The Dynamics of Collective Creativity in Human-AI Hybrid Societies

Fuente: arXiv
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Autores principales: Shiiku, Shota, Marjieh, Raja, Anglada-Tort, Manuel, Jacoby, Nori
Formato: Preprint
Publicado: 2025
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author Shiiku, Shota
Marjieh, Raja
Anglada-Tort, Manuel
Jacoby, Nori
author_facet Shiiku, Shota
Marjieh, Raja
Anglada-Tort, Manuel
Jacoby, Nori
contents 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.
format Preprint
id arxiv_https___arxiv_org_abs_2502_17962
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle The Dynamics of Collective Creativity in Human-AI Hybrid Societies
Shiiku, Shota
Marjieh, Raja
Anglada-Tort, Manuel
Jacoby, Nori
Social and Information Networks
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.
title The Dynamics of Collective Creativity in Human-AI Hybrid Societies
topic Social and Information Networks
url https://arxiv.org/abs/2502.17962