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Case file

Automation Bias

Filed under
Not Enough Meaning

The charge

Automation bias is trusting automated output too much and neglecting contrary evidence or obvious context.


How it operates

Machine recommendations feel objective and reduce effort, so scrutiny drops and override behavior weakens.

Logged incidents

  1. Incident 01

    A recruiter accepts resume-screening output despite a clearly strong portfolio.

  2. Incident 02

    A fraud team lets good customers churn because the model flags them.

  3. Incident 03

    A PM trusts a dashboard trend that is actually caused by a tracking bug.

What to watch for

Ask: What would I conclude if the system gave no recommendation at all?

Recommended action

Keep a human in the loop with override checklists and track false positives and false negatives.

Known associates

Source of record

en.wikipedia.org

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