COMMUNITY-DRIVEN AI MODELS FOR CULTURAL ART EDUCATION - Khurana, Jatin; Gupta, Shikha; Homavazir, Zuleika; Desai, Sandip; Nanda, Simranjeet; Singh, Yaduvir (ShodhKosh: Journal of Visual and Performing Arts, 2025)
This paper discusses the concept of community-based engagement in the implementation of artificial intelligence in cultural art education, how artificial intelligence can be used to facilitate creative learning without affecting the cultural authenticity. A four-week student-teacher-local artisan case study established that AI considerably promoted creative interactions, multimodal learning, as well as cultural cognition. Nevertheless, the results also provide evidence that the output of AI can be significantly biased in a symbolic way and the necessity of the community verification and human control is evident. Repeat human in the loop refinement enhanced cultural precision and enhanced the exchange of knowledge between generations. It is concluded that when integrated into an ethically informed participatory approach, which focuses on local cultural knowledge, AI can be useful in supplementing cultural art education. It outlines the necessity of databases rich in culture, effective governance and ongoing participation by the community in order to achieve responsible and meaningful implementation.