INTELLIGENT CURATION OF DIGITAL PORTFOLIOS FOR ARTISTS - Sarna, Shilpi; Bibhu, Vimal; Das, Debayan; Singh, Yaduvir; Guntaj J; Rajagopal, Swetha; Deshpande, Anupama Abhijeet (ShodhKosh: Journal of Visual and Performing Arts, 2025)
Intelligent curation represents a novel paradigm of digital art management where AI exists to supplement human creativity to make artistic portfolios more organized, interpreted, and personal. The current work describes a multimodal system consisting of computer vision, transformer-based language models, and reinforcement training that allows creating adaptive, explainable, and human aligning curation. The system evaluates works of art in terms of visual, semantic and emotional embedding to come up with aesthetic scores and curatorial suggestions which develop through the feedback of artists, curators and viewers. As proven by experimental case studies, such as solo views, multi-artist shows, and bespoke experiences of the viewer, AI can be used to improve the coherence of the curatorship, the range of subjects, and the experience of the viewer without losing interpretive integrity. The system has been assessed by precision, F1-score, aesthetic diverse metrics, and engagement index to indicate that the system is analytically robust. The conclusion of the paper is that human-AI co-curation is a contributor to a collaborative form of intelligence that builds upon the data analytics of curatorial reasoning into culture making and provides an ethically sound and scalable channel through which digital exhibition design can be carried out in the future.