In “Trust in Automation: Designing for Appropriate Reliance,” Lee and See (2004) review research on how people develop trust in automated systems and how that trust influences their use of technology. They explain that trust becomes especially relevant when a system is too complex for someone to understand completely. A central distinction is between trust as an attitude and reliance as behavior: feeling confident in a system and choosing to follow its recommendations are related, but they are not identical. The authors also emphasize that greater trust is not always desirable. Trust should correspond to the system’s actual capabilities; otherwise, people may depend on it too much or reject useful assistance. Their framework considers how system characteristics, context, and cognitive and emotional processes shape these relationships.
This article helps me clarify a problem I am facing in my project: what exactly would count as evidence of trust after the magic interaction? My demo uses webcam-based eye-tracking to predict a participant’s choice. A successful prediction might make the system seem impressive, but that does not necessarily mean the participant would rely on it in another situation. I am considering whether a later decision task could help me examine this distinction. However, if that task involves a gamble, participants’ decisions could also reflect their attitudes toward risk or their understanding of the game. I would therefore need to examine their reported trust alongside their choices. The article also gives me a more specific question about machine authority: could the ritual and magic presentation encourage participants to attribute abilities to the system beyond what the demonstration actually shows? This connects my creative idea to a research question without assuming that the goal is simply to increase trust.
This week, I continued working toward a focused research question and a workable experiment, and I updated the demo. I have completed all the training modules last time. I didn’t meet with committee members this week. My main challenge remains connecting the creative interaction with a clear experimental comparison. I’ll do this next few weeks and meet with my committee then.
Reference
Lee, J. D., & See, K. A. (2004). Trust in automation: Designing for appropriate reliance. Human Factors, 46(1), 50–80. https://doi.org/10.1518/hfes.46.1.50_30392