Who expands the human creative frontier with generative AI: Hive minds or masterminds?
Eric Zhou, Dokyun Lee, Bin Gu · Science Advances · 3 Sep 2025
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Abstract
Artists are rapidly integrating generative text-to-image models into their workflows, yet how this affects creative discovery remains unclear. Leveraging large-scale data from an online art platform, we compare artificial intelligence (AI)-assisted creators to matched nonadopters to assess novel idea contributions. Initially, a concentrated subset of AI-assisted creators contributes more novel artifacts in absolute terms through increased output-the productivity effect-although the average rate of contributing novel artifacts decreases because of a dilution effect. This reflects a shift toward high-volume, incremental exploration, ultimately yielding a greater aggregate of novel artifacts by AI-assisted creators. We observe no evidence of a human-AI effect above and beyond the productivity effect. The release of open-source Stable Diffusion accelerates novel contributions across a more diverse group, suggesting that text-to-image tools facilitate exploration at scale, initially enabling persistent breakthroughs by select "masterminds," driven by increased volume, and subsequently enabling widespread novel contributions from a "hive mind."
About this publication
Leading field journal. A leading journal in economics or a neighbouring field (on the Tinbergen Institute’s A list or near the top of the RePEc ranking), or a top-rated computer-science venue.
Placed by: Leading field journal. How sources are ranked.
- Published
- 2025 (14 months ago)
- Citations
- 10 (OpenAlex)
Citations in context
10 citations — 58th percentile among the 33 indexed papers from 2025 in this collection. Citation counts favor older papers; this compares only same-year papers here, not the whole literature.
□ added to this collection in 2026.
author affiliation matches seed institution boston university — part of why this paper is in the collection.
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