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.
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A.M. thanks Michael Vermeer and Henry Willis for helpful discussions on risk. The RAND-affiliated authors acknowledge support from RAND Independent Research funding.
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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
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DOI: https://doi.org/10.1038/s44260-026-00090-2
Source: Ecology - nature.com
