Transparency, bias, and human oversight
On This Lesson 4 topics
This lesson is planned. The outline below lists the topics it will cover. The full lesson has not been published yet.
In this lesson
design controls for explainability, fairness, and human involvement.
Planned topics
- Transparency: tell people when they are dealing with AI and how decisions can be challenged.
- Bias: evaluate quality across groups and languages and monitor after launch.
- Human oversight: a trained person can review, override, and stop the system; avoid rubber stamping.
- An appeal path is needed wherever a decision affects people materially.
Draft outline details
Demonstration
a flow for an automated decision: model proposes, human reviews the cases above a risk threshold, decision logged, the affected party notified with an appeal route.
Check your understanding
What is the weakness of human oversight that only clicks "approve"?
Show answer
It is rubber stamping; the reviewer needs information, time, and authority to override.
Practice
Apply this lesson with the module's lab, exercises and quiz.
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