In-Situ Mode: Generative AI-Driven Characters Transforming Art Engagement Through Anthropomorphic Narratives

• Published in: arXiv.org
• Main Authors: Li, Yongming, Zhang, Hangyue, Cui, Andrea Yaoyun, Ma, Zisong, Song, Yunpeng, Cai, Zhongmin, Huang, Yun
• Format: Paper
• Language: English
• Published: Ithaca Cornell University Library, arXiv.org 24.09.2024
• Subjects: Anthropomorphism; Generative artificial intelligence; Narratives
• ISSN: 2331-8422

Art appreciation serves as a crucial medium for emotional communication and sociocultural dialogue. In the digital era, fostering deep user engagement on online art appreciation platforms remains a challenge. Leveraging generative AI technologies, we present EyeSee, a system designed to engage users through anthropomorphic characters. We implemented and evaluated three modes (Narrator, Artist, and In-Situ) acting as a third-person narrator, a first-person creator, and first-person created objects, respectively, across two sessions: Narrative and Recommendation. We conducted a within-subject study with 24 participants. In the Narrative session, we found that the In-Situ and Artist modes had higher aesthetic appeal than the Narrator mode, although the Artist mode showed lower perceived usability. Additionally, from the Narrative to Recommendation session, we found that user-perceived relatability and believability within each interaction mode were sustained, but the user-perceived consistency and stereotypicality changed. Our findings suggest novel implications for applying anthropomorphic in-situ narratives to other educational settings.