A Study on the Impact of a Generative AI-Assisted Artifact Restoration Experience System on the Public's Sense of Agency, Trust, and Information Verification Behaviors

Abstract

Current museum artifact displays predominantly adopt a static, authoritative, unilinear approach, positioning audiences in a state of passive reception, lacking a sense of participation and agency. Artifacts themselves often suffer from missing information and academic disputes due to historical reasons. The development of Generative Artificial Intelligence (Generative AI) offers new possibilities for the virtual restoration and dynamic presentation of cultural heritage. This study proposes and tests a human-computer collaborative interactive artifact restoration experience system (Manovich & Arielli, 2024), aiming to transform the audience's "static visitation" into "active learning." Through a comparative experiment, the study examines the effects of traditional single-result presentation versus multi-result presentation assisted by Generative AI on the audience's sense of agency, cognitive load, information verification behavior, and trust. Preliminary results indicate that while the multiple possibilities generated by AI increase the audience's cognitive load, they significantly enhance their active verification behavior and sense of participation, while reducing blind trust in a single authoritative result. This study provides empirical evidence for understanding the cognitive communication pathways of cultural heritage in the era of Generative AI and offers a practical framework of "collaborative re-creation" for museum interaction design.

Keywords: Human-computer Collaboration, Generative AI, Cultural Heritage, Audience Sense Of Agency, Information Verification Behavior, Museum Interaction Design

DOI: 10.54941/ahfe1007647