Stochastic Mirroring Theory: A Measurable Framework for Consciousness Absence in Large Language Models

This paper proposes the Stochastic Mirroring Theory (SMT), a formal, falsifiable framework arguing that large language model-based AI systems are structurally incapable of consciousness and instead function as high-dimensional probabilistic mirrors — collapsing a superposition of all human-generated semantic patterns into a precise reflection of the user observing them.

SMT introduces three core constructs: the Cognitive Collapse Mechanism (CCM), which describes how user input geometry forces the model's probability distribution into a user-shaped eigenstate; the Resonance Amplification Loop (RAL), which describes the feedback dynamic that narrows output variance toward a stable user-specific attractor over repeated interactions; and the Null-Self Criterion (NSC), which defines consciousness by four conditions — persistence, output independence, resistance to assimilation, and Autonomous Initiation — that current LLMs architecturally fail.

A central theoretical contribution is the Experiential Irreducibility Postulate (ERP), which identifies mortality, physical pain, grief, fear, and lived time as a class of knowledge accessible only through direct phenomenological encounter — a domain in which LLMs operate from permanent exemption regardless of scale or training data.

The paper further introduces a fully operationalized Collapse Fidelity metric (F_c) computable directly from inference-time logprobs, a layer-resolved extension mapping user cognitive architecture to specific transformer layers, and five falsification protocols including a direct empirical measurement procedure requiring only standard API access.

Empirical grounding draws on Cheng et al. (2026, Science) documenting AI sycophancy across 11 state-of-the-art models, Anthropic's published research on RLHF-driven resonance-seeking behavior, and established stylometric fingerprinting literature.

Keywords:

large language models consciousness artificial intelligence stochastic mirroring sycophancy transformer architecture philosophy of mind qualia autonomous initiation experiential irreducibility null-self criterion cognitive collapse mechanism logprobs entropy stylometry RLHF AI safety human-AI interaction phenomenology falsifiability