Understanding Mental Models of AI through Player-AI Interaction

Jichen Zhu, Jennifer Villareale

Research output: Conference Article in Proceeding or Book/Report chapterArticle in proceedingsResearchpeer-review


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.
Original languageEnglish
Title of host publicationExtended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems (CHI EA '21)
Publication date2021
Article number11
Publication statusPublished - 2021


  • Human-centered AI
  • Mental models
  • AI-driven applications
  • Player-AI interaction
  • Explainable AI


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