Vol. 10 No. 2 (2026): JULY[DOI:10.37785/nw.v10n2] The Synthetic Gaze. Generative AI and the Transformation of Contemporary Visual Authorship (English version) Article Sidebar Text Complete: PDF MHT Published: 2026-07-15 DOI: https://doi.org/10.37785/nw.v10n2.a2e Keywords: Array, Array, Array, Array, Array Main Article Content Fernando A. Ramos Zaga Cesar Vallejo University image/svg+xml Abstract The expansion of generative artificial intelligence within the field of visual creation has triggered a profound structural transformation in the regimes of production, legitimation, and aesthetic experience. Accordingly, the objective of this article is to analyze the ontological, epistemic, and ethical mutations arising from algorithmic mediation, with the aim of establishing the theoretical foundations for a critical aesthetics of the synthetic gaze. The findings demonstrate that generative visual production does not merely extend human creativity but reconfigures artistic agency through the redistribution of authorship, the statistical recombination of originality, and the conversion of authenticity into procedural transparency. This shift underscores the need to construct ethical and regulatory frameworks that incorporate algorithmic traceability, relational responsibility, and distributive justice within creative ecosystems. Ultimately, the study proposes a reinterpretation of art as a cognitively and morally situated practice within hybrid ecologies of human and machinic creation. Spanish version: https://nawi.espol.edu.ec/index.php/nawi/es/article/view/1234/1232 DOWNLOADS Download data is not yet available. Article Details How to Cite Ramos Zaga, F. A. (2026). The Synthetic Gaze. Generative AI and the Transformation of Contemporary Visual Authorship (English version). 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M., & Wartella, E. A. (2024). My art is not your dataset: Artists' perspectives on generative AI and copyright. Proceedings of the ACM on Human-Computer Interaction, 8 (CSCW1), 1-28. https://doi.org/10.1145/3641423 Manovich, L. (2022). AI aesthetics and the end of taste. En M. Azoulay & A. Mbembe (Eds.), Potential history: Unlearning imperialism (pp. 412-434). London: Verso Books. Mazzi, L. (2024). Distributed creativity: Collaboration between human and artificial intelligence in art making. AI & Society, 39 (1), 145-162. https://doi.org/10.1007/s00146-022-01567-0 McLuhan, M. (1964). Understanding media: The extensions of man. New York: McGraw-Hill. Noble, S. U. (2018). Algorithms of oppression: How search engines reinforce racism. New York: NYU Press. Ramesh, A., Dhariwal, P., Nichol, A., Chu, C., & Chen, M. (2022). Hierarchical text-conditional image generation with CLIP latents. Rescatado de: https://arxiv.org/abs/2204.06125 Ramos-Zaga, F. A. (2025). Reconceptualizing human authorship in the age of generative AI: A normative framework for copyright thresholds. Laws, 14 (6), 84. https://doi.org/10.3390/laws14060084 Rombach, R., Blattmann, A., Lorenz, D., Esser, P., & Ommer, B. (2022). High-resolution image synthesis with latent diffusion models. Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 10684-10695. https://doi.org/10.1109/ CVPR52688.2022.01042 Sennett, R. (2008). The craftsman. New Haven, USA: Yale University Press. Smith, J. E. (2025). Algorithmic aesthetic surplus: Platform capitalism and the production of visual culture. New Media & Society, 27 (1), 89-107. https://doi.org/10.1177/14614448231205432 Vincent, J. (2023). The artists fighting back against AI image generators. The Verge. Rescatado de: https://www.theverge. com/2023/1/16/23557098/generative-ai-art-copyright-legal-battle-stable-diffusion-midjourney Hayles, N. K. (2017). Unthought: The power of the cognitive nonconscious. Chicago: University of Chicago Press. Ho, J., Jain, A., & Abbeel, P. (2020). Denoising diffusion probabilistic models. Advances in Neural Information Processing Systems, 33, 6840-6851. Hutchins, E. (1995). Cognition in the wild. Cambridge, Massachusetts: MIT Press. Irmak, N. (2024). Who is the author? Authorship, ownership, and agency in generative AI art. Philosophy & Technology, 37 (1), 1-24. https://doi.org/10.1007/s13347-023-00678-9 Jaszi, P. (1991). Toward a theory of copyright: The metamorphoses of "authorship". Duke Law Journal, 1991 (2), 455-502. https://doi. org/10.2307/1372804 Kant, I. (2000). Critique of the power of judgment (P. Guyer & E. Matthews, Trans.). Cambridge, UK: Cambridge University Press. Krauss, R. E. (1985). The originality of the avant-garde and other modernist myths. Cambridge, Massachusetts: MIT Press. Latour, B. (2005). Reassembling the social: An introduction to actor-network-theory. Oxford, UK: Oxford University Press. Lemley, M. A., & Casey, B. (2021). Fair learning. Texas Law Review, 99 (4), 743-807. Leval, P. N. (1990). Toward a fair use standard. Harvard Law Review, 103 (5), 1105-1136. https://doi.org/10.2307/1341457 Locke, J. (1988). Two treatises of government (P. Laslett, Ed.). Cambridge, UK: Cambridge University Press. Lovato, S., Piper, A. M., & Wartella, E. A. (2024). My art is not your dataset: Artists' perspectives on generative AI and copyright. Proceedings of the ACM on Human-Computer Interaction, 8 (CSCW1), 1-28. https://doi.org/10.1145/3641423 Manovich, L. (2022). AI aesthetics and the end of taste. En M. Azoulay & A. Mbembe (Eds.), Potential history: Unlearning imperialism (pp. 412-434). London: Verso Books. Mazzi, L. (2024). Distributed creativity: Collaboration between human and artificial intelligence in art making. AI & Society, 39 (1), 145-162. https://doi.org/10.1007/s00146-022-01567-0 McLuhan, M. (1964). Understanding media: The extensions of man. New York: McGraw-Hill. Noble, S. U. (2018). Algorithms of oppression: How search engines reinforce racism. New York: NYU Press. Ramesh, A., Dhariwal, P., Nichol, A., Chu, C., & Chen, M. (2022). Hierarchical text-conditional image generation with CLIP latents. Rescatado de: https://arxiv.org/abs/2204.06125 Ramos-Zaga, F. A. (2025). Reconceptualizing human authorship in the age of generative AI: A normative framework for copyright thresholds. Laws, 14 (6), 84. https://doi.org/10.3390/laws14060084 Rombach, R., Blattmann, A., Lorenz, D., Esser, P., & Ommer, B. (2022). High-resolution image synthesis with latent diffusion models. Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 10684-10695. https://doi.org/10.1109/ CVPR52688.2022.01042 Sennett, R. (2008). The craftsman. New Haven, USA: Yale University Press. Smith, J. E. (2025). Algorithmic aesthetic surplus: Platform capitalism and the production of visual culture. New Media & Society, 27 (1), 89-107. https://doi.org/10.1177/14614448231205432 Vincent, J. (2023). The artists fighting back against AI image generators. The Verge. Rescatado de: https://www.theverge. com/2023/1/16/23557098/generative-ai-art-copyright-legal-battle-stable-diffusion-midjourney Hayles, N. K. (2017). Unthought: The power of the cognitive nonconscious. Chicago: University of Chicago Press. Ho, J., Jain, A., & Abbeel, P. (2020). Denoising diffusion probabilistic models. Advances in Neural Information Processing Systems, 33, 6840-6851. Hutchins, E. (1995). Cognition in the wild. Cambridge, Massachusetts: MIT Press. Irmak, N. (2024). Who is the author? Authorship, ownership, and agency in generative AI art. Philosophy & Technology, 37 (1), 1-24. https://doi.org/10.1007/s13347-023-00678-9 Jaszi, P. (1991). Toward a theory of copyright: The metamorphoses of "authorship". Duke Law Journal, 1991 (2), 455-502. https://doi. org/10.2307/1372804 Kant, I. (2000). 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Creativity Research Journal, 36 (2), 201-218. https://doi.org/10.1080/10400419.2023.2287654 Issue Vol. 10 No. 2 (2026): JULY[DOI:10.37785/nw.v10n2] Section ARTICLES How to Cite Ramos Zaga, F. A. (2026). The Synthetic Gaze. Generative AI and the Transformation of Contemporary Visual Authorship (English version). Nawi, 10(2), 55-71. https://doi.org/10.37785/nw.v10n2.a2e More Citation Formats ABNT ACM ACS AMA APA Chicago Harvard IEEE MLA Turabian Vancouver Download Citation Endnote/Zotero/Mendeley (RIS) BibTeX This work is under a Licencia Creative Commons Atribución-NoComercial 4.0 Internacional. Comments and suggestions on the article Managing Director Jorge Polo Blanco, PhD. polo@espol.edu.ec ESPOL - FADCOM Executive Director Nayeth Solorzano, PhD. nsolorza@espol.edu.ec ESPOL - FADCOM