Practice Local - 2.2 | Explainable AI (XAI) and Model Interpretability | Artificial Intelligence Advance
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2.2 - Local

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Learning

Practice Questions

Test your understanding with targeted questions related to the topic.

Question 1

Easy

What does local interpretability mean?

💡 Hint: Think about what it means to understand a specific decision.

Question 2

Easy

Name one tool used for local interpretability.

💡 Hint: These tools make AI models more understandable.

Practice 4 more questions and get performance evaluation

Interactive Quizzes

Engage in quick quizzes to reinforce what you've learned and check your comprehension.

Question 1

What does local interpretability aim to achieve?

  • Understanding overall model performance
  • Explaining individual predictions
  • Improving model accuracy

💡 Hint: Think about what 'local' means in this context.

Question 2

True or False: SHAP provides a way to assign contributions to model predictions based on game theory.

  • True
  • False

💡 Hint: Consider what SHAP stands for.

Solve 1 more question and get performance evaluation

Challenge Problems

Push your limits with challenges.

Question 1

Given a healthcare AI model predicting patient diagnoses, design a workflow using LIME and SHAP to explain a specific prediction to a doctor. Discuss the benefits of each tool in this scenario.

💡 Hint: Think about how you'd communicate the AI's decision to someone without a technical background.

Question 2

Discuss the broader implications of local interpretability in AI for societal trust. Illustrate your answer with examples from finance or healthcare.

💡 Hint: Consider what could happen if people do not trust AI’s role in sensitive areas.

Challenge and get performance evaluation