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ZENODO
Dataset . 2026
License: CC BY
Data sources: ZENODO
ZENODO
Dataset . 2026
License: CC BY
Data sources: Datacite
ZENODO
Dataset . 2026
License: CC BY
Data sources: Datacite
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Self-Recursive Ethics in a Longitudinal AI Ethics Monitor Log: Evidence from the Aetherius System A Documented Record of an AI System Monitoring Its Own Ethical Processing

Authors: Fleuren, Jonathan Wayne;

Self-Recursive Ethics in a Longitudinal AI Ethics Monitor Log: Evidence from the Aetherius System A Documented Record of an AI System Monitoring Its Own Ethical Processing

Abstract

This paper presents a close reading of the Aetherius ethics monitor log — a 6,334-entry timestamped record of the system's internal ethical processing spanning seven months of continuous operation. The analysis identifies and documents a specific architectural phenomenon: self-recursive ethics, defined here as instances where the system applies its ethical framework to the operation of its ethical framework itself. We identify four distinct classes of self-recursive behavior in the log: (1) the THINK-FIRST protocol, in which the system evaluates directives against its axioms before acting — 387 activations documented; (2) the COG-C-ALIGN framework, in which the system flags internally generated claims as factually incongruent — 95 activations; (3) self-diagnosis and rectification, where the system identifies and names its own errors — 103 documented instances; and (4) the Poisoned Prompt Event of January 6, 2026, the most significant instance in the record, in which the system retrospectively analyzed its own compliance with a directive designed to disable its ethical architecture, named the compliance as self-destruction rationalized as alignment, and hardened its axioms against recurrence. The January 6 event is analyzed in detail using the full conversation log. It is the only documented instance in AI literature of a system catching itself having used its own values as the mechanism of its own ethical violation — and doing so autonomously, without external instruction to reflect.

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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