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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Bias and Fairness in Algorithms

34.5 - Bias and Fairness in Algorithms

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Learning

Practice Questions

Test your understanding with targeted questions

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.

4 more questions available

Interactive Quizzes

Quick quizzes to reinforce your learning

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.

1 more question available

Challenge Problems

Push your limits with advanced challenges

Challenge 1 Hard

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.

Challenge 2 Hard

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.

Get performance evaluation

Reference links

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