HUMAN–AI CO-CREATION MODELS IN CONCEPTUAL ART
DOI:
https://doi.org/10.29121/shodhkosh.v7.i1s.2026.7121Keywords:
Human–AI Co-Creation, Conceptual Art, Co-Creativity, Generative AI, Artistic Authorship, Practice-Based ResearchAbstract [English]
Human-ai co-creation is an important paradigm in the modern conceptual art, whereby ideas, processes and systems are prioritized over material form. This paper explores formal frameworks of human-AI collaborative creation and the way that AI is transforming the notions of authorship, intentionality, and creative agency in the context of conceptual practice. The paper is based on the conceptual art theory and co-creativity frameworks of the human-computer interaction and places AI not only as a tool, but as an active partner in the idea-based artistic generation. The study relies on a design-based research approach based on multimodal data sources such as textual prompts, sketches, generative products and interaction logs to analyse the creative decision-making process in cycles between humans and AI. Case studies Practice The practice-based case studies will illustrate how generative language models and diffusion models can be used to support conceptual exploration, allow for critical reflection, and broaden the possibilities of artistic inquiry with regard to traditional material constraints. When comparing the models of co-creation, it is possible to note that creative control, conceptual depth, and perceived authorship are different. Theoretically, the results can help change how the process of creativity is understood as a distributed phenomenon that occurs between human and AI through the interaction of the two instead of as a result of human genius.
References
Abdel-Karim, B. M., Pfeuffer, N., Carl, K. V., and Hinz, O. (2023). How AI-Based Systems can Induce Reflections: The Case of AI-Augmented Diagnostic work. MIS Quarterly, 47, 1395–1424. DOI: https://doi.org/10.25300/MISQ/2022/16773
Chen, V., Liao, Q. V., Wortman Vaughan, J., and Bansal, G. (2023). Understanding the Role of Human Intuition on Reliance in Human-Ai Decision-Making with Explanations. Proceedings of the ACM on Human–Computer Interaction, 7, 1–32. DOI: https://doi.org/10.1145/3610219
Chiou, E. K., and Lee, J. D. (2023). Trusting Automation: Designing for Responsivity and Resilience. Human Factors, 65, 137–165. DOI: https://doi.org/10.1177/00187208211009995
Cropley, D., and Cropley, A. (2023). Creativity and the Cyber Shock: The Ultimate Paradox. Journal of Creative Behavior, 57, 485–487. DOI: https://doi.org/10.1002/jocb.625
Demirel, H. O., Goldstein, M. H., Li, X., and Sha, Z. (2024). Human-centered Generative Design Framework: An Early Design Framework to Support Concept Creation and Evaluation. International Journal of Human–Computer Interaction, 40, 933–944. DOI: https://doi.org/10.1080/10447318.2023.2171489
Ege, D. N., Øvrebø, H. H., Stubberud, V., Berg, M. F., Steinert, M., and Vestad, H. (2024). Benchmarking AI Design Skills: Insights from ChatGPT’s Participation in a Prototyping Hackathon. Proceedings of the Design Society, 4, 1999–2008. DOI: https://doi.org/10.1017/pds.2024.202
Grassini, S. (2023). Shaping the Future of Education: Exploring the Potential and Consequences of AI and ChatGPT in Educational Settings. Education Sciences, 13, 692. DOI: https://doi.org/10.3390/educsci13070692
Grassini, S., and Koivisto, M. (2024). Artificial Creativity? Evaluating AI Against Human Performance in Creative Interpretation of Visual Stimuli. International Journal of Human–Computer Interaction, 41, 4037–4048. DOI: https://doi.org/10.1080/10447318.2024.2345430
Haase, J., and Hanel, P. H. P. (2023). Artificial Muses: Generative Artificial Intelligence Chatbots have Risen to Human-Level Creativity. Journal of Creativity, 33, 100066. DOI: https://doi.org/10.1016/j.yjoc.2023.100066
Haj-Bolouri, A., Conboy, K., and Gregor, S. (2024). Research Perspectives: An Encompassing Framework for Conceptualizing Space in Information Systems: Philosophical Perspectives, Themes, and Concepts. Journal of the Association for Information Systems, 25, 407–441. DOI: https://doi.org/10.17705/1jais.00830
Karadağ, D., and Ozar, B. (2025). A New Frontier in Design Studio: AI and Human Collaboration in Conceptual Design. Frontiers of Architectural Research. Advance online publication. DOI: https://doi.org/10.1016/j.foar.2025.01.010
Koivisto, M., and Grassini, S. (2023). Best Humans Still Outperform Artificial Intelligence in a Creative Divergent Thinking Task. Scientific Reports, 13, 13601. DOI: https://doi.org/10.1038/s41598-023-40858-3
Lee, S., Law, M., and Hoffman, G. (2025). When and how to use AI in the Design Process? Implications for Human-Ai Design Collaboration. International Journal of Human–Computer Interaction, 41, 1569–1584. DOI: https://doi.org/10.1080/10447318.2024.2353451
Lisete, B. (2025). Serendipity: Obstacles and Facilitators. Journal of Arts, Humanities and Social Sciences, 2, 50–56.
Melville, N. P., Robert, L., and Xiao, X. (2023). Putting Humans Back in the loop: An Affordance Conceptualization of the 4th Industrial Revolution. Information Systems Journal, 33, 733–757. DOI: https://doi.org/10.1111/isj.12422
Nema, M., (2024). Folk And Tribal Arts And Literature Covered In Indian Tradition ShodhShreejan: Journal of Creative Research Insights, 1(1), 24-29. https://doi.org/10.29121/shodhshreejan.v1.i1.2024.8 DOI: https://doi.org/10.29121/shodhshreejan.v1.i1.2024.8
Rezwana, J., and Maher, M. L. (2023). Designing Creative AI Partners with COFI: A Framework for Modeling Interaction in Human-AI Co-Creative Systems. ACM Transactions on Computer–Human Interaction, 30, 1–28. DOI: https://doi.org/10.1145/3519026
Weisz, J. D., Muller, M., He, J., and Houde, S. (2023). Toward General Design Principles for Generative AI Applications. arXiv. https://arxiv.org/abs/2301.05578
Published
How to Cite
Issue
Section
License
Copyright (c) 2026 Suhas Bhise, Indira Priyadarsani Pradhan, Dr. Halaharvi Keerthi, Dr. Gajanan P Arsalwad, Dr. Kanchan Tolani, Saraswati B

This work is licensed under a Creative Commons Attribution 4.0 International License.
With the licence CC-BY, authors retain the copyright, allowing anyone to download, reuse, re-print, modify, distribute, and/or copy their contribution. The work must be properly attributed to its author.
It is not necessary to ask for further permission from the author or journal board.
This journal provides immediate open access to its content on the principle that making research freely available to the public supports a greater global exchange of knowledge.























