Responsible AI

Lesson goals

• Risk identification before release
• Testing diverse groups and contexts
• Documentation and monitoring

Core idea

Safety, fairness, transparency, and accountability across the lifecycle.

1. Risk identification before release: understand it in context, identify inputs and outputs, and define how the result will be verified.

2. Testing diverse groups and contexts: understand it in context, identify inputs and outputs, and define how the result will be verified.

3. Documentation and monitoring: understand it in context, identify inputs and outputs, and define how the result will be verified.

Practical example

Consider a real application of “Responsible AI.” Start small, identify available data, and compare the system with a clear baseline before expanding it.

Check your understanding

1. Explain “Responsible AI” in your own words.
2. Give one appropriate and one misleading application.
3. What risk or limitation should be monitored?