Recall & Review
beginner
What is governance in the context of ML systems?
Governance in ML means setting clear rules and processes to manage how models are built, tested, and used to ensure they work well and fairly.
Click to reveal answer
beginner
How does governance help build trust in ML systems?
Governance ensures transparency, fairness, and accountability, so users and stakeholders can trust the ML system's decisions.
Click to reveal answer
beginner
Name one key component of ML governance.
One key component is monitoring model performance continuously to catch errors or bias early.
Click to reveal answer
beginner
Why is transparency important in ML governance?
Transparency means showing how models make decisions, which helps users understand and trust the system.
Click to reveal answer
beginner
What role does accountability play in ML governance?
Accountability means someone is responsible for the ML system’s outcomes, making sure problems are fixed quickly.
Click to reveal answer
What does ML governance primarily aim to improve?
✗ Incorrect
ML governance focuses on trust and reliability by managing how models are built and used.
Which of these is NOT a part of ML governance?
✗ Incorrect
Random data deletion is not part of governance; governance requires careful data management.
Why is continuous monitoring important in ML governance?
✗ Incorrect
Monitoring helps detect problems early, keeping the model trustworthy.
What does transparency in ML governance help with?
✗ Incorrect
Transparency helps users see how the model works, building trust.
Who is responsible for fixing problems in ML systems under governance?
✗ Incorrect
Governance assigns responsibility to a person or team to fix issues.
Explain how governance builds trust in ML systems.
Think about how rules and checks make people feel confident about a system.
You got /5 concepts.
Describe the key components of ML governance and their roles.
Consider what makes a system trustworthy and fair.
You got /4 concepts.