User Experiences with Personal Intelligent Agents: A Sensory, Physical, Functional and Cognitive Affordances View

ABSTRACT

The interaction between users and their personal intelligent agents like Apple's Siri, Amazon's Alexa, and Google Home is getting more personal, therefore raising questions about the ethical obligations of technology companies. Thus, a thorough examination of users' experiences with these agents is indispensable. After all, it is merely the interaction between the human actor and the system that enables the artifact to be of consequence. This study uses an affordances lens to explore such use patterns. We qualitatively analyze 232 interviews with personal intelligent agents' users. The results reveal sensory affordances that support functional ones (hands-free and eyes-free use, familiarity and emotional connection) and dominate the users' experience with these agents. We also detect cognitive (personalization and learning from interactions), functional (speedy assistance and usefulness), and physical affordances (potential improvement). These findings have implications for researchers and practitioners alike seeking to understand usability patterns and challenges resulting from the integration of Apple's Siri, Google Now, Amazon's Echo and Microsoft's Cortana into users' everyday life.

References

1. Andres, H. (2017). Alexa, Can You Prevent Suicide? How Amazon trains its AI to handle the most personal questions imaginable. The Wall Street Journal. Retrieved from https://www.wsj.com/articles/alexa-can-you-prevent-suicide-1508762311
2. Benbunan-Fich, R. (2017). Usability of Wearables without Affordances. Paper presented at the Twenty-third Americas Conference on Information Systems, Boston.
3. Chen, S. (2017). AI Research Is In Desperate Need Of An Ethical Watchdog Wired. Retrieved from https://www.wired.com/story/ai-research-is-in-desperate-need-of-an-ethical-watchdog/
4. Eisenhardt, K. M. (1989). Building theories from case study research. Academy of Management Review, 14(4), 532--550.
5. Gibson, J. J. (1986). The ecological approach to visual perception. Hillsdale, NJ: Erlbaum.
6. Goh, J. M., Gao, G., & Agarwal, R. (2011). Evolving work routines: adaptive routinization of information technology in healthcare. Information Systems Research, 22(3), 565--585.
7. Gregor, S., & Benbasat, I. (1999). Explanations from intelligent systems: Theoretical foundations and implications for practice. MIS quarterly, 497--530.
8. Guest, G., Bunce, A., & Johnson, L. (2006). How many interviews are enough? An experiment with data saturation and variability. Field methods, 18(1), 59--82.
9. Hartson, R. (2003). Cognitive, physical, sensory, and functional affordances in interaction design. Behaviour & Information Technology, 22(5), 315--338.
10. Ivory, M. Y., & Hearst, M. A. (2001). The state of the art in automating usability evaluation of user interfaces. ACM Computing Surveys (CSUR), 33(4), 470--516.
11. Kaptelinin, V., & Nardi, B. (2012). Affordances in HCI: toward a mediated action perspective. Paper presented at the Proceedings of the SIGCHI Conference on Human Factors in Computing Systems.
12. Knijnenburg, B., & Willemsen, M. C. (2014). Inferring Capabilities of Intelligent Agents. Paper presented at the Special Interest Group on Human-Computer Interaction.
13. Kurzweil, R., Richter, R., & Schneider, M. L. (1990). The age of intelligent machines (Vol. 579): MIT press Cambridge.
14. Leonardi, P. M. (2011). When flexible routines meet flexible technologies: Affordance, constraint, and the imbrication of human and material agencies. MIS quarterly, 147--167.
15. March, S., Hevner, A., & Ram, S. (2000). Research commentary: an agenda for information technology research in heterogeneous and distributed environments. Information Systems Research, 11(4), 327--341.
16. Markus, M. L., & Silver, M. S. (2008). A foundation for the study of IT effects: A new look at DeSanctis and Poole's concepts of structural features and spirit. Journal of the Association for Information Systems, 9(10/11), 609.
17. Mihale-Wilson, C., Zibuschka, J., & Hinz, O. (2017). About User Preferences And Willingness To Pay For A Secure And Privacy Protective Ubiquitous Personal Assistant. Paper presented at the Twenty-Fifth European Conference on Information Systems (ECIS), Guimarães, Portugal.
18. Miner, A. S., Milstein, A., Schueller, S., Hegde, R., Mangurian, C., & Linos, E. (2016). Smartphone-based conversational agents and responses to questions about mental health, interpersonal violence, and physical health. JAMA internal medicine, 176(5), 619--625.
19. Myers, M. D. (2013). Qualitative research in business and management (Second ed.): SAGE Publications.
20. Nguyen, Q. N., & Sidorova, A. (2017). AI capabilities and user experiences: a comparative study of user reviews for assistant and non-assistant mobile apps. Paper presented at the Twenty-third Americas Conference on Information Systems, Boston.
21. Norman, D. A. (1988). The Psychology of Everyday Things. Basic Books: New York.
22. Norman, D. A. (1999). Affordance, conventions, and design. interactions, 6(3), 38--43.
23. Nunamaker, J. F., Derrick, D. C., Elkins, A. C., Burgoon, J. K., & Patton, M. W. (2011). Embodied conversational agent-based kiosk for automated interviewing. Journal of Management Information Systems, 28(1), 17--48.
24. Paré, G. (2004). Investigating information systems with positivist case research. The Communications of the Association for Information Systems, 13(1), 57.
25. Perez, S. (2017). Siri usage and engagement dropped since last year, as Alexa and Cortana grew. Retrieved from https://techcrunch.com/2017/07/11/siri-usage-and-engagement-dropped-since-last-year-as-alexa-and-cortana-grew/
26. Robey, D., Anderson, C., & Raymond, B. (2013). Information technology, materiality, and organizational change: A professional odyssey. Journal of the Association for Information Systems, 14(7), 379.
27. Russell, S., & Norvig, P. (2010). Artificial Intelligence: A modern approach (Third ed. Vol. 25). New Jersey: Pearson Education.
28. Savoli, A., & Barki, H. (2013). Functional Affordance Archetypes: a New Perspective for Examining the Impact of IT Use on Desirable Outcomes.
29. Schultze, U. (2010). Embodiment and presence in virtual worlds: a review. Journal of Information Technology, 25(4), 434--449.
30. Shoham, Y. (1993). Agent-oriented programming. Artificial intelligence, 60(1), 51--92.
31. Steels, L., & Brooks, R. A. (1995). The artificial life route to artificial intelligence: Building embodied, situated agents: L. Erlbaum Associates Hillsdale, NJ.
32. Stendal, K., Thapa, D., & Lanamäki, A. (2016). Analyzing the concept of affordances in information systems. Paper presented at the System Sciences (HICSS), 2016 49th Hawaii International Conference on.
33. Turkle, S. (2012). Alone together: Why we expect more from technology and less from each other: Basic books.
34. Vincent, J. (2016). Twitter taught Microsoft's AI chatbot to be a racist asshole in less than a day. Retrieved from http://www.theverge.com/2016/3/24/11297050/tay-microsoft-chatbot-racist
35. Wooldridge, M., & Jennings, N. R. (1995). Intelligent agents: Theory and practice. The knowledge engineering review, 10(02), 115--152.
36. Zammuto, R. F., Griffith, T. L., Majchrzak, A., Dougherty, D. J., & Faraj, S. (2007). Information technology and the changing fabric of organization. Organization science, 18(5), 749--762.
37. Zeng, D. (2015). AI Ethics: Science Fiction Meets Technological Reality. IEEE Intelligent Systems, 30(3), 2--5.

Index Terms

• Human-centered computing

  • Human computer interaction (HCI)

    • Empirical studies in HCI