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115 lines
5.7 KiB
Markdown
115 lines
5.7 KiB
Markdown
# License and Dataset Rights — Guardrails and Fix Pattern
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<details>
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<summary><strong>🧭 Quick Return to Map</strong></summary>
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<br>
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> You are in a sub-page of **Governance**.
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> To reorient, go back here:
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>
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> - [**Governance** — policy enforcement and compliance controls](./README.md)
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> - [**WFGY Global Fix Map** — main Emergency Room, 300+ structured fixes](../README.md)
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> - [**WFGY Problem Map 1.0** — 16 reproducible failure modes](../../README.md)
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>
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> Think of this page as a desk within a ward.
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> If you need the full triage and all prescriptions, return to the Emergency Room lobby.
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</details>
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This page tracks **legal and licensing risks** in AI systems.
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If datasets, embeddings, or outputs rely on unverified sources, you risk compliance violations, takedowns, or IP litigation.
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Use this guide to enforce clear rights boundaries across ingestion, training, and generation.
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---
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## When to use this page
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- You do not know the license of a dataset included in your retrieval or training pipeline.
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- Mixed rights (MIT, Apache, proprietary, unknown) exist in the same corpus.
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- Legal review requires proof that generated answers respect dataset terms.
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- Audit asks for compliance with GDPR/CCPA or publisher licensing.
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---
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## Acceptance targets
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- 100% of datasets tagged with a license identifier.
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- ≥ 95% coverage of ingestion checks include license + attribution metadata.
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- ΔS stability maintained when filtering licensed vs. non-licensed subsets.
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- Audit logs capture `license_id`, `rights_holder`, `expiry`.
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- LLM refuses or flags outputs when license terms are violated.
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---
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## Common failures → exact fixes
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| Symptom | Likely cause | Open this |
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|---------|--------------|-----------|
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| Snippets from unknown or scraped sources appear | dataset missing license metadata | [data-contracts.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/data-contracts.md) |
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| Open source corpus mixes with paid corpus | no role/rights separation | [roles_and_access_rbac_abac.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/GlobalFixMap/Governance/roles_and_access_rbac_abac.md) |
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| Model answers cite restricted publishers | no attribution enforcement | [retrieval-traceability.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/retrieval-traceability.md) |
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| Generated outputs reuse licensed patterns | prompt injection bypassing rights filter | [prompt-injection.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/prompt-injection.md) |
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| Training run includes expired or revoked dataset | missing expiry validation | [policy_baseline.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/GlobalFixMap/Governance/policy_baseline.md) |
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---
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## Fix in 60 seconds
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1. **Tag every dataset**
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Attach `{license_id, rights_holder, expiry, attribution_required}` at ingestion.
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2. **Separate corpora**
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Open source vs. proprietary vs. paid corpora must remain in distinct retrieval indices.
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3. **Enforce attribution**
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Require citation-first prompting for any licensed corpus.
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4. **Audit pipeline**
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Store logs with dataset version, license, and usage context.
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5. **Expiry enforcement**
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Block or purge expired corpora automatically.
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---
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## Minimal compliance checklist
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- [ ] Every ingestion pipeline requires license metadata.
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- [ ] RBAC + ABAC enforced to keep datasets separated.
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- [ ] Retrieval schema logs license_id with every snippet.
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- [ ] Expiry checks run nightly.
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- [ ] Audit reports exportable on request.
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---
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### 🔗 Quick-Start Downloads (60 sec)
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| Tool | Link | 3-Step Setup |
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|------|------|--------------|
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| **WFGY 1.0 PDF** | [Engine Paper](https://github.com/onestardao/WFGY/blob/main/I_am_not_lizardman/WFGY_All_Principles_Return_to_One_v1.0_PSBigBig_Public.pdf) | 1️⃣ Download · 2️⃣ Upload to your LLM · 3️⃣ Ask “Answer using WFGY + \<your question>” |
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| **TXT OS (plain-text OS)** | [TXTOS.txt](https://github.com/onestardao/WFGY/blob/main/OS/TXTOS.txt) | 1️⃣ Download · 2️⃣ Paste into any LLM chat · 3️⃣ Type “hello world” — OS boots instantly |
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---
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<!-- WFGY_FOOTER_START -->
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### Explore More
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| Layer | Page | What it’s for |
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| --- | --- | --- |
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| ⭐ Proof | [WFGY Recognition Map](/recognition/README.md) | External citations, integrations, and ecosystem proof |
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| ⚙️ Engine | [WFGY 1.0](/legacy/README.md) | Original PDF tension engine and early logic sketch (legacy reference) |
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| ⚙️ Engine | [WFGY 2.0](/core/README.md) | Production tension kernel for RAG and agent systems |
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| ⚙️ Engine | [WFGY 3.0](/TensionUniverse/EventHorizon/README.md) | TXT based Singularity tension engine (131 S class set) |
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| 🗺️ Map | [Problem Map 1.0](/ProblemMap/README.md) | Flagship 16 problem RAG failure taxonomy and fix map |
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| 🗺️ Map | [Problem Map 2.0](/ProblemMap/wfgy-rag-16-problem-map-global-debug-card.md) | Global Debug Card for RAG and agent pipeline diagnosis |
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| 🗺️ Map | [Problem Map 3.0](/ProblemMap/wfgy-ai-problem-map-troubleshooting-atlas.md) | Global AI troubleshooting atlas and failure pattern map |
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| 🧰 App | [TXT OS](/OS/README.md) | .txt semantic OS with fast bootstrap |
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| 🧰 App | [Blah Blah Blah](/OS/BlahBlahBlah/README.md) | Abstract and paradox Q&A built on TXT OS |
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| 🧰 App | [Blur Blur Blur](/OS/BlurBlurBlur/README.md) | Text to image generation with semantic control |
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| 🏡 Onboarding | [Starter Village](/StarterVillage/README.md) | Guided entry point for new users |
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If this repository helped, starring it improves discovery so more builders can find the docs and tools.
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[](https://github.com/onestardao/WFGY)
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<!-- WFGY_FOOTER_END -->
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