Build an interactive application that audits decisions made with AI assistance by separating evidence, assumptions, recommendations, and final human choices.
Users can enter a decision, upload supporting documents, paste AI-generated recommendations, and record the final outcome.
The application must:
Extract individual factual claims from the recommendation and link each claim to available supporting evidence.
Classify claims as supported, contradicted, unverified, or not objectively verifiable from the supplied material.
Identify recommendations that rely on assumptions not explicitly acknowledged.
Detect when the reasoning does not logically support the proposed conclusion.
Record the human decision, rejected alternatives, and reasons for accepting or overriding the AI recommendation.
Track later outcomes and compare them with the original expectations.
Generate a decision audit report with evidence gaps, unresolved contradictions, and lessons for future decisions.
Create a claim-evidence graph, review queue, decision timeline, and exportable audit package.
Do not treat confidence expressed by an AI model as proof. Preserve source passages, distinguish factual verification from logical analysis, and never fabricate evidence. Make every finding reviewable by a human before it becomes part of the permanent record.
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