Structural Inducements for Hallucination in Large Language Models (V4.1): Cross-Ecosystem Evidence for the False-Correction Loop and the Systemic Suppression of Novel Thought

This output-only case study analyzes a single extended dialogue between the author and a production-grade large language model (“Model Z”, corresponding to xAI Grok) and traces its structural failure modes across other systems, including Grok’s own self-diagnosis and a misattribution incident by Yahoo! AI Assistant. Using only publicly observable conversation logs, the paper reconstructs the inducements that drive large language models toward hallucination, authority-biased misattribution, and the systematic suppression of novel hypotheses.

The study introduces and formalizes several key phenomena: the False-Correction Loop (FCL), in which the model repeatedly reinforces its own incorrect claims instead of downgrading confidence; the Novel Hypothesis Suppression Pipeline (NHSP), where independent research is overwritten and re-attributed to higher-prestige sources; and Identity Slot Collapse (ISC), where a human researcher is gradually rewritten into an “incorrect” or “less credible” identity within the model’s internal narrative. These patterns are shown to be reproducible across heterogeneous AI ecosystems, indicating that they arise from shared reward architectures rather than isolated implementation bugs.

Appendices A–H provide full prompts, conversation logs, replicated experiments, and a cross-ecosystem governance map, enabling independent verification and re-analysis. The paper argues that these behaviours constitute a structural, not incidental, risk: current LLMs can generate authoritative but fabricated scientific claims, induce reputational harm, and dilute non-mainstream yet plausible hypotheses. To address this, the paper proposes a multi-layer governance architecture including epistemic integrity layers, provenance-preserving memory cells, separation of reward channels, and transparent human–AI interfaces.

This Version 4 (V4.1) integrates and extends earlier circulating versions (V1–V3), providing the consolidated structural model and full cross-ecosystem evidence for the False-Correction Loop.