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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 about how predictions could unfairly favor one group over another.
Question 2
Easy
What does XAI stand for?
💡 Hint: Consider what this acronym seeks to accomplish in understanding AI decisions.
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 purpose of Explainable AI (XAI)?
- To improve model accuracy
- To make AI decisions understandable
- To increase data collection
- To enhance model performance
💡 Hint: Remember the effects of understanding on user confidence.
Question 2
True or False: Historical bias does not influence AI models.
- True
- False
💡 Hint: Consider how historical events shape data collection.
Solve 1 more question and get performance evaluation
Challenge Problems
Push your limits with challenges.
Question 1
Evaluate a scenario where an AI system, designed to assist with hiring, exhibits bias against certain demographic groups. Identify potential sources of bias and propose mitigation strategies.
💡 Hint: Consider the completeness of the training data and how it reflects societal inequalities.
Question 2
Consider a public health AI tool that predicts patient outcomes but shows lower accuracy for certain minority groups. Analyze the ethical implications and suggest a framework for accountability.
💡 Hint: Think about the societal consequences of unequal health outcomes and the role of transparency.
Challenge and get performance evaluation