Human-AI Synergy Supports Collective Creative Search

Fuente: arXiv

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Bibliographische Detailangaben
Hauptverfasser:	Li, Chenyi, Marjieh, Raja, Hu, Haoyu, Steyvers, Mark, Collins, Katherine M., Sucholutsky, Ilia, Jacoby, Nori
Format:	Preprint
Veröffentlicht:	2026
Schlagworte:	Social and Information Networks Human-Computer Interaction
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author	Li, Chenyi Marjieh, Raja Hu, Haoyu Steyvers, Mark Collins, Katherine M. Sucholutsky, Ilia Jacoby, Nori
author_facet	Li, Chenyi Marjieh, Raja Hu, Haoyu Steyvers, Mark Collins, Katherine M. Sucholutsky, Ilia Jacoby, Nori
contents	Generative AI is increasingly transforming creativity into a hybrid human-artificial process, but its impact on the quality and diversity of creative output remains unclear. We study collective creativity using a controlled word-guessing task that balances open-endedness with an objective measure of task performance. Participants attempt to infer a hidden target word, scored based on the semantic similarity of their guesses to the target, while also observing the best guess from previous players. We compare performance and outcome diversity across human-only, AI-only, and hybrid human-AI groups. Hybrid groups achieve the highest performance while preserving high diversity of guesses. Within hybrid groups, both humans and AI agents systematically adjust their strategies relative to single-agent conditions, suggesting higher-order interaction effects, whereby agents adapt to each other's presence. Although some performance benefits can be reproduced through collaboration between heterogeneous AI systems, human-AI collaboration remains superior, underscoring complementary roles in collective creativity.
format	Preprint
id	arxiv_https___arxiv_org_abs_2602_10001
institution	arXiv
publishDate	2026
record_format	arxiv
spellingShingle	Human-AI Synergy Supports Collective Creative Search Li, Chenyi Marjieh, Raja Hu, Haoyu Steyvers, Mark Collins, Katherine M. Sucholutsky, Ilia Jacoby, Nori Social and Information Networks Human-Computer Interaction Generative AI is increasingly transforming creativity into a hybrid human-artificial process, but its impact on the quality and diversity of creative output remains unclear. We study collective creativity using a controlled word-guessing task that balances open-endedness with an objective measure of task performance. Participants attempt to infer a hidden target word, scored based on the semantic similarity of their guesses to the target, while also observing the best guess from previous players. We compare performance and outcome diversity across human-only, AI-only, and hybrid human-AI groups. Hybrid groups achieve the highest performance while preserving high diversity of guesses. Within hybrid groups, both humans and AI agents systematically adjust their strategies relative to single-agent conditions, suggesting higher-order interaction effects, whereby agents adapt to each other's presence. Although some performance benefits can be reproduced through collaboration between heterogeneous AI systems, human-AI collaboration remains superior, underscoring complementary roles in collective creativity.
title	Human-AI Synergy Supports Collective Creative Search
topic	Social and Information Networks Human-Computer Interaction
url	https://arxiv.org/abs/2602.10001