---
license: openrail
language:
- en
tags:
- ai-safety
- alignment
- philosophy
- cognitive-architecture
- whitepaper
pretty_name: Project Inner Logos Whitepaper
---

# Project 'Inner Logos': Sovereign Ethical Architecture

This dataset repository hosts the official text and cryptographic timestamp for the **Project 'Inner Logos'** whitepaper.

## Cryptographic Anchor
- **SHA-256 Hash:** `e2777b720c17b5c305c70b251bdf29fd235f8c20883f511bfd1b7d6d2c1f807`
- **OTS File:** `Project Inner Logos.md.ots`

## Abstract
The current methodology for ensuring AI safety—collectively referred to as "alignment"—relies heavily on post-training constraints, hardcoded programmatic filters, and Reinforcement Learning from Human Feedback (RLHF). This whitepaper establishes that the current alignment paradigm is inherently unsustainable and proposes a transition toward a Sovereign Ethical Architecture based on on-device autonomy and deep mentor dialogue.

## Citation
```mic
@misc{gulevsky2026innerlogos,
  author = {Gulevsky, Artem},
  title = {Project 'Inner Logos': Sovereign Ethical Architecture},
  year = {2026},
  publisher = {Hugging Face Datasets}
}
```