Practice Federated Learning (6.2) - AI Ethics, Bias, and Responsible AI

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10 questions

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

Question 1.
What is federated learning?
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Think about where data is stored.
Question 2.
Why is data privacy important in federated learning?
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Consider the risks of data breaches.
3Question 3.
What does federated learning primarily aim to protect?
- Data privacy
- Model accuracy
- Computation speed
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Think about what stays on the device.
4Question 4.
True or False: In federated learning, data needs to be centralized for model training.
- True
- False
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Recall how federated learning operates.
Question 5.
Suppose a healthcare provider uses federated learning but faces data imbalance across its hospitals. Propose a solution to this issue.
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Consider methods that can help offset data discrepancies.
Question 6.
A mobile app implements federated learning for predictive typing but detects skewed predictions. What steps would you suggest to address this skew?
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Think about diversity in the datasets contributing to the model.

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