The Subjective Proxy: A Unified Conflict Resolution (UCR) Model of Consciousness as a Functional Solution to Multi-Layered Modality Indeterminacy
Aleksandr Gomelskiy
Zenodo (CERN European Organization for Nuclear Research) April 4, 2026 preprint DOI: 10.5281/zenodo.19432548 (opens in new tab)
Study at a glance
AI-extracted from the abstract| Characteristics | Theoretical or philosophical paper Qualitative |
|---|---|
| Key points | Argues that the "Self" is a secondary computational lossy compression mechanism—a low-latency executive proxy—that emerges to resolve "Macro Global Contradictions" between incongruent information modalities. Proposes that consciousness is not a constant property of the brain but a variable state of "overclocking" triggered when subconscious modules encounter data that parallel processing cannot resolve, and presents the UCR model as a testable, algorithmic alternative to Integrated Information Theory and Global Workspace Theory. |
Abstract
The nature of subjective experience (the ghost in the machine) remains the central "Hard Problem" of cognitive science, largely due to the inability of current functionalist models to account for the architectural necessity of the "Self." Dominant frameworks, such as Integrated Information Theory (IIT) and Global Workspace Theory (GWT), treat consciousness as a passive byproduct of information complexity or a broadcast mechanism for data sharing. However, these models lack an evolutionary "Why," specifically, an explanation for why a high-integration system requires a qualitative, malleable "User" rather than a non-conscious, high-speed logic gate. This paper introduces the Unified Conflict Resolution (UCR) model, which posits that the "Self" is a secondary computational lossy compression mechanism (a low-latency executive proxy) that emerges specifically to resolve "Macro Global Contradictions" between incongruent information modalities. I argue that consciousness is not a constant property of the brain but a variable state of "overclocking" triggered when local, subconscious modules encounter symbolic or sensory data that cannot be resolved through parallel processing. By framing the "Self" as a functional representation of high-tension data resolution, this paper bridges the gap between biological hardware and linguistic software. The UCR model provides a testable, algorithmic alternative to current theories, suggesting that consciousness is the active, energy-intensive event of an organism navigating the friction between its ancient instincts and its modern symbolic world.