Practice Accountability, Transparency, and Privacy in AI: Foundational Ethical Pillars - 2 | Module 7: Advanced ML Topics & Ethical Considerations (Weeks 14) | Machine Learning
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2 - Accountability, Transparency, and Privacy in AI: Foundational Ethical Pillars

Learning

Practice Questions

Test your understanding with targeted questions related to the topic.

Question 1

Easy

Define accountability in the context of AI. Why is it important?

πŸ’‘ Hint: Think about who is responsible when AI makes mistakes.

Question 2

Easy

What does transparency in AI involve?

πŸ’‘ Hint: How can transparency build trust in AI?

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 is the primary purpose of accountability in AI?

  • To build trust
  • To design more efficient algorithms
  • To create complex models

πŸ’‘ Hint: Think about why stakeholders need to feel secure about AI's use.

Question 2

True or False: Transparency makes AI's decision-making process completely understandable to everyone.

  • True
  • False

πŸ’‘ Hint: Consider the complexity of AI systems.

Solve 1 more question and get performance evaluation

Challenge Problems

Push your limits with challenges.

Question 1

Consider a scenario where an AI system in a healthcare setting results in misdiagnosis due to biased data. Analyze the accountability involved and propose possible preventive measures.

πŸ’‘ Hint: Consider how each participant in the AI lifecycle contributes to accountability.

Question 2

An AI used for financial transactions exploits users' data resulting in privacy breaches. Evaluate the implications and suggest strategies to address this issue.

πŸ’‘ Hint: Think about how organizations can safeguard privacy while deploying AI.

Challenge and get performance evaluation