Practice Sources of Bias in AI - 16.3 | 16. Ethics and Responsible AI | Data Science Advance
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Sources of Bias in AI

16.3 - Sources of Bias in AI

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Learning

Practice Questions

Test your understanding with targeted questions

Question 1 Easy

What is historical bias in AI?

💡 Hint: Think about past societal inequalities.

Question 2 Easy

What does sampling bias mean?

💡 Hint: Consider how sampling can affect results.

4 more questions available

Interactive Quizzes

Quick quizzes to reinforce your learning

Question 1

What is historical bias?

Bias that occurs in real-time data
Bias derived from systemic inequalities in historical data
Error from human labeling

💡 Hint: Consider how past practices affect current data.

Question 2

Sampling bias occurs when:

True
False

💡 Hint: Think about whether a sample can show the whole picture.

3 more questions available

Challenge Problems

Push your limits with advanced challenges

Challenge 1 Hard

Design an AI system to provide equitable loan approvals. Discuss potential biases that could arise in data collection, model training, and outcomes.

💡 Hint: Consider each type of bias and how they could affect loan decisions.

Challenge 2 Hard

Critically analyze a real-world AI application (like facial recognition). Identify any bias issues and propose measures to mitigate these biases.

💡 Hint: Look at current controversies surrounding the application for insights.

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Reference links

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