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Code Issues Projects Releases Packages Wiki Activity Actions 93

fix: rewrite Article 14 section and fix Mermaid node shapes

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Address Greptile review:
- P1: Article 14 table incorrectly mapped automated controls as human
  oversight. Rewritten to clarify that guardrails are Art 9/15 controls,
  not Art 14 human oversight. New table shows actual Art 14 requirements.
- P2: Consistent stadium/pill shapes for all provider nodes in diagram.
This commit is contained in:
Bipin Rimal 2026-03-23 11:07:19 +05:45
parent 067988ac24
commit 6a6ef5751b
1 changed files with 18 additions and 17 deletions
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35
docs/my-website/docs/eu-ai-act-compliance.md
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@ -52,15 +52,15 @@ graph LR
LiteLLM -->|routed request| Anthropic([Anthropic API])
LiteLLM -->|routed request| OpenAI([OpenAI API])
LiteLLM -->|routed request| Google([Google GenAI])
LiteLLM -->|routed request| Bedrock{{AWS Bedrock}}
LiteLLM -->|routed request| VertexAI{{GCP Vertex AI}}
LiteLLM -->|routed request| Azure{{Azure OpenAI}}
LiteLLM -->|routed request| Bedrock([AWS Bedrock])
LiteLLM -->|routed request| VertexAI([GCP Vertex AI])
LiteLLM -->|routed request| Azure([Azure OpenAI])
Anthropic -->|response| LiteLLM
OpenAI -->|response| LiteLLM
Google -->|response| LiteLLM
Bedrock -->|response| LiteLLM
VertexAI -->|response| LiteLLM
Azure -->|response| LiteLLM
Bedrock -->|response| LiteLLM
VertexAI -->|response| LiteLLM
Azure -->|response| LiteLLM
LiteLLM -->|response| APP
classDef processor fill:#60a5fa,stroke:#1e40af,color:#000
@ -140,19 +140,20 @@ What you need to add:
## Article 14: Human oversight
LiteLLM's guardrails feature provides a foundation for human oversight:
Article 14 requires high-risk AI systems to be designed so that natural persons can effectively oversee them: interpret outputs, decide not to use them, and intervene or halt the system. This means human actors in the loop, not automated controls.
| Guardrails Feature | Article 14 Mapping |
|-------------------|-------------------|
| Content moderation | Pre-response filtering for harmful content |
| Rate limiting | Prevents runaway AI usage |
| Budget controls | Cost caps per user/team/organization |
| Model access controls | Restricts which models specific users can access |
LiteLLM's guardrails (content moderation, rate limiting, budget controls, model access controls) are **automated technical controls** that fall under Articles 9 (risk management) and 15 (accuracy/robustness). They are useful infrastructure, but they do not satisfy Article 14 on their own.
What you need to add:
- Escalation procedures when guardrails trigger
- Human review pipeline for high-stakes decisions
- Override mechanism to halt AI responses
What you need to build for Article 14 compliance:
| Requirement | What it means | LiteLLM foundation |
|-------------|---------------|-------------------|
| Human interpretation of outputs | A person can review what the AI produced before it acts | Logged responses via callbacks |
| Decision not to use output | A person can reject an AI recommendation | Requires your application layer |
| Intervention / halt | A person can stop the system mid-operation | Guardrails trigger points can route to human review |
| Escalation procedures | When automated filters flag content, a human reviews | Callback hooks available; escalation logic is yours |
LiteLLM provides the **logging and hook infrastructure** to build human oversight on top of. The oversight logic itself — review queues, approval workflows, kill switches — lives in your application layer.
## GDPR considerations