How do I establish document provenance and trust scoring for RAG sources?
To establish document provenance and trust scoring for RAG sources, organizations should maintain an inventory of AI systems and their data flows, and implement policies for tracking provenance of third-party models, datasets, and tools.
Organizations should implement the following controls:
- NIST-GOVERN-6.1 requires policies to address risks from third-party models, datasets, and tools, including tracking provenance. This cross-maps to OWASP LLM03/LLM05 (supply chain).
- NIST-MAP-1.5 mandates maintaining a current inventory of AI/agent systems, which includes models, agents, tools, and data flows. This is foundational for governing AI systems.
- NIST-MEASURE-2.8 specifies that mechanisms must exist to log decisions and trace AI behavior. This can be implemented by logging every AI decision with structured data.
- NIST-MEASURE-3.1 requires approaches for tracking identified and emergent risks over time, such as monitoring and logging. This cross-maps to ISO/IEC 42001 monitoring.
The provided sources do not explicitly detail methods for "trust scoring" of RAG sources, beyond general risk tracking and provenance.
- nist_ai_rmf
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