International Journal of Computer Science & Network Security

International Journal of Computer Science & Network Security (국제컴퓨터통신보호논문지학회)
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Impact of Artificial Intelligence on the Development of Art Projects: Opportunities and Limitations

  • Zheng, Xiang (A. N. Kosygin Russian State University (Technology. Design. Art)) ;
  • Xiong, Jinghao (A. N. Kosygin Russian State University (Technology. Design. Art)) ;
  • Cao, Xiaoming (A. N. Kosygin Russian State University (Technology. Design. Art)) ;
  • Nazarov, Y.V. (A. N. Kosygin Russian State University (Technology. Design. Art))
  • Received : 2022.09.05
  • Published : 2022.09.30
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Abstract

To date, the use of artificial intelligence has already brought certain results in such areas of art as poetry, painting, and music. The development of AI and its application in the creative process opens up new perspectives, expanding the capabilities of authors and attracting a new audience. The purpose of the article is to analyze the essential, artistic, and technological limitations of AI art. The article discusses the methods of attracting AI to artistic practices, carried out a comparative analysis of the methods of using AI in visual art and in the process of writing music, identified typical features in the creative interaction of the author of a work of art with AI. The basic principles of working with AI have been determined based on the analysis of ways of using AI in visual art and music. The importance of neurobiology mechanisms in the course of working with AI has been determined. The authors conclude that art remains an area in which AI still cannot replace humans, but AI contributes to the further formation of methods for modifying and rethinking the data obtained into innovative art projects.

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References

  1. Aleksandrova, I. B., Vorobyova, K. I., Gileva, N. V., Livson, M., Cheprasova, T. V., Bazhin, G. M.: Influence of ddigital assistive technologies used in higher education on the development of individual educational strategies among students with disabilities. International Journal of Early Childhood Special Education 13(2), 1146-1153 (2021). https://doi.org/10.9756/INT-JECSE/V13I2.211160
  2. Nimatulaev, M. M., Sirbiladze, K. K., Tsvetkova, O. N., Ivanova, L. I., Shelygov, A. V.: Digital technologies as a factor in increasing services sales in tourism industry. Journal of Environmental Management and Tourism 12(4), 916-921 (2021). https://doi.org/10.14505//jemt.v12.4(52).06
  3. Kirillova, E. A., Zulfugarzade, T. E., Blinkov, O. E., Serova, O. A., Mikhaylova, I. A.: Prospects for developing the legal regulation of digital platforms. JURIDICAS CUC 18(1), 35-52 (2021).
  4. Mkrttchian, V., Kharicheva, D., Aleshina, E., Panasenko, S., Vertakova, Yu., Gamidullaeva, L.A., Ivanov, M., Chernyshenko, V.: Avatar-based learning and teaching as a concept of new perspectives in online education in Post-Soviet Union countries: theory, environment, approaches, tools. International Journal of Virtual and Personal Learning Environments 10(2), 66-82 (2020). https://doi.org/10.4018/ijvple.2020070105
  5. Bezpalov, V. V., Solopova, N. A., Shilina, M. G., Avtonomova, S. A., Gorina, T. V.: Formation of an intelligent control system in the field of electric power industry based on the technological development of power supply components. Periodicals of Engineering and Natural Sciences 9(3), 218-235 (2021). https://doi.org/10.21533/pen.v9i3.2112
  6. Korneev, D. G., Gasparian, M. S., Gavrilov, A. V., Sysoev, N. A., Filyuk, M. A.: Creating a service-oriented information and educational space. International Journal of Emerging Technology and Advanced Engineering 12(2), 153-158 (2022).
  7. Esin, I. V., Balakin, K. V.: Medical diagnostic decision support systems based on artificial intelligence algorithms. International Journal of Emerging Technology and Advanced Engineering 11(12), 28-38 (2021). https://doi.org/10.46338/ijetae1221_04
  8. McCormack, J., Gifford, T., Hutchings, P.: Autonomy, authenticity, authorship, and intention in computer generated art. In: Ekart, 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, Cham (2019). https://doi.org/10.1007/978-3-030-16667-0_3
  9. Lomas, A.: On hybrid creativity. Arts 7, 38-48 (2018). https://doi.org/10.3390/arts7030038
  10. Savenkova, L., Fomina, N.: Object-spatial approach to studying fine art: development of three-dimensional and spatial perception among students. Rupkatha Journal on Interdisciplinary Studies in Humanities 9(2), 282-292 (2017).
  11. Arcas, B.A.Y.: Art in the age of machine intelligence+. Arts 6(4), 34-43 (2017).
  12. Du Sautoy, M.: Can AI ever be truly creative? The New Scientist 242(3229), 38-41 (2019). https://doi.org/10.1016/S0262-4079(19)30840-1
  13. Hertzmann, A.: Computers do not make art, people do. Communications of the ACM 63(5), 45-48 (2020). https://doi.org/10.1145/3347092
  14. Chen, W., Shidujaman, M., Tang, X.: AiArt: towards artificial intelligence art. In: MMEDIA 2020: The Twelfth International Conference on Advances in Multimedia, pp. 47-52. IARIA (2020).
  15. McCarthy, D., Minsky, M. L., Rochester, N., Shannon, C. E.: A proposal for the Dartmouth Summer Research Project on artificial intelligence. AI Magazine 27(4), 12-14 (2006).
  16. Pearlman, E.: AI comes of age. A Journal of Performance and Art 42(3(126)), 55-62 (2020). https://doi.org/10.1162/pajj_a_00539
  17. Li, Y.: 20 years of digital art. IT Manager World 495, 68-71 (2018).
  18. Torre, G.: Expectations versus reality of artificial intelligence using art to examine ontological issues. Leonardo 50(1), 31-35 (2017). https://doi.org/10.1162/leon_a_01342
  19. Morkhat, P. M.: Iskusstvennyi intellekt: pravovoi vzglyad: monografiya [Artificial intelligence: legal view: a monograph]. Buki Vedi, Moscow, 258 pp. (2017).
  20. Zylinska, J.: AI art machine visions and warped dreams. Open Humanities Press, London, 176 pp. (2020).
  21. Galanter, P.: Towards ethical relationships with machines that make art. Artnodes 26, 14-22 (2020).
  22. Caldas Vianna, B.: Generative art: between the nodes of neuron networks. Artnodes 26, 80-87 (2020).
  23. Cho, O. H., Lee, W. H.: Application of reinforcement learning system to interactive digital art. Journal of Internet Technology 14, 99-106 (2013).
  24. Czarnecki, G.: Artworks. Gina Czarnecki's Website (2018). https://www.ginaczarnecki.com/artworks
  25. Eaton, S.: Entangled II. Scott Eaton's Website (2020). http://www.scott-eaton.com/2020/entangled-ii
  26. Ebcioglu, K.: An expert system for harmonizing four-part chorales. Computer Music Journal 12(3), 43-51 (1988). https://doi.org/10.2307/3680335
  27. Galanter, P.: Generative art theory. In: Paul, C. (ed.) A companion to digital art, pp. 146-180. John Wiley & Sons, Inc., Chichester (2016).
  28. Reckwitz, A.: The invention of creativity: Modern society and the culture of the new. Polity Press, Cambridge, pp. 324-333 (2017).
  29. Smith, G. W., Leymarie, F. F.: The machine as artist: an introduction. Arts 6(2), 5 (2017).
  30. Elgammal, A., Liu, B., Elhoseiny, M., Mazzone, M.: CAN: creative adversarial networks generating 'Art' by learning about styles and deviating from style norms. In: Eighth International Conference on Computational Creativity (ICCC) (2017). https://arxiv.org/abs/1706.07068