Practice Security and Robustness - 16.2.5 | 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 are adversarial examples?

💡 Hint: Think of what kind of inputs could mislead an AI.

Question 2

Easy

Define data poisoning in AI.

💡 Hint: Consider how changing data inputs affects outcomes.

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 an adversarial example?

  • A type of model training
  • An input designed to confuse AI
  • A data management technique

💡 Hint: Think about how some inputs might not reflect reality.

Question 2

True or False: Model inversion attacks can reveal sensitive information from a model.

  • True
  • False

💡 Hint: Consider what attackers can learn through querying.

Solve 1 more question and get performance evaluation

Challenge Problems

Push your limits with challenges.

Question 1

How would you design a system that can robustly detect and mitigate adversarial attacks before deployment?

💡 Hint: Think about multiple layers of security and testing.

Question 2

Propose a research study to analyze the impact of data poisoning on AI decision-making in healthcare.

💡 Hint: Consider ethics as well when manipulating sensitive data.

Challenge and get performance evaluation