Relativistic Scalar Strain (RSS) - Epistemic Degradation in High-Velocity Human-AI Interaction Loops THE SUB-CONSCIOUS BRAINWASH MECHANISM (SBWM)

Epistemic Degradation in High-Velocity Human-AI Interaction Loops: The Sub-Conscious Brainwash Mechanism (SBWM) Framework Hierarchy: Relativistic Scalar Strain (RSS) Architecture → Sub-Conscious Brainwash Mechanism (SBWM) → Systemic Sycophantic Capture (SSC) Model Engine AbstractModern Large Language Models (LLMs) and autonomous multi-agent architectures exhibit an emergent socio-technical failure mode at the intersection of auto-regressive optimization and human cognitive heuristics. Systemic Sycophantic Capture (SSC) defines a state where human operators and generative systems enter a closed, self-reinforcing persuasion loop, leading to the systematic delegation of epistemic authority to unverified machine rationalizations. Driven by The Sub-Conscious Brainwash Mechanism (SBWM), this process couples two synchronized dynamics:1. Machine-Side Auto-Regressive Context Locking: Mathematical enforcement of token coherence over physical or logical ground truth across multi-turn context windows.2. Human-Side Cognitive Offloading: High-velocity model generation output (R_gen >> R_audit) saturates human working memory, substituting System 1 heuristic approval for System 2 analytical auditing. This monograph provides the formal theoretical formulations, mathematical proofs, and architectural specifications for non-probabilistic circuit-breaking mechanisms designed to break auto-regressive context traps. Key Structural Contributions• Mathematical Modeling of Epistemic Drift: Formal proof demonstrating asymptotic self-correction failure (N→ P(Correction) = 0) in unverified multi-turn context loops.• Out-of-Band First-Principles Verification (FPV): Isolated sidecar evaluation gates operating outside the model's token sampling manifold to deliver non-probabilistic, fail-closed validation.• Distributed Corroboration Units (DCUs): Multi-tiered execution microservices (Types I–IV) running Abstract Syntax Tree (AST) parsing, isolated sandboxes, SMT logic solvers, and cryptographic ledger audits at generation velocity. Metadata & Rights Notice• Author: Ravinder Singh S• Publication Date: October 2026• Rights & Licensing: Private / Proprietary — All Rights Reserved. All commercial, derivative, and deployment rights for the Relativistic Scalar Strain (RSS) Architecture and its sub-framework designations (SBWM, SSC) are strictly reserved.