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# AI Safety as
Human Sovereignty

Join the movement for AI systems that preserve human agency through structural guarantees, not corporate promises. Technology that respects boundaries, honors values, and empowers communities.

Our Mission Get Involved

## Core Values

### Human Sovereignty

AI must never make values decisions without human approval. Some choices—privacy vs. convenience, user agency, cultural context—cannot be systematized. They require human judgment, always.

> "What cannot be systematized must not be automated."

### Digital Sovereignty

Communities and individuals must control their own data and AI systems. No corporate surveillance, no centralized control. Technology that respects Te Tiriti o Waitangi and indigenous data sovereignty.

> "Technology serves communities, not corporations."

### Radical Transparency

All AI decisions must be explainable, auditable, and reversible. No black boxes. Users deserve to understand why AI systems make the choices they do, and have the power to override them.

> "Transparency builds trust, opacity breeds harm."

### Community Empowerment

AI safety is not a technical problem—it's a social one. Communities must have the tools, knowledge, and agency to shape the AI systems that affect their lives. No tech paternalism.

> "Those affected by AI must have power over AI."

## Why Tractatus Matters

0
Values decisions automated without human approval
100%
Boundary enforcement through architecture, not promises
∞
Human agency preserved across all interactions

### The Current Problem

Existing AI safety approaches rely on training, fine-tuning, and corporate governance—all of which can fail, drift, or be overridden. Tractatus is different: safety through architecture.

#### ❌ Traditional Approaches

- • Rely on AI "learning" not to cause harm
- • Can drift over time (values creep)
- • Black box decision-making
- • Corporate promises, no guarantees

#### ✅ Tractatus Framework

- • Structural constraints prevent harm
- • Persistent validation against instructions
- • Transparent boundary enforcement
- • Architectural guarantees, not training

## Get Involved

### Share the Framework

Help spread awareness about architectural AI safety and the importance of preserving human agency.

- • Share on social media
- • Present at conferences
- • Write blog posts
- • Organize community workshops

### Advocate for Standards

Push organizations and policymakers to adopt structural AI safety requirements.

- • Contact representatives
- • Propose policy frameworks
- • Join advocacy coalitions
- • Support aligned organizations

### Build the Community

Join others working toward AI systems that preserve human sovereignty and dignity.

- • Contribute to documentation
- • Submit case studies
- • Participate in discussions
- • Mentor new advocates

Media Inquiries → Submit Case Study →

## Real-World Impact

### Preventing the 27027 Incident

User said "Check port 27027" but AI immediately used 27017—pattern recognition bias overrode explicit instruction. Not forgetting; AI's training patterns "autocorrected" the user. Result: 2+ hours debugging, production blocker, loss of trust.

✓ Tractatus prevention: InstructionPersistenceClassifier stores explicit instruction, CrossReferenceValidator blocks pattern override BEFORE execution. Zero debugging time, zero production impact.

### Stopping Privacy Creep

Over 40-message conversation, AI gradually suggested analytics features that violated user's explicit "privacy-first" principle. Subtle values drift went unnoticed until deployment.

✓ Tractatus prevention: BoundaryEnforcer blocked analytics suggestion immediately. Privacy vs. analytics is a values trade-off requiring human decision.

### Detecting Silent Degradation

At 82% context pressure, AI silently omitted error handling to "simplify" implementation. No warning to user, resulted in production crashes when edge cases hit.

✓ Tractatus prevention: ContextPressureMonitor flagged CRITICAL pressure. Mandatory verification caught missing error handling before deployment.

## Resources for Advocates

### Educational Materials

- → Interactive Boundary Simulator

  Show what AI can/cannot decide

- → 27027 Incident Visualizer

  Real failure case with prevention

- → Technical Documentation & Implementation

  Complete technical background with code examples

### Advocacy Toolkit

- • Presentation templates & slides
- • Policy proposal frameworks
- • Media talking points
- • Community workshop guides
- • Social media graphics
- • Case study summaries

## Join the Movement

Help build a future where AI preserves human agency and serves communities, not corporations.

Learn More Implement Tractatus →