Automation and human oversight
Define meaningful human control over AI-supported work.
Covered in this guide
- Identify high-impact and ambiguous decisions.
- Define the human reviewer's evidence and authority.
- Monitor automation error and unequal impact.
Human oversight is meaningful only when the reviewer can understand the relevant evidence, disagree with the system and change the outcome. A ceremonial approval step is not enough.
Oversight has to be able to disagree
Human oversight is meaningful only when the reviewer can understand the relevant evidence, disagree with the system and change the outcome. A ceremonial approval step is not enough.
A reviewer who could only click approve
An automated system ranks scholarship applications, and reviewers see only a score and an “approve” button.
Try this
Identify the minimum controls required for responsible review.
Review answer guidance
Reviewers need the criteria, source data, material limitations and reasons for the recommendation; authority and time to override it; bias and error monitoring; an audit record; and an accessible route for applicant correction or appeal.
What ‘human in the loop’ means here
Say what the human can actually see, change and be accountable for. If they cannot inspect the evidence, the oversight is decorative.