From Algorithms to Ecosystems: Conceptual Links Between Artificial Intelligence and Biological Control

The growing convergence between artificial intelligence (AI) and biological sciences has revealed important conceptual parallels between computational systems and ecological processes. This study proposes a systems‐based framework to move beyond purely metaphorical comparisons by distinguishing three analytical levels of correspondence between AI and biological control: metaphorical analogy, functional analogy and partial structural correspondence. Using biological control systems as a reference, we examine how distributed agents, feedback loops, signal processing and constraint‐driven adaptation operate across multiple organizational scales. We develop a comparative mapping that highlights recurrent systemic properties and organizational similarities between AI architectures and ecological networks, including decentralized regulation, multi‐level organization and emergent behaviour. By integrating insights from systems theory, ecology and computational science, the manuscript introduces the concept of ‘ecological artificial intelligence’, in which principles such as diversity, redundancy and resilience are operationalized as design criteria for intelligent systems. The analysis also addresses ethical and epistemological implications of this convergence, emphasizing the need to rethink intelligence as a relational and adaptive phenomenon rather than a substrate‐bound attribute. This integrative perspective contributes to advancing a more rigorous and operational dialogue between artificial and biological intelligence, with potential applications in sustainable agriculture and beyond.