AI tools as science policy advisers? The potential and the pitfalls

Chris Tyler; K. L. Akerlof; Alessandro Allegra; Zachary Arnold; Henriette Canino; Marius A. Doornenbal; Josh A. Goldstein; David Budtz Pedersen; William J. Sutherland

doi:10.1038/d41586-023-02999-3

AI tools as science policy advisers? The potential and the pitfalls

Chris Tyler, K. L. Akerlof, Alessandro Allegra, Zachary Arnold, Henriette Canino, Marius A. Doornenbal, Josh A. Goldstein, David Budtz Pedersen, William J. Sutherland

Research output: Contribution to journal › Comment/debate › Research › peer-review

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Abstract

Recent advances in artificial intelligence (AI) have stoked febrile commentary around large language models (LLMs), such as ChatGPT and others, that can generate text in response to typed prompts. Although these tools can benefit research1, there are widespread concerns about the technology — from loss of jobs and the effects of over-reliance on AI assistance, to AI-generated disinformation undermining democracies. Less discussed is how such technologies might be used constructively, to create tools that sift and summarize scientific evidence for policymaking. Across the world, science advisers act as knowledge brokers providing presidents, prime ministers, civil servants and politicians with up-to-date information on how science and technology intersects with societal issues

Original language	English
Journal	Nature
Volume	622
Issue number	7981
Pages (from-to)	27-30
Number of pages	4
ISSN	0028-0836
DOIs	https://doi.org/10.1038/d41586-023-02999-3
Publication status	Published - 5 Oct 2023

Keywords

Computer science
Government
Machine learning
Policy

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10.1038/d41586-023-02999-3

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AU - Goldstein, Josh A.

AU - Budtz Pedersen, David

AU - Sutherland, William J.

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AI tools as science policy advisers? The potential and the pitfalls

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