Advertisement

AI & SOCIETY

, Volume 34, Issue 3, pp 625–638 | Cite as

Exploratory analysis of Sony AIBO users

  • Csaba KertészEmail author
  • Markku Turunen
Open Forum

Abstract

It is important to understand how the cultural background, the age and the gender influence the expectations towards social robots. Although past works studied the user adaptation for some months, the users with multiple years of ownership (heavy users) were not subjects of any experiment to compare these criteria over the years. This exploratory research examines the owners of the discontinued Sony AIBO because these robots have not been abandoned by some enthusiastic users and they are still resold on the secondhand market. 78 Sony AIBO owners were recruited online and their quantitative data were analyzed by four independent variables (age, gender, culture, and length of ownership), user contribution and model preference points of view. The results revealed the motives to own these robots for years and how the heavy users perceived their social robots after a long period in the robot acceptance phase.

Keywords

Quantitative research Heavy users Social robot Sony AIBO 

Notes

Acknowledgements

The authors want to say thanks to all enthusiastic members of the aibo-life.org forums to fill out my questionnaire. Special thanks to Christoph Bartneck who shared his valuable research data to draw better conclusions in this paper.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Supplementary material

146_2018_818_MOESM1_ESM.pdf (663 kb)
Supplementary material 1 (PDF 663 KB)

References

  1. Bartneck C, Suzuki T, Kanda T, Nomura T (2007) The influence of people’s culture and prior experiences with AIBO on their attitudes towards robots. AI Soc 21(1–2):217–230Google Scholar
  2. Bernhauerova M (2013) American vs. Japanese management style: which one yields success. MG 201, Introduction to Functions of ManagementGoogle Scholar
  3. Coninx A et al (2016) Towards long-term social child-robot interaction: using multi-activity switching to engage young users. J Hum Robot Interact 5(1):32–67CrossRefGoogle Scholar
  4. Ezer N (2008) Is a robot an appliance, teammate, or friend? Age-related differences in expectations of and attitudes towards personal home-based robots. Georgia Institute of Technology, PhD DissertationGoogle Scholar
  5. Fernaeus Y, Håkansson M, Jacobsson M, Ljungblad S (2010) How do you play with a robotic toy animal?: A long-term study of pleo. In: Proceedings of 9th international conference on interaction design and children ACM, New York, pp 39–48Google Scholar
  6. François D, Powell S, Dautenhahn K (2009) A long-term study of children with autism playing with a robotic pet: taking inspirations from non-directive play therapy to encourage children’s proactivity and initiative-taking. Interact Stud 10(3):324–373CrossRefGoogle Scholar
  7. Friedman B, Kahn PH, Hagman J (2003) ‘‘Hardware companions?’’: what online AIBO discussion forums reveal about the human-robotic relationship. CHI Lett 5(1):273–280Google Scholar
  8. Fujita M (2004) On activating human communications with pet-type robot AIBO. Proc IEEE 92(11):1804–1813CrossRefGoogle Scholar
  9. Gockley R, Bruce A, Forlizzi J, Michalowski M, Mundell A, Rosenthal S, Sellner B, Simmons R, Snipes K, Schultz A, Wang J (2005) Designing robots for long-term social interaction. In: 2005 IEEE/RSJ international conference on intelligent robots and systems (IROS), pp 1338–1343Google Scholar
  10. Graaf MM, Ben Allouch S, Dijk JA (2014) Long-term evaluation of a social robot in real homes. In: 3rd international symposium on new frontiers in human-robot interaction (AISB)Google Scholar
  11. Graaf MM, Ben Allouch S, Dijk JA (2016) Long-term acceptance of social robots in domestic environments: insights from a user’s perspective. AAAIGoogle Scholar
  12. Haring KS, Mougenot C, Fuminori ONO, Watanabe K (2014) Cultural differences in perception and attitude towards robots. Int J Affect Eng 13(3):149–157CrossRefGoogle Scholar
  13. Haring KS, Silvera-Tawil D, Takahashi T, Velonaki M, Watanabe K (2015) Perception of a humanoid robot: a cross-cultural comparison. In: Proc. of 24th IEEE international workshop on robot and human interactive communication (ROMAN), pp 821–826Google Scholar
  14. Kaplan F (2004) Who is afraid of the humanoid? Investigating cultural differences in the acceptance of robots. Int J Humanoid Rob 1:465–480CrossRefGoogle Scholar
  15. Kertész C, Turunen M (2017) What can we learn from the long-term users of a social robot? In: Proc. of 9th international conference on social robotics (ICSR), 2017Google Scholar
  16. Koay K, Syrdal D, Walters M, Dautenhahn K (2007) Living with robots: investigating the habituation effect in participants’ preferences during a longitudinal human-robot interaction study. In: The 16th IEEE international symposium on robot and human interactive communication (RO-MAN), pp 564–569Google Scholar
  17. Leite I, Martinho C, Paiva A (2013) Social robots for long-term interaction: a survey. Int J Soc Robot 5(2):291–308CrossRefGoogle Scholar
  18. Nomura T et al (2005) Questionnaire–based research on opinions of visitors for communication robots at an exhibition in japan. In: Proc. of IFIP conference on human-computer interaction, pp 685–698Google Scholar
  19. Nomura T, Suzuki T, Kanda T, Kato K (2006) Altered attitudes of people toward robots: investigation through the Negative Attitudes toward Robots Scale. In: Proc. AAAI-06 workshop on human implications of human-robot interaction, pp 29–35Google Scholar
  20. Nomura T, Sugimoto K, Syrdal DS, Dautenhahn K (2012) Social acceptance of humanoid robots in Japan: a survey for development of the Frankenstein syndrome questionnaire. In: Proc. of 12th IEEE-RAS international conference on humanoid robots, pp 242–247Google Scholar
  21. Norman DA (2004) Emotional design: why we love (or hate) everyday things. Basic Books, New YorkCrossRefGoogle Scholar
  22. Salter T, Dautenhahn K, Bockhorst R (2004) Robots moving out of the laboratory—detecting interaction levels and human contact in noisy school environments. In: Proc. of 13th IEEE international workshop on robot and human interactive communication (ROMAN), pp 563–568Google Scholar
  23. Samuels D, Zucco C (2012) Using Facebook as a subject recruitment tool for survey-experimental research. Working paper, Social Science Research NetworkGoogle Scholar
  24. Scopelliti M, Giuliani MV, Fornara F (2005) Robots in a domestic setting: a psychological approach. J Univ Access Inf Soc 4(2):146–155CrossRefGoogle Scholar
  25. Sung J, Grinter RE, Christensen HI (2010) Domestic robot ecology. Int J Social Robot 2(4):417–429CrossRefGoogle Scholar
  26. Yoldas S (2012) A Research About Buying Behaviours of Online Customers. MSc Thesis, University of RoehamptonGoogle Scholar
  27. Zhan K, Zukerman I, Moshtaghi M, Rees G (2016) Eliciting users’ attitudes toward smart devices. In: Proc. of the conference on user modeling adaptation and personalization, pp. 175–184Google Scholar

Copyright information

© Springer-Verlag London Ltd., part of Springer Nature 2018

Authors and Affiliations

  1. 1.Faculty of CommunicationsUniversity of TampereTampereFinland

Personalised recommendations