The ARTificial revolution. Introducing generative artificial intelligence tools into artistic education

Authors

Keywords:

artificial intelligence, content generator, creativity, art education, critical thinking, technology

Abstract

This article presents an experience of integrating generative artificial intelligence (AI) technologies in artistic education in the Primary School Teaching degree course. The aim of combining AI algorithms with traditional image editing techniques is not only to teach instrumental skills but also to foster a critical understanding of the limitations and risks associated with these technologies, promoting responsible and ethical use. The ability of AI to rapidly generate original content from text, images, video, and code, presents a complex landscape of opportunities and challenges. AI is redefining human cognitive processes and creativity, making it crucial to emphasise the importance of maintaining human intelligence as an irreplaceable complement to technology. The implementation of generative AI in art education not only enriches visual and aesthetic learning but also prepares students to contribute critically and creatively to the intersection of art and technology, equipping them with essential skills for innovation in their artistic practices.

Downloads

Download data is not yet available.

References

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

Bhandari, B., Park, G., & Shafiabady, N. (2023). Implementation of transformer-based deep learning architecture for the development of surface roughness classifier using sound and cutting force signals. Neural Computing and Applications, 1-18.

Buschow, C., & Suhr, M. (2022). Change management and new organizational forms of content creation. In Media and Change Management: Creating a Path for New Content Formats, Business Models, Consumer Roles, and Business Responsibility (pp. 381-397). Springer International Publishing.

Campbell, C., Plangger, K., Sands, S., & Kietzmann, J. (2022). Preparing for an era of deepfakes and AI-generated ads: A framework for understanding responses to manipulated advertising. Journal of Advertising, 51(1), 22-38.

Dwivedi, Y. K., Kshetri, N., Hughes, L., Slade, E. L., Jeyaraj, A., Kar, A. K., ... & Wright, R. (2023). “So what if ChatGPT wrote it?” Multidisciplinary perspectives on opportunities, challenges and implications of generative conversational AI for research, practice and policy. International Journal of Information Management, 71, 102642.

Gangadharbatla, H. (2022). The role of AI attribution knowledge in the evaluation of artwork. Empirical Studies of the Arts, 40(2), 125-142.

Habbal, A., Ali, M. K., & Abuzaraida, M. A. (2024). Artificial Intelligence Trust, risk and security management (AI trism): Frameworks, applications, challenges and future research directions. Expert Systems with Applications, 240, 122442.

Köbis, N. C., Doležalová, B., y Soraperra, I. (2021). Fooled twice: People cannot detect deepfakes but think they can. Iscience, 24(11).

Montasari, R. (2024). The Dual Role of Artificial Intelligence in Online Disinformation: A Critical Analysis. In Cyberspace, Cyberterrorism and the International Security in the Fourth Industrial Revolution: Threats, Assessment and Responses (pp. 229-240). Springer International Publishing.

Mulé, S., Lawrance, L., Belkouchi, Y., Vilgrain, V., Lewin, M., Trillaud, H., ... & Lassau, N. (2023). Generative adversarial networks (GAN)-based data augmentation of rare liver cancers: The SFR 2021 Artificial Intelligence Data Challenge. Diagnostic and Interventional Imaging, 104(1), 43-48.

Navarro, E. & Torres, A. (2023). Jo també hi era | Fake Mundet. In Bosch E. (ed.) No és un llibre de receptres (pp. 105-119). Rosa Sensat.

Nguyen, T. T., Nguyen, Q. V. H., Nguyen, D. T., Nguyen, D. T., Huynh-The, T., Nahavandi, S. & Nguyen, C. M. (2022). Deep learning for deepfakes creation and detection: A survey. Computer Vision and Image Understanding, 223, 103525.

Nguyen, T.H. (2021). 5 impactful technologies from the Gartner emerging technologies and trends impact radar for 2022. Gartner. https://www.gartner.com/en/articles/5-impactful-technologies-from-the-gartner-emerging-technologies-and-trends-impact-radar-for-2022

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 Applications.

Downloads

Published

2024-11-01

How to Cite

Torres-Carceller, A. (2024). The ARTificial revolution. Introducing generative artificial intelligence tools into artistic education. Revista Catalana De Pedagogia, 26, 64–81. Retrieved from https://revistes.iec.cat/index.php/RCP/article/view/153243

Issue

Vol. 26 (2024): Artificial intelligence in education, a gamble from pedagogy

Section

Experience articles

License

Copyright (c) 2024 Andrés Torres Carceller

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

The intellectual property of articles belongs to the respective authors.
 
On submitting articles for publication to the journal Revista Catalana de Pedagogia, authors accept the following terms:
  1. Authors grant to Societat Catalana de Pedagogia (a subsidiary of Institut d’Estudis Catalans) the rights of reproduction, communication to the public and distribution of the articles submitted for publication to Revista Catalana de Pedagogia.
  2. Authors answer to Societat Catalana de Pedagogia for the authorship and originality of submitted articles.
  3. Authors are responsible for obtaining permission for the reproduction of all graphic material included in articles.
  4. Societat Catalana de Pedagogia declines all liability for the possible infringement of intellectual property rights by authors.
  5. The contents published in the journal, unless otherwise stated in the text or in the graphic material, are subject to a Creative Commons Attribution-NonCommercial-NoDerivs (by-nc-nd) 3.0 Spain licence, the complete text of which may be found at https://creativecommons.org/licenses/by-nc-nd/3.0/es/deed.en. Consequently, the general public is authorised to reproduce, distribute and communicate the work, provided that its authorship and the body publishing it are acknowledged, and that no commercial use and no derivative works are made of it.
  6. The journal is not responsible for the ideas and opinions expressed by the authors of the published articles.