# The Dynamics of Collective Creativity in Human-AI Hybrid Societies

arXiv: https://arxiv.org/abs/2502.17962 · HTML: https://mlsanity.com/paper/2502.17962/

## Key facts

- Cited by 5 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 25 Feb 2025.

## Built on by (most cited first, 5 of 5)

- [Why Human Guidance Matters in Collaborative Vibe Coding](https://mlsanity.com/paper/2602.10473/) (2026)
- [The Variance Paradox: How AI Reduces Diversity but Increases Novelty](https://mlsanity.com/paper/2508.19264/) (2025)
- [Dynamics of collective creativity in AI art competitions](https://mlsanity.com/paper/2605.17141/) (2026)
- [AI as intermediary in modern-day ritual: An immersive, interactive production of the roller disco musical Xanadu at UCLA](https://mlsanity.com/paper/2511.06195/) (2025)
- ["Looking for Something Weird to Happen": How Humans Sustain AI Agent Novelty Amid Semantic Collapse](https://mlsanity.com/paper/2609.16051/) (2026)

## Abstract (arXiv)

Generative AI is shaping an increasingly hybrid society, where ideas and cultural artefacs are created both by humans and intelligent machines. Human creativity is influenced in complex, nonlinear ways by the actions of AI-driven agents within their social networks, but these influences are difficult to measure using traditional methods. This study examines how human-AI interactions shape the evolution of collective creation within large-scale social network experiments, where human and AI participants collectively create stories. Participants (either humans or AI) joined 5x5 grid-based networks in which stories were selected, modified, and shared over many iterations. Initially, AI-only networks showed greater creativity (rated by a separate group of human raters) and collective diversity of stories than human-only and human-AI networks. However, over time, hybrid human-AI networks became more diverse in their creations than AI-only networks. In part, this is because AI agents retained little from the original stories, while human-only networks preserved continuity. These findings highlight the value of experimental social networks in understanding human-AI hybrid societies.