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Generative AI enhances individual creativity but reduces the collective diversity of novel content

Computer Science

Generative AI enhances individual creativity but reduces the collective diversity of novel content

A. R. Doshi and O. P. Hauser

Generative AI can boost individual creativity but risks narrowing collective novelty. In an online experiment where some writers received story ideas from an LLM, AI-assisted stories were rated more creative, better written, and more enjoyable—especially for less creative writers—yet showed greater similarity across stories. Research conducted by Anil R. Doshi and Oliver P. Hauser.... show more
Abstract
Creativity is core to being human. Generative artificial intelligence (AI)—including powerful large language models (LLMs)—holds promise for humans to be more creative by offering new ideas, or less creative by anchoring on generative AI ideas. We study the causal impact of generative AI ideas on the production of short stories in an online experiment where some writers obtained story ideas from an LLM. We find that access to generative AI ideas causes stories to be evaluated as more creative, better written, and more enjoyable, especially among less creative writers. However, generative AI-enabled stories are more similar to each other than stories by humans alone. These results point to an increase in individual creativity at the risk of losing collective novelty. This dynamic resembles a social dilemma: With generative AI, writers are individually better off, but collectively a narrower scope of novel content is produced. Our results have implications for researchers, policy-makers, and practitioners interested in bolstering creativity.
Publisher
Science Advances
Published On
Jul 12, 2024
Authors
Anil R. Doshi, Oliver P. Hauser
Tags
generative AI
large language models
creativity
short stories
human-AI collaboration
collective novelty
social dilemma
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