Abstract
If we could build an android as a very humanlike robot, how would we, humans, distinguish a real human from the android? The answer to this question is not simple. In human–android interactions, we cannot see the internal mechanism of the android, and thus, we may simply believe that it is a human. This means that humans can be defined in two ways: by their organic mechanism and by their appearance. Further, the current rapid progress in the development of artificial organs makes this distinction confusing. The approach discussed in this paper is to create artificial humans based on humanlike appearances. The developed artificial humans, an android and a geminoid, can be used to understand humans through psychological and cognitive tests. We call this new approach to understanding humans “Android Science.”
This chapter is a modified version of a previously published paper [1], edited to be comprehensive and fit with the context of this book.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Ishiguro, H., and S. Nishio. 2007. Building artificial humans to understand humans. Journal of Artificial Organs 10 (3): 133–142.
Pascalis, O., M. Haan, and C.A. Nelson. 2002. Is face processing species-specific during the first year of life? Science 296: 1321–1323.
Reeves, B., and C. Nass. 1996. The media equation. CSLI: Cambridge University Press.
Fong, T., I. Nourbakhsh, and K. Dautenhahn. 2003. A survey of socially interactive robots. Robotics and Autonomous Systems 42: 143–166.
Breazeal, C. 2004. Social interactions in HRI: The robot view. IEEE Transactions on Man, Cybernetics and Systems: Part C 34: 181–186.
Kanda, T., H. Ishiguro, M. Imai, and T. Ono. 2004. Development and evaluation of interactive humanoid robots. Proceedings of the IEEE, 1839–1850.
Perani, D., F. Fazio, N.A. Borghese, M. Tettamanti, S. Ferrari, J. Decety, and M.C. Gilardi. 2001. Different brain correlates for watching real and virtual hand actions. NeuroImage 14: 749–758.
Han, S., Y. Jiang, G.W. Humphreys, T. Zhou, and P. Cai. 2005. Distinct neural substrates for the perception of real and virtual visual worlds. NeuroImage 24: 928–935.
Blakemore, S.J., and U. Frith. 2004. How does the brain deal with the social world? NeuroReport 15: 119–128.
Ishiguro, H. 2005. Android science: Toward a new cross-disciplinary framework. In Proceedings of toward social mechanisms of android science: A CogSci 2005 workshop, 1–6.
Perlin, K. 1995. Real time responsive animation with personality. IEEE Transactions on Visualization and Computer Graphics 1: 5–15.
Ishiguro, H. 1997. Distributed vision system: A perceptual information infrastructure for robot navigation. In Proceedings of international joint conference on artificial intelligence (IJCAI), 36–41.
Ikeda, T., T. Ishida., and H. Ishiguro. 2004. Framework of distributed audition. In Procecedings of 13th IEEE international workshop on robot and human interactive communication (RO-MAN), 77–82.
Ishiguro, H. and T. Nishimura. 2001. VAMBAM: View and motion based aspect models for distributed omnidirectional vision systems. In Proceedings of international joint conference on artificial intelligence (IJCAI), 1375–1380.
Minato, T., M. Shimada, S. Itakura, K. Lee, and H. Ishiguro. 2006. Evaluating the human likeness of an android by comparing gaze behaviors elicited by the android and a person. Advanced Robotics 20: 1147–1163.
Kilner, J.M., Y. Paulignan, and S.J. Blakemore. 2003. An interference effect of observed biological movement on action. Current Biology 13: 522–525.
Kuhl, P.K., F.M. Tsao, and H.M. Liu. 2003. Foreign-language experience in infancy: Effects of short-term exposure and social interaction on phonetic learning. Proceedings of the National Academy of Sciences 100: 9096–9101.
Acknowledgements
The establishment of android science as a new interdisciplinary framework has been supported by many researchers. Prof. Shoji Itakura, Kyoto University, is one of the closest collaborative researchers. He designed several android experiments from the perspective of cognitive science. Prof. Kazuo Hiraki, Tokyo University, is another key collaborator. He gave us many suggestions that originate in brain science and cognitive science. The authors appreciate their helpful support.
Dr. Takahiro Miyashita, ATR Intelligent Robotics and Communication Laboratories, initiated the android project with the authors and developed the skin sensors used for the androids and geminoid. Prof. Takashi Minato, Osaka University, developed software for controlling the androids and coordinated several cognitive experiments. Dr. Takayuki Kanda, ATR Intelligent Robotics and Communication Laboratories, collaborated with the authors in developing methods of evaluating human–robot interactions. Dr. Carlos Toshinori Ishii and Mr. Daisuke Sakamoto developed the geminoid server and helped us conduct studies with the geminoid.
Finally, the author appreciates the collaboration and support of Kokoro Co., Ltd. The adult androids of the Repliee Q series have been developed in a collaborative project with this company.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer Nature Singapore Pte Ltd.
About this chapter
Cite this chapter
Ishiguro, H., Nishio, S. (2018). Building Artificial Humans to Understand Humans. In: Ishiguro, H., Dalla Libera, F. (eds) Geminoid Studies. Springer, Singapore. https://doi.org/10.1007/978-981-10-8702-8_2
Download citation
DOI: https://doi.org/10.1007/978-981-10-8702-8_2
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-10-8701-1
Online ISBN: 978-981-10-8702-8
eBook Packages: EngineeringEngineering (R0)