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ZENODO
Preprint . 2026
License: CC BY
Data sources: ZENODO
ZENODO
Preprint . 2026
License: CC BY
Data sources: Datacite
ZENODO
Preprint . 2026
License: CC BY
Data sources: Datacite
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The Dangers of AI-Narrative Judgment Substitution - A Judgment-Centric Risk Analysis under CESI, IFRG, and LF²ES

Authors: Xu, Lucas Xiaochun;

The Dangers of AI-Narrative Judgment Substitution - A Judgment-Centric Risk Analysis under CESI, IFRG, and LF²ES

Abstract

Abstract Using a Judgment-Centric Epistemic Niche (J-CEN) perspective situated within the Co-Evolutionary Science of Intelligence (CESI), this study analyzes how AI-generated strategic narratives induce judgment drift, create explainability illusions, and accelerate Cognitive Species Divergence (CSD) between human judgment systems and machine-generated pseudo-judgment. Within CESI, intelligence is treated as a co-evolving system across biological, artificial, and organizational substrates. AI-narrative judgment substitution is therefore analyzed not merely as a governance failure, but as a degenerative evolutionary mechanism acting at the cognitive-architectural level. By integrating Cognitive Architectonics (CAX) with Irreversibility-First Risk Governance (IFRG) and Lethality-First Fast-Filter Elimination Search (LF²ES), the paper situates AI-narrative outputs as high-risk cognitive artifacts within the Enterprise Irreversible Risk Operating System (E-IROS).

Declaration This paper is an original conceptual and operational framework developed independently by Lucas Xiaochun Xu. The author declares that this work is an original conceptual and analytical contribution. No confidential information, proprietary data, or identifiable individuals were used or referenced. This paper is intended solely for academic, governance, and risk-analysis purposes. Any resemblance to real systems or practices is structural rather than specific.

Keywords

CESI, judgment drift, narrative bias, irreversible risk governance, LF²ES, enterprise AI governance, AI judgment substitution, IFRG, human-AI decision boundaries

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average