Generation and Symbiosis: An Analysis of Evolutionary Trends in AI Art Design Based on Bibliometric Data

DOI

10.2991/978-2-38476-511-9_83How to use a DOI?

Keywords

Artificial intelligence; art design; bibliometrics

Abstract

Against a backdrop of rapid digitalization and technological advances, the integration of artificial intelligence (AI) technology and art design has emerged as a key area of interest in academia and industry. This paper uses bibliometric methods combined with CiteSpace software to systematically analyze research on the integration of AI technology and art design. Based on an analysis of over 2,900 articles from the Web of Science database, the study examines various dimensions, including publication volume, author collaboration networks, keyword co-occurrence, topic clustering, institutional collaboration and temporal evolution, in order to reveal the current state of affairs, key areas of focus and emerging trends in this field. It found that the application of AI in art design has evolved from early theoretical exploration to rapid technological-driven development, particularly after 2016 when breakthroughs in generative AI (such as GANs and DALL-E) sparked a research boom. While Chinese scholars and institutions dominate in terms of publication volume and collaboration networks, interdisciplinary integration (e.g. between computer science and design aesthetics) still needs to be strengthened. Current research focuses on technological innovations (e.g. deep learning and generative design), but social issues such as ethics and sustainability are not receiving sufficient attention. Future research should strike a balance between technological breakthroughs and social responsibility and delve deeper into the mechanisms of human-machine interaction.

Copyright

© 2025 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Download article (PDF)

TY  - CONF
AU  - Chao Chen
PY  - 2025
DA  - 2025/12/31
TI  - Generation and Symbiosis: An Analysis of Evolutionary Trends in AI Art Design Based on Bibliometric Data
BT  - Proceedings of the 7th International Conference on Literature, Art and Human Development (ICLAHD 2025)
PB  - Atlantis Press
SP  - 720
EP  - 731
SN  - 2352-5398
UR  - https://doi.org/10.2991/978-2-38476-511-9_83
DO  - 10.2991/978-2-38476-511-9_83
ID  - Chen2025
ER  -