Practice Fairness In Ai (12.2.1) - Ethics and Bias in AI

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8 questions

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

Question 1.
What does fairness in AI mean?
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Think about race and gender.
Question 2.
Give an example of biased training data.
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Consider data from past hiring practices.
3Question 3.
What is a key objective of fairness in AI?
- To maximize profit
- To ensure impartial decision-making
- To simplify algorithms
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Think about the definitions we discussed.
4Question 4.
True or False: Biased training data can negatively affect AI outcomes.
- True
- False
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Consider the impact of discriminatory data.
Question 5.
Design an AI system for hiring that mitigates biases. Describe the data sources you would use and how you would ensure fairness.
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Think about including data that represents various genders and ethnicities.
Question 6.
Critique a form of AI used in social media for content moderation. Identify potential biases in training data and suggest improvements.
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Reflect on past moderation decisions that weren’t inclusive.

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