Group and Individual Fairness
Explore the concepts of group and individual fairness in AI to understand how bias affects different populations. Learn about the challenges in defining fairness for groups versus individuals and why both approaches matter in creating fair AI systems. This lesson helps you recognize fairness trade-offs and the complexities in evaluating protected attributes, aiming to equip you with a foundation for measuring and addressing bias in AI models.
We'll cover the following...
Group vs. individual fairness
Many of us experience a phenomenon called collective responsibility. It is a situation when the inappropriate behavior of even a single member of a group causes punishment for the entire group. It is natural to consider it profoundly unjust. But wait, so far, we have discussed fairness in the context of groups. Does it mean we fall into this trap? The meaning of fairness for a group and an individual can differ. There is ongoing discussion if there is a trade-off between them or if they can be achieved simultaneously.