Practice Deconstructing The Sources Of Bias: How Unfairness Enters The System (1.1)
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Deconstructing the Sources of Bias: How Unfairness Enters the System

Practice - Deconstructing the Sources of Bias: How Unfairness Enters the System

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Practice Questions

Test your understanding with targeted questions

Question 1 Easy

What is historical bias in machine learning?

💡 Hint: Think about how past hiring practices influence current models.

Question 2 Easy

Explain representation bias.

💡 Hint: Consider how diverse your training images are.

4 more questions available

Interactive Quizzes

Quick quizzes to reinforce your learning

Question 1

What is historical bias?

A. Bias in new data
B. Bias from past data
C. No bias

💡 Hint: Think about how the past influences present practices.

Question 2

True or False: Representation bias occurs when data is equally represented.

💡 Hint: Reflect on what it means for a population to be represented.

1 more question available

Challenge Problems

Push your limits with advanced challenges

Challenge 1 Hard

Develop a strategy for mitigating historical bias in a hiring algorithm using input from diverse stakeholders.

💡 Hint: Incorporate discussions with affected groups.

Challenge 2 Hard

Analyze a scenario where a healthcare AI disproportionately misdiagnoses one demographic due to measurement bias. Propose a solution.

💡 Hint: Think about adjusting how you collect data across different groups.

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Reference links

Supplementary resources to enhance your learning experience.