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AI Observability for Trust Building
A system design approach that makes AI decision-making transparent by providing complete traceability of every output back to its source
How It Works
Every AI-generated result includes citations, source materials, and reasoning chains that humans can verify independently
Components
Implement citation systems for all data sources
Provide reasoning transparency
Enable drill-down verification
Show confidence levels and uncertainty
Allow easy correction of errors
When to Use
For high-stakes AI applications where users must trust and verify outputs, especially in finance, legal, or critical business decisions
When Not to Use
For low-stakes creative tasks where some uncertainty is acceptable, or when full traceability is technically impossible
Anti-Patterns to Avoid
Example
“A financial model shows revenue projections with clickable links to the specific pages of SEC filings where each number originated”