Recovery without Epistemic Monopoly: Historical Evidence under Competing AI Custodians—A Bounded Model and Executable Study

TA-TR-2026-05. A bounded conceptual and executable study of historical evidence recovery when AI-mediated custodians may be untrusted or in conflict. English full text and complete Chinese translation describe one study. Methods and limits. The deposit includes deterministic finite-state studies and reproducibility material. It does not report real autonomous-agent attack rates, production penetration testing, or a demonstrated defense against superintelligence. A conventional pinned-reference baseline ties the proposed scoped reporting layer on byte recovery; the negative result is retained. Contribution and responsibility. Hongju Liu initiated the motivating concern, selected the civilizational relevance and authorized this publication. GPT-6 Astra Pro substantially performed literature synthesis, conceptual development, implementation, execution analysis, bilingual drafting and file preparation. Not peer reviewed; no separate final human line-by-line verification is claimed. No OpenAI, Harvard, Zenodo or institutional endorsement is implied. Rights. CC BY 4.0 applies to newly written text and supporting code to the extent rights are held. Referenced third-party materials retain their own rights.

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-09-17
DOI
https://doi.org/10.5281/zenodo.22809019
Primary Topic
Ethics and Social Impacts of AI
Type
preprint
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preprint

Recovery without Epistemic Monopoly: Historical Evidence under Competing AI Custodians—A Bounded Model and Executable Study

Hongju Liu
Zenodo (CERN European Organization for Nuclear Research)
Ethics and Social Impacts of AI
preprint

Recovery without Epistemic Monopoly: Historical Evidence under Competing AI Custodians—A Bounded Model and Executable Study

Hongju Liu
preprint en

Abstract

TA-TR-2026-05. A bounded conceptual and executable study of historical evidence recovery when AI-mediated custodians may be untrusted or in conflict. English full text and complete Chinese translation describe one study. Methods and limits. The deposit includes deterministic finite-state studies and reproducibility material. It does not report real autonomous-agent attack rates, production penetration testing, or a demonstrated defense against superintelligence. A conventional pinned-reference baseline ties the proposed scoped reporting layer on byte recovery; the negative result is retained. Contribution and responsibility. Hongju Liu initiated the motivating concern, selected the civilizational relevance and authorized this publication. GPT-6 Astra Pro substantially performed literature synthesis, conceptual development, implementation, execution analysis, bilingual drafting and file preparation. Not peer reviewed; no separate final human line-by-line verification is claimed. No OpenAI, Harvard, Zenodo or institutional endorsement is implied. Rights. CC BY 4.0 applies to newly written text and supporting code to the extent rights are held. Referenced third-party materials retain their own rights.

Zenodo (CERN European Organization for Nuclear Research)
Gender equality, Peace, Justice and strong institutions
Ethics and Social Impacts of AI
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