Review AI interview summaries for people risk
Decide how to handle an AI-generated people summary that may overstate evidence.
The risky move is letting a confident label outrun the interview evidence. The AI summary labels the candidate as lacking ownership, but Laila has not checked the transcript or rubric. What should she do? Trace the label to the transcript and rubric, remove it if unsupported, and ask the panel lead for second review if it affects the decision. Correct. Human-impact AI work needs provenance, hallucination checks, and four-eyes review when the claim changes an outcome. Keep the label because AI summaries are meant to synthesize patterns across messy interview notes. Weaker. Synthesis is useful only when grounded. Unsupported people…
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