Translation Tutorial - Causal Fairness Analysis

Explore the critical intersection of causality and fairness in AI through this comprehensive tutorial presented by Elias Bareinboim from Columbia University at FAccT 2021. Delve into the challenges faced by AI systems and understand the importance of causal reasoning in addressing fairness issues. Learn about structural causal models, causal diagrams, and their applications through practical examples. Examine demographic disparities and potential responses using thought experiments. Gain valuable insights into causal fairness analysis, equipping yourself with essential knowledge to tackle ethical concerns in AI development and implementation.

Introduction
Challenges AI faces
Why causality matters
Outline
Structural causal model
Causal diagram
Example
Structural model
Questions
Demographic disparities
Potential response
Thought experiment