Studio Ghibli: Counter IP perspective on visual styles generated by AI image generators
DOI:
https://doi.org/10.30998/jd.v13i2.905Keywords:
AI Image Generator, Studio Ghibli Copyright, Digital Ethics, Transformative Fair Use, Cultural Soft PowerAbstract
This study quantitatively analyzes how the use of AI Image Generators to replicate Studio Ghibli’s visual style is perceived in public and academic discourse, particularly concerning legal, ethical, and cultural dimensions. Employing a quantitative content analysis using NVivo-assisted coding of secondary data gathered from 20 scholarly and professional publications between 2020 and 2025, the research investigates the evolving relationship between human creativity and generative technology. The results indicate that the majority of sources (60%) interpret AI’s role in the Ghibli context as a non-commercial form of transformative fair use that serves as a medium of Japanese cultural promotion, whereas 30% regard it as a potential copyright infringement, and 10% emphasize the need for new ethical regulation. The findings reveal the ambivalence of AI as both a challenge to human authorship and a catalyst for collaborative innovation that redefines aesthetic expression through algorithmic creativity. The phenomenon of Ghibli-style AI art also contributes to Japan’s cultural soft power, reinforcing its humanistic and ecological aesthetic values within the global digital sphere. The study concludes that conventional copyright frameworks are insufficient to regulate hybrid authorship involving humans and machines, necessitating new policies grounded in fairness, transparency, and moral responsibility. Furthermore, the study offers pedagogical and industrial implications, highlighting the importance of integrating AI ethics and intellectual property literacy into art education and creative practices to ensure a responsible and inclusive generative art future.
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References
Beveridge, A. (2023). ‘AI Art And Copyright: The Ethics Of Machine-Made Creativity.’ Journal of Intellectual Property Law & Practice, 18(4), 265–278. https://doi.org/10.1093/jiplp/jpad025
Cavallaro, D. (2021). ‘The Animism Of Ghibli: Aesthetic Symbolism and Ecological Ethics In Japanese Animation.’ Animation Studies, 16(2), 41–58. https://doi.org/10.1386/anim_00057_1
Darmawan, A. J., Arimbawa, I. M. G., Heptariza, A., & Brayen, H. (2024). ‘Harnessing Ai Image Generator Prompt Engineering For Academic Excellence.’ In Proceeding Bali-Bhuwana Waskita: Global Art Creativity Conference (Vol. 4), 192-202.
Darmawan, A. J., Yoo, P. M. H., & Hartawan, R. A. (2024). ‘Teknik Prompt ANVS Progresif untuk Bing Image Creator dan Interpretasi Kesenjangan Gambar AI.’ Visualita: Jurnal Online Desain Komunikasi Visual, 13(1).
Dyer, C. (2024). ‘The Generative Dilemma: Authorship and Imitation In AI Art.’ Digital Creativity, 35(1), 23–40. https://doi.org/10.1080/14626268.2024.1012379
Elgammal, A. (2023). ‘Creative Adversarial Networks and The Future Of Digital Authorship.’ AI & Society, 38(2), 587–601. https://doi.org/10.1007/s00146-022-01456-0
Flew, T. (2022). ‘AI, Creativity, and The Digital Economy Of Culture.’ New Media & Society, 24(9), 1998–2014. https://doi.org/10.1177/14614448211068191
Geiger, D., & Gross, C. (2022). ‘Algorithmic Aesthetics: Ethics and Ownership In Generative Art.’ Information Systems Journal, 32(3), 465–480. https://doi.org/10.1111/isj.12345
Iwabuchi, K. (2022). ‘Cultural Hybridization and The Soft Power Of Anime: Revisiting Ghibli In The AI Era.’ Asian Journal of Communication, 32(5), 512–529. https://doi.org/10.1080/01292986.2022.2084521
Khosla, R. (2023). ‘Human–AI Collaboration In Digital Design: Rethinking Originality.’ Design Studies, 89(1), 102–119. https://doi.org/10.1016/j.destud.2023.102119
Manovich, L. (2020). ‘AI Aesthetics: Between Human Intuition and Machine Logic.’ Leonardo, 53(2), 105–111. https://doi.org/10.1162/leon_a_01957
Rieder, B. (2023). ‘Algorithmic Creativity and User Participation In Generative Platforms.’ Computers in Human Behavior, 146, 107739. https://doi.org/10.1016/j.chb.2023.107739
Sorensen, J. (2023). ‘Copyright In The Age Of AI-Generated Imagery: Global Implications.’ International Review of Law, Computers & Technology, 37(1), 44–63. https://doi.org/10.1080/13600869.2023.2184127
Thompson, M. (2024). ‘Machine-Made Art and Moral Rights: Toward A New Ethical Framework.’ Ethics and Information Technology, 26(2), 201–218. https://doi.org/10.1007/s10676-024-09645-8
Vial, G. (2019). ‘Understanding Digital Transformation: A Review and A Research Agenda.’ Journal of Strategic Information Systems, 28(2), 118–144. https://doi.org/10.1016/j.jsis.2019.01.003
Yoon, H. (2021). ‘Fandom As Informal Marketing: Digital Circulation Of Anime Aesthetics.’ Media, Culture & Society, 43(7), 1278–1295. https://doi.org/10.1177/01634437211003218
Zhao, L. (2024). ‘Legal Personhood for AI-Generated Works: Rethinking Copyright Authorship.’ Artificial Intelligence and Law, 32(3), 333–349. https://doi.org/10.1007/s10506-024-09322-2
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