Iolanda Leite
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.
- 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. Google Scholar
Digital Library
- Luigi Atzori, Antonio Iera, and Giacomo Morabito. 2010. The internet of things: A survey. Computer networks 54, 15 (2010), 2787--2805. Google ScholarDigital Library
- Simon Baron-Cohen. 1997. Mindblindness: An essay on autism and theory of mind. MIT press.Google Scholar
- 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.Google ScholarCross Ref
- 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.Google Scholar
- 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/B0080448542010889Google Scholar
- 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.Google Scholar
- 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.Google ScholarCross Ref
- 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.Google Scholar
- 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. DOI: http://dx.doi.org/10.1145/2470654.2466467 Google ScholarDigital Library
- 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).Google Scholar
- 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_39Google Scholar
- 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.Google ScholarCross Ref
- 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. Google ScholarDigital Library
- 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.Google Scholar
- Jean Piaget. 1997. The moral judgement of the child. Simon and Schuster.Google Scholar
- 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 Google ScholarDigital Library
- 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.Google ScholarCross Ref
- 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. Google ScholarDigital Library
- 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. Google ScholarDigital Library
- 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.Google ScholarCross Ref
- 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).Google Scholar
- 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.Google ScholarCross Ref
- 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).Google Scholar
- 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.Google Scholar
- 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).Google Scholar
- 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.Google Scholar
- 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.Google Scholar
Index Terms
- The Robot Who Knew Too Much: Toward Understanding the Privacy/Personalization Trade-Off in Child-Robot Conversation
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