The ARTificial Revolution: Challenges for Redefining Art Education

Authors

  • Andrés Torres Carceller Universitat de Barcelona

DOI:

https://doi.org/10.1344/der.2024.45.84-90

Keywords:

Generative artificial intelligence, image, artistic education, education

Abstract

After years of development in the background, Artificial Intelligence (AI) has burst onto the global stage thanks to open tools for generating textual, visual, auditory, and audiovisual content. In this emerging context, AI is not only emerging as a technological phenomenon but also as a catalyst for innovation in the artistic and educational fields. Although we are only at the dawn, AI is rapidly evolving and leading us towards a revolution, opening a new field of possibilities in creative domains that will transform current aesthetic, procedural, and authorial conceptions. Its potential as a creative tool is currently limited to being a support that facilitates obtaining results of great formal quality and style quickly, but without human intervention based on clear objectives, it becomes an empty generator. Artistic Education must embrace this technology not as an intruder or rival, but as a tool to be known and integrated as another means of creation, developing skills that allow students not only to use these tools effectively but also to reflect on their implications in society and culture. Promoting a conscious, responsible, safe, and ethical use that ensures a critical stance towards generative AI. Understand that it is not a creative tool. It is for creators. 

References

Aggarwal, K., Mijwil, M. M., Al-Mistarehi, A. H., Alomari, S., Gök, M., Alaabdin, A. M. Z., & Abdulrhman, S. H. (2022). Has the future start-ed? The current growth of artificial intelligence, machine learning, and deep learning. Iraqi Journal for Computer Science and Mathe-matics, 3(1), 115-123. https://doi.org/10.52866/ijcsm.2022.01.01.013

Akinwalere, S. N., & Ivanov, V. (2022). Artificial Intelligence in Higher Education: Challenges and Opportunities. Border Crossing, 12(1), 1-15. https://doi.org/10.33182/bc.v12i1.2015

Anantrasirichai, N., & Bull, D. (2022). Artificial intelligence in the crea-tive industries: a review. Artificial intelligence review, 1-68. https://doi.org/10.1007/s10462-021-10039-7

Badea, C., & Gilpin, L. (2022). Establishing meta-decision-making for AI: an ontology of relevance, representation and reasoning. arXiv pre-print arXiv:2210.00608.

Bakpayev, M., Baek, T. H., van Esch, P., & Yoon, S. (2022). Program-matic creative: AI can think but it cannot feel. Australasian Market-ing Journal, 30(1), 90-95. https://doi.org/10.1016/j.ausmj.2020.04.002

Bernaschina, D. (2023). Artes mediales e inteligencia artificial: la crisis de la ética y la precariedad laboral en el campo artístico-digital. Revista Avenir, 7(1), 10-25.

Benjamin, W. (2018) La obra de arte en la era de su reproductibilidad técnica. Taurus.

Carceller, A. T. (2015). Forma y Color: La grisalla en la pintura; aproxi-mación a un procedimiento inadvertido. BRAC: Barcelona, Re-search, Art Creation, 3(2), 179-200. https://doi.org/10.17583/brac.2015.1350

Choi, S. K. (2022). The AI Laocoön: Art and the Artificial Imagination or, Survival Aesthetics in the Anthropocene. Leonardo, 1-13. https://doi.org/10.1162/leon_a_02307

Csikszentmihalyi, M. (2011). Fluir: Una psicología de la felicidad. Kai-rós.

Dwivedi, Y. K., Kshetri, N., Hughes, L., Slade, E. L., Jeyaraj, A., Kar, A. K., ... & Wright, R. (2023). “So what if ChatGPT wrote it?” Multidisci-plinary perspectives on opportunities, challenges and implications of generative conversational AI for research, practice and policy. In-ternational Journal of Information Management, 71, 102642. https://doi.org/10.1016/j.ijinfomgt.2023.102642

Gangadharbatla, H. (2022). The role of AI attribution knowledge in the evaluation of artwork. Empirical Studies of the Arts, 40(2), 125-142. https://doi.org/10.1177/0276237421994697

Halaweh, M. (2023). ChatGPT in education: Strategies for responsible implementation. Contemporary Educational Technology, 15(2). https://doi.org/10.30935/cedtech/13036

Haraway, D. J. (2016). The cyborg manifesto. In Haraway, D. J. Manifest-ly Haraway (pp. 117-158). University of Minnesota Press.

Hill-Yardin, E. L., Hutchinson, M. R., Laycock, R., & Spencer, S. J. (2023). A Chat (GPT) about the future of scientific publishing. Brain, behavior, and immunity, S0889-1591. 10.1016/j.bbi.2023.02.022

Hunde, B. R., & Woldeyohannes, A. D. (2022). Future prospects of computer-aided design (CAD)–A review from the perspective of arti-ficial intelligence (AI), extended reality, and 3D printing. Results in Engineering, 100478. https://doi.org/10.1016/j.rineng.2022.100478

Jaskot, P. B. (2019). Digital art history as the social history of art: To-wards the disciplinary relevance of digital methods. Visual Re-sources, 35(1-2), 21-33. https://doi.org/10.1080/01973762.2019.1553651

Jovanovic, M., & Campbell, M. (2022). Generative artificial intelligence: Trends and prospects. Computer, 55(10), 107-112. https://doi.org/10.1109/MC.2022.3192720

Khalil, M., & Er, E. (2023). Will ChatGPT get you caught? Rethinking of plagiarism detection. arXiv preprint arXiv:2302.04335.

Leach, N. (2022). From Deconstruction to Artificial Intelligence: The New Theoretical Paradigm. In The Contested Territory of Architectural Theory (pp. 229-241). Routledge.

LeCun, Y., Bengio, Y., & Hinton, G. (2015). Deep learn-ing. nature, 521(7553), 436-444. https://doi.org/10.1038/nature14539

Lee, H. K. (2022). Rethinking creativity: creative industries, AI and everyday creativity. Media, Culture & Society, 44(3), 601-612.

Lund, B. D., & Wang, T. (2023). Chatting about ChatGPT: how may AI and GPT impact academia and libraries?. Library hi tech news, 40(3), 26-29. https://doi.org/10.1177/01634437221077009

Matas, C. R. (2018). El impacto de la inteligencia artificial y de la robóti-ca en el empleo público. GIGAPP Estudios Working Papers, 5(98-110), 401-421.

McCulloch, W. S., & Pitts, W. (1943). A logical calculus of the ideas immanent in nervous activity. The Bulletin of Mathematical Bio-physics, 5(4), 115-133. https://doi.org/10.1007/BF02478259

Mitchell, T. M. (1997). Machine Learning. McGraw Hill.

Radhakrishnan, A. M. (2023). Is Midjourney-ai a new anti-hero of archi-tectural imagery and creativity?. GSJ, 11(1).

Ruiz, N. B. (2022). El arte reproductivo de Joan Rabascall en el ‘tiempo de la contestación. Archivo Español de Arte, 95(377), 81-98. https://doi.org/10.3989/aearte.2022.05

Schellekens, M. (2022). Artificial intelligence and the re-imagination of inventive step. J. Intell. Prop. Info. Tech. & Elec. Com. L., 13, 89.

Song, B., & Koo, A. (2022). Paradigm shift: Artificial intelligence, con-temporary art, and implications for gifted arts education. Journal of Gifted Education in Arts, 8, 5-38. https://doi.org/10.22752/KRIGA.2022.08.001

Tello, A. M. (2015). El arte y la subversión del archivo. Aisthesis, (58), 125-143. http://dx.doi.org/10.4067/S0718-71812015000200007

Torres-Carceller, A. (2022). Mentiras reveladoras: el fake como práctica artística contra la defactualización. VISUAL REVIEW. International Visual Culture Review/Revista Internacional de Cultura Visual, 9(Monográfico), 1-13. https://doi.org/10.37467/revvisual.v9.3560

Vartiainen, H., & Tedre, M. (2024). How Text-to-Image Generative AI is Transforming Mediated Action. IEEE Computer Graphics and Appli-cations. https://doi.org/10.1109/MCG.2024.3355808

Wellner, G. (2022). Digital Imagination, Fantasy, AI Art. Foundations of Science, 1-7. https://doi.org/10.1007/s10699-020-09747-0

Xiao, Y., Chatterjee, S., & Gehringer, E. (2022, November). A New Era of Plagiarism the Danger of Cheating Using AI. In 2022 20th Interna-tional Conference on Information Technology Based Higher Educa-tion and Training (ITHET) (pp. 1-6). IEEE.

Zhuk, A. (2023). Navigating the legal landscape of AI copyright: a com-parative analysis of EU, US, and Chinese approaches. AI Ethics. https://doi.org/10.1007/s43681-023-00299-0

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Published

2024-07-01