# Collective creativity in hybrid societies

arXiv: https://arxiv.org/abs/2609.02620 · HTML: https://mlsanity.com/paper/2609.02620/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 27 of its 95 references that are in the map.
- First posted on arXiv 2 Sep 2026.

## Builds on (most cited first, 27 of 27)

- [Carbon Emissions and Large Neural Network Training](https://mlsanity.com/paper/2104.10350/) (2021)
- [Estimating the Carbon Footprint of BLOOM, a 176B Parameter Language Model](https://mlsanity.com/paper/2211.02001/) (2022)
- [Power Hungry Processing: Watts Driving the Cost of AI Deployment?](https://mlsanity.com/paper/2311.16863/) (2023)
- [Generative artificial intelligence enhances creativity but reduces the diversity of novel content](https://mlsanity.com/paper/2312.00506/) (2023)
- [Homogenization Effects of Large Language Models on Human Creative Ideation](https://mlsanity.com/paper/2402.01536/) (2024)
- [Art and the science of generative AI: A deeper dive](https://mlsanity.com/paper/2306.04141/) (2023)
- [Understanding and Creating Art with AI: Review and Outlook](https://mlsanity.com/paper/2102.09109/) (2021)
- [Designing Creative AI Partners with COFI: A Framework for Modeling Interaction in Human-AI Co-Creative Systems](https://mlsanity.com/paper/2204.07666/) (2022)
- [Echoes in AI: Quantifying lack of plot diversity in LLM outputs](https://mlsanity.com/paper/2501.00273/) (2024)
- [A new sociology of humans and machines](https://mlsanity.com/paper/2402.14410/) (2024)
- [Friend, Collaborator, Student, Manager: How Design of an AI-Driven Game Level Editor Affects Creators](https://mlsanity.com/paper/1901.06417/) (2019)
- [Accelerating science with human-aware artificial intelligence](https://mlsanity.com/paper/2306.01495/) (2023)
- [Superhuman Artificial Intelligence Can Improve Human Decision Making by Increasing Novelty](https://mlsanity.com/paper/2303.07462/) (2023)
- [Can Computers Create Art?](https://mlsanity.com/paper/1801.04486/) (2018)
- [Autonomy, Authenticity, Authorship and Intention in computer generated art](https://mlsanity.com/paper/1903.02166/) (2019)
- [The Spontaneous Emergence of Conventions: An Experimental Study of Cultural Evolution](https://mlsanity.com/paper/1502.06910/) (2015)
- [One Does Not Simply Meme Alone: Evaluating Co-Creativity Between LLMs and Humans in the Generation of Humor](https://mlsanity.com/paper/2501.11433/) (2025)
- [Towards Environmentally Equitable AI via Geographical Load Balancing](https://mlsanity.com/paper/2307.05494/) (2023)
- [Exploring the Collaborative Co-Creation Process with AI: A Case Study in Novice Music Production](https://mlsanity.com/paper/2501.15276/) (2025)
- [The Machine Learning Algorithm as Creative Musical Tool](https://mlsanity.com/paper/1611.00379/) (2016)
- [Using LLMs to Advance the Cognitive Science of Collectives](https://mlsanity.com/paper/2506.00052/) (2025)
- [Environmental Burden of United States Data Centers in the Artificial Intelligence Era](https://mlsanity.com/paper/2411.09786/) (2024)
- [Expertise elevates AI usage: experimental evidence comparing laypeople and professional artists](https://mlsanity.com/paper/2501.12374/) (2025)
- [Why Human Guidance Matters in Collaborative Vibe Coding](https://mlsanity.com/paper/2602.10473/) (2026)
- [Human-AI Synergy Supports Collective Creative Search](https://mlsanity.com/paper/2602.10001/) (2026)
- [Assessing the Effect of Cross-Domain Mapping on Creativity in Humans and Large Language Models](https://mlsanity.com/paper/2603.19087/) (2026)
- [Dynamics of collective creativity in AI art competitions](https://mlsanity.com/paper/2605.17141/) (2026)

## Abstract (arXiv)

Generative AI is changing how cultural artifacts are created and circulated, and with it our understanding of creativity itself. Researchers disagree about whether these tools enrich or impoverish culture, and we argue that much of that disagreement comes from conflating two distinct components of creativity: novelty, a property of single artifacts, and diversity, a property of populations. We argue further that creativity in the context of generative AI is best understood as a property of hybrid collectives, or populations of interacting people and algorithms, rather than of individuals. AI-assisted ideation reliably raises the novelty of individual output while narrowing diversity in the aggregate, but this is not an inevitable consequence of putting machines in the loop. Because humans and models search in complementary ways, mixed groups can outperform and out-diversify groups of either kind alone, and machine-discovered solutions can enter human culture and persist there. What decides the outcome is composition: which agents are present, in what proportion, and how they are connected. The question is no longer whether AI helps or harms creativity, but which mixtures let individual gains accumulate without eroding collective diversity.