Who expands the human creative frontier with generative AI: Hive minds or masterminds?
Year: 2025
Type: article
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."
Source: Science Advances
Authors: Eric B. Zhou, Dokyun Lee, Bin Gu
Institution: Boston University
Language: English
Topic: Art, Technology, and Culture
Subfield: Visual Arts and Performing Arts
Field: Arts and Humanities
Domain: Social Sciences
Open Access status: gold
Estimated APC paid: $4,500
OpenAlex ID: W4414003396