Expertise elevates AI usage: experimental evidence comparing laypeople and professional artists
Project Overview
The document examines the role of generative AI in education by analyzing a study that compared its use among professional artists and laypeople, highlighting the strengths and limitations of AI in creative tasks. The study employed a custom platform to evaluate participants' abilities to generate both accurate and imaginative images using generative AI models. Findings indicate that while generative AI can enhance content creation, the expertise of professional artists remains crucial in producing higher-quality artistic work. This underscores the importance of integrating artistic skills with AI training to effectively harness technological advancements within creative fields and educational contexts. The results advocate for a balanced approach that combines human creativity and AI capabilities, suggesting that educational frameworks should evolve to include training in both areas to prepare students and professionals for future challenges in the arts and beyond.
Key Applications
Text-to-image generative AI models (e.g., Stable Diffusion, Dall-E)
Context: Artistic education and practice for both professional artists and laypeople.
Implementation: Participants completed controlled tasks using a bespoke online platform to generate images based on prompts.
Outcomes: Artists produced more faithful and creative outputs than laypeople, indicating the value of professional expertise.
Challenges: The low variance in generated outputs limited the demonstration of curation skills.
Implementation Barriers
Technical and Ethical barriers
The performance of generative AI tools may not always meet the expectations of professional artistic standards, alongside legal and moral issues surrounding the use of AI in art, including job displacement fears.
Proposed Solutions: Integrating traditional artistic training with AI tools to enhance creative outcomes, while engaging in discussions about AI ethics and integrating AI education into art curricula.
Project Team
Thomas F. Eisenmann
Researcher
Andres Karjus
Researcher
Mar Canet Sola
Researcher
Levin Brinkmann
Researcher
Bramantyo Ibrahim Supriyatno
Researcher
Iyad Rahwan
Researcher
Contact Information
For information about the paper, please contact the authors.
Authors: Thomas F. Eisenmann, Andres Karjus, Mar Canet Sola, Levin Brinkmann, Bramantyo Ibrahim Supriyatno, Iyad Rahwan
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