Art meets AI

Exploring the opportunities and challenges of integrating artificial intelligence in the art classroom

Authors

  • Jeremy Blair Tennessee Tech University, USA

DOI:

https://doi.org/10.32674/5hm64807

Keywords:

Artificial Intelligence, Art, Art Education, Generative, STEAM

Abstract

As artificial intelligence (AI) reshapes creative fields, its influence on art education presents both exciting possibilities and pressing challenges. This article explores how AI-powered tools can enhance creativity, pedagogy, and digital literacy, while raising concerns about authorship, equity, and the role of traditional techniques. From early algorithmic works like Harold Cohen’s AARON to contemporary AI artists like Refik Anadol, the article traces AI’s evolving role in art and STEAM education. While AI enables new forms of collaboration and interactive learning, its classroom integration introduces ethical, pedagogical, and creative dilemmas. The article advocates for a balanced approach, one that integrates AI to support, not replace, traditional practices, ensuring technology enhances rather than diminishes the creative agency of students and educators.

Author Biography

  • Jeremy Blair, Tennessee Tech University, USA

    JEREMY BLAIR, PhD, is an Associate Professor of Art Education in the School of Art, Craft & Design at Tennessee Tech University. His visual art practice, teaching, and scholarship investigate the intersections of art and science, with a particular focus on STEAM Education. Email: jmblair@tntech.edu

References

Ahn, I.-K., & Lee, M.-Y. (2024). Action research on developing elementary art instruction programme using generative AI. Journal of Research in Art Education, 25(1), 1–31. https://doi.org/10.20977/kkosea.2024.25.1.1

Anadol, R. (2022). Space in the mind of a machine: Immersive narratives. Architectural Design, 92(3), 28–37. https://doi.org/10.1002/ad.2810

Bender, S. M. (2024). Awareness of artificial intelligence as an essential digital literacy: ChatGPT and Gen-AI in the classroom. Changing English, 31(2), 161–174. https://doi.org/10.1080/1358684X.2024.2309995

Blair, J. (2024). Virtual reality art education. In N. Walkup & T. Hunter-Doniger (Eds.), STEAM education: Transdisciplinarity of art in the curriculum. National Art Education Association Publishing.

Cave, S., & Dihal, K. (2020). The whiteness of AI. Philosophy & Technology, 33(4), 685–703. https://doi.org/10.1007/s13347-020-00415-6

Cayley, J. (2018). Grammalepsy: Essays on digital language art. Bloomsbury Academic. https://doi.org/10.5040/9781501335792

Chalmers, D. J., French, R. M., & Hofstadter, D. R. (1992). High-level perception, representation, and analogy: A critique of artificial intelligence methodology. Journal of Experimental & Theoretical Artificial Intelligence, 4(3), 185–211. https://doi.org/10.1080/09528139208953747

Chung, S. (n.d.). Drawing operations. https://sougwen.com/project/drawing-operations

Colton, S., McCormack, J., & d’Inverno, M. (2012). The Painting Fool: Stories from building an automated painter. In Computers and Creativity (pp. 3–38). Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-642-31727-9_1

Cotroneo, P., & Hutson, J. (2023). Generative AI tools in art education: Exploring prompt engineering and iterative processes for enhanced creativity. Metaverse, 4(1), 1–14. https://doi.org/10.54517/m.v4i1.2164

Crespo, S. (2020, September 17). AI-powered natural history: Sofia Crespo’s artificial lifeforms explore the intersection of nature and machine learning. Colossal. https://www.thisiscolossal.com/2020/09/sofia-crespo-ai-natural-history/

Doherty, H. (2016). Virtual art: Google’s DeepDream. University Wire. Uloop, Inc.

Gatys, L. A., Bethge, M., Hertzmann, A., & Shechtman, E. (2016). Preserving color in neural artistic style transfer. https://doi.org/10.48550/arxiv.1606.05897

Hargittai, I. (2024). Remembering Benoit Mandelbrot on his centennial – His fractal geometry changed our view of nature. Structural Chemistry, 35(5), 1657–1661. https://doi.org/10.1007/s11224-024-02290-9

Hunt, K. (2001). PIXELS: STATEWIDE Edition. The Hartford Courant.

Hutson, J., & Lang, M. (2023). Content creation or interpolation: AI generative digital art in the classroom. Metaverse, 4(1), 1–13. https://doi.org/10.54517/m.v4i1.2158

Kang, Q., & Lee, J. W. (2023). Artificial intelligence: The perspective of omnivore. Journal of Digital Art Engineering and Multimedia, 10(3), 279–292. https://doi.org/10.29056/jdaem.2023.09.01

Kannonier, R., Kluszczyński, R. W., Mersmann, B., Moriyama, T., Ohlenschlager, K., Reichle, I., & Zielinski, S. (2022). Christa Sommerer & Laurent Mignonneau: The artwork as a living system 1992–2022. ZKM Center for Art and Media Karlsruhe.

Kaufman, S. L. (2020). Artist Sougwen Chung wanted collaborators. So she designed and built her own AI robots. The Washington Post.

Lambert, N., Latham, W., & Leymarie, F. F. (2013). The emergence and growth of evolutionary art—1980–1993. Leonardo, 46(4), 367–375. https://doi.org/10.1162/LEON_a_00608

LeCun, Y., Bengio, Y., & Hinton, G. (2015). Deep learning. Nature, 521(7553), 436–444. https://doi.org/10.1038/nature14539

Mao, X., & Li, Q. (2021). Generative adversarial networks for image generation (1st ed. 2021). Springer. https://doi.org/10.1007/978-981-33-6048-8

Martin, N., & Willemars, I. (2024). The replaceability paradigm: Replacement and irreplaceability from Dante to DeepDream. DeGruyter. https://doi.org/10.1515/9783111286402

McCorduck, P. (1991). Aaron’s code: Meta-art, artificial intelligence, and the work of Harold Cohen. W.H. Freeman.

Miller, A. I. (2019). The artist in the machine: The world of AI-powered creativity. The MIT Press.

Montero, J. B. (2024). Revolutionising creativity: Unleashing the power of AI in upper elementary art education. International Journal of Learning and Teaching, 10(4), 510–515. https://doi.org/10.18178/ijlt.10.4.510-515

Park, Y. S. (2023). Creative and critical entanglements “with” AI in art education. Studies in Art Education, 64(4), 406–425. https://doi.org/10.1080/00393541.2023.2255084

Putnam, K. W. (1997). David Cope: Experiments in musical intelligence. Computer Music Journal, 21(3), 102.

Raines, A. D. (2024). Balancing art and science: Guiding the responsible use of AI systems in the context of art [Doctoral dissertation, ProQuest Dissertations & Theses].

Refik Anadol. (2024, March 9). Archive Dreaming - AI Data Sculpture. https://refikanadol.com/works/archive-dreaming/

Rogers, H. S. (2020). Cheering artificial intelligence leader: Creative writing and materialising design fiction. Leonardo, 53(1), 58–62. https://doi.org/10.1162/leon_a_01578

Salimbeni, G., Benford, S., Reeves, S., & Martindale, S. (2024). Decoding AI in contemporary art: A five-trope classification for understanding and categorisation. Leonardo, 57(4), 415–421. https://doi.org/10.1162/leon_a_02546

Schlichtmann, S. (2023, September 8). Generative AI art programme Midjourney sparks new artistic potential. The New Hampshire.

Schmuckli, C. (2020). Beyond the uncanny valley: Being human in the age of AI. Cameron.

Shoemaker, E. (2024). Is AI art theft? The moral foundations of copyright law in the context of AI image generation. Philosophy & Technology, 37(3), 114–135. https://doi.org/10.1007/s13347-024-00797-x

Sims, K. (1994). Evolving virtual creatures. Proceedings of the 21st Annual Conference on Computer Graphics and Interactive Techniques (SIGGRAPH '94), 15–22. https://www.karlsims.com/papers/siggraph94.pdf

Sundararajan, L. (2014). Mind, machine, and creativity: An artist’s perspective. The Journal of Creative Behavior, 48(2), 136–151. https://doi.org/10.1002/jocb.44Sweeny, R. (2023). Editorial: Digital and

postdigital media in art education. Studies in Art Education: A Journal of Issues and Research, 64(4), 401–405.

Tatar, K., Ericson, P., Cotton, K., Del Prado, P. T. N., Batlle-Roca, R., Cabrero-Daniel, B., Ljungblad, S., Diapoulis, G., & Hussain, J. (2024). A shift in artistic practices through artificial intelligence. Leonardo, 57(3), 293–297.

Tavin, K., Kolb, G., & Tervo, J. (Eds.). (2021). Post-digital, post-internet art and education: The future is all-over. Palgrave Macmillan.

Tremblay, É. (2014). Stranger Visions by Heather Dewey-Hagborg: Reinterpreting portraiture through new forensic and 3D printing techniques. ETC Media, 103, 44–48.

Tschmuck, P. (2024, April 1). AI in the music industry – part 10: François Pachet: The Continuator, Flow Machines and “Daddy’s Car.” Music Business Research. https://musicbusinessresearch.wordpress.com/2024/04/08/ai-in-the-music-industry-part-10-francois-pachet-the-continuator-flow-machines-and-daddys-car/

van den Berg, G., & du Plessis, E. (2023). ChatGPT and generative AI: Possibilities for its contribution to lesson planning, critical thinking and openness in teacher education. Education Sciences, 13(10), 998–1009. https://doi.org/10.3390/educsci13100998

Yoo, H.-J. (2022). A case study on artificial intelligence’s music creation: Focusing on Google’s AI Magenta Project. The Journal of Next-Generation Convergence Technology Association, 6(9), 1737–1745. https://doi.org/10.33097/JNCTA.2022.06.09.1737

Yuk, J.-M., Kim, Y.-G., & Chun, J.-Y. (2023). Study on performing arts in virtual environments using artificial intelligence and augmented reality. Journal of Digital Contents Society, 24(12), 2981–2991. https://doi.org/10.9728/dcs.2023.24.12.2981

Zhou, Y. (2024). The impact of the artificial intelligence (AI) art generator in pre-service art teacher training. 2024 IEEE Conference on Artificial Intelligence (CAI), 1406–1407. https://doi.org/10.1109/CAI59869.2024.00250

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Published

2025-07-25

Issue

Section

Art and Technology in STEM

How to Cite

Blair, J. (2025). Art meets AI: Exploring the opportunities and challenges of integrating artificial intelligence in the art classroom. American Journal of STEM Education, 14, 59-74. https://doi.org/10.32674/5hm64807

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