What is in a Text-to-Image Prompt: The Potential of Stable Diffusion in Visual Arts Education
Project Overview
The document explores the transformative role of generative AI, particularly Stable Diffusion, in enhancing visual arts education. It emphasizes the technology's capability to generate original visual art from textual prompts, which opens up innovative teaching methodologies for subjects like art history, aesthetics, and techniques. The findings indicate that while generative AI presents cost-effective avenues for artistic experimentation and learning, it also prompts important discussions about intellectual property rights and the necessity for revised legal and economic frameworks to safeguard the interests of artists. Overall, the use of generative AI in education not only enriches the learning experience but also challenges existing paradigms regarding creativity and ownership in the digital age.
Key Applications
Stable Diffusion
Context: Visual arts education, targeting art students and educators.
Implementation: Incorporated into curricula for teaching art history, aesthetics, and technique.
Outcomes: Provides new, cost-effective possibilities for experimentation and expression in art education.
Challenges: Raises questions about the ownership of generated art and the need for new legal frameworks.
Implementation Barriers
Legal
Concerns about the ownership of artworks generated by AI models and the rights of artists whose works are used in training these models.
Proposed Solutions: Establishing new legal and economic models to protect the rights of artists.
Project Team
Nassim Dehouche
Researcher
Kullathida Dehouche
Researcher
Contact Information
For information about the paper, please contact the authors.
Authors: Nassim Dehouche, Kullathida Dehouche
Source Publication: View Original PaperLink opens in a new window
Project Contact: Dr. Jianhua Yang
LLM Model Version: gpt-4o-mini-2024-07-18
Analysis Provider: Openai