Causal Inference Skill

"Current deep learning is System 1: fast, intuitive, but easily fooled. We need System 2: slow, deliberate, causal." — Yoshua Bengio

Overview

Causal inference enables:

1. Interventional reasoning: What happens if I do X?
2. Counterfactual reasoning: What would have happened if...?
3. Transfer: Causal structure generalizes across domains
4. Robustness: Causal models resist distribution shift

Pearl's Causal Hierarchy

Level 3: Counterfactual (Imagining)
  "What would have happened if I had done X?"
  P(y_x | x', y')