Practice Bias and Fairness in Algorithms - 34.5 | 34. Ethical Considerations in the Use of Automation | Robotics and Automation - Vol 3
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34.5 - Bias and Fairness in Algorithms

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Learning

Practice Questions

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

Interactive Quizzes

Engage in quick quizzes to reinforce what you've learned and check your comprehension.

Question 1

What is the main issue with algorithmic bias?

  • It results from too much data
  • It leads to unfair treatment
  • It improves decision accuracy

💡 Hint: Think about the effect of data bias.

Question 2

True or False: Using diverse datasets can help reduce bias in AI.

  • True
  • False

💡 Hint: Consider the variety of input data used.

Solve 1 more question and get performance evaluation

Challenge Problems

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