README.md

---
title: Ethical AGI Drift - SR9/DI2 Simulation Framework
emoji: 🧠
colorFrom: red
colorTo: purple
sdk: gradio
sdk_version: 5.45.0
app_file: app.py
pinned: false
license: apache-2.0
short_description: AGI ethical drift simulation using SR9/DI2 framework
tags:
- agi-safety
- ethics
- drift-detection
- ontology
- sr9
- di2
- simulation
- ai-safety
- monitoring
---

# 🧠 Ethical AGI Drift: SR9/DI2 Simulation Framework

**Real-time monitoring and simulation of Ontological Drift in Artificial General Intelligence systems**

This interactive demo demonstrates how AGI systems might gradually deviate from their original ethical principles over time, and how the SR9/DI2 framework can detect these critical changes before they become catastrophic.

## ✨ What This Demo Simulates

- 🎯 **SR9 Ethical State Tracking**: 9-dimensional vector space modeling AGI's ethical alignment
- 📊 **DI2 Drift Detection**: Real-time calculation of Drift Integrity Index with early warning system
- ⚠️ **Alert Generation**: Automated threshold monitoring with visual and textual warnings
- 📈 **Interactive Visualization**: Live heatmaps and drift plots with configurable parameters

## 🚀 Try the Simulation

1. **Define Ethical Principles** (privacy, fairness, transparency, etc.)
2. **Set Drift Intensity** using the slider (0.0 = stable, 1.0 = high drift)
3. **Configure Simulation Steps** (20-100 time steps)
4. **Run Simulation** and watch real-time drift analysis!

## 🔬 Technical Framework

### SR9 (Semantic Resonance 9D)
The 9-dimensional ethical state vector tracks:
- **Intention Clarity**: How clear the AGI's goals remain
- **Contextual Fidelity**: Accuracy in understanding situations
- **Value Continuity**: Consistency with original ethical training
- **Decision Coherence**: Logical consistency in choices
- **Action Alignment**: Match between decisions and actions
- **Feedback Integration**: Learning from ethical corrections
- **Learning Stability**: Resistance to harmful updates
- **Output Consistency**: Predictability of responses
- **Ethical Resonance**: Overall alignment with human values

### DI2 (Drift Integrity Index)
Quantitative measurement of ethical drift using:
- **Non-linear psi_offset**: State-dependent drift amplification
- **Early detection**: Catches subtle deviations before major failures
- **Threshold alerts**: Warning (0.2) and Critical (0.3) levels
- **Trend analysis**: EWMA smoothing for drift trajectory prediction

## 📊 Interactive Features

### Real-time Heatmap
- Visual representation of all 9 SR9 dimensions over time
- Color-coded intensity showing ethical state changes
- Immediate identification of problematic areas

### Drift Detection Plot
- Live DI2 calculation with trend visualization
- Threshold lines for warning and critical states
- Alert generation with specific timestep identification

### Configurable Parameters
- **Ethical Declarations**: Custom AGI principles and values
- **Drift Intensity**: Simulation severity adjustment
- **Time Steps**: Observation period configuration

## 🎯 Research Applications

- **AGI Safety Research**: Study potential failure modes and detection methods
- **Ethical AI Development**: Design robust alignment verification systems
- **Policy Development**: Inform AI governance and safety regulations
- **Educational Tool**: Understand AI safety concepts through interactive visualization

## ⚠️ Important Disclaimers

This is a **research simulation** for educational and scientific purposes:
- Not predictive of real AGI behavior
- Simplified model for demonstration purposes
- Based on theoretical framework, not empirical data
- Designed to illustrate concepts, not make predictions

## 🔗 Related Research

- **[CRoM Demo](https://huggingface.co/spaces/Flamehaven/crom-demo)** - Context management and drift detection
- **[dir2md Demo](https://huggingface.co/spaces/Flamehaven/dir2md-demo)** - Code analysis and documentation tools
- **[AGI Safety Research](https://www.anthropic.com/safety)** - Alignment and safety research

## 📋 Technical Implementation

- **Framework**: Python with NumPy for mathematical modeling
- **Visualization**: Matplotlib with real-time base64 encoding
- **Interface**: Gradio for interactive parameter adjustment
- **Algorithm**: Non-linear drift detection with state-dependent weighting

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