MODELING OF AESTHETIC PERCEPTION AND EMOTIONS THROUGH ARTIFICIAL INTELLIGENCE
Keywords:
aesthetics, artificial intelligence, aesthetic perception, emotions, neural networks, machine learning, digital art, affective computing, algorithmic creativity, AI art, cognitive modeling, visual cultureAbstract
This article examines the modeling of aesthetic perception and emotional responses through artificial intelligence technologies. The study explores how AI systems simulate human aesthetic judgment, emotional engagement, and artistic creativity. Special attention is given to machine learning algorithms and neural networks. The paper argues that AI not only reproduces aesthetic forms but also reshapes perception in the digital age.
References
1. Kant, I. Critique of Judgment. Oxford University Press, 1994.
2. Russell, S., Norvig, P. Artificial Intelligence: A Modern Approach. Pearson, 2021.
3. Goodfellow, I., Bengio, Y., Courville, A. Deep Learning. MIT Press, 2016.
4. Picard, R. Affective Computing. MIT Press, 1997.
5. Manovich, L. The Language of New Media. MIT Press, 2001.
6. McCormack, J. et al. (2019). Autonomy, Authenticity and Authorship in AI Art. Leonardo Journal.
7. Elgammal, A. et al. (2017). Creative Adversarial Networks. arXiv.
8. Hertzmann, A. (2018). Can Computers Create Art? Arts Journal.
9. Colton, S. (2008). Creativity in Computational Systems. AAAI.
10. Kodirova G.M. (2024). Digital Aesthetics and AI Influence. SamDU Bulletin.