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Test your understanding with targeted questions related to the topic.
Question 1
Easy
What is algorithmic bias?
💡 Hint: Think about how data influences AI decisions.
Question 2
Easy
Name one way to reduce algorithmic bias.
💡 Hint: Consider types of data used in training.
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 the main issue with algorithmic bias?
💡 Hint: Think about the effect of data bias.
Question 2
True or False: Using diverse datasets can help reduce bias in AI.
💡 Hint: Consider the variety of input data used.
Solve 1 more question and get performance evaluation
Push your limits with challenges.
Question 1
Evaluate a real-world AI application in terms of its risk of algorithmic bias. Propose improvements.
💡 Hint: Identify cases like facial recognition systems and their downsides.
Question 2
Design a bias-detection algorithm for a new AI product focused on recruitment. What metrics will you use, and how will you implement it?
💡 Hint: Consider tracking hiring rates across demographics.
Challenge and get performance evaluation