Recursive Ontology: A Unified Lens for Intelligence Across Biology, AI, and Epistemology

This paper proposes ontology as the missing bridge between biological evolution and artificial intelligence. It offers a unified, recursive lens through which knowledge, meaning, and structure can be interpreted—from genetic systems and epigenetics to knowledge graphs and generative AI. We explore how current AI models, though computationally powerful, suffer from ontological misalignment—operating without grounding in recursive meaning structures. Drawing inspiration from biology, mathematics, and consciousness studies, the paper introduces new concepts like the Recursive Ontology Mapping System (ROMS), Ontological Inheritance, and Epistemic Pathways. We argue for a fundamental shift from data pipelines to meaning-centered AI architectures, capable of epistemic awareness and long-term coherence. The work spans multiple domains—biology, physics, economics, AI—and concludes with a 10,000-year vision for the role of ontology in shaping intelligence and civilization. This is both a philosophical blueprint and a technical call to action for the emergence of ontological architects who will lead the post-AI renaissance.