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Who expands the human creative frontier with generative AI: Hive minds or masterminds?
Eric B Zhou1, Dokyun Lee1,2, Bin Gu1
1Questrom School of Business, Boston University, Boston, MA 02215, USA.
Science Advances
|September 3, 2025
Summary
Generative AI tools boost novel art creation by increasing output, not by enhancing human creativity directly. Open-source models like Stable Diffusion later democratize these advancements, fostering widespread artistic innovation.
Area of Science:
- Digital Art
- Artificial Intelligence
- Creative Processes
Background:
- Artists increasingly use generative text-to-image models.
- The impact of AI on creative discovery is not well understood.
Purpose of the Study:
- To assess how artificial intelligence (AI)-assisted art creation influences novel idea contributions.
- To compare AI-assisted creators with non-adopters using large-scale data from an online art platform.
Main Methods:
- Large-scale data analysis from an online art platform.
- Comparative study of AI-assisted artists versus non-adopters.
- Examination of novel artifact contributions and output volume.
Main Results:
- AI-assisted creators initially show increased novel contributions due to higher output (productivity effect).
- The rate of novel contributions per artifact decreased due to a dilution effect, favoring incremental exploration.
- No significant human-AI interaction effect was found beyond the productivity boost.
- Open-source Stable Diffusion release broadened novel contributions across more artists.
Conclusions:
- Text-to-image AI tools facilitate large-scale exploration and innovation.
- Initial breakthroughs are driven by a few "masterminds" via increased volume.
- Widespread novel contributions emerge subsequently, indicating a "hive mind" effect.
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