AI Response Analysis becomes most useful when different verification techniques are combined into a single workflow. In this handout, we will use domain knowledge to identify vague concepts, hidden variables and suspicious causal claims, then apply inter-response consistency to test whether the model maintains the same position under paraphrases and cross-aspect questions.
We will continue with retrospective verification, making criteria, assumptions, conditions and measurable indicators explicit, and finally use cross-checking to compare the claims with external evidence such as accessibility guidelines, analytics, usability tests and comparative experiments. The process concludes by rewriting the original response with a degree of certainty proportionate to the evidence obtained.
Response Analysis: Example
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