Designing human-centered AI-driven applications require deep understandings of how people develop mental models of AI. Currently, we have little knowledge of this process and limited tools to study it. This paper presents the position that AI-based games, particularly the player-AI interaction component, offer an ideal domain to study the process in which mental models evolve. We present a case study to illustrate the beneﬁts of our approach for explainable AI.
|Title of host publication||Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems (CHI EA '21)|
|Publication status||Published - 2021|