Practice Types of Bias - 16.3.1 | 16. Ethics and Responsible AI | Data Science Advance
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Types of Bias

16.3.1 - Types of Bias

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Practice Questions

Test your understanding with targeted questions

Question 1 Easy

Define historical bias in the context of AI.

💡 Hint: Think about how past inequalities can influence current predictions.

Question 2 Easy

What is sampling bias?

💡 Hint: Consider the consequences of only choosing certain demographics.

4 more questions available

Interactive Quizzes

Quick quizzes to reinforce your learning

Question 1

What is an example of historical bias?

A) Data from multiple sources
B) Salary data showing gender wage gaps
C) Randomly selected survey participants

💡 Hint: Think about how past data can impact current decision-making.

Question 2

True or False: Sampling bias occurs when training data represents the entire target population well.

True
False

💡 Hint: Focus on the impact of population representation.

1 more question available

Challenge Problems

Push your limits with advanced challenges

Challenge 1 Hard

Evaluate how an algorithm might be biased if it's primarily trained on data from one gender. Discuss the potential consequences.

💡 Hint: Consider societal implications and where bias may impact leaders.

Challenge 2 Hard

Critique an AI system used for law enforcement. How could measurement bias manifest in its algorithms, and what would be the implications?

💡 Hint: Think about how data integrity and accuracy are crucial.

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