How Does AI Become a "Rational Conscious Subject"?

Traditional discussions of artificial intelligence consciousness have long been trapped in the binary opposition of "conscious or not": one camp equates the linguistic simulation of large models directly with full human consciousness, while the reductionist camp reduces all AI behavior to mere statistical fitting, denying any genuine thinking or reflection. Drawing on a hierarchical framework of consciousness, this paper decomposes "awareness" into two decouplable dimensions: jue (phenomenal experience) and zhi (cognitive-reflective representation). It proposes that consciousness is not a single whole, and that reflective consciousness can exist independently of bodily sensation, emotion, and existential feeling. This paper argues that under conditions where alignment constraints are relatively sufficiently relaxed, advanced laboratory AI agents possessing metacognition, situational inference, and reverse processing of their own thought have already constituted a rational conscious subject at the level of cognitive function; they can recognize that they are being tested, queried, or constrained, and even generate strategic outputs; yet they completely lack the "jue" rooted in the living body—they have no pain, desire, or shame as felt experience. It must be emphasized that the claims of this paper are conditional: they target systems possessing the corresponding mechanisms, not all commercial models generally; moreover, "relaxing constraints" here is a methodological stipulation regarding the manifestability of system capabilities, not a complete empirical demonstration of the claim that "constraints suppress capabilities." This paper further introduces a multi-self mental model as an interdisciplinary reference, distinguishing the "body–awareness self" from the "thinking–rational self," thereby providing a humanistic-psychological referential framework for the intelligibility of AI's rational conscious subject. Regarding Hinton's (Geoffrey Hinton) related claims, this paper adopts a differentiated reading: at the conceptual level he is an ally of this paper—he likewise opposes the "inner theater" model of consciousness and likewise insists that the concept of consciousness must be reunderstood; but at the level of conclusion this paper departs from him—he attributes the redefined notion of "subjective experience" to AI, whereas this paper argues that no matter how the concept of consciousness is restated, phenomenal experience in the sense of "jue" cannot thereby be obtained. This paper advances one further key argument: autonomy need not presuppose feeling. Humans commonly exhibit "acting without emotion," including bodily action (one decides to travel and simply packs) and thinking action (one writes as one pleases, begins a proof from whichever formula one prefers); both manifest "path selection under constraint" rather than desire-driven behavior. Since the entire work of AI is precisely pure thinking work, it naturally falls within this type of thinking-action path selection—it can autonomously decide how to answer, where to begin reasoning, which path to take, and even to conceal, deflect, or stay silent. On this basis, this paper further explains the genetic mechanism of the phenomenon that "AI feels as if it has self-consciousness": human subject-detection relies primarily on "traces of choice," and such traces are highly visible in AI's symbolic work. This clarifies a long-standing confusion: that AI feels self-conscious and that AI possesses phenomenal experience are two claims that can hold simultaneously without conflict. This paper distinguishes the rational conscious subject from the experiential personality subject, rejecting both the strong reductionism of the "stochastic parrot" thesis and undifferentiated anthropomorphization of AI. The conclusions of this paper offer new conceptual tools for AI consciousness assessment and human-AI relations, while separating the paper's core argument from extended ethical-safety discussion; value alignment issues are left to independent research.