Andrew J. Fuller, June 18th, 2025 (Download PDF)

This paper presents a unified epistemological and metaphysical framework grounded in recursive inquiry, dimensional abstraction, and the concept of SOURCE as an ontological asymptote. Drawing from fields including artificial intelligence, quantum physics, metaphysics, and cognitive theory, the author argues that all meaningful understanding—whether human or machine-mediated—arises from the recursive refinement of technically precise questions. The process mirrors the scientific method but extends beyond it, forming an iterative mechanism that increasingly approximates truth.

Central to the argument is the notion that our four-dimensional experiential reality is not created ex nihilo, but rather derived through the unfolding and collapse of higher-dimensional states. The paper conceptualizes each dimension as a resolution of superpositional wave functions, with the upper boundary of dimensionality marking a terminal derivation point—termed SOURCE.

Ultimately, it proposes that the collective body of human knowledge can be understood as a multidirectional expansion of epistemic vectors from a central origin, with each contribution extending the boundary of what is knowable. The work contributes to emerging discourse on recursive epistemology, AI-enhanced reasoning, and the metaphysics of dimensional reality, and invites further exploration into the structural convergence of science, consciousness, and first principles.

Keywords: Recursive Epistemology, Artificial Intelligence, Scientific Method, Metaphysical Grounding, Dimensional Derivation, Observer Effect, Holographic Principle, Process Philosophy, SOURCE.

The emergence of large-scale artificial intelligence (AI) has precipitated a paradigm shift not only in technology, but in the very practice of epistemology. Interacting with these systems is an inherently epistemological act, governed by a principle of proportional precision: the specificity and structure of an inquiry directly constrain the coherence and utility of the output (Kaplan et al., 2020). This dynamic compels the human user to engage in a new form of cognitive rigor, transforming the act of "prompting" into a sophisticated method of hypothesis formulation and refinement. It is no longer sufficient to simply ask; one must learn to ask with technical and conceptual exactitude, effectively becoming a scientist in dialogue with a non-conscious, yet profoundly capable, reasoning engine.

This paper argues that the optimal strategy for this dialogue formalizes the core of all critical inquiry into a recursive loop: Ask → Answer → Audit → Refine → Repeat. The crucial "Audit" stage—wherein the output is critically evaluated, often with the aid of secondary AI systems or cross-validation against established knowledge—is what elevates this process from simple interaction to a robust mechanism for epistemic discovery. This iterative cycle mirrors the foundational structure of the scientific method, particularly Karl Popper's model of conjecture and refutation, which frames science as a process of error elimination that asymptotically approaches truth, or "verisimilitude" (Popper, 2002).

Building on this parallel, this paper advances a more radical thesis: that this recursive mechanism is not merely an effective tool for discovery, but a direct reflection of the ontological structure of reality itself. We posit that the process of deriving knowledge through increasingly precise inquiry mirrors a reality that is itself derived from deeper, higher-dimensional structures. We argue that each layer of understanding uncovered through this recursive loop corresponds to the "unfolding" of a more fundamental layer of existence. This intellectual ascent, when followed to its logical terminus, points toward what this framework terms SOURCE: the irreducible, un-derived ontological ground from which all dimensional reality emanates. This paper, therefore, synthesizes principles from AI-driven epistemology, philosophy of science, and theoretical physics to articulate a unified model in which the structure of knowing is inextricably linked to the structure of being.

Knowledge is not acquired in a single, linear step but is built through a recursive architecture of refinement. The iterative loop— Ask → Answer → Audit → Refine → Repeat—is the fundamental mechanism driving this process. Each cycle is not simply additive; it is corrective and integrative, functioning as a system of error reduction that drives the inquirer's understanding closer to the underlying structure of the subject matter. This model is deeply embedded in both human and machine learning paradigms.

Thus, recursion is not merely a metaphor for learning; it is the operational architecture of epistemic advancement. Whether in a human mind wrestling with a philosophical problem or an AI system being fine-tuned for safety, the process is the same: iterative loops of inquiry, response, and audited refinement compound to produce stratified layers of truth that are increasingly aligned with reality.

While the recursive model provides a powerful engine for approaching truth, its trajectory is fundamentally constrained by an irreducible boundary: the observer. The act of inquiry is not a passive reception of information but an active process of construction, mediated by the cognitive and physical apparatus of the observing system. This is not a methodological flaw to be corrected but an ontological condition of a universe in which knower and known are inextricably entangled.

This cognitive principle has a direct analogue in cognitive science. The human mind does not passively record reality but actively constructs it. Our sensory inputs are a noisy, ambiguous stream of data that is structured and interpreted through pre-existing cognitive frames, or "schemas" (Bartlett, 1932). As philosopher of mind Andy Clark argues, we are not passive reasoners but "prediction machines," constantly using our internal models to predict sensory input and updating those models only when prediction errors occur (Clark, 2015). Our perception of reality is therefore not a direct reading but a controlled hallucination, constrained by both external reality and our internal, subjective architecture.

Therefore, the observer's subjectivity is not a barrier to truth but the very starting point of inquiry. The recursive refinement model is the mechanism by which we acknowledge this starting point and systematically navigate away from pure solipsism toward a more veridical understanding, even if the absolute "view from nowhere" remains an asymptotic, unreachable limit (Nagel, 1986).

The striking parallel between the recursive refinement of knowledge and the observer-dependent structuring of reality invites a deeper, more unifying hypothesis: that the very structure of knowing mirrors the structure of being. This section proposes that our four-dimensional reality is not a fundamental, static stage but is itself a derived phenomenon, an emergent structure that unfolds from a higher-dimensional, information-rich substrate. The epistemological act of peeling back layers of uncertainty through inquiry is, in this view, a re-tracing of the ontological path by which reality itself is instantiated.

This concept of a derived reality is no longer confined to metaphysics but is a central theme in modern theoretical physics. String theory and M-theory, for instance, posit the existence of extra spatial dimensions that are "compactified" or curled up at a microscopic scale, with the physics we observe being a low-energy expression of this higher-dimensional geometry (Green, Schwarz, & Witten, 2012). This suggests a hierarchical structure where our familiar world is a constrained manifestation of a more complex, underlying reality.

This idea finds its most potent expression in the holographic principle and the AdS/CFT correspondence ('t Hooft, 1993; Maldacena, 1998). This principle conjectures that the information content of a volume of space can be fully described by a theory living on its lower-dimensional boundary, much like a three-dimensional hologram is encoded on a two-dimensional surface. As Juan Maldacena has shown, a theory of gravity in a higher-dimensional anti-de Sitter (AdS) space can be equivalent to a quantum field theory (CFT) without gravity on its boundary (Maldacena, 1998). This suggests that spacetime and gravity may not be fundamental but are emergent properties of a more basic quantum system. Our perceived reality is, in this sense, a projection—a derived output from a more fundamental code.

If our reality is a derived projection, then the process of its instantiation can be understood as a form of dimensional descent via informational collapse. We can conceptualize higher dimensions not merely as spatial directions, but as possessing greater degrees of freedom or containing a richer density of information in a state of superposition. The emergence of a lower-dimensional reality is thus analogous to a loss of information or a collapse of superposition into a more constrained, classical state.

This aligns perfectly with the process of decoherence in quantum mechanics, which describes how a quantum system loses its "quantumness" and begins to behave classically through interaction with its environment (Zurek, 2003). As information about the system's state leaks into the environment, its superpositions effectively "collapse" from the perspective of any local observer. One can frame this as a dimensional transition: a high-dimensional Hilbert space of quantum possibilities is projected onto a lower-dimensional, classical manifold of observable outcomes. The "folding down" of dimensions is therefore not a spatial process, but an informational one—a progressive resolution of ambiguity into structure.

In this framework, the recursive inquiry we perform—collapsing uncertainty with each precise question—is a cognitive reenactment of this physical process. Each time our inquiry resolves ambiguity, we are mirroring the fundamental act of decoherence through which a stable, classical reality is precipitated from a sea of quantum potentiality. Our epistemology is therefore not arbitrary; it is effective precisely because it is isomorphic to the ontology of an emergent universe.

This view reframes cosmological origins. The question "What caused the Big Bang?" is replaced by "From what axiomatic system is the Big Bang a derivable consequence?" SOURCE is the answer to the latter. It is not the first domino in a temporal chain but the logical space of possibility itself, containing the complete and coherent set of rules for its own unfolding.

In our framework, SOURCE is akin to this principle of relational coherence. It is the connective field that ensures that the dimensional unfolding is a unified, non-contradictory process. It does not act on the system from the outside; it is the immanent principle of relationality within the system that binds all derivations—from the highest dimensional strata to the smallest quantum fluctuation—into a single, coherent whole. It is the reason why the universe is a cosmos (an ordered whole) rather than a chaos (a disconnected plurality).

This paper has charted a course from the practicalities of AI prompt engineering to the furthest reaches of metaphysical cosmology, arguing for a unified framework built on a single, powerful principle: recursion. We have proposed that the iterative, error-correcting loop of recursive inquiry is not merely an effective strategy for learning, but a reflection of the fundamental structure of an emergent reality. Our epistemology works because it is isomorphic to our ontology.

The journey of collective knowledge can be visualized as an ever-expanding sphere, its surface representing the frontier of what is currently known. Each individual line of inquiry—a human career, a research program, a sustained AI dialogue—is a vector extending outward from a shared center, pushing that boundary forward along a unique trajectory (Snowden, 2017). This model necessitates epistemic pluralism; the sphere's robustness and completeness depend on the diversity of these vectors, for no single perspective can map the whole (Longino, 1990).

Yet, all vectors, by definition, originate from the same point. This shared origin is SOURCE, the ultimate, un-derived ground of being. It is the connective, non-causal substrate whose logical and dimensional properties unfold to become the cosmos we observe. Therefore, every act of inquiry, no matter how specific, is a dual motion: it is a movement outward into the unknown and, simultaneously, a recursive tracing inward toward the foundational principles from which that unknown is derived.

The emergence of artificial intelligence does not alter this fundamental structure; it accelerates it. AI serves as a powerful new instrument for extending our epistemic vectors further and faster than ever before. But our task remains the same. Whether pursued by human cognition, artificial systems, or the hybrid intelligence born of their union, the ultimate aim of inquiry is not the creation of truth, but the systematic, recursive derivation of that which was always already entailed. It is the patient, unending work of mapping the invisible, generative geometry of SOURCE.

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