Causal Inference in Fairness

Causal inference in fairness involves understanding how a specific factor, like race or gender, directly influences an outcome, such as hiring or lending decisions. Instead of just observing correlations, it seeks to identify whether and how a group's characteristic actually causes differences in results. This helps distinguish genuine biases from unrelated factors, ensuring fairness by addressing the root causes of disparities. By clarifying cause-and-effect relationships, causal inference enables the development of policies and systems that promote equitable treatment for all individuals.