Abstract
This paper explores the intersection of art history and AI technology. Special attention is paid to Generative Adversarial Networks (GANs), a machine learning technology widely used in AI art. This technology is particularly interesting to art history and the philosophy of art because it raises enduring questions about the creative process of artmaking, especially what constitutes a new and original work of art. While this is a relatively new area, it is possible to discern emerging directions where art and AI intersect. One pressing issue concerns the use (or misuse) of algorithmically enabled technologies and datasets to perpetuate longstanding art-historical biases. The critical position adopted in this paper shares this concern. I examine a notable example of GAN technology that claims to create original art styles. While such experiments in computational creativity are technically interesting, their artistic aims can be questionable. I argue a mechanical model of artistic development based solely on the autonomy of style is problematic for at least two reasons: 1) it uncritically reinstates a formalist view of art history; 2) it recreates a narrow style-centric ‘historical modernism.’ However, despite voicing these reservations, I also discuss the potential of this technology to engage with topics of critical relevance to art history and the philosophy of art.
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References
Ackerman, J. S. (2002). Origins, imitation, conventions: Representation in the visual arts. MIT Press.
Bailey, J. (2018). The AI art at Christie’s is not what you think. Artnome. Retrieved January 4, 2024. https://www.artnome.com/news/2018/10/13/the-ai-art-at-christies-is-not-what-you-think
Bailey, J. (2020). The Tools of Generative Art, From Flash to Neural Networks. Art in America. Retrieved January 4, 2024. https://www.artnews.com/art-in-america/features/generative-art-tools-flash-processing-neural-networks-1202674657/
Barr, A. H. (1966). Cubism and abstract art. Museum of Modern Art.
Bell, C. (1982). The aesthetic hypothesis. In F. Frascina & C. Harrison (Eds.), Modern art and modernism: A critical anthology (pp. 67–78). Harper & Row.
Belting, H. (1987). The end of the history of art? University of Chicago Press.
Belting, H. (2003). Art history after modernism. University of Chicago Press.
Berryman, J. (2023). Wollheim on art’s historicity: an intersection of theoretical art history and the philosophy of art. The British Journal of Aesthetics, ayad024. https://doi.org/10.1093/aesthj/ayad024
Carroll, N. (1988). Art, practice, and narrative. The Monist, 71(2), 140–156. https://doi.org/10.5840/monist198871212
Carroll, N. (2003). Art, Creativity, and Tradition. In B. Gaut & L. Paisley (Eds.), The creation of art: New essays in philosophical aesthetics (pp. 208–234). CUP.
Christie’s. (2018). Is artificial intelligence set to become art’s next medium?. Christies.com. Retrieved January 4, 2024, from https://www.christies.com/features/A-collaboration-between-two-artists-one-human-one-a-machine-9332-1.aspx
Clark, T. J. (1999). Farewell to an idea: Episodes from a history of modernism. Yale University Press.
Coeckelbergh, M. (2017). Can machines create art? Philosophy and Technology, 30(3), 285–303. https://doi.org/10.1007/s13347-016-0231-5
Colton, S., Pease, A, & Saunders, R. (2018). Issues of authenticity in autonomously creative systems. In Proceedings of the 9th International Conference on Computational Creativity (ICCC), Salamanca, Spain, June 25–29, 2018, 272–279. Retrieved January 4, 2024. https://computationalcreativity.net/iccc2018/sites/default/files/papers/ICCC_2018_paper_64.pdf
Crane, D. (1987). The transformation of the avant-garde: The New York art world, 1940–1985. University of Chicago Press.
Danto, A. C. (1992). Beyond the Brillo box: The visual arts in post-historical perspective. University of California Press.
Danto, A. C. (1997). After the end of art: Contemporary art and the pale of history. Princeton University Press.
Davies, S. (2001). Definitions of Art. In B. Gaut & D. Lopes (Eds.), The Routledge companion to aesthetics (pp. 169–179). Routledge.
De Duve, T. (1996). Kant after Duchamp. MIT 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. In Proceedings of the 8th International Conference on Computational Creativity, ICCC 2017. Retrieved January 4, 2024. http://arxiv.org/abs/1706.07068
Elgammal, A. (2018a). Meet AICAN, a machine that operates as an autonomous artist. The Conversation. Retrieved January 4, 2024, https://theconversation.com/meet-aican-a-machine-that-operates-as-an-autonomous-artist-104381
Elgammal, A., Liu, B., Kim, D., Elhoseiny, M., & Mazzone, M. (2018b). The shape of art history in the eyes of the machine. 32nd AAAI Conference on Artificial Intelligence, New Orleans, USA, February 2–7, 2018, 2183–2191. https://arxiv.org/abs/1801.07729
Elkins, J. (2005). Master narratives and their discontents. Routledge.
Epstein, Z., Levine, S., Rand, D. G., & Rahwan, I. (2020). Who gets credit for AI-generated art? iScience, 23(9), 101515. Retrieved January 4, 2024. https://www.sciencedirect.com/science/article/pii/S2589004220307070
Eshraghian, J. (2020). Human ownership of artificial creativity. Nature Machine Intelligence, 2(3), 157–160. https://doi.org/10.1038/s42256-020-0161-x
Foçillon, H. (1989). The life of forms in art. Zone Books.
Frank, S. J., & Frank, A. M. (2022). Complementing connoisseurship with artificial intelligence. Curator, 65(4), 835–868. https://doi.org/10.1111/cura.12492
Fry, R. (1982). An essay in aesthetics. In F. Frascina & C. Harrison (Eds.), Modern art and modernism: A critical anthology (pp. 79–87). Harper & Row.
Gombrich, E.H. (2002). Art and illusion: a study in the psychology of pictorial representation (6th ed.). Phaidon.
Greenberg, C. (1961). Art and culture: critical essays. Beacon Press.
Greenberg, C. (1982). Modernist painting. In F. Frascina & C. Harrison (Eds.), Modern art and modernism: A critical anthology (pp. 5–10). Harper & Row.
Hakopian, M. F. (2023). Art histories from nowhere: On the coloniality of experiments in art and artificial intelligence. AI and Society. https://doi.org/10.1007/s00146-023-01768-0
Hassine, T., & Neeman, Z. (2019). The Zombification of art history: How AI resurrects dead masters, and perpetuates historical biases. Journal of Science and Technology of the Arts, 11(2), 28–35. https://doi.org/10.7559/citarj.v11i2.663
Hauser, A. (1959). The philosophy of art history. Knopf.
Hertzmann, A. (2020). Visual indeterminacy in GAN art. Leonardo, 53(4), 424–428. https://doi.org/10.1162/leon_a_01930
Jackson, P. (2022). The art of copying art. Palgrave Macmillan.
Kantor, S.G. (2002). Alfred H. Barr, Jr., and the intellectual origins of the Museum of Modern Art. MIT Press.
Krauss, R. E. (1985). The originality of the avant-garde and other modernist myths. MIT Press.
Kubler, G. (2008). The shape of time: Remarks on the history of things. Yale University Press.
Levinson, J. (1979). Defining art historically. British Journal of Aesthetics, 19(3), 232–250. https://doi.org/10.1093/bjaesthetics/19.3.232
Levinson, J. (1993). Extending art historically. Journal of Aesthetics and Art Criticism, 51(3), 411–423. https://doi.org/10.2307/431513
Malraux, A. (1978). The voices of silence. Princeton University Press.
Mansfield, E. (2002). Art history and modernism. In E. Mansfield (Ed.), Art history and its institutions: Foundations of a discipline (pp. 11–27). Routledge.
Martindale, C. (1990). The clockwork muse: The predictability of artistic change. Basic Books.
McCormack, J., Gifford, T., & Hutchings, P. (2019). Autonomy, authenticity, authorship and intention in computer generated art. In Ekárt, A., Liapis, A., Castro Pena, M.L. (Eds.), Computational intelligence in music, sound, art and design. EvoMUSART 2019. Lecture notes in computer science, vol. 11453 (pp. 35–50). Springer.
Miller, A. (2019). The artist in the machine: The world of AI-powered creativity. MIT Press.
Nagel, A., & Wood, C. S. (2010). Anachronic renaissance. Zone Books.
Riegl, A. (2004). Historical grammar of the visual arts. Zone Books.
Shiner, L. (2001). The invention of art: A cultural history. University of Chicago Press.
Soussloff, C. (1997). The absolute artist: The historiography of a concept. University of Minnesota Press.
Steinert, S. (2017). Art: Brought to you by creative machines. Philosophy and Technology, 30(3), 267–284. https://doi.org/10.1007/s13347-016-0230-6
Stork, D. G. (2023). How AI is expanding art history. Nature, 623(7988), 685–687. https://doi.org/10.1038/d41586-023-03604-3
Wasielewski, A. (2023). Computational formalism: Art history and machine learning. MIT Press.
Wölfflin, H. (1950). Principles of art history: The problem of the development of style in later art. Dover.
Wollheim, R. (1980). Art and its objects. CUP.
Zeilinger, M. (2021a). Tactical entanglements: AI art, creative agency, and the limits of intellectual property. Meson Press.
Zeilinger, M. (2021b). Generative adversarial copy machines. Culture Machine, 20. Retrieved January 4, 2024. https://culturemachine.net/vol-20-machine-intelligences/generative-adversarial-copy-machines-martin-zeilinger/
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Material preparation, data collection and analysis were performed by Jim Berryman. The first draft of the manuscript was written by Jim Berryman. No other authors were involved in the writing of this manuscript. No Large Language Models (LLMs), such as ChatGPT, were used during the writing or research of this manuscript.
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Berryman, J. Creativity and Style in GAN and AI Art: Some Art-historical Reflections. Philos. Technol. 37, 61 (2024). https://doi.org/10.1007/s13347-024-00746-8
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DOI: https://doi.org/10.1007/s13347-024-00746-8