AI AS A MEDIUM IN CONCEPTUAL ART PRACTICE

Authors

  • Dr. Peeyush Kumar Gupta Assistant Professor, ISDI - School of Design & Innovation, ATLAS SkillTech University, Mumbai, Maharashtra, India
  • Dr. Ankayarkanni B Professor, Department of Computer Science and Engineering, Sathyabama Institute of Science and Technology, Chennai, Tamil Nadu, India
  • Amit Kumar Centre of Research Impact and Outcome, Chitkara University, Rajpura- 140417, Punjab, India
  • Kuldeep Dhiman Assistant,Professor,School,of,Sciences,,Noida,international,University,203201
  • Romil Jain Chitkara Centre for Research and Development, Chitkara University, Himachal Pradesh, Solan, 174103, India
  • Amrut Ramchandra Pawar Department of CSE (AIML), Vishwakarma Institute of Technology, Pune, Maharashtra, 411037 India.
  • Dipti Nitin Dixit Department of CSE (AIML), Vishwakarma Institute of Technology, Pune, Maharashtra, 411037 India.

DOI:

https://doi.org/10.29121/shodhkosh.v6.i3s.2025.6817

Keywords:

Artificial Intelligence, Conceptual Art, Authorship, Computational Aesthetics, Algorithmic Art, Creative Agency

Abstract [English]

This paper sets out to review the advent of artificial intelligence as an important medium in modern conceptual art practice, with particular reference to its ability to both extend and confuse the traditional operating assumption of ideas being the primary element in conceptual art practice. The study is based on the historical development of conceptualism, starting with the early linguistic and systemic arts and moving to the subsequent computational experimentalism, which orients AI to a tradition of artistic and process-oriented approaches, in which processes, instructions, and networks of meaning take the place of conventional object-based production. The distinctive language, image, and symbolic manipulatory skills of AI present new forms of authorship, autonomy, and indeterminacy and provide artists with the opportunity to create works that predetermine system-directed meaning, algorithmic patterning, and computational aesthetics. By presenting the history of algorithmic practices and the current case study, the paper will show that AI is not only a technical tool but also an active conceptual agent that can act to construct the propositions of art. This incorporates its role as partner, actor, and even proxy author, and leads to a rethinking of the agency of the creative and agency, and purposefulness. The theoretical consequences of the changes throw down challenges to the accepted versions of interpretation, work of art, and the limits of the intelligent in the artistic frames. Finally, the paper concludes that AI has a transformative potential to conceptual art that relates to the possibility of producing novel types of ideas, speculative questions, and bringing immaterial ideas to life.

References

Alotaibi, N. S. (2024). The Impact of AI and LMS Integration on the Future Of Higher Education: Opportunities, Challenges, and Strategies for Transformation. Sustainability, 16(23), 10357. https://doi.org/10.3390/su162310357 DOI: https://doi.org/10.3390/su162310357

Cao, Y., Li, S., Liu, Y., Yan, Z., Dai, Y., Yu, P. S., and Sun, L. (2023). A Comprehensive Survey of AI-Generated Content (AIGC): A History of Generative AI from GAN to ChatGPT. ArXiv Preprint Arxiv:2303.04226.

Chan, C. K. Y., and Lee, K. K. W. (2023). The AI Generation Gap: Are Gen Z Students More Interested in Adopting Generative AI such as ChatGPT in Teaching and Learning Than Their Gen X and Millennial Generation teachers? arXiv preprint arXiv:2305.02878. https://doi.org/10.1186/s40561-023-00269-3 DOI: https://doi.org/10.1186/s40561-023-00269-3

Chiu, M. C., Hwang, G. J., Hsia, L. H., and Shyu, F. M. (2022). Artificial Intelligence-Supported Art Education: A Deep Learning-Based System for Promoting University Students’ Artwork Appreciation and Painting Outcomes. Interactive Learning Environments, 32(5), 824–842. Https://Doi.Org/10.1080/10494820.2022.2100426 DOI: https://doi.org/10.1080/10494820.2022.2100426

Davidovitch, N., and Cohen, E. (2024). Administrative Roles in Academia—Potential Clash with Research Output and Teaching Quality? Cogent Education, 11, 2357914. https://doi.org/10.1080/2331186X.2024.2357914 DOI: https://doi.org/10.1080/2331186X.2024.2357914

Dehouche, N., and Dehouche, K. (2023). What’s in a Text-to-Image Prompt? The Potential of Stable Diffusion in Visual Arts Education. Heliyon, 9(8), e16757. https://doi.org/10.1016/j.heliyon.2023.e16757 DOI: https://doi.org/10.1016/j.heliyon.2023.e16757

Ernesto, D., and Gerardou, F. S. (2023). Challenges and Opportunities of Generative AI for Higher Education as Explained by ChatGPT. Education Sciences, 13(9), 856. https://doi.org/10.3390/educsci13090856 DOI: https://doi.org/10.3390/educsci13090856

Hutson, J., and Lang, M. (2023). Content Creation or Interpolation: AI Generative Digital Art in the Classroom. Metaverse, 4(1), 13. https://doi.org/10.54517/m.v4i1.2158 DOI: https://doi.org/10.54517/m.v4i1.2158

Ivanov, S., and Soliman, M. (2023). Game of Algorithms: ChatGPT Implications for the Future of Tourism Education and Research. Journal of Tourism Futures, 9(2), 214–221. https://doi.org/10.1108/JTF-02-2023-0038 DOI: https://doi.org/10.1108/JTF-02-2023-0038

Kalniņa, D., Nīmante, D., and Baranova, S. (2024). Artificial Intelligence for Higher Education: Benefits and Challenges for Pre-Service Teachers. Frontiers in Education, 9, 1501819. Https://Doi.Org/10.3389/Feduc.2024.1501819 DOI: https://doi.org/10.3389/feduc.2024.1501819

Lacey, M. M., and Smith, D. P. (2023). Teaching and Assessment of the Future Today: Higher Education and AI. Microbiology Australia, 44(3), 124–126. https://doi.org/10.1071/MA23036 DOI: https://doi.org/10.1071/MA23036

Lim, W. M., Gunasekara, A., Pallant, J. L., Pallant, J. I., and Pechenkina, E. (2023). Generative AI and the Future of Education: Ragnarök or Reformation? A Paradoxical Perspective from Management Educators. International Journal of Management Education, 21, 100790. https://doi.org/10.1016/j.ijme.2023.100790 DOI: https://doi.org/10.1016/j.ijme.2023.100790

O’Dea, X. (2024). Generative AI: Is it a Paradigm Shift for Higher Education? Studies in Higher Education, 49(5), 811–816. https://doi.org/10.1080/03075079.2024.2332944 DOI: https://doi.org/10.1080/03075079.2024.2332944

Pataranutaporn, P., Danry, V., Leong, J., Punpongsanon, P., Novy, D., Maes, P., and Sra, M. (2021). AI-Generated Characters for Supporting Personalized Learning and Well-Being. Nature Machine Intelligence, 3(11), 1013–1022. https://doi.org/10.1038/s42256-021-00417-9 DOI: https://doi.org/10.1038/s42256-021-00417-9

Sullivan, M., Kelly, A., and McLaughlan, P. (2023). ChatGPT in Higher Education: Considerations for Academic Integrity and Student Learning. Journal of Applied Learning and Teaching, 6(1), 1–10. https://doi.org/10.37074/jalt.2023.6.1.17 DOI: https://doi.org/10.37074/jalt.2023.6.1.17

Walczak, K., and Cellary, W. (2023). Challenges for Higher Education in the Era of Widespread Access to Generative AI. Economics and Business Review, 9(2), 71–100. https://doi.org/10.18559/ebr.2023.2.743 DOI: https://doi.org/10.18559/ebr.2023.2.743

Downloads

Published

2025-12-20

How to Cite

Gupta, D. P. K., Ankayarkanni B, Kumar, A., Dhiman, K., Jain, R., Pawar, A. R., & Dixit, D. N. (2025). AI AS A MEDIUM IN CONCEPTUAL ART PRACTICE. ShodhKosh: Journal of Visual and Performing Arts, 6(3s), 186–195. https://doi.org/10.29121/shodhkosh.v6.i3s.2025.6817