Chinese Whispers: The Cross-Border Application of AIGC in Art Appreciation
- 1 Graduate School of Creative Industry Design, TUA, New Taipei City
- 2 Department of Chinese Literature and Application, Fo Guang University, Yilan
- 3 Graduate School of Creative Industry Design, TUA, New Taipei City
- 4 Graduate School of Creative Industry Design, TUA, New Taipei City
- 5 Department of Product and Media Design, Fo Guang University, Yilan
Abstract
Artificial Intelligence Generated Content (AIGC) has redefined the interaction between individuals and artistic works, injecting new sources of creative inspiration into artistic expression and providing exploratory directions and interpretative perspectives in response to the transformations of the digital era. This study employs portraiture as the research sample, integrating formalism and emotion theory, supplemented by literature on art education and cognition, to construct an art appreciation framework facilitated by the operation of AIGC tools. The proposed framework consists of six sequential stages: Recognize, Describe, Modify, Dissect, Reframe, and Integrate. This framework leverages AI-driven capabilities in image recognition, analysis, and generation to facilitate viewers’ engagement with aesthetic appreciation across dimensions such as composition, color, and emotional expression in artistic forms. Additionally, it examines variations in appreciation outcomes through the perceptual perspectives of diverse AIGC systems, thereby transcending reliance on specialized expertise and subjective interpretation. The findings not only expand the scope of art appreciation and AIGC applications, enriching aesthetic experiences, but also establish multidimensional and personalized pathways for aesthetic education, thus advancing the modernization and democratization of art education.
- Anderson, L. W., & Krathwohl, D. R. (2001). A Taxonomy for Learning, Teaching, and Assessing: A Revision of Bloom’s Taxonomy of Educational Objectives. In P. W. Airasian, K. A. Cruikshank, R. E. Mayer, P. R. Pintrich, J. Raths, & M. C. Wittrock (Eds.), A Taxonomy for Learning, Teaching, and Assessing: A Revision of Bloom ’ s Taxonomy of Educational Objectives . Longman.
- Carney, J. D. (1994). A Historical Theory of Art Criticism. Journal of Aesthetic Education, 28, 13-29. https://doi.org/10.2307/3333153
- Chang, Y., Yoon, I., Park, J., Jegal, Y., & Lee, J. (2023). Understanding AI Image Generator and Exploring Educational Possibilities in Art Education. Society for Art Education of Korea, 88, 277-298. https://doi.org/10.25297/aer.2023.88.277
- Ekman, P. (1992). Facial Expressions of Emotion: An Old Controversy and New Findings. Philosophical Transactions of the Royal Society of London. Series B: Biological Sciences, 335, 63-69. https://doi.org/10.1098/rstb.1992.0008
- Ekman, P., & Friesen, W. V. (1990). The Facial Action Coding System: A Technique for the Measurement of Facial Movement . Consulting Psychologists Press.
- Elgammal, A., Liu, B., Elhoseiny, M., & Mazzone, M. (2017). CAN: Creative Adversarial Networks, Generating “ Art ” by Learning About Styles and Deviating from Style Norms . https://doi.org/10.48550/arXiv.1706.07068
- Feldman. E. B. (1970). Becoming Human through Art: Aesthetic Experience in the School . Prentice Hall.
- Hanninen, D. A. (2004). Feldman, Analysis, Experience. Twentieth-Century Music, 1, 225-251. https://doi.org/10.1017/s1478572205000137
- Hur, N. Y. (2023). The Potential of Generative AI in Art Appreciation Education: A Study of the Appreciation of the Chaesekhwa “Ilwolobongdo”. Knowledge and Culture , 12, 391-414. https://doi.org/10.54698/kl.2023.12.391
- Lee, I., & Yoo, S. B. (2022). Latent-PER: ICA-Latent Code Editing Framework for Portrait Emotion Recognition. Mathematics, 10, Article No. 4260. https://doi.org/10.3390/math10224260
- Li, C. (2024). Research on the Application of Artificial Intelligence Generated Content (AIGC) in Art Design Education. Integration of Industry and Education, 6, 26-44.
- Liang, R., & Mokhtar, E. S. b. (2024). Teaching for Art Criticism: Application of Feldman’s “Method of Art Criticism” to Students’ Expressive Ink Figure Paintings. International Journal of Education and Humanities, 12, 29-34. https://doi.org/10.54097/fv2k8m75