Practice - Critical Importance - 2.2.2
Practice Questions
Test your understanding with targeted questions
What is bias in the context of machine learning?
💡 Hint: Think about outcomes that are influenced by the training data.
Define fairness in AI systems.
💡 Hint: Consider how different demographics are impacted by AI decisions.
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Interactive Quizzes
Quick quizzes to reinforce your learning
What is the primary definition of bias in machine learning?
💡 Hint: Think about how certain groups might be systematically affected.
True or False: Transparency in AI only matters for technical users.
💡 Hint: Consider the importance of trust in technology.
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Challenge Problems
Push your limits with advanced challenges
Design a machine learning project aimed at AI hiring. Identify potential bias points from data collection to model deployment and propose strategies for mitigation.
💡 Hint: Think about the entire lifecycle of the data and the model.
Evaluate an AI's fairness in predicting loan approvals. Determine if there’s evidence of disparate impact and suggest improvements.
💡 Hint: Check if the model performs consistently across different demographic groups.
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Reference links
Supplementary resources to enhance your learning experience.