Practice Case Study 3: Predictive Policing and Judicial Systems – The Risk of Reinforcing Injustice - 4.2.3 | Module 7: Advanced ML Topics & Ethical Considerations (Weeks 14) | Machine Learning
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4.2.3 - Case Study 3: Predictive Policing and Judicial Systems – The Risk of Reinforcing Injustice

Learning

Practice Questions

Test your understanding with targeted questions related to the topic.

Question 1

Easy

What is predictive policing?

💡 Hint: Think about how police can use data to prevent crime.

Question 2

Easy

Define algorithmic bias.

💡 Hint: Consider what happens when data is skewed.

Practice 4 more questions and get performance evaluation

Interactive Quizzes

Engage in quick quizzes to reinforce what you've learned and check your comprehension.

Question 1

What is predictive policing primarily used for?

  • To arrest individuals
  • To forecast criminal activity
  • To train officers

💡 Hint: Consider the purpose of using data in law enforcement.

Question 2

True or False: Algorithmic bias can reinforce existing social inequalities.

  • True
  • False

💡 Hint: Think about the consequences of flawed data.

Solve and get performance evaluation

Challenge Problems

Push your limits with challenges.

Question 1

Discuss how you would design an AI system for predictive policing that minimizes bias. Consider data sources, algorithm choice, and transparency measures.

💡 Hint: Think of how to represent all communities fairly.

Question 2

Critique a hypothetical case where an algorithm recommended increased police presence based solely on historical crime data. What are the potential consequences?

💡 Hint: Consider broader societal impacts beyond immediate outcomes.

Challenge and get performance evaluation