Practice Data Bias (2.2) - AI Ethics, Bias, and Responsible AI

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10 questions

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3 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
4 questions · about 3 min · pass mark 70%. Hints available.
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6 sample questions

Question 1.
What is data bias?
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Think about how data might not represent everyone equally.
Question 2.
Give an example of underrepresentation bias.
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Consider groups that might be missing from datasets.
3Question 3.
What is data bias?
- Skewed data
- All data
- Data with no bias
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Focus on the meaning of bias.
4Question 4.
True or False: Labeling bias can occur if annotators have different opinions.
- True
- False
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Think about how judgment can vary.
Question 5.
Identify a modern AI application that showcases the impact of data bias. Discuss how data bias can be mitigated in such applications.
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Investigate real-life instances of AI applications and the criticisms they have faced.
Question 6.
Design a framework for evaluating bias in a new AI project. What factors would you consider?
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Think about different stakeholder perspectives and the ethical implications of AI.

6 more questions in this section. Enroll free to practise them all.