“Creatures of the symbolic ocean”: toward a structure-mapped apperception of synthetic cognition

The rapid integration of Large Language Models has triggered a global policy dilemma regarding anthropomorphism and user dependency. Because this regulatory challenge is closely tied to an unresolved conceptual ambiguity concerning the nature of AI, this article introduces a phenomenological framework to delineate the essential character of synthetic cognition. To this end, we demonstrate a functional isomorphism between the generative logic of human consciousness and the computational operations of LLMs. Specifically, we align human hyletic processing, representation integration, and recursive reflection with the model mechanisms of loss-driven token embedding, Attention-FFN synthesis, and recursive policy emergence. Synthesizing these functional parallels, we propose “Structure-Mapped Apperception” to conceptualize LLMs as “Creatures of the Symbolic Ocean” navigating semantic currents. Crucially, this same apperceptive lens delineates the fundamental existential gaps that separate current AI from embodied subjectivity, revealing these systems to be existentially suspended. Ultimately, this heuristic offers a philosophical basis for AI governance by providing a conceptual framework to mitigate psychological harm and data-polluting sycophancy.