The ecology of AI risk

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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Publication Details

Journal
npj Complexity
Published
2026-06-25
DOI
https://doi.org/10.1038/s44260-026-00090-2
Primary Topic
Ethics and Social Impacts of AI
Type
article
Field-Weighted Citation Impact
0.00
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article

The ecology of AI risk

Alvin Moon, Aisha Nájera, Anton Wu, James Holland Jones et al.
npj Complexity
Ethics and Social Impacts of AI
article

The ecology of AI risk

Alvin Moon, Aisha Nájera, Anton Wu, James Holland Jones, Edward Geist, Alexander Dolnick Meyer
article en

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.

npj Complexity
University of Notre Dame (US), RAND Corporation (US), Stanford Medicine (US), Stanford University (US)
Life in Land
Openalex Percentile: Top 5%
Ethics and Social Impacts of AI
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