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Fundamentals of AI Fairness

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1.Introduction to AI Fairness

What Is AI Fairness and Why It Matters?Real-Life Examples Formal Definition and Fairness in Regulations

2.Motivating Example

Credit Scoring Problem Building a Model Is the Model Fair?Challenge: Fairness through Unawareness Quiz on German Scoring Problem

3.Measuring Fairness

Protected Attributes Space University Example Simpson’s Paradox Group and Individual Fairness A Quick Recap of Common Metrics Demographic Parity Predictive Parity Equality of Opportunity Equalized Odds Effect of Threshold Selection Quiz: Fairness Metrics

Mini Project

Project: Fix Bias Using Threshold Optimization

4.Mitigation Methods

Data vs. Model Bias Introduction to Mitigation Methods More on Threshold Optimization Reweighing Reductions Adversarial Debiasing Other Methods and Summary Quiz: Mitigating Bias

Mini Project

Project: Make a Fair Classifier

5.Fairness in Natural Language Processing

Word Embeddings Biased Vectors Debiasing Vectors Word Embedding Association Test Data Augmentation Quiz: Fairness in NLP

Mini Project

Project: Explore Fairness in NLP Models

6.Conclusion

Summary and Next Steps

Assessment

Check Your Knowledge About Fair AI

Fundamentals of AI Fairness

Project: Explore Fairness in NLP Models

In this project, we will explore fairness in NLP classification tasks. This time, we will not train any model; instead, we will analyze the behavior of existing models.