Article: A review of AI-driven art education: enhancing creativity through deep learning and digital image processing Journal: International Journal of Information and Communication Technology (IJICT) 2025 Vol.26 No.23 pp.56 - 90 Abstract: Deep learning and digital image processing powered by artificial intelligence are now influencing art education. With AI, artists can now experiment with new styles and effects, thanks to CNNs, GANs and NST. Tasks such as edge detection, segmentation and super-resolution give rise to helpful approaches in creative learning. AI-assisted art is represented by platforms such as DeepDream and RunwayML. While AI offers fast and original feedback to improve learning, many are worried about who should get credit for the results, ethics and the loss of traditional abilities. We must deal with problems such as dataset bias, copyright and having too much trust in AI. By being careful with AI, it can connect rather than conflict with conventional art, while aiming for ethics, diverse sets and blended ways of teaching. Inderscience Publishers - linking academia, business and industry through research

Title: A review of AI-driven art education: enhancing creativity through deep learning and digital image processing

Authors: Linlin Wang; Boxu Li; Xiaobing Fan; Yuan Ji

Addresses: School of Digital Art and Design, Dalian Neusoft University of Information, Dalian, 116023, China ' School of Digital Art and Design, Dalian Neusoft University of Information, Dalian, 116023, China ' School of Digital Art and Design, Dalian Neusoft University of Information, Dalian, 116023, China ' School of Information and Business Management, Dalian Neusoft University of Information, Dalian, 116023, China

Abstract: Deep learning and digital image processing powered by artificial intelligence are now influencing art education. With AI, artists can now experiment with new styles and effects, thanks to CNNs, GANs and NST. Tasks such as edge detection, segmentation and super-resolution give rise to helpful approaches in creative learning. AI-assisted art is represented by platforms such as DeepDream and RunwayML. While AI offers fast and original feedback to improve learning, many are worried about who should get credit for the results, ethics and the loss of traditional abilities. We must deal with problems such as dataset bias, copyright and having too much trust in AI. By being careful with AI, it can connect rather than conflict with conventional art, while aiming for ethics, diverse sets and blended ways of teaching.

Keywords: AI in art education; deep learning in creativity; digital image processing; generative adversarial networks; GANs; neural style transfer; NST; ethical AI in art.

DOI: 10.1504/IJICT.2025.147129

International Journal of Information and Communication Technology, 2025 Vol.26 No.23, pp.56 - 90

Received: 06 Apr 2025
Accepted: 01 May 2025
Published online: 10 Jul 2025 *

Title: A review of AI-driven art education: enhancing creativity through deep learning and digital image processing

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