Abstract
Researchers have shown that intelligent assistants can improve human productivity in teamwork. With the development of VR technology, such human-computer teamwork will also be able to take place in digital environments. In order to achieve this, this study developed a virtual reality platform called Synneure. The program contains an intelligent assistant that can be configured with a variety of personality traits, skills, and data sets. The platform builds a virtual space with stereoscopic interaction and supports human-machine teamwork between intelligent assistants and humans in virtual reality. Five valid conclusions were derived from prototyping, design fiction, and user testing. For example, reconstructing design tools in a stereoscopic way can help users improve the discussion process in a way that increases the efficiency of spatial manipulation. However, additional instruction is needed. In addition, conclusions are drawn regarding intelligent assistants, such as collaborative functions and emotional functions that follow the discussion phase. Last but not least, people will have a higher expectation of interaction with an intelligent assistant in comparison to the real one, and this will be the next design direction for the follow-up of this study.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Cho, J., Rader, E.: The role of conversational grounding in supporting symbiosis between people and digital assistants. ACM Human-Comput. Interact. 4(CSCW1), 1–28 (2020). https://doi.org/10.1145/3392838
Licklider, J.C.R.: Man-Computer Symbiosis. IRE Trans. Hum. Factors Electron. HFE-1, 4–11 (1960). https://doi.org/10.1109/THFE2.1960.4503259
Ma, X.: Towards Human-Engaged AI. In: 27th International Joint Conference on Artificial Intelligence, pp. 5682–5686. , Stockholm, Sweden (2018)
Paschkewitz, J., Patt, D.: Can AI make your job more interesting? Issues Sci. Technol. 37, 74–78 (2020)
Chakraborti, T., Kambhampati, S., Scheutz, M., Zhang, Y.: AI Challenges in Human-Robot Cognitive Teaming, http://arxiv.org/abs/1707.04775 (2017)
ShiJian, L.: Design of Intelligent Product. Publishing House of Electronics Industry (2017)
LuxAI: QT Robot, https://luxai.com/
Tao, F., et al.: Digital twin-driven product design framework. Int. J. Prod. Res. 57, 3935–3953 (2019). https://doi.org/10.1080/00207543.2018.1443229
Zhuang, C., Liu, J., Xiong, H.: Digital twin-based smart production management and control framework for the complex product assembly shop-floor. Int. J. Adv. Manufact. Technol. 96(1–4), 1149–1163 (2018). https://doi.org/10.1007/s00170-018-1617-6
Gushima, K., Nakajima, T.: A design space for virtuality-introduced internet of things. Future Internet. 9, 60 (2017). https://doi.org/10.3390/fi9040060
Xu, J., Chao, C.-J., Fu, Z.: Research on Intelligent Design Tools to Stimulate Creative Thinking. In: Rau, P.-L. (ed.) HCII 2020. LNCS, vol. 12192, pp. 661–672. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-49788-0_50
Xia, Q., Fu, Z.: NEXT! Toaster: Promoting Design Process with a Smart Assistant. In: Rau, P.-L. (ed.) HCII 2021. LNCS, vol. 12773, pp. 396–409. Springer, Cham (2021). https://doi.org/10.1007/978-3-030-77080-8_31
Sidner, C.L., Lee, C., Kidd, C.D., Lesh, N., Rich, C.: Explorations in engagement for humans and robots. Artif. Intell. 166, 140–164 (2005). https://doi.org/10.1016/j.artint.2005.03.005
Jarrahi, M.H.: Artificial intelligence and the future of work: Human-AI symbiosis in organizational decision making. Bus. Horiz. 61, 577–586 (2018). https://doi.org/10.1016/j.bushor.2018.03.007
Damm, L.: Moral machines: teaching robots right from wrong. Philos. Psychol. 25, 149–153 (2012). https://doi.org/10.1080/09515089.2011.583029
Grigsby, S.S.: Artificial Intelligence for Advanced Human-Machine Symbiosis. In: Schmorrow, D.D., Fidopiastis, C.M. (eds.) AC 2018. LNCS (LNAI), vol. 10915, pp. 255–266. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-91470-1_22
Zong, Y., GuangXin, W.: Anthropomorphism: The Psychological Application in the Interaction between Human and Computer. Psychol. : Tech. Appl. 4(5), 296–305 (2016). https://doi.org/10.16842/j.cnki.issn2095-5588.2016.05.007
Liying, X., Feng, Y., Jiahua, W., Tingting, H., Liang, Z.: Anthropomorphism: antecedents and consequences. Adv. Psychol. Issue 11, 1942–1954 (2017). https://doi.org/10.3724/SP.J.1042.2017.01942
Norman, D.A.: Emotional Design: Why We Love (or Hate) Everyday Things. Basic Books, New York (2004)
Asada, M.: Towards artificial empathy. Int. J. Soc. Robot. 7(1), 19–33 (2014). https://doi.org/10.1007/s12369-014-0253-z
Nass, C., Steuer, J., Tauber, E.R.: Computers are social actors. In: Conference Companion on Human Factors in Computing Systems, p. 204. Association for Computing Machinery, New York, NY, USA (1994)
Kuipers, B.: How can we trust a robot? Commun. ACM 61, 86–95 (2018). https://doi.org/10.1145/3173087
Jianhua, M.: Understanding and theory: the optimistic attitude and pessimistic attitude in the discussion of artificial intelligence. J. Dialectics Nature 40, 1–8 (2018). https://doi.org/10.15994/j.1000-0763.2018.04.001
Ishiguro, H.: Studies on Humanlike Robots – Humanoid, Android and Geminoid. In: Carpin, S., Noda, I., Pagello, E., Reggiani, M., von Stryk, O. (eds.) SIMPAR 2008. LNCS (LNAI), vol. 5325, pp. 2–2. Springer, Heidelberg (2008). https://doi.org/10.1007/978-3-540-89076-8_2
Jonathan Chapman: Emotionally Durable Design. Routledge (2012)
Rodrigues, S.H., Mascarenhas, S., Dias, J., Paiva, A.: A process model of empathy for virtual agents. Interact. Comput. 27, 371–391 (2015). https://doi.org/10.1093/iwc/iwu001
Afzal, S., et al.: The personality of AI systems in education: experiences with the watson tutor, a one-on-one virtual tutoring system. Child. Educ. 95, 44–52 (2019). https://doi.org/10.1080/00094056.2019.1565809
Zhou, M.X., Mark, G., Li, J., Yang, H.: Trusting virtual agents: the effect of personality. ACM Trans. Interact. Intell. Syst. 9, 1–36 (2019). https://doi.org/10.1145/3232077
Cooper, B., Brna, P., Martins, A.: Effective Affective in Intelligent Systems – Building on Evidence of Empathy in Teaching and Learning. In: Paiva, A. (ed.) IWAI 1999. LNCS (LNAI), vol. 1814, pp. 21–34. Springer, Heidelberg (2000). https://doi.org/10.1007/10720296_3
Gubrium, J.F., Holstein, J.A.: Handbook of Interview Research: Context and Method. SAGE Publications (2001)
Acknowledgement
This project is supported by Graduate Education Innovation Grants, Tsinghua University.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Chao, C., Wang, Q., Wu, H., Fu, Z. (2023). Synneure: Intelligent Human-Machine Teamwork in Virtual Space. In: Rau, PL.P. (eds) Cross-Cultural Design. HCII 2023. Lecture Notes in Computer Science, vol 14023. Springer, Cham. https://doi.org/10.1007/978-3-031-35939-2_25
Download citation
DOI: https://doi.org/10.1007/978-3-031-35939-2_25
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-35938-5
Online ISBN: 978-3-031-35939-2
eBook Packages: Computer ScienceComputer Science (R0)