Human oversight mechanisms that let a qualified reviewer: Which design-stage control most directly satisfies
Human oversight is the design-stage control that lets a person meaningfully review and override system outputs before they take effect.
The question
While applying design best practices to an AI system that recommends loan approvals, the team wants to build in a control ensuring a person can meaningfully review and override system outputs before they take effect. Which design-stage control most directly satisfies this need?
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- Human oversight mechanisms that let a qualified reviewer interpret, question and override the system's recommendations before decisions take effect. ✓Correct: designing human oversight so a person can meaningfully review and override outputs is exactly the control the requirement describes.
- Data minimization rules that restrict the system to the smallest set of personal attributes strictly necessary for producing a single recommendation.Plausible but wrong: data minimization is a valid design practice for privacy but does not provide reviewer override of outputs.
- Metric and threshold evaluation that defines the accuracy and error levels the model must reach before it is permitted to enter production.Plausible but wrong: setting performance thresholds governs model quality, not a person's ability to review and override individual decisions.
- Operational access controls that limit which staff can deploy new model versions into the live recommendation environment after testing.Plausible but wrong: deployment access control secures release, but it does not enable meaningful human review of the system's recommendations.
The trap
Believing other good design practices (minimization, thresholds, access control) satisfy a human-oversight requirement. How to remember it
Human oversight is the design-stage control that lets a person meaningfully review and override system outputs before they take effect.
How many of these would you get right?
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