Practice Inherent Challenges (2.3.3) - Advanced ML Topics & Ethical Considerations (Weeks 14)
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Inherent Challenges

Practice - Inherent Challenges - 2.3.3

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Practice Questions

Test your understanding with targeted questions

Question 1 Easy

Define bias in the context of machine learning.

💡 Hint: Think about how historical data can influence AI decisions.

Question 2 Easy

What is accountability in AI?

💡 Hint: Consider who is responsible when an AI system makes a mistake.

4 more questions available

Interactive Quizzes

Quick quizzes to reinforce your learning

Question 1

What is bias in AI?

An improvement in model performance
A systematic prejudice leading to unfair outcomes
A measure of accuracy

💡 Hint: Consider how data can reflect societal inequalities.

Question 2

True or False: Transparency in AI helps foster public trust.

True
False

💡 Hint: Think about how clear information affects opinions.

2 more questions available

Challenge Problems

Push your limits with advanced challenges

Challenge 1 Hard

Design an AI system intended for credit scoring. Discuss the potential biases that could arise, how you would detect them, and what strategies you’d implement to mitigate them.

💡 Hint: Consider both the data sources and the algorithm choices.

Challenge 2 Hard

Given a scenario where an AI model exhibited unfair loan denial rates for a demographic group, detail an ethical analysis framework based on the ethical principles covered in this section.

💡 Hint: Reflect on the principles discussed earlier in our sessions.

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