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

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posted on 2025-08-02, 12:12 authored by AR Doshi, OP Hauser
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.

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University College London

University of Exeter

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© 2024 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. Distributed under a Creative Commons Attribution License 4.0 (CC BY).

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  • No

Submission date

2023-08-16

Notes

This is the final version. Available from American Association for the Advancement of Science via the DOI in this record. Data and materials availability: All data and code needed to replicate these analyses are available at Dryad: https://doi.org/10.5061/dryad.qfttdz0pm. All other data needed to evaluate the conclusions in the paper are present in the paper and/or the Supplementary Materials.

Journal

Science Advances

Publisher

American Association for the Advancement of Science

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  • Version of Record

Language

en

FCD date

2024-06-11T21:30:31Z

FOA date

2024-07-17T10:36:15Z

Citation

Vol. 10, article eadn5290

Department

  • Economics

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