Evolving Framework for Building Companionship Among Human and Assistive Systems

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9733)

Abstract

The recent progress in artificial intelligence is allowing assistive systems like the voice-based assistant, virtual agents to become more personalized and adaptable. The role of these systems is also shifting from being a mere assistant to a person-al companion. However ‘personal companionship’ being a subjective term lies open to interpretation, thus posing a challenge for the creators of these assistive systems. This study is an attempt to address this challenge with a user-centric approach. Based on insights gathered from an activity based method called forced photo elicitation techniques with 25 users, we evolved Human Machine Companionship Framework, as a reference tool for designing effective personalized connections between assistive systems and its user. We describe each of the essential behavioural traits that a companion should exhibit and their evolution with time and information gained. Lastly, we establish the use of this companionship framework by discussing its application in case of the social robots.

Keywords

Companionship Personalization Elicitation techniques Assistive systems Human-Human interaction Human-Computer interaction 

References

  1. 1.
    Wilks, Y.: Artificial companions as a new kind of interface to the future internet. Chicago (2006)Google Scholar
  2. 2.
    Floridi, L.: Artificial intelligence’s new frontier: artificial companions and the fourth revolution. Metaphilosophy 39(4–5), 651–655 (2008). ChicagoCrossRefGoogle Scholar
  3. 3.
    Traue, H.C., Ohl, F., Brechmann, A., Schwenker, F., Kessler, H., Limbrecht, K., Walter, S.: A framework for emotions and dispositions in man-companion interaction. In: Coverbal Synchrony in Human-Machine Interaction, pp. 99–140. Science Publishers, New Hampshire, USA (2013)Google Scholar
  4. 4.
    Dautenhahn, K., Woods, S., Kaouri, C., Walters, M.L., Koay, K.L., Werry, I.: What is a robot companion-friend, assistant or butler? In: 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2005), pp. 1192–1197. IEEE (2005)Google Scholar
  5. 5.
    Meerbeek, B., Saerbeck, M., Bartneck, C.: Iterative design process for robots with personality. In: Kerstin Dautenhahn, editeur, AISB2009 Symposium on New Frontiers in Human-Robot Interaction, pp. 94–101 (2009)Google Scholar
  6. 6.
    Ruckert, J.H., Kahn Jr., P.H., Kanda, T., Ishiguro, H., Shen, S., Gary, H.E.: Designing for sociality in HRI by means of multiple personas in robots. In: Proceedings of the 8th ACM/IEEE International Conference on Human-Robot Interaction, pp. 217–218. IEEE Press (2013)Google Scholar
  7. 7.
    Pereira, A., Leite, I., Mascarenhas, S., Martinho, C., Paiva, A.: Using empathy to improve human-robot relationships. In: Lamers, M.H., Verbeek, F.J. (eds.) Human-Robot Personal Relationships. LNICST, vol. 59, pp. 130–138. Springer, Heidelberg (2011)CrossRefGoogle Scholar
  8. 8.
    Tapus, A., Mataric, M.J.: Socially assistive robots: the link between personality, empathy, physiological signals, and task performance. In: AAAI Spring Symposium: Emotion, Personality, and Social Behavior, pp. 133–140 (2008)Google Scholar
  9. 9.
    Walter, S., Wendt, C., Böhnke, J., Crawcour, S., Tan, J.W., Chan, A., Traue, H.C.: Similarities and differences of emotions in human–machine and human–human interactions: what kind of emotions are relevant for future companion systems? Ergonomics 57(3), 374–386 (2014)CrossRefGoogle Scholar
  10. 10.
    Reeves, B., Nass, C.: The media equation: how people treat computers, televisions, and new media like real people and places. Cambridge University Press, New York (1996)Google Scholar
  11. 11.
    Harper, D.: Talking about pictures: a case for photo elicitation. Visual Stud. 17(1), 13–26 (2002)CrossRefGoogle Scholar
  12. 12.
    Zaltman, G., Dotlich, D.L., Cairo, P.C.: How Customers Think. Audio-Tech Business Book Summaries (2003)Google Scholar
  13. 13.
    Hart, S., Boroush, M., Enk, G., Hornick, W.: Managing complexity through consensus mapping: technology for the structuring of group decisions. Acad. Manag. Rev. 10(3), 587–600 (1985)Google Scholar
  14. 14.
    Ryan, G.W., Bernard, H.R.: Techniques to identify themes. Field Methods 15(1), 85–109 (2003)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.Samsung R&D InstituteBangaloreIndia

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