False Negative

A false negative occurs when a test, detector, review, or decision process reports no relevant condition even though the condition is present. A security scanner misses a vulnerability; a health check reports healthy while the user path is broken; an interview process rejects a capable candidate because the sample did not expose their ability.

Interview relevance

False negatives matter when absence of evidence is treated as evidence of absence. Reducing them can require broader sampling, better labels, repeated measurement, or a second detection path. Those changes may increase false positives, cost, or review load.

The acceptable balance depends on consequence. Missing a catastrophic condition may justify expensive review, while a low-impact detector may reasonably favor fewer interruptions. State whose harm is counted when selecting the threshold.

Useful test

Define the ground truth, then examine known positive cases that the process failed to detect. Report the miss rate by meaningful segment rather than only as one aggregate number; rare or high-impact segments can disappear inside a healthy average.