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

Artists are rapidly integrating generative text-to-image models into their
workflows, yet how this human–AI collaboration affects creative discovery
remains unclear. Leveraging large-scale data from an online art platform,
we compare AI-assisted creators to matched non-adopters to assess novel
idea contributions. Initially, generative AI increases novelty among a
concentrated subset of artists, driven primarily by substantial
productivity gains; however, marginal novelty per artifact declines
post‑adoption, reflecting a shift toward high‑volume, incremental
exploration, ultimately yielding a greater aggregate of novel artifacts by
AI adopters. We observe no evidence of a human–AI complementarity effect
beyond productivity-driven gains. Notably, the release of open-source
Stable Diffusion accelerates novel contributions across a broader, more
diverse group, suggesting that text‑to‑image tools facilitate exploration
at scale, initially enabling persistent breakthroughs by a select
“mastermind” group, driven by substantial volume increases, and
subsequently enabling widespread novel contributions from an emergent
“hivemind” of artists.