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Test your understanding with targeted questions related to the topic.
Question 1
Easy
Define fairness in the context of AI.
💡 Hint: Think about how AI decisions should treat everyone equally.
Question 2
Easy
What is data bias?
💡 Hint: Consider how the data used differs across populations.
Practice 4 more questions and get performance evaluation
Engage in quick quizzes to reinforce what you've learned and check your comprehension.
Question 1
What is fairness in AI?
💡 Hint: Think about fairness in the context of social justice.
Question 2
True or False: Fairness only applies to the data used in AI systems.
💡 Hint: Consider the different stages of AI processes.
Solve and get performance evaluation
Push your limits with challenges.
Question 1
Design a set of evaluation metrics to determine fairness in a predictive policing algorithm. What risks might your metrics overlook?
💡 Hint: Think about all the groups affected and how metrics capture their experiences.
Question 2
Discuss the implications of deploying an AI system that lacks fairness measures within healthcare. What might the consequences be?
💡 Hint: Consider the impact on treatment outcomes and overall equality.
Challenge and get performance evaluation