Abstract
When interacting with an agent, some users with utilitarian orientation tend to treat an agent as an instrumental tool, while others with relational orientation find the design of humanlike features more pleasing. Along with technological advances in user modeling and prediction algorithms, intelligent agents nowadays can personalize their interaction by identifying such orientation of users towards them. While prior work has revealed several behavioral signs resulting from such difference in orientation, little attention is directed to more fundamental cues that precede the occurrence of actual interaction. In light of this issue, this study explores intrinsic properties of users related to their utilitarian or relational orientation towards intelligent agents. Qualitative analysis of responses revealed three user propensities contributing to individual differences in orientation: tolerance to unpredictability, sensitivity to privacy, and sensitivity to an agent’s autonomy. We discuss future directions for leveraging our findings to design personalized interaction in intelligent agents.
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References
Abelson, R.P.: Psychological status of the script concept. Am. Psychol. 36(7), 715 (1981)
Bati, G.F., Singh, V.K.: “Trust Us” mobile phone use patterns can predict individual trust propensity. In: Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems, pp. 1–14. ACM (2018)
Blom, J.: Personalization: a taxonomy. In: CHI'00 Extended Abstracts on Human Factors in Computing Systems, pp. 313–314. ACM (2000)
Boyatzis, R.E.: Transforming Qualitative Information: Thematic Analysis and Code Development. Sage (1998)
Friedman, B., Kahn Jr., P.H., Hagman, J.: Hardware companions? What online AIBO discussion forums reveal about the human-robotic relationship. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 273–280. ACM (2003)
Kim, D.J., Lim, Y.K.: Co-performing agent: design for building user-agent partnership in learning and adaptive services. In: Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems, pp. 1–14. ACM (2019)
Lee, M.K., Kiesler, S., Forlizzi, J.: Receptionist or information kiosk: how do people talk with a robot? In: Proceedings of the 2010 ACM Conference on Computer Supported Cooperative Work, pp. 31–40. ACM (2010)
Lee, M.K., Kiesler, S., Forlizzi, J., Srinivasa, S., Rybski, P.: Gracefully mitigating breakdowns in robotic services. In: 2010 5th ACM/IEEE International Conference on Human-Robot Interaction, pp. 203–210. ACM (2010)
Lee, Y., Bae, J.E., Kwak, S.S., Kim, M.S.: The effect of politeness strategy on human-robot collaborative interaction on malfunction of robot vacuum cleaner. In: RSS Workshop on HRI (2011)
Lee, N., Shin, H., Sundar, S.S.: Utilitarian vs. hedonic robots: role of parasocial tendency and anthropomorphism in shaping user attitudes. In: Proceedings of the 6th International Conference on Human-robot Interaction, pp. 183–184. ACM (2011)
Liao, Q.V., Davis, M., Geyer, W., Muller, M., Shami, N. S.: What can you do? Studying social-agent orientation and agent proactive interactions with an agent for employees. In: Proceedings of the 2016 ACM Conference on Designing Interactive Systems, pp. 264–275. ACM (2016)
Müller, H., Sedley, A., Ferrall-Nunge, E.: Survey research in HCI. In: Ways of Knowing in HCI, pp. 229–266 (2014)
Nass, C., Steuer, J., Tauber, E.R.: Computers are social actors. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 72–78 (1994)
Ogan, A., Finkelstein, S., Mayfield, E., D’Adamo, C., Matsuda, N., Cassell, J.: “Oh dear stacy!” social interaction, elaboration, and learning with teachable agents. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 39–48. ACM (2012)
Purington, A., Taft, J.G., Sannon, S., Bazarova, N. N., Taylor, S.H.: “Alexa is my new BFF” social roles, user satisfaction, and personification of the amazon echo. In: Proceedings of the 2017 CHI Conference Extended Abstracts on Human Factors in Computing Systems, pp. 2853–2859. ACM (2017)
Singer, E., Couper, M.P.: Some methodological uses of responses to open questions and other verbatim comments in quantitative surveys. Methods Data Analyses J. Quant. Methods Surv. Methodol. 11(2), 115–134 (2017)
Singh, V.K., Agarwal, R.R.: Cooperative phoneotypes: exploring phone-based behavioral markers of cooperation. In: Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing, pp. 646–657. ACM (2016)
Acknowledgement
This work was mainly supported by Institute of Information & Communications Technology Planning & Evaluation (IITP) grant funded by the Korea government (MSIT) (No.2016-0-00564, Development of Intelligent Interaction Technology Based on Context Awareness and Human Intention Understanding) and partially supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (No. NRF-2021R1A2C2004263).
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Kim, H., Nam, H., Lee, U., Lim, Yk. (2021). Utilitarian or Relational? Exploring Indicators of User Orientation Towards Intelligent Agents. In: Stephanidis, C., Antona, M., Ntoa, S. (eds) HCI International 2021 - Posters. HCII 2021. Communications in Computer and Information Science, vol 1419. Springer, Cham. https://doi.org/10.1007/978-3-030-78635-9_58
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DOI: https://doi.org/10.1007/978-3-030-78635-9_58
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