Section 184 · Companion Reference, Testing AI
Appendix: How to Read an AI Eval Report
Most eval reports look more precise than they are. Learn where the uncertainty is hiding.
read eval report
What to do
- Review eval reports like experimental evidence.
- Ask about provenance, holdouts, multiple comparisons, judge drift, dataset drift, effect size, and practical significance.
- Define runnable checks that exercise read eval report.
Evidence to preserve
- Preserve the inputs, versions, configurations, raw outcomes, and results for read eval report needed to reproduce work on Appendix: How to Read an AI Eval Report.
- Report results for read eval report by relevant slice, separate blocker failures from averages, state uncertainty and blind spots, and connect the result to a release decision.
Expert note
Review eval reports like experimental evidence. Ask about provenance, holdouts, multiple comparisons, judge drift, dataset drift, effect size, and practical significance.
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Cite this page
Jason Arbon. "Appendix: How to Read an AI Eval Report." Testing AI Knowledge Edition, section 184.
https://jarbon.ai/testing-ai/knowledge/ch184-read-eval-report.html