Practice Transparency and Explainability - 16.2.2 | 16. Ethics and Responsible AI | Data Science Advance
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Practice Questions

Test your understanding with targeted questions related to the topic.

Question 1

Easy

What is transparency in the context of AI?

💡 Hint: Think about what it means to understand the workings of a system.

Question 2

Easy

Define explainability in AI terms.

💡 Hint: Consider how you would need to understand your teacher's grading.

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 transparency in AI refer to?

  • Visibility of user data
  • Understanding the decision-making process
  • Speed of data processing

💡 Hint: Think about what it means to see inside a system.

Question 2

True or False: Explainability is unnecessary in low-stakes AI applications.

  • True
  • False

💡 Hint: Consider the importance of understanding any decision that affects you.

Solve and get performance evaluation

Challenge Problems

Push your limits with challenges.

Question 1

Analyze a scenario where an AI model made a critical decision in the healthcare sector without transparency. Discuss the potential consequences.

💡 Hint: Consider who is affected if a wrong diagnosis is made.

Question 2

Propose a method to enhance explainability in autonomous vehicle decision-making systems.

💡 Hint: Think about how you would explain a car's choices to a passenger.

Challenge and get performance evaluation