In Part 1 and Part 2 of this three-part series, I reviewed what is known about AI’s ability to generate poetry and music. This article is about what AI can do for creative art. 

As AI systems like DALL-E, Midjourney, and Stable Diffusion aggressively penetrate the art world, questions arise regarding how AI-generated works are perceived, valued, and integrated into human creative workflows. Two studies—one by Bellaiche et al. (2023) and another by Zhou & Lee (2024)—offer key insights into this debate, exploring AI’s role in augmenting human creativity and highlighting the biases influencing our appreciation of AI-generated art.

AI? No, please!

Bellaiche et al. (2023) investigate whether people prefer human-created artworks over those made by AI and, if so, why. Through a series of experiments, they find that individuals tend to rate artworks labeled as “human-created” more positively than those labeled “AI-created,” even when all images were, by the study design, produced by AI. The study shows that people associate greater meaning, effort, and emotional impact with human-made works—and this contributes to higher aesthetic evaluations.

Interestingly, participants with positive attitudes toward AI exhibited reduced bias against AI-labeled artwork. Additionally, people who scored lower on cognitive reflection tests were more likely to rate human-labeled art as more beautiful. That suggests that AI-created artwork is subject to top-down biases rather than bottom-up sensory judgments. 

These findings have important implications for AI-generated content in creative industries. While AI can produce high-quality artwork indistinguishable from human-made pieces, public perception remains a significant barrier to AI’s acceptance in creative fields. As AI-generated art becomes more common, overcoming biases and fostering appreciation for AI as a creative tool will be crucial.

AI? Yes, please!

While Bellaiche et al. focus on biases against AI-generated art, Zhou & Lee (2024) explore how AI enhances human creative productivity. Analyzing a dataset of over four million artworks, their research shows that AI can help art creators: AI-assisted artists experience a 25% boost in creative productivity and a 50% increase in positive evaluations of their work by peers.

However, the study also uncovers a paradox: while peak creativity—measured as content novelty—increases over time, average novelty declines. This suggests that while AI enables some artists to push creative boundaries and produce exceptionally novel artifacts, many others relying on AI’s capabilities begin producing aesthetically pleasing but less original work. 

The authors introduce the concept of “generative synesthesia,” describing the harmonious blending of human ideation and AI execution as a new form of creative workflow. This positions AI’s role not as a replacement for human creativity but as a tool that expands the creative process when used effectively.

The Evolving Landscape of Art Creation 

Together, these two studies offer a nuanced perspective on the role of AI in artistic creation. While AI can meaningfully enhance artistic output, psychological perceptions still favor human-made art. In other words, AI’s impact on creativity depends on how artists engage with AI tools and how audiences perceive the resulting work.

As AI-generated art will continue to proliferate—and there must be no doubt about that—it will be essential to address these biases and develop a more comprehensive understanding of creativity in the age of AI. Will society embrace AI-assisted art as a legitimate form of creativity, or will human authorship remain the gold standard? 

One thing remains clear though: the definition of art and the role of the artist are evolving, and AI is at the center of this transformation.