TLDR Tech / Design
One AI Output is an Example, Not an Evaluation
A single AI output only demonstrates a system can perform a task once—it cannot show how reliably that performance holds across different situations. Rigorous evaluation, much like quantitative UX research, requires testing multiple representative inputs across repeated runs, then reporting averages with confidence intervals to capture both test-input and run-to-run variability. Systems with identical overall scores can fail in very different ways—consistently on specific inputs versus unpredictably across all inputs—so understanding failure patterns matters as much as the aggregate score itself.
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