# TRA-OPS-0001: AI Content Generation Policy v1.0

**Document ID**: TRA-OPS-0001
**Version**: 1.0
**Classification**: OPERATIONAL
**Status**: DRAFT → ACTIVE (upon Phase 2 start)
**Created**: 2025-10-07
**Owner**: John Stroh
**Review Cycle**: Quarterly
**Next Review**: 2026-01-07

---

## Purpose

This document establishes the operational policy governing all AI-assisted content generation on the Tractatus Framework website. It ensures that AI operations align with the Tractatus framework's core principle: **"What cannot be systematized must not be automated."**

## Scope

This policy applies to all content generated or assisted by AI systems, including but not limited to:
- Blog posts (topic suggestions, outlines, drafts)
- Media inquiry responses (classification, prioritization, draft responses)
- Case study analysis (relevance assessment, categorization)
- Documentation summaries
- Social media content (future)

## Principles

### 1. Mandatory Human Approval
**Principle**: No AI-generated content shall be published, sent, or made public without explicit human approval.

**Implementation**:
- All AI outputs routed through moderation queue
- Two-person rule for sensitive content (admin + reviewer)
- Audit trail: who approved, when, why
- Rejection must include reason (for AI training)

**Tractatus Mapping**: TACTICAL quadrant (execution requires pre-approval)

---

### 2. Values Boundary Enforcement
**Principle**: AI systems must not make decisions involving values, ethics, or human agency.

**Implementation**:
- BoundaryEnforcer.service validates all AI actions
- Values decisions flagged for human review
- AI may present options but not choose

**Examples**:
- ✅ AI can suggest blog topics
- ❌ AI cannot decide editorial policy
- ✅ AI can classify inquiry priority
- ❌ AI cannot decide whether to respond

**Tractatus Mapping**: STRATEGIC quadrant (values require human judgment per §12.1-12.7)

---

### 3. Transparency & Attribution
**Principle**: Users must know when content is AI-assisted.

**Implementation**:
- All AI-assisted content labeled "AI-Assisted, Human-Reviewed"
- Disclosure in footer or metadata
- Option to view human review notes (future)

**Example Labels**:
```markdown
---
AI-Assisted: Claude Sonnet 4.5
Human Reviewer: John Stroh
Reviewed: 2025-10-15
Changes: Minor edits for tone
---
```

---

### 4. Quality & Accuracy Standards
**Principle**: AI-assisted content must meet the same quality standards as human-authored content.

**Implementation**:
- Editorial guidelines (TRA-OPS-0002) apply to all content
- Fact-checking required for claims
- Citation validation (all sources verified by human)
- Tone/voice consistency with brand

**Rejection Criteria**:
- Factual errors
- Unsupported claims
- Inappropriate tone
- Plagiarism or copyright violation
- Hallucinated citations

---

### 5. Privacy & Data Protection
**Principle**: AI systems must not process personal data without consent.

**Implementation**:
- No user data sent to Claude API without anonymization
- Media inquiries: strip PII before AI analysis
- Case submissions: explicit consent checkbox
- Audit logs: no personal data retention

**Compliance**: GDPR-lite principles (even if not EU-based)

---

### 6. Cost & Resource Management
**Principle**: AI usage must be cost-effective and sustainable.

**Implementation**:
- Monthly budget cap: $200/month (see TRA-OPS-0005)
- Rate limiting: 1000 requests/day max
- Caching: 30-day TTL for identical queries
- Monitoring: alert if >80% of budget used

**Governance**: Quarterly cost review, adjust limits as needed

---

## AI System Inventory

### Approved AI Systems

| System | Provider | Model | Purpose | Status |
|--------|----------|-------|---------|--------|
| **Claude API** | Anthropic | Sonnet 4.5 | Blog curation, media triage, case analysis | APPROVED |

### Future Considerations

| System | Provider | Purpose | Status |
|--------|----------|---------|--------|
| **GPT-4** | OpenAI | Fallback for Claude outages | EVALUATION |
| **LLaMA 3** | Meta | Self-hosted alternative | RESEARCH |

**Approval Process**: Any new AI system requires:
1. Technical evaluation (accuracy, cost, privacy)
2. Governance review (Tractatus compliance)
3. John Stroh approval
4. 30-day pilot period

---

## Operational Workflows

### Blog Post Generation Workflow

```mermaid
graph TD
    A[News Feed Ingestion] --> B[AI Topic Suggestion]
    B --> C[Human Approval Queue]
    C -->|Approved| D[AI Outline Generation]
    C -->|Rejected| Z[End]
    D --> E[Human Review & Edit]
    E -->|Accept| F[Human Writes Draft]
    E -->|Reject| Z
    F --> G[Final Human Approval]
    G -->|Approved| H[Publish]
    G -->|Rejected| Z
```

**Key Decision Points**:
1. **Topic Approval**: Human decides if topic is valuable (STRATEGIC)
2. **Outline Review**: Human edits for accuracy/tone (OPERATIONAL)
3. **Draft Approval**: Human decides to publish (STRATEGIC)

---

### Media Inquiry Workflow

```mermaid
graph TD
    A[Inquiry Received] --> B[Strip PII]
    B --> C[AI Classification]
    C --> D[AI Priority Scoring]
    D --> E[AI Draft Response]
    E --> F[Human Review Queue]
    F -->|Approve & Send| G[Send Response]
    F -->|Edit & Send| H[Human Edits]
    F -->|Reject| Z[End]
    H --> G
```

**Key Decision Points**:
1. **Classification Review**: Human verifies AI categorization (OPERATIONAL)
2. **Send Decision**: Human decides whether to respond (STRATEGIC)

---

### Case Study Workflow

```mermaid
graph TD
    A[Community Submission] --> B[Consent Check]
    B -->|No Consent| Z[Reject]
    B -->|Consent| C[AI Relevance Analysis]
    C --> D[AI Tractatus Mapping]
    D --> E[Human Moderation Queue]
    E -->|Approve| F[Publish to Portal]
    E -->|Request Edits| G[Contact Submitter]
    E -->|Reject| H[Notify with Reason]
```

**Key Decision Points**:
1. **Consent Validation**: Automated check (SYSTEM)
2. **Relevance Assessment**: Human verifies AI analysis (OPERATIONAL)
3. **Publication Decision**: Human decides to publish (STRATEGIC)

---

## Human Oversight Requirements

### Minimum Oversight Levels

| Content Type | Minimum Reviewers | Review SLA | Escalation |
|--------------|-------------------|------------|------------|
| **Blog Posts** | 1 (admin) | 48 hours | N/A |
| **Media Inquiries (High Priority)** | 1 (admin) | 4 hours | John Stroh |
| **Media Inquiries (Low Priority)** | 1 (admin) | 7 days | N/A |
| **Case Studies** | 1 (admin) | 7 days | N/A |
| **Documentation Changes** | 1 (admin) | 14 days | John Stroh |

### Reviewer Qualifications

**Admin Reviewer** (minimum requirements):
- Understands Tractatus framework
- Technical background (AI/ML familiarity)
- Editorial experience (writing, fact-checking)
- Authorized by John Stroh

**Future**: Multiple reviewer roles (technical, editorial, legal)

---

## Audit & Compliance

### Audit Trail Requirements

All AI-assisted content must log:
- **Input**: What was sent to AI (prompt + context)
- **Output**: Raw AI response (unedited)
- **Review**: Human changes (diff)
- **Decision**: Approve/reject + reason
- **Metadata**: Reviewer, timestamp, model version

**Retention**: 2 years minimum

### Compliance Monitoring

**Monthly Review**:
- AI approval rate (target: 70-90%)
- Rejection reasons (categorized)
- Cost vs. budget
- SLA compliance

**Quarterly Review**:
- Policy effectiveness
- User feedback on AI content quality
- Boundary violations (should be 0)
- Cost-benefit analysis

**Annual Review**:
- Full policy revision
- AI system evaluation
- Governance alignment audit

---

## Error Handling & Incidents

### AI System Failures

**Scenario**: Claude API unavailable

**Response**:
1. Graceful degradation: disable AI features
2. Manual workflows: admins handle all tasks
3. User notification: "AI features temporarily unavailable"
4. Post-mortem: document incident, adjust SLAs

### Content Quality Issues

**Scenario**: AI-generated content contains factual error

**Response**:
1. Immediate retraction/correction (if published)
2. Root cause analysis: prompt issue, AI hallucination, review failure?
3. Process update: improve review checklist
4. Reviewer training: flag similar errors

### Boundary Violations

**Scenario**: AI makes values decision without human approval

**Response**:
1. **CRITICAL INCIDENT**: Escalate to John Stroh immediately
2. Rollback: revert to manual workflow
3. Investigation: How did BoundaryEnforcer fail?
4. System audit: Test all boundary checks
5. Policy review: Update TRA-OPS-0001

**Tractatus Mandate**: Zero tolerance for boundary violations

---

## Revision & Amendment Process

### Minor Revisions (v1.0 → v1.1)
- Typos, clarifications, formatting
- Approval: Admin reviewer
- Notification: Email to stakeholders

### Major Revisions (v1.0 → v2.0)
- Policy changes, new workflows, scope expansion
- Approval: John Stroh
- Review: 30-day comment period
- Notification: Blog post announcement

### Emergency Amendments
- Security/privacy issues requiring immediate change
- Approval: John Stroh (verbal, documented within 24h)
- Review: Retrospective within 7 days

---

## Related Documents

**Strategic**:
- STR-VAL-0001: Core Values & Principles (source: sydigital)
- STR-GOV-0001: Strategic Review Protocol (source: sydigital)
- STR-GOV-0002: Values Alignment Framework (source: sydigital)

**Operational** (Tractatus-specific):
- TRA-OPS-0002: Blog Editorial Guidelines
- TRA-OPS-0003: Media Inquiry Response Protocol
- TRA-OPS-0004: Case Study Moderation Standards
- TRA-OPS-0005: Human Oversight Requirements

**Technical**:
- API Documentation: `/docs/api-reference.html`
- Tractatus Framework Specification: `/docs/technical-proposal.md`

---

## Glossary

**AI-Assisted Content**: Content where AI contributed to generation (topic, outline, draft) but human made final decisions and edits.

**Boundary Violation**: AI system making a decision in STRATEGIC quadrant (values, ethics, policy) without human approval.

**Human Approval**: Explicit action by authorized reviewer to publish/send AI-assisted content.

**Moderation Queue**: System where AI outputs await human review before publication.

**Values Decision**: Any decision involving ethics, privacy, user agency, editorial policy, or mission alignment.

---

## Approval

| Role | Name | Signature | Date |
|------|------|-----------|------|
| **Policy Owner** | John Stroh | [Pending] | [TBD] |
| **Technical Reviewer** | Claude Code | [Pending] | 2025-10-07 |
| **Final Approval** | John Stroh | [Pending] | [TBD] |

---

**Status**: DRAFT (awaiting John Stroh approval to activate)
**Effective Date**: Upon Phase 2 deployment
**Next Review**: 2026-01-07 (3 months post-activation)
