Practice Ethical Considerations in Deep Learning - 8.10 | 8. Deep Learning and Neural Networks | Data Science Advance
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Practice Questions

Test your understanding with targeted questions related to the topic.

Question 1

Easy

What is bias in training data?

💡 Hint: Consider how historical biases might persist in data.

Question 2

Easy

Why is model explainability important?

💡 Hint: Think of situations where understanding AI decisions is critical.

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 can bias in training data lead to?

  • Fair outcomes
  • Unfair outcomes
  • Balanced decisions

💡 Hint: Remember how historical data might affect future decisions.

Question 2

Is model explainability important for trust?

  • True
  • False

💡 Hint: Consider the consequences of not understanding decisions.

Solve 1 more question and get performance evaluation

Challenge Problems

Push your limits with challenges.

Question 1

Discuss how a biased AI model in healthcare could lead to potential harm.

💡 Hint: Consider scenarios involving misdiagnoses or unequal healthcare access.

Question 2

Evaluate the efforts several tech companies have made to reduce their carbon footprints in AI.

💡 Hint: Research recent sustainability reports from major tech firms.

Challenge and get performance evaluation