Development of Mental Models in Human-AI Collaboration: A Conceptual Framework

Artificial intelligence has become integral to organizational decision - making and while research has explored many facets of this human - AI collaboration, the focus has mainly been on designing the AI agent(s) and the way the collaboration is set up -- generally assuming a human decision - maker to be "fixed". However, it has largely been neglected that decision - makers' mental models evolve through their continuous interaction with AI systems. This paper addresses this gap by conceptualizing how the design of human - AI collaboration influences the development of three complementary and interdependent mental models necessary for this collaboration. We develop an integrated socio - technical framework that identifies the mechanisms driving the mental model evolution: data contextualization, reasoning transparency, and performance feedback.