Practice Algorithmic Bias (Optimization Bias / Inductive Bias) - 1.1.5 | Module 7: Advanced ML Topics & Ethical Considerations (Weeks 14) | Machine Learning
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1.1.5 - Algorithmic Bias (Optimization Bias / Inductive Bias)

Learning

Practice Questions

Test your understanding with targeted questions related to the topic.

Question 1

Easy

What is algorithmic bias?

πŸ’‘ Hint: Think about discrimination in decisions made by AI.

Question 2

Easy

Define historical bias.

πŸ’‘ Hint: Consider how society's past influences 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

Algorithmic bias leads to A) Fair outcomes B) Unfair discrimination C) Increased diversity

  • A
  • B
  • C

πŸ’‘ Hint: Think about how bias affects fairness.

Question 2

True or False: Historical bias can directly influence the performance of AI models.

  • True
  • False

πŸ’‘ Hint: Consider past inequalities when thinking about the data.

Solve 1 more question and get performance evaluation

Challenge Problems

Push your limits with challenges.

Question 1

Create a detailed strategy for mitigating algorithmic bias in a healthcare AI system.

πŸ’‘ Hint: Consider the various stages of model development and deployment.

Question 2

Analyze how a specific AI system's design choices might lead to unintended biases.

πŸ’‘ Hint: Evaluate choices that prioritize performance metrics ideally.

Challenge and get performance evaluation