- Comment
- Published:
Nature Astronomy volume 10, pages 472–474 (2026)Cite this article
-
4334 Accesses
-
48 Altmetric
Subjects
If a Large Language Model (LLM) can replicate your scientific contribution, the problem is not the LLM. What does it say about our field that so much of the anxiety about AI comes down to the fear that a machine could do what we do? Perhaps it says we should be doing something better.
This is a preview of subscription content, access via your institution
Access options
Access Nature and 54 other Nature Portfolio journals
Get Nature+, our best-value online-access subscription
$32.99 / 30 days
cancel any time
Subscribe to this journal
Receive 12 digital issues and online access to articles
$119.00 per year
only $9.92 per issue
Buy this article
- Purchase on SpringerLink
- Instant access to the full article PDF.
USD 39.95
Prices may be subject to local taxes which are calculated during checkout
References
Hogg, D. W. Preprint at https://arXiv.org/abs/2602.10181 (2026).
Ting, Y.-S. Nat. Astron. 9, 317–318 (2025).
Peiris, H. in How to Get Your PhD: A Handbook for the Journey (ed. Brown, G.) 177–184 (Oxford Univ. Press, 2021).
Metcalfe, T. S. Publ. Astron. Soc. Pac. 120, 229 (2008).
Trotta, R. Nat. Astron. 9, 1748–1749 (2025).
Ethics declarations
Competing interests
The author declares no competing interests.
Rights and permissions
About this article
Cite this article
Peiris, H.V. Large language models are not the problem. Nat Astron 10, 472–474 (2026). https://doi.org/10.1038/s41550-026-02837-2
Published:
Version of record:
Issue date:
DOI: https://doi.org/10.1038/s41550-026-02837-2