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 “master..., , # Who expands the human creative frontier with generative AI: Hiveminds or masterminds?

Dataset DOI: [10.5061/dryad.xpnvx0ksf](10.5061/dryad.xpnvx0ksf)

\"Leveraging large-scale data from an online art platform, we compare AI-assisted creators to matched non-adopters to assess novel idea contributions.\"

The dataset consists of a main folder, Hiveminds-Masterminds.zip.

## Data

**All data has been anonymized (userid, postid) to protect user privacy.**

The repository contains the following datasets.

1. **`posts`**: Post-level data containing artwork performance metrics and embeddings. This dataset describes the performance of individual artworks and associated feature representations.
* **userid**: anonymized user identifier
* **postid**: anonymized post identifier
* **published_time**: year-month-date time
* **umap**: UMAP dimensionality-reduced embedding
2. **`users`**: User-level data containing creator performance metrics, treatment assignment, and propensity scores. ...,