Making art accessible: How prompted AI use for simplifying art descriptions enhances museum visit satisfaction

Descriptions of art at museums can be challenging for novices. AI tools can simplify these descriptions, but their impact on overall visit satisfaction is underexplored, especially when novices use them for simplifying descriptions. Grounded in affordance, cognitive load, flow, and self-determination theory, this research examines how prompting art novices to use AI tools influences their satisfaction with the overall museum visit. Findings from an open-ended survey and a series of online experiments show that, although only a small proportion of art novices initially report adopting AI tools to simplify complex art descriptions, most do so when prompted and prefer AI-simplified descriptions over curator-created, complex ones. These simplified descriptions enhance overall visit satisfaction by reducing cognitive load and fostering a higher level of flow. Notably, overall visit satisfaction is higher when novices actively adopt AI tools after being prompted, rather than passively receive AI-simplified descriptions from curators. Theoretically, this research extends affordance theory to the understudied context of art museums by conceiving of AI-simplified art descriptions as hidden affordances and by providing an underlying mechanism that explains why affording simplified descriptions enhances overall visit satisfaction among these novices. Furthermore, this research synthesizes affordance theory with self-determination theory, advancing a motivation-based perspective on affordance. Empirically, it provides guidance for museums using AI to improve novice satisfaction and museum accessibility.