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Who expands the human creative frontier with generative AI: Hive minds or masterminds?

Eric B Zhou¹, Dokyun Lee^1,2, Bin Gu¹

¹Questrom School of Business, Boston University, Boston, MA 02215, USA.

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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.

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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.