HUMAN–AI COLLABORATION IN ABSTRACT ART CREATION - Premalatha. P; Patil, Suvarna Milind; Kushwaha, Nitesh Kumar; Jaiswal, Rohit; Rajashri C K; Karule, Kalyani P. (ShodhKosh: Journal of Visual and Performing Arts, 2026)
Human-AI collaboration is becoming a new paradigm in the modern form of abstract art production with the redefinition of the concept of creativity, authorship, and aesthetic choice. This paper explores a computer-assisted human and AI-based collaborative system where human artists create abstract art with artificial intelligence systems. The proposed solution is based on co-creation, a concept where human intuition and emotion and intent to generate are combined with the computational exploration, finding patterns, and generative abilities of AI as compared to fully automated generative art or purely human-driven abstraction. The study compiles the experiences of the AI-generated art systems, human-in-the-loop creative systems and machine-learning-generated abstract art to create a conceptual and implementation framework of collaborative creativity. The methodology will be based on an experimental design with three creative conditions and will include human-only creation, AI-only generation, and human-AI collaboration. Several generative models such as diffusion-based and transformer-inspired are used with interactive interfaces that enable the use of human guidance in an iterative manner, constraint setting, and feedback-based refinement. The quantitative evaluation metrics, including the compositional complexity, color variety, new score of novelty, and aesthetic integrity scores are supported by qualitative ones of artistic intent and expressive depth. Findings show that collaborative artworks are always more successful than the human-only and AI-only works in their novelty-coherence balance, conceptual diversity, and fashion variety.