matters too!Applied Sciences10.3390/app1315874313:15(8743)Online publication date: 28-Jul-2023
https://doi.org/10.3390/app13158743
Kumar PO'Connell FLi LByrne VChetty MClegg TVitak J(2023)Understanding Research Related to Designing for Children's Privacy and Security: A Document AnalysisProceedings of the 22nd Annual ACM Interaction Design and Children Conference10.1145/3585088.3589375(335-354)Online publication date: 19-Jun-2023
https://dl.acm.org/doi/10.1145/3585088.3589375
van Straten CPeter JKühne R(2023)Transparent robots: How children perceive and relate to a social robot that acknowledges its lack of human psychological capacities and machine statusInternational Journal of Human-Computer Studies10.1016/j.ijhcs.2023.103063177(103063)Online publication date: Sep-2023
https://doi.org/10.1016/j.ijhcs.2023.103063
Kraus MDettenhofer VMinker WBellogin ABoratto LSantos OArdissono LKnijnenburg B(2022)Responsible Interactive Personalisation for Human-Robot CooperationAdjunct Proceedings of the 30th ACM Conference on User Modeling, Adaptation and Personalization10.1145/3511047.3536419(58-62)Online publication date: 4-Jul-2022
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van Straten CPeter JKühne RBarco A(2022)On sharing and caringComputers in Human Behavior10.1016/j.chb.2021.107135129:COnline publication date: 1-Apr-2022
https://dl.acm.org/doi/10.1016/j.chb.2021.107135
Björling ELouie BWiesmann PKuo A(2021)Engaging English Language Learners as Cultural Informants in the Design of a Social Robot for EducationMultimodal Technologies and Interaction10.3390/mti50700355:7(35)Online publication date: 30-Jun-2021
https://doi.org/10.3390/mti5070035
Zguda PKołota AVenture GSniezynski BIndurkhya B(2021)Exploring the Role of Trust and Expectations in CRI Using In-the-Wild StudiesElectronics10.3390/electronics1003034710:3(347)Online publication date: 2-Feb-2021
https://doi.org/10.3390/electronics10030347
Heuer TSchiering IGerndt R(2021)Privacy framework for context-aware robot developmentPaladyn, Journal of Behavioral Robotics10.1515/pjbr-2021-003212:1(468-480)Online publication date: 31-Dec-2021
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