Policy & Compliance · October 8, 2025 · 13 min read
Ethical Sourcing in AI Art: A Guide to Licensing and Provenance for High-Quality Media Assets
Roman Circus's Clean Data Mandate and Provenance Audit Log protocol for auditable AI media
Introduction: The New Scarcity of Trust
As generative media floods the web, provenance becomes the deciding factor for Trust. Google’s quality systems scrutinize licensing clarity and origin transparency. Roman Circus’ production pipeline relies on verifiable sourcing to maintain high-value, monetizable content.
This policy outlines our Clean Data Mandate and Provenance Audit Log (PAL) protocol, demonstrating how every generated asset earns its place in our E-A-T strategy.
Section 1: The Clean Data Mandate – Tiered Model Selection
We categorize models by training-data transparency to protect legal standing and creative fidelity. Only Tier 1 (T1) and Tier 2 (T2) models are approved.
| Tier | Training Corpus | Usage Policy |
|---|---|---|
| T1 | Public domain, CC0/CC-BY-A, explicit contributor datasets | Preferred for conceptual generation (e.g., Grok IG foundational work). |
| T2 | Licensed or indemnified data (cloud provider APIs, licensed stock corpora) | Permitted with retained documentation of indemnity/ToS. |
| T3 | Undisclosed, contested, or litigated datasets | Prohibited. Risk of legal exposure and style contamination. |
T3 models are banned from high-E-A-T projects. Style contamination from disputed datasets undermines authority and trustworthiness.
Section 2: The Provenance Audit Log (PAL)
Every high-value asset receives a PAL entry stored in a secure database, linked via a cryptographic hash in the filename. The PAL provides technical proof of origin.
PAL Components
- Full Prompt String (FPS) & Parameter Lock (PL): Records prompt, weights, seeds, and version identifiers.
- Model Environment & Training Tier Tag (METT): Logs model version and tier classification (T1/T2).
- Cross-Reference Hash & Seed (CRHS): Links the digital file to the PAL entry.
- Human Audit & Review Timestamp (HART): Captures reviewer ID and approval timestamp.
- Licensing & Usage Rights Tag (LURT): Specifies the final commercial license.
PAL transforms each image into auditable evidence, reinforcing Expertise and Authority.
Section 3: The Human Audit Layer (HAL)
Automation handles generation; humans ensure factual and historical accuracy. Subject Matter Experts (SMEs) validate Conceptual Fidelity and guard against logical contradictions.
- Conceptual Contradictions: Detect violations like anachronistic armor or physics errors.
- Reference Policy: Prompts never reference living artists. Only historical styles or public-domain aesthetics are allowed.
HAL ensures human expertise remains the decisive factor in every published asset.
Section 4: Implementing PAL – Infrastructure and E-A-T Impact
PAL entries are stored in a secure, atomic database (e.g., Firestore) with CRHS as the document ID. Only authorized staff can modify records, and each entry is immutable once published.
E-A-T Benefits:
- Expertise: Demonstrates mastery of advanced generation techniques.
- Authority: Provides reproducible records (CRHS) and a human sign-off (HART).
- Trust: Clarifies licensing and model tiers, ensuring legal compliance.
This documentation layer sets our media apart from low-value, unverifiable content.
Conclusion: Provenance as a Pillar of Value
Ethical sourcing and verifiable provenance convert AI media from risk to competitive advantage. By enforcing the Clean Data Mandate and maintaining a complete PAL, Roman Circus ensures that every asset strengthens our E-A-T credentials.
With our policy foundation established, we are prepared to tackle the next challenge in our automation roadmap.