Human-AI Synergy Supports Collective Creative Search

TL;DR

This study investigates how human-AI collaboration enhances collective creative search, demonstrating that hybrid groups outperform human-only or AI-only groups in both performance and diversity, with humans and AI adapting strategies in interaction.

Contribution

It provides empirical evidence that human-AI hybrid collaboration improves creative search outcomes and reveals adaptive strategies in collective human-AI tasks.

Findings

Hybrid human-AI groups achieve highest performance.

Hybrid groups maintain high diversity of guesses.

Humans and AI adapt strategies when collaborating.

Abstract

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.