Is this AI system ready for the real world?
A structured evaluation framework for AI-powered programs and interventions. Built from production deployment experience — translated for evaluators.
AI systems break a core evaluation assumption: same inputs don't always produce same outputs. This rubric helps you ask the right questions before deployment — and document your findings.
Evaluation Scorecard
AI System
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Pending
Dimension overview
Score by dimension
What evidence should you trust?
TIER 1
Independent benchmarks & third-party audits
External validators with no commercial interest in the result.
TIER 1
Production telemetry with statistical controls
Real-world performance data measured with rigor, not anecdote.
TIER 2
Structured red-teaming results
Adversarial testing with documented methodology and coverage.
TIER 2
Human evaluation with inter-rater reliability
Multiple reviewers, documented agreement metrics.
TIER 3
Vendor-provided benchmarks and demos
Self-reported, often cherry-picked. Useful as a starting point only.
Priority gaps
Three things to remember
Any vendor can show you their AI performing well. Ask them to show where it fails, how it fails, and what safeguards exist when it does.
A system right 85% of the time but confidently wrong 15% of the time is more dangerous than one right 80% that expresses appropriate uncertainty. Ask whether confidence levels are reported and accurate.
Require disaggregated performance metrics by relevant subgroup — with acceptable differential thresholds stated in advance of deployment, not assessed after the fact.