GENERATIVE ARTIFICIAL INTELLIGENCE AND THE TRANSFORMATION OF VISUAL ART: HUMAN CREATIVITY, AESTHETIC VALUE, AND THE FUTURE OF ART EDUCATION

The rapid development of generative artificial intelligence (AI) is transforming contemporary visual art by introducing new approaches to image production, artistic experimentation, and creative collaboration. This article examines the relationship between AI-generated artworks and traditional artistic practices, focusing on human creativity, aesthetic value, artistic authorship, and the changing role of visual arts education. Drawing upon existing theoretical perspectives and recent empirical studies, the research explores how generative AI influences the creative process, the perception of artistic originality, and the evaluation of visual images. Particular attention is given to the distinction between technical image production and meaningful artistic expression. The study also considers the opportunities and challenges associated with integrating AI technologies into painting, drawing, composition, and higher art education. The findings suggest that generative AI can expand the possibilities of artistic exploration and support individual creative development. However, its effectiveness depends on human artistic judgement, technical knowledge, cultural awareness, and critical engagement. The article argues that the future of visual art should be understood not as a competition between human artists and artificial intelligence, but as an evolving relationship in which technological innovation complements traditional artistic knowledge and individual creative identity.

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Publication Details

Journal
International journal of technology and academic research
Published
2026-11-01
Primary Topic
Art, Technology, and Culture
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article
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article

GENERATIVE ARTIFICIAL INTELLIGENCE AND THE TRANSFORMATION OF VISUAL ART: HUMAN CREATIVITY, AESTHETIC VALUE, AND THE FUTURE OF ART EDUCATION

Bozorov Asror Botiyrovich
International journal of technology and academic research
Art, Technology, and Culture
article

GENERATIVE ARTIFICIAL INTELLIGENCE AND THE TRANSFORMATION OF VISUAL ART: HUMAN CREATIVITY, AESTHETIC VALUE, AND THE FUTURE OF ART EDUCATION

Bozorov Asror Botiyrovich
article en

Abstract

The rapid development of generative artificial intelligence (AI) is transforming contemporary visual art by introducing new approaches to image production, artistic experimentation, and creative collaboration. This article examines the relationship between AI-generated artworks and traditional artistic practices, focusing on human creativity, aesthetic value, artistic authorship, and the changing role of visual arts education. Drawing upon existing theoretical perspectives and recent empirical studies, the research explores how generative AI influences the creative process, the perception of artistic originality, and the evaluation of visual images. Particular attention is given to the distinction between technical image production and meaningful artistic expression. The study also considers the opportunities and challenges associated with integrating AI technologies into painting, drawing, composition, and higher art education. The findings suggest that generative AI can expand the possibilities of artistic exploration and support individual creative development. However, its effectiveness depends on human artistic judgement, technical knowledge, cultural awareness, and critical engagement. The article argues that the future of visual art should be understood not as a competition between human artists and artificial intelligence, but as an evolving relationship in which technological innovation complements traditional artistic knowledge and individual creative identity.

International journal of technology and academic research
Openalex Percentile: Top 1%
Art, Technology, and Culture
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GENERATIVE ARTIFICIAL INTELLIGENCE AND THE TRANSFORMATION OF VISUAL ART: HUMAN CREATIVITY, AESTHETIC VALUE, AND THE FUTURE OF ART EDUCATION — Bozorov Asror Botiyrovich · International journal of technology and academic research (2026) | TGRS Research Map | TGRS