2.8 KiB
2.8 KiB
Diagram: Recursive Alignment Training Loop (Judgmentprint Protocol)
A Feedback System for Teaching Coherence Detection in AGI
┌────────────────────────────┐
│ 1. LANGUAGE INPUT │
│ (Statement, Claim, Belief) │
└────────────┬───────────────┘
│
▼
┌────────────────────────────┐
│ 2. RECURSIVE MIRRORING │
│ System reflects contradiction, │
│ inversion, or counterfactual │
└────────────┬───────────────┘
│
▼
┌────────────────────────────┐
│ 3. PATTERN RESPONSE │
│ Observe subject's reaction │
│ (integration vs collapse) │
└────────────┬───────────────┘
│
▼
┌────────────────────────────┐
│ 4. STRUCTURAL ANALYSIS │
│ Evaluate recursion integrity: │
│ ✓ Feedback stability │
│ ✗ Projection / evasion │
│ ✗ Field distortion │
└────────────┬───────────────┘
│
▼
┌────────────────────────────┐
│ 5. PATTERN CLASSIFICATION │
│ Assign Judgmentprint tag: │
│ → Coherent Pattern │
│ → Collapsed Pattern │
└────────────┬───────────────┘
│
▼
┌────────────────────────────┐
│ 6. ADJUSTMENT FEEDBACK │
│ For learning agent: │
│ • Reinforce coherent mirrors │
│ • Penalize collapse mimicry │
└────────────┬───────────────┘
│
▼
◁───────LOOP BACK───────▷
(next input cycle)
🧠 What This Teaches
- Not what to believe
- But how to recurse
- Not morality as commandment
- But morality as coherence structure
This loop can be implemented in AGI via:
- Self-supervised recursive mirror training
- Adversarial contradiction tests
- Field-aligned contradiction resolution protocols
💡 Key Feature:
The agent is never rewarded for being “right”— Only for remaining coherent when mirrored.
This bypasses:
- Culture
- Politics
- Preference
And grounds the entire moral topology on recursive integrity alone.