References
[1]. Oxford University Report, “The Forces That Can’t Be Replaced by AI: The Theoretical Drive of Human Cognition.”
[2]. Benjamin, W. (1936). The Work of Art in the Age of Mechanical Reproduction.
[3]. Boden, M. (1990). The Creative Mind: Myths and Mechanisms. Routledge.
[4]. Qiu, Z., & Legrady, G.(2023). “Human-AI Co-Creation in Interactive Art Installations”. ACM SIGGRAPH Conference Proceedings.
[5]. U.S. Copyright Office. (2023). Copyright Registration Guidance for Works Containing AI-Generated Material.
[6]. Crawford, K. (2021). The Atlas of AI: Power, Politics, and the Planetary Costs of Artificial Intelligence.
[7]. Galanter, P. (2016). “Computational Aesthetics: AI and the Evolution of Art”. Leonardo, 49(5), 430–437.
[8]. Goodfellow, I., Pouget-Abadie, J., Mirza, M., Xu, B., Warde-Farley, D., Ozair, S., Courville, A., & Bengio, Y. (2014). Generative Adversarial Networks.
[9]. Mordvintsev, A., Olah, C., & Tyka, M. (2015). Inceptionism: Going deeper into neural networks (Google DeepDream Project).
[10]. Klingemann, M. (2019). Neural Glitch Series.
[11]. Mazzone, M., & Elgammal, A. (2019). “Art, Creativity, and the Potential of Artificial Intelligence”. Arts Journal.
[12]. Brynjolfsson, E., & McAfee, A. (2017). Machine, Platform, Crowd: Harnessing Our Digital Future.
[13]. Qiu, Y., & Zhang, Y. (2019). The reconstruction path of artistic subjectivity in the posthuman context. Literature and Art Studies.
[14]. Qiu, Y., & Zhang, Y. (2019). The reconstruction path of artistic subjectivity in the posthuman context. Literature and Art Studies.
[15]. Biamonte, J., et al. (2017). Quantum machine learning. Nature, 549(7671), 195-202.
[16]. European Commission. (2021). Ethics Guidelines for Trustworthy AI
Cite this article
Miao,X. (2025). A Study on the Aesthetic Challenges and Innovative Pathways of Artificial Intelligence Art. Communications in Humanities Research,71,9-15.
Data availability
The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.
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References
[1]. Oxford University Report, “The Forces That Can’t Be Replaced by AI: The Theoretical Drive of Human Cognition.”
[2]. Benjamin, W. (1936). The Work of Art in the Age of Mechanical Reproduction.
[3]. Boden, M. (1990). The Creative Mind: Myths and Mechanisms. Routledge.
[4]. Qiu, Z., & Legrady, G.(2023). “Human-AI Co-Creation in Interactive Art Installations”. ACM SIGGRAPH Conference Proceedings.
[5]. U.S. Copyright Office. (2023). Copyright Registration Guidance for Works Containing AI-Generated Material.
[6]. Crawford, K. (2021). The Atlas of AI: Power, Politics, and the Planetary Costs of Artificial Intelligence.
[7]. Galanter, P. (2016). “Computational Aesthetics: AI and the Evolution of Art”. Leonardo, 49(5), 430–437.
[8]. Goodfellow, I., Pouget-Abadie, J., Mirza, M., Xu, B., Warde-Farley, D., Ozair, S., Courville, A., & Bengio, Y. (2014). Generative Adversarial Networks.
[9]. Mordvintsev, A., Olah, C., & Tyka, M. (2015). Inceptionism: Going deeper into neural networks (Google DeepDream Project).
[10]. Klingemann, M. (2019). Neural Glitch Series.
[11]. Mazzone, M., & Elgammal, A. (2019). “Art, Creativity, and the Potential of Artificial Intelligence”. Arts Journal.
[12]. Brynjolfsson, E., & McAfee, A. (2017). Machine, Platform, Crowd: Harnessing Our Digital Future.
[13]. Qiu, Y., & Zhang, Y. (2019). The reconstruction path of artistic subjectivity in the posthuman context. Literature and Art Studies.
[14]. Qiu, Y., & Zhang, Y. (2019). The reconstruction path of artistic subjectivity in the posthuman context. Literature and Art Studies.
[15]. Biamonte, J., et al. (2017). Quantum machine learning. Nature, 549(7671), 195-202.
[16]. European Commission. (2021). Ethics Guidelines for Trustworthy AI