The Symbiotic Generative Field: Toward a Relational Ontology of Hybrid Cognition

Recent advances in artificial intelligence have exposed a deep but often unarticulated philosophical divide within AI research. While spatial modeling approaches in computer vision, robotics, and embodied AI presuppose that intelligence emerges from the accurate reconstruction of the physical world, generative language models challenge this assumption by demonstrating sophisticated reasoning and hypothesis formation without perceptual grounding. This paper argues that these two approaches do not represent complementary techniques within a unified paradigm, but rather instantiate two ontologically incompatible conceptions of intelligence: a reconstructive paradigm oriented toward fidelity and closure, and a generative paradigm oriented toward semantic openness and conceptual possibility. To clarify this divide, the paper introduces the concept of tensional generativity, a theoretical framework explaining how conceptual novelty arises from unresolved semantic tensions, contradictions, and indeterminacies internal to language rather than from sensory data or spatial representation. On this basis, the paper contends that spatial modeling systems—regardless of their technical sophistication—remain structurally incapable of crossing the threshold into genuine generativity. The paper further proposes a relational account of symbiotic intelligence, according to which intelligence is not a property of isolated agents, human or artificial, but an emergent field produced through human–AI interaction. Within this field, human intentionality and value-laden ambiguity interact with the combinatorial and inferential capacities of generative models to produce forms of conceptual novelty unattainable by either alone. The paper concludes by arguing that the ethical frontier of artificial intelligence should be reframed not around autonomy or control, but around the responsible design of generative relations in which meaning is co-created.