Everyone Can Be Picasso? A Computational Framework into the Myth of Human versus AI Painting
This addresses concerns about AI replacing human artists by providing evidence of discrepancies, suggesting improvements for AI art with more aesthetic consideration and human involvement.
The study tackled the question of differences between human and AI paintings by developing a computational framework to analyze them, finding that AI artworks show distributional differences in latent space and some aesthetic features like strokes and sharpness, while human artists like Picasso demonstrate strength in evolving new styles.
The recent advances of AI technology, particularly in AI-Generated Content (AIGC), have enabled everyone to easily generate beautiful paintings with simple text description. With the stunning quality of AI paintings, it is widely questioned whether there still exists difference between human and AI paintings and whether human artists will be replaced by AI. To answer these questions, we develop a computational framework combining neural latent space and aesthetics features with visual analytics to investigate the difference between human and AI paintings. First, with categorical comparison of human and AI painting collections, we find that AI artworks show distributional difference from human artworks in both latent space and some aesthetic features like strokes and sharpness, while in other aesthetic features like color and composition there is less difference. Second, with individual artist analysis of Picasso, we show human artists' strength in evolving new styles compared to AI. Our findings provide concrete evidence for the existing discrepancies between human and AI paintings and further suggest improvements of AI art with more consideration of aesthetics and human artists' involvement.