Recall & Review
beginner
What is responsible machine learning?
Responsible machine learning means creating and using ML models carefully to avoid mistakes and harm to people or society.
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beginner
How can ML models cause harm if not responsible?
They can make unfair decisions, invade privacy, or spread wrong information, which can hurt individuals or groups.
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intermediate
Why is fairness important in responsible ML?
Fairness ensures ML treats everyone equally and does not favor or discriminate against any group unfairly.
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intermediate
What role does transparency play in responsible ML?
Transparency means explaining how ML models make decisions so people can trust and check them.
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beginner
How does responsible ML help prevent harm?
By checking data quality, avoiding bias, protecting privacy, and testing models carefully before use.
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What is a key goal of responsible machine learning?
✗ Incorrect
Responsible ML aims to prevent harm and unfairness by careful design and use.
Which of these can cause harm if ML is not responsible?
✗ Incorrect
Bias and discrimination in ML can harm people and groups.
Transparency in ML means:
✗ Incorrect
Transparency helps users understand and trust ML decisions.
Which practice helps prevent harm in ML?
✗ Incorrect
Careful testing helps find and fix problems before harm occurs.
Fairness in ML means:
✗ Incorrect
Fairness means equal treatment without bias or discrimination.
Explain why responsible machine learning is important to prevent harm.
Think about how ML can affect people if not used carefully.
You got /4 concepts.
List key practices that help make machine learning responsible.
Consider steps to avoid mistakes and build trust.
You got /4 concepts.