3.1 - Fairness
Enroll to start learning
You’ve not yet enrolled in this course. Please enroll for free to listen to audio lessons, classroom podcasts and take practice test.
Practice Questions
Test your understanding with targeted questions
Define fairness in the context of AI.
💡 Hint: Think about how AI decisions should treat everyone equally.
What is data bias?
💡 Hint: Consider how the data used differs across populations.
4 more questions available
Interactive Quizzes
Quick quizzes to reinforce your learning
What is fairness in AI?
💡 Hint: Think about fairness in the context of social justice.
True or False: Fairness only applies to the data used in AI systems.
💡 Hint: Consider the different stages of AI processes.
Get performance evaluation
Challenge Problems
Push your limits with advanced challenges
Design a set of evaluation metrics to determine fairness in a predictive policing algorithm. What risks might your metrics overlook?
💡 Hint: Think about all the groups affected and how metrics capture their experiences.
Discuss the implications of deploying an AI system that lacks fairness measures within healthcare. What might the consequences be?
💡 Hint: Consider the impact on treatment outcomes and overall equality.
Get performance evaluation
Reference links
Supplementary resources to enhance your learning experience.