Practice Ethical Considerations In Deep Learning (8.10)

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9 questions

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5 cards from this section. Quick, good the night before a test.
Exercise
6 questions · about 4 min · pass mark 70%. Hints available.
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Quiz
3 questions · about 2 min · pass mark 70%. Hints available.
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6 sample questions

Question 1.
What is bias in training data?
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Consider how historical biases might persist in data.
Question 2.
Why is model explainability important?
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Think of situations where understanding AI decisions is critical.
3Question 3.
What can bias in training data lead to?
- Fair outcomes
- Unfair outcomes
- Balanced decisions
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Remember how historical data might affect future decisions.
4Question 4.
Is model explainability important for trust?
- True
- False
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Consider the consequences of not understanding decisions.
Question 5.
Discuss how a biased AI model in healthcare could lead to potential harm.
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Consider scenarios involving misdiagnoses or unequal healthcare access.
Question 6.
Evaluate the efforts several tech companies have made to reduce their carbon footprints in AI.
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Research recent sustainability reports from major tech firms.

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