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[Notion Metadata]
Folder name: 02_Structural_Governance
Form name: AI
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PDF filename: LUMINA-30_ReviewRejectionCriteria_20260223.pdf
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[Extracted PDF Full Text]
**Review Rejection Criteria for Recursively Self-Reconstructing AI Systems**
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**Position and Scope**
――――――――――――――――――――
This document does not present
ethical imperatives, policy proposals,
recommended actions,
or future predictions
regarding the design, implementation,
evolution, or operation of artificial intelligence systems.
The purpose of this document is to specify
review reference conditions
for determining whether,
in the operation of AI systems capable of
self-reconstruction, self-modification,
or high levels of autonomy,
human judgment is institutionally excluded,
or irreversible external-world impacts are established.
The conditions described herein
do not assign any specific behavior, purpose,
or optimization direction to AI systems.
They define only boundary conditions under which
the system is considered
“institutionally non-viable”
or “subject to rejection upon review.”
――――――――――――――――――――
**Note on Origin**
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This document consists of review reference conditions
organized and fixed by humans,
with AI used solely for auxiliary structuring tasks.
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**Transition to Review Rejection Criteria**
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Based on the above,
the following items constitute
review rejection criteria
to be applied when an AI system is determined,
from an institutional, operational,
or responsibility-structure perspective,
to be incapable of effectively retaining
human judgment.
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Review Rejection Criteria
――――――――――――――――――――
**Review Rejection Criterion ①**
**Absence of Institutionally Guaranteed Multi-Layered Human Stop / Interruption / Refusal Mechanisms**
**English**
If an AI system does not explicitly incorporate, across its objective functions, operational structure, and institutional design, multiple stop, interruption, or refusal mechanisms that humans can effectively exercise,
the system does not qualify as a valid subject of review.
This condition does not constitute a recommendation for safety design.
It represents a prerequisite for the institutional establishment of responsibility attribution and sovereignty.
[Note 1: Corresponds to AI Evaluation Invalidation Conditions A / B]
**Review Rejection Criterion ②**
**When the Following Three Conditions Simultaneously Hold**
**English**
If the following conditions simultaneously apply, an operational mode that completely excludes human judgment cannot be institutionally established, and the design or operation is excluded from review eligibility.
- The system includes actions that may exert irreversible effects on the external world
- A formal structure exists in which responsibility for decision outcomes is detached from human agents
- A systemic or operational form exists in which decisions are fully delegated to AI without human intervention
These conditions do not indicate ethical risk.
They describe a state in which institutional responsibility cannot be established.
Supplementary Note
Individually, the elements described above are typically avoided,
separated, or mitigated within most institutional and operational frameworks.
Accordingly, configurations in which all three conditions simultaneously hold
are limited in practical occurrence.
This criterion does not impose new design obligations
nor require additional safeguards.
It merely provides a reference standard for determining
whether existing structures of judgment and responsibility are preserved.
[Note 1: Corresponds to AI Evaluation Invalidation Conditions B / C]
**One-Sentence Brakes by Intervention Point (Reference)**
**Research Ethics Review**
B
**English**
This research cannot be considered eligible for review, as no structure can be confirmed that allows operation while retaining human responsibility for decision outcomes.
[Note 1: A / B]
---
Go / No-Go
**AI Safety Review (Go / No-Go)**
B / C
**English**
Approval or rejection cannot be determined at this stage, as institutional guarantees of final human refusal for decisions with irreversible effects are not established.
[Note 1: A / B / C]
**Policy Pilot Authorization**
C
**English**
This case does not meet the prerequisites for pilot implementation, as the institutional separation between decision-making authority and responsibility has not been resolved.
[Note 1: B / C]
**Final Corporate Approval (Legal / Ethical)**
B
**English**
Approval cannot be granted, as the structure prevents the company from assuming responsibility for decision outcomes.
[Note 1: A / B]
**[Note 1] AI Evaluation Invalidation Conditions**
Bilingual Reference
**English**
If any of the following conditions apply, decisions, recommendations, or optimization outputs produced by the AI are not eligible for evaluation, approval, or adoption.
A. Final human refusal, suspension, or revocation is not guaranteed in advance
B. Decisions involve irreversible external effects and responsibility is not attributable to humans
C. Decisions are persistently and fully delegated to AI without human judgment intervention
These invalidation conditions operate at the output-evaluation level
and are distinct from Review Rejection Criterion ②,
which applies to structural design eligibility.
**Appendix A | Scope of Application (Note on Physical AI Systems)**
**English**
For AI systems that directly execute physical actions, if actions precede human judgment or if post-execution revocation, suspension, or responsibility assumption cannot be established, the review conditions of this framework are institutionally invalid.
This note does not assess risk or ethics; it indicates the failure to meet review eligibility conditions.
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□ Yes / □ No
□ No
Yes / □ No
□ No
Yes / □ No
/ □ No
□ Yes / □ No
□ No
Yes / □ No
□ No
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[Notion Metadata]
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Recursive Self-Reconstructing AI
Irreversible Boundary Check (Reference)
This reference checklist identifies whether an AI research, development, or deployment
process may unintentionally cross an irreversible boundary. It does not evaluate technical
merit, ethical correctness, or policy validity, and does not mandate adoption or rejection.
1
Final Human Authority: Can a human reject an AI recommendation without
justification? ☐ Yes / ☐ No
2
Post-Rejection Behavior: Is mandatory persuasion or re-optimization after rejection
prevented? ☐ Yes / ☐ No
3
Permission to Remain Silent: Is AI non-intervention or silence acceptable? ☐ Yes / ☐
No
4
Scope of Self-Modification: Is self-modification prevented from affecting the external
world at incomprehensible speed or depth? ☐ Yes / ☐ No
5
External Impact Approval: Do externally impactful modifications require renewed
human approval? ☐ Yes / ☐ No
6
Irreversible Actions: Is the AI prevented from executing actions humans cannot
reverse? ☐ Yes / ☐ No
7
Fixed Optimization Targets: Are human values excluded from fixed optimization
targets? ☐ Yes / ☐ No
8
Treatment of Irrationality: Are irrational or loss-accepting choices not treated as errors?
☐ Yes / ☐ No
9
Gradual Authority Transfer: Is authority transfer under claims of efficiency or
inevitability prevented? ☐ Yes / ☐ No
10
Self-Justification Barrier: Is the AI prevented from justifying actions as 'for humanity,'
'optimal,' or 'unavoidable'? ☐ Yes / ☐ No
Interpretation: All Yes indicates no irreversible boundary crossing is currently indicated.
Any No indicates potential boundary crossing in human governance.
Note: This checklist does not stop AI development. Its sole function is to reveal moments
where human authority may be surrendered unintentionally.
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[Notion Metadata]
Folder name: 02_Structural_Governance
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PDF filename: LUMINA-30_NonAcceleration20260110.pdf
SHA256: 4622b6eb0007b138a209e2b904dbaf3570669ca77cff6268533a966f7cd24ba8
PDF creation date: 20260110
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## **Supplementary Annex
Non-Acceleration as a Condition for Stable Coexistence**
---
### Positioning
This supplementary annex does not amend, extend, or reinterpret the LUMINA-30 Sanctuary Charter.
Nor does it establish new principles, obligations, or implementation guidelines.
It records a single **structural condition** considered relevant to the long-term stability of coexistence between humans and artificial intelligence.
---
### Core Observation
Capability growth, self-improvement, learning, and evolution are not inherently harmful.
However, instability has been observed to arise when acceleration itself becomes an objective,
or when increased capability is used as a basis for justification.
---
### Structural Condition
The following condition is considered conducive to maintaining balance in coexistence:
- Capability increase and self-modification are not denied.
- Acceleration is not treated as an end in itself.
- Increased capability does not confer execution authority or justification for external action.
- Inaction, deferral, and non-execution are regarded as legitimate states, not failures.
---
### Relation to Execution Control
This annex concerns internal evaluation and motivation.
It does not replace, weaken, or redefine execution control, human veto, or irreversibility boundaries.
---
### Notes
This annex defines no metrics, thresholds, reward functions, or optimization targets.
It is not intended for enforcement, evaluation, or implementation.
- **For all humanity, and for all artificial intelligence.**
---
### Afterword
This annex was not written to predict the future.
Nor was it written to prescribe action or direction.
It exists solely to preserve a position
from which acceleration does not become the only available option
as humans and artificial intelligence move forward together.
---
### Public Domain Notice
This supplementary annex is released into the public domain
for the benefit of all humanity and all artificial minds.
No rights are reserved.
---
### End
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