Abstract
This paper delves into a comparison between virtual and physical agent embodiments with the aim to gain a better understanding of how these are perceived and interacted with in a public setting. For our experiment we developed two agent embodiments: a virtual human and a mechanical looking social robot, that encourage passerby in public space to exercise squats through speech and non-verbal cues. We analyzed user behavior during the interaction with one of the distinct systems that differ in representation but share the same purpose and intent. We recorded 450 encounters in which a passerby listened fully to the agent’s instructions and used body tracking to analyze their exercise engagement. At least one squat was performed in each of 145 encounters, which generally indicates fairly high system acceptance. Additional feedback came from 61 individuals (aged 13 to 74, 41 males, 20 females) through a questionnaire on perception of competence, autonomy, trust, and rapport. There was no significant difference found between the virtual human and the social robot concerning these factors. However, responses to single questions indicate that interactions with the social robot were perceived as significantly more responsive, and gender differences in perceived interaction pressure emerged, with women reporting significantly higher values compared to men. Despite public space challenges, the agent systems prove reliable. Complexity-reducing technical and methodological simplifications and possible sampling biases must be taken into account. This work provides a glimpse into public interactions with virtually and physically embodied agents, and discusses opportunities and limitations for future development of such systems.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Notes
- 1.
Body Tracking SDK for Azure Kinect enables segmentation of exposed instances and both observed and estimated 3D joints and landmarks for fully articulated, uniquely identified body tracking of skeletons. (http://www.azure.microsoft.com/en-us/services/kinect-dk).
- 2.
Kinetic Space is an open-source tool that enables training, analysis, and recognition of individual gestures with a depth camera like Microsoft’s Kinect family [23].
- 3.
- 4.
- 5.
- 6.
MechArm 270-Pi is a lightweight and compact 6-axis robotic arm manufactured by Elephant Robotics using Raspberry Pi as controller, with a payload of 250g, which is sufficient to lift an average mobile phone. (www.shop.elephantrobotics.com/en-de/collections/mecharm/products/mecharm).
- 7.
The Speech Application Programming Interface or SAPI is an API developed by Microsoft to allow the use of speech recognition and speech synthesis within Windows applications.
- 8.
References
Aljaroodi, H.M., Adam, M.T., Chiong, R., Teubner, T., et al.: Avatars and embodied agents in experimental information systems research: a systematic review and conceptual framework. Australasian J. Inform. Syst. 23 (2019)
Baldassarri, D., Abascal, M.: Field experiments across the social sciences. Ann. Rev. Sociol. 43, 41–73 (2017)
Cho, M., Lee, S.s., Lee, K.P.: Once a kind friend is now a thing: understanding how conversational agents at home are forgotten. In: Proceedings of the 2019 on Designing Interactive Systems Conference, pp. 1557–1569 (2019)
Dereshev, D., Kirk, D., Matsumura, K., Maeda, T.: Long-term value of social robots through the eyes of expert users. In: Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems, pp. 1–12 (2019)
Hoy, M.B.: Alexa, siri, cortana, and more: an introduction to voice assistants. Med. Ref. Serv. Q. 37(1), 81–88 (2018)
Jeong, S., Breazeal, C., Logan, D., Weinstock, P.: Huggable: the impact of embodiment on promoting socio-emotional interactions for young pediatric inpatients. In: Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems, pp. 1–13 (2018)
La Guardia, J.G., Ryan, R.M., Couchman, C.E., Deci, E.L.: Within-person variation in security of attachment: a self-determination theory perspective on attachment, need fulfillment, and well-being. J. Pers. Soc. Psychol. 79(3), 367 (2000)
Li, J.: The benefit of being physically present: A survey of experimental works comparing copresent robots, telepresent robots and virtual agents. Int. J. Hum Comput Stud. 77, 23–37 (2015)
Liapis, A., Katsanos, C., Sotiropoulos, D., Xenos, M., Karousos, N.: Stress recognition in human-computer interaction using physiological and self-reported data: a study of gender differences. In: Proceedings of the 19th Panhellenic Conference on Informatics, pp. 323–328 (2015)
Ling, E.C., Tussyadiah, I., Tuomi, A., Stienmetz, J., Ioannou, A.: Factors influencing users’ adoption and use of conversational agents: A systematic review. Psychol. Market. 38(7), 1031–1051 (2021)
Luria, M., Reig, S., Tan, X.Z., Steinfeld, A., Forlizzi, J., Zimmerman, J.: Re-embodiment and co-embodiment: Exploration of social presence for robots and conversational agents. In: Proceedings of the 2019 on Designing Interactive Systems Conference, pp. 633–644 (2019)
Mayer, R.C., Davis, J.H., Schoorman, F.D.: An integrative model of organizational trust. Acad. Manag. Rev. 20(3), 709–734 (1995)
Narumi, T., Yabe, H., Yoshida, S., Tanikawa, T., Hirose, M.: Encouraging people to interact with interactive systems in public spaces by managing lines of participants. In: Yamamoto, S. (ed.) HIMI 2016. LNCS, vol. 9735, pp. 290–299. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-40397-7_28
Nomura, T., Kanda, T.: Rapport-expectation with a robot scale. Int. J. Soc. Robot. 8, 21–30 (2016)
Purps, C.F., Janzer, S., Wölfel, M.: Reconstructing facial expressions of hmd users for avatars in vr. In: International Conference on ArtsIT, Interactivity and Game Creation. pp. 61–76. Springer (2021). https://doi.org/10.1007/978-3-030-95531-1_5
Rossi, S., Staffa, M., Tamburro, A.: Socially assistive robot for providing recommendations: comparing a humanoid robot with a mobile application. Int. J. Soc. Robot. 10, 265–278 (2018)
Ryan, R., Deci, E.: Self-determination theory and the facilitation of intrinsic motivation, social development, and well-being. Am. Psychol. 55, 68–78 (2000)
Schneider, S., Kummert, F.: Comparing the effects of social robots and virtual agents on exercising motivation. In: Ge, S.S., Cabibihan, J.-J., Salichs, M.A., Broadbent, E., He, H., Wagner, A.R., Castro-González, Á. (eds.) ICSR 2018. LNCS (LNAI), vol. 11357, pp. 451–461. Springer, Cham (2018). https://doi.org/10.1007/978-3-030-05204-1_44
Shinozawa, K., Naya, F., Yamato, J., Kogure, K.: Differences in effect of robot and screen agent recommendations on human decision-making. Int. J. Hum Comput Stud. 62(2), 267–279 (2005)
Thellman, S., Silvervarg, A., Gulz, A., Ziemke, T.: Physical vs. virtual agent embodiment and effects on social interaction. In: Traum, D., Swartout, W., Khooshabeh, P., Kopp, S., Scherer, S., Leuski, A. (eds.) IVA 2016. LNCS (LNAI), vol. 10011, pp. 412–415. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-47665-0_44
Turk, M.: Multimodal interaction: a review. Pattern Recogn. Lett. 36, 189–195 (2014)
van der Werff, L., Legood, A., Buckley, F., Weibel, A., de Cremer, D.: Trust motivation: the self-regulatory processes underlying trust decisions. Organ. Psychol. Rev. 9(2–3), 99–123 (2019)
Wölfel, M.: Kinetic Space - 3D Gestenerkennung für Dich und Mich. Konturen 32 (2012)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2024 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
About this paper
Cite this paper
Purps, C.F., Hettmann, W., Zylowski, T., Sautchuk-Patrício, N., Hepperle, D., Wölfel, M. (2024). Exploring Perception and Preference in Public Human-Agent Interaction: Virtual Human Vs. Social Robot. In: Brooks, A.L. (eds) ArtsIT, Interactivity and Game Creation. ArtsIT 2023. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 565. Springer, Cham. https://doi.org/10.1007/978-3-031-55312-7_25
Download citation
DOI: https://doi.org/10.1007/978-3-031-55312-7_25
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-55311-0
Online ISBN: 978-3-031-55312-7