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Practice Questions
Test your understanding with targeted questions related to the topic.
Question 1
Easy
What does bias in machine learning refer to?
💡 Hint: Think of examples where AI might treat groups differently.
Question 2
Easy
Name one source of bias in AI.
💡 Hint: Consider the origins of the training data.
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 is the main goal of fairness in machine learning?
- To maximize accuracy
- To ensure equitable treatment among groups
- To minimize data usage
💡 Hint: Think about the societal implications of AI decisions.
Question 2
True or False: Explainable AI techniques are only necessary for highly complex models.
- True
- False
💡 Hint: Consider the importance of clarity in all AI applications.
Solve and get performance evaluation
Challenge Problems
Push your limits with challenges.
Question 1
Design a framework for ensuring fairness in an AI system used for hiring. What steps would you include?
💡 Hint: Think about each phase from data collection to system deployment.
Question 2
Analyze the potential weaknesses of relying solely on one metric like accuracy to evaluate an AI model.
💡 Hint: Consider what other metrics might provide a better understanding.
Challenge and get performance evaluation