Jiaxin Dai
Signify Research, Eindhoven, Netherlands
It has been shown that providing explanations about AI-based systems’ decisions can be an effective way to increase users’ trust and acceptance. The effect of explanation design in smart home systems on users’ acceptance and perceptions is however less known. We therefore explored the effect of different explanation designs on acceptance in the context of the Philips Hue smart home lighting system. We conducted interviews (N = 10) and an online experiment (N = 452) using three everyday smart home lighting scenarios with different explanation types. The results showed that although participants indicated a positive attitude towards explanations, receiving an explanation can potentially reduce the perceived control of the lighting system. Furthermore, participants preferred system-based explanations rather than user-based explanations. Our study also provides recommendations for the design of explanations in smart home systems.
https://doi.org/10.1145/3544548.3581263
The ACM CHI Conference on Human Factors in Computing Systems (https://chi2023.acm.org/)