Understanding Mental Models of AI through Player-AI Interaction
This addresses the problem of understanding human-AI interaction for researchers in explainable AI, though it is incremental as it builds on existing game-based methods.
The paper argues that AI-based games provide an ideal domain to study how people develop mental models of AI, presenting a case study to illustrate this approach for explainable AI.
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.