From Digitization to the AI Era: Digital Technology Trajectories in Fine-Art Creation

Hu Yang; Yu  Zou; Bo Gao

doi:10.62177/apemr.v3i1.1086

Authors

Hu Yang Jinan University
Yu Zou Macau University of Science and Technology
Bo Gao Nanjing University of the Arts

DOI:

https://doi.org/10.62177/apemr.v3i1.1086

Keywords:

Digitization, Digital Art, Platformization, Generative AI, Authorship, Technological Humanism

Abstract

This article analyzes how digital technologies have reconfigured fine-art creation from early computer graphics to contemporary generative AI. It advances a practice-centered periodization that links changing tool affordances to shifts in authorship, originality, distribution, and the political economy of creative labor. Three phases are identified: medium translation (1980–2000), when images became file-based and procedural logics entered artistic craft; platformized networking (2000–2010), when Web 2.0 expanded participation while structuring visibility through interfaces, metrics, and attention regimes; and algorithmic autonomy (2010–present), when GANs and diffusion models made style and composition statistically learnable and widely replicable. The AI phase intensifies long-standing debates by redistributing artistic agency across prompts, model priors, datasets, and post-selection, while deepening dependence on data extraction and platform governance. In response, the article proposes technological humanism as a normative-analytic framework for AI-mediated art: it centers traceable delegation, situated cultural responsibility, and infrastructural transparency as conditions of accountable creation. The paper concludes with operational principles for artists, educators, and museums to evaluate and sustain agency and cultural integrity under algorithmic production.

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References

Shi, J., & Pan, Z. (2001). Computer graphics around the world: Computer graphics in China: An overview. SIGGRAPH Computer Graphics, 35(2), 22–27. doi:10.1145/563693.563697.

Manovich, L. (2013). Software takes command. Bloomsbury Academic.

Benjamin, W. (2008). The work of art in the age of its technological reproducibility, and other writings on media (M. W. Jennings, B. Doherty, & T. Y. Levin, Eds.; E. Jephcott, R. Livingstone, & H. Eiland, Trans.). Harvard University Press.

Reas, C., & Fry, B. (2014). Processing (2nd ed.): A programming handbook for visual designers and artists. The MIT Press.

Jenkins, H. (2006). Convergence culture: Where old and new media collide. New York University Press.

Hu, Y., & Cai, Y. (2025). The beginning of China’s animation industry: A brief history of Guangzhou Generation Animation. ASIFA Academic Magazine, 2(1), 71–80.

Moulier-Boutang, Y. (2011). Cognitive capitalism. Polity Press.

Terranova, T. (2000). Free labor: Producing culture for the digital economy. Social Text, 18(2), 33–58. doi:10.1215/01642472-18-2_63-33.

Goodfellow, I., Pouget-Abadie, J., Mirza, M., Xu, B., Warde-Farley, D., Ozair, S., Courville, A., & Bengio, Y. (2014). Generative adversarial nets. In Advances in Neural Information Processing Systems, 27, 2672–2680.

Ho, J., Jain, A., & Abbeel, P. (2020). Denoising diffusion probabilistic models. In Advances in Neural Information Processing Systems, 33, 6840–6851.

Oppenlaender, J., Linder, R., & Silvennoinen, J. (2024). Prompting AI art: An investigation into the creative skill of prompt engineering. International Journal of Human–Computer Interaction, 41(16), 10207–10229. doi:10.1080/10447318.2024.2431761.

Bender, E. M., Gebru, T., McMillan-Major, A., & Shmitchell, S. (2021). On the dangers of stochastic parrots: Can language models be too big? In Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency (FAccT ’21), 610–623. doi:10.1145/3442188.3445922.

Crawford, K. (2021). Atlas of AI: Power, politics, and the planetary costs of artificial intelligence. Yale University Press.

Ihde, D. (1990). Technology and the lifeworld: From garden to earth. Indiana University Press.

Pajkovic, N. (2022). Algorithms and taste-making: Exposing the Netflix recommender system’s operational logics. Convergence: The International Journal of Research into New Media Technologies, 28(1), 214–235. doi:10.1177/13548565211014464.

Said, E. W. (1985). Orientalism reconsidered. Cultural Critique, (1), 89–107. doi:10.2307/1354282.

Bhabha, H. K. (1994). The location of culture. Routledge.

Bonini, T., & Treré, E. (2024). Algorithms of resistance: The everyday fight against platform power. The MIT Press.

Couldry, N., & Mejias, U. A. (2019). Data colonialism: Rethinking big data’s relation to the contemporary subject. Television & New Media, 20(4), 336–349. doi:10.1177/1527476418796632.

Nadini, M., Alessandretti, L., Di Giacinto, F., Martino, M., Aiello, L. M., & Baronchelli, A. (2021). Mapping the NFT revolution: market trends, trade networks, and visual features. Scientific Reports, 11, 20902. doi:10.1038/s41598-021-00053-8.

Truby, J., Brown, R. D., Dahdal, A., & Ibrahim, I. A. (2022). Blockchain, climate damage, and death: Policy interventions to reduce the carbon emissions, mortality, and net-zero implications of non-fungible tokens and Bitcoin. Energy Research & Social Science, 88, 102499. doi:10.1016/j.erss.2022.102499.

Stiegler, B. (2018). The neganthropocene (D. Ross, Trans.). Open Humanities Press.

Latour, B. (2005). Reassembling the social: An introduction to actor-network-theory. Oxford University Press.

Derrida, J. (1981). Positions (A. Bass, Trans.). University of Chicago Press.

Wang, J., Zhang, J., Li, J., Liang, W., Shenhui, Ruan, J., ... & Wu, P. (2026). From Awareness to Participation: Diffusion of Innovation and Engagement of Older People in Barrier-Free Communities in Zhuhai, China. Journal of Aging & Social Policy, 1-23.

Liang, Y., Zhang, J., Chen, J., Wu, J., Shen, H., & Liang, W. (2025). Generative large language models and academic integrity: ethical risks, detection challenges, and Governance in the age of AI. Ethics & Behavior, 1-19.

Wen, J., Tong, S., Liang, W., He, H., & Shen, H. (2025). Is the emotional and cultural need satisfied or not?–A qualitative study based on youth users learning dance through Douyin. Research in Dance Education, 1-22.