Practice Week 14: Ethics In Ml & Model Interpretability (7.1) - Advanced ML Topics & Ethical Considerations (Weeks 14)
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Week 14: Ethics in ML & Model Interpretability

Practice - Week 14: Ethics in ML & Model Interpretability

Learning

Practice Questions

Test your understanding with targeted questions

Question 1 Easy

What is bias in machine learning?

💡 Hint: Think about societal influences in training data.

Question 2 Easy

Define fairness in AI systems.

💡 Hint: Relate back to how AI affects different people.

4 more questions available

Interactive Quizzes

Quick quizzes to reinforce your learning

Question 1

What does bias in machine learning refer to?

Reflecting societal norms
Accuracy of predictions
All of the above

💡 Hint: Consider the various influences on data.

Question 2

Is transparency important in AI systems?

True
False

💡 Hint: Think about the stakeholders involved.

1 more question available

Challenge Problems

Push your limits with advanced challenges

Challenge 1 Hard

Discuss how you would establish accountability and transparency in an AI system used for job recruitment, considering potential biases.

💡 Hint: Think about who is affected and how trust can be fostered.

Challenge 2 Hard

Evaluate the trade-offs between privacy and model accuracy in healthcare AI applications.

💡 Hint: How can both aspects coexist?

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Reference links

Supplementary resources to enhance your learning experience.