reviewing-ai-output-groundedness

Human review protocol for whether AI output is grounded in its sources: claim-by-claim attribution, hallucination classes, citation verification, sampling that is defensible, and a recorded attestation because groundedness cannot be fully automated. Also covers the responsible-AI pass - harmful output, bias, disclosure and privacy. Use when checking whether RAG answers or summaries are supported by the retrieved documents, when factuality matters more than fluency, or when an eval suite needs the human check it cannot replace.