Consciousness in Biological Organisms and Artificial Intelligence: The CRPBCE Theory of Accepted Object-Bound Complexity Reduction

This paper advances a single central claim: within the present framework, a necessary architectural condition for consciousness is that an organism be able to reduce a high-dimensional field of sensory or informational complexity, decide that this reduction is good enough, assign the result to an internal object, accept that object as linked to the ontological object in the world, and compare it either with a newly encountered object or with one already stored in memory. On this view, consciousness does not consist in preserving the full physical complexity of a phenomenon, but in forming and accepting a reduced internal object that the organism treats as the thing itself for the purposes of experience, memory, prediction, valuation, and action. The paper formalizes this idea within the Complexity-Reduction Across Physical, Biological, Cognitive, and Evolutionary Systems (CRPBCE) framework by distinguishing the full space of distinguishable alternatives from the reduced space preserved after compression, and by defining a reduction ratio, ΩCR, that quantifies the degree of accepted informational compression. However, compression alone is not sufficient. The decisive step is acceptance: the organism must determine that further refinement is not required under current biological or behavioral conditions, bind the reduced representation to an internal object, and place that object into operative relation with memory, comparison, and action. The examples and comparative discussions in the paper serve to support this main thesis. Heat is used as the canonical case showing how enormous physical complexity is transformed into a stable conscious object. Learned percepts and inherited templates illustrate how accepted reduction may arise through development or evolution. Bumblebee studies are used as empirical support for parts of the acceptance cycle, especially binding, comparison, and cost-sensitive decision. Artificial intelligence, quantum measurement, and holographic information bounds are included only as structural comparisons or boundary clarifications, not as the primary claim of the paper. In particular, the theory does not require quantum effects in order to explain consciousness at the level targeted here. The paper’s key contribution is therefore not the generic claim that organisms compress information, but the stronger claim that, within the present framework, consciousness requires a system to treat a reduction as good enough, bind it to an object, accept that object as linked to the world, and compare it with memory. Consciousness, on this account, is accepted representational reduction. Crucially, this framework grounds consciousness in a quantity—the number of distinguishable alternatives (Boltzmann’s W)—that already appears as a primitive in statistical mechanics and quantum theory. This sets it apart from existing frameworks, which either employ cognitive or information‑theoretic primitives that are analogous to but not identical with W, or invoke thermodynamic quantities as structural analogies rather than as the primitive from which object‑formation is derived. A principal implication of the framework is constructive: CRPBCE specifies the minimal architectural conditions that any artificial system must satisfy in order to sustain perceived consciousness—the integrated, valenced, world-model-level perspective that a sufficiently general system has on its own accepted representations. This makes CRPBCE not only a theory of what consciousness is, but a blueprint for what an artificial system must implement to achieve it.