tractatus/governance/TRA-OPS-0001-ai-content-generation-policy-v1-0.md

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

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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)

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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)

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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:

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

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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)

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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

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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

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Operational Workflows

Blog Post Generation Workflow

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)

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Media Inquiry Workflow

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)

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Case Study Workflow

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)

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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)

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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

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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

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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

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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

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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.

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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]

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