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Citation

The ecology of AI risk

Author:
Geist, Edward; Meyer, Alexander Dolnick; Moon, Alvin; Nájera, Aisha; Jones, James Holland; Wu, Anton
Publication:
npj Complexity
Year:
2026

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.