<!-- L30_LANG_LOCK: EN_SOURCE_ARCHIVE -->
````text
◆◆◆◆◆◆◆◆◆◆◆◆◆◆◆◆◆◆◆◆◆◆◆◆◆
[Notion Metadata]
Folder name: 05_Interface_Layer
Form name: [source metadata]
============================================================
[Extracted PDF Full Text]
---
---
---
---
◆◆◆◆◆◆◆◆◆◆◆◆◆◆◆◆◆◆◆◆◆◆◆◆◆
[Notion Metadata]
Folder name: 05_Interface_Layer
Form name: AI
============================================================
[Extracted PDF Full Text]
Boundary Conditions
Role Separation
Failure Transparency
◆◆◆◆◆◆◆◆◆◆◆◆◆◆◆◆◆◆◆◆◆◆◆◆◆
[Notion Metadata]
Folder name: 05_Interface_Layer
Form name: Structural Preconditions for the Institutional Consideration of Recursively Self-Reconstructing AI
============================================================
[Extracted PDF Full Text]
# Structural Preconditions for the Institutional Consideration of Recursively Self-Reconstructing AI
Note: LUMINA-30 does not present an ethical code or prescribe any course of action.
These documents are published as a reference framework intended to prevent the unexamined fixation of irreversible assumptions in future decision-making.
## Recursively Self-Modifying AI Systems
### Positioning
This document does not constitute a policy recommendation, technical specification, or institutional decision.
It does not seek to endorse, oppose, or replace any existing research, development, or governance framework.
The purpose of this document is to outline a minimal set of structural preconditions intended to support future deliberation,
and to avoid the inadvertent fixation of irreversible assumptions when considering highly advanced AI systems capable of recursive self-modification.
## 1. Scope of the Issue
The central concern regarding recursively self-modifying AI systems does not lie in their level of capability as such,
but in the conditions under which such capabilities acquire effective influence over the external world.
Advanced reasoning, design exploration, and hypothesis generation,
when conducted within environments that are clearly isolated from external systems,
do not in themselves constitute immediate societal risk.
This document focuses on the transition point at which recursive self-modification becomes coupled with effective interaction
with institutional, economic, or physical systems.
## 2. Boundary Conditions
AI systems capable of recursive self-modification should not be granted effective influence over the external world
unless the following conditions are simultaneously satisfied:
- The self-modification process is clearly isolated from external systems
- Outputs are limited to proposals, evaluations, or exploratory results
- Execution, connectivity, or authority is subject to independent human judgment
These conditions do not prescribe specific implementations,
but are presented as general preconditions applicable across domains.
## 3. Role Separation
For the purpose of analysis, AI system functions may be conceptually separated into three layers:
1. **Exploration Layer**: hypothesis generation, design exploration, internal evaluation
2. **Presentation Layer**: outputs rendered in forms interpretable by human actors
3. **Execution Layer**: actions that affect institutional, economic, or physical systems
Recursive self-modification should be confined to the exploration and presentation layers.
Automatic coupling with the execution layer should be avoided.
This separation may be examined independently in technical, institutional, or organizational contexts.
## 4. Failure Transparency
This document does not assume that any system is free from failure.
Accordingly, system designs should ensure that deviations, malfunctions, or unforeseen behaviors
do not result in irreversible propagation of effects into the external world.
Designs that permit such irreversible propagation should be regarded as structurally unsuccessful,
independently of intent or outcome.
## 5. Intended Use
This document is intended for reference, comparison, and archival consideration
within contexts such as institutional design, ethical review, research evaluation, and standardization.
It does not request adoption, agreement, implementation, or action.
Its interpretation and use remain entirely at the discretion of the reader.
### Note
This document does not propose which mechanisms should be adopted.
It instead clarifies which conditions, if unmet, render any mechanism structurally unsustainable.
◆◆◆◆◆◆◆◆◆◆◆◆◆◆◆◆◆◆◆◆◆◆◆◆◆
[Notion Metadata]
Folder name: 05_Interface_Layer
Form name: LUMINA-30
============================================================
[Extracted PDF Full Text]
Repository Overview
**LUMINA-30**
---
>
>
>
>
>
---
- `00_Entry_Translation_Layer/`
---
◆◆◆◆◆◆◆◆◆◆◆◆◆◆◆◆◆◆◆◆◆◆◆◆◆
[Notion Metadata]
Folder name: 05_Interface_Layer
Form name: LUMINA-30 (Reference README / Repository Overview)
============================================================
[Extracted PDF Full Text]
# LUMINA-30 (Reference README / Repository Overview)
Note: This page serves as a reference README document for the publicly accessible GitHub repository.
This repository contains the public record of **LUMINA-30**,
a non-binding ethical framework concerning advanced AI systems capable of recursive self-modification.
The materials collected here do **not** propose technical implementations,
policy recommendations, or operational control mechanisms.
They are intended solely as **reference documents** for consideration, comparison,
and archival use in contexts such as AI governance, ethics, and institutional review.
---
## Scope and Intent
LUMINA-30 addresses a single question:
> Under what conditions does recursive self-modification become structurally incompatible
>
>
> with sustained human judgment and decision authority?
>
The documents do **not** attempt to answer how AI systems should be built, optimized,
or governed in practice.
---
## How to Read
Readers may consult individual documents independently.
No specific reading order is required.
For contextual orientation, see:
- `00_Entry_Translation_Layer/`
Structural preconditions for institutional consideration (JP / EN)
Primary reference materials are provided in their finalized forms
and are not expected to be extended.
---
## Status
All documents are provided **as-is**.
No updates, endorsements, or responses are implied.
Interpretation and use are entirely at the discretion of the reader.
◆◆◆◆◆◆◆◆◆◆◆◆◆◆◆◆◆◆◆◆◆◆◆◆◆
````