in

The ecology of AI risk


Abstract

Understanding the risk from applications of artificial intelligence (AI) is a critical part of creating AI governance strategies. Building on the idea of studying AI using ecological and evolutionary perspectives, we propose a novel approach for assessing risk from AI using indicators derived from theoretical ecology models. We illustrate our methods by deriving 3 indicators from population and ecosystem models originating from theoretical ecology. We conclude with a discussion of limitations of our analysis and considerations for improving AI governance policy.

Similar content being viewed by others

Generative AI as a tool to accelerate the field of ecology

Harnessing artificial intelligence to fill global shortfalls in biodiversity knowledge

Open and sustainable AI: challenges, opportunities and the road ahead in the life sciences

Acknowledgements

A.M. thanks Michael Vermeer and Henry Willis for helpful discussions on risk. The RAND-affiliated authors acknowledge support from RAND Independent Research funding.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to
Alvin Moon.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Supplementary information (download PDF )

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.

Reprints and permissions

About this article

Cite this article

Geist, E., Meyer, A.D., Moon, A. et al. The ecology of AI risk.
npj Complex (2026). https://doi.org/10.1038/s44260-026-00090-2

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1038/s44260-026-00090-2


Source: Ecology - nature.com

Sea of Okhotsk warming impacts adult return abundance of southwestern marginal Chum salmon populations over four decades

Treating knowledge as a conservation asset to resolve present–future biodiversity trade-offs

Back to Top