Causal Inference Part 1: Causation and Correlation

tabularasa8931@gmail.com (Han) — Sat, 22 Nov 2025 00:00:00 +0000

Most of the time when we say “my model learned something,” what it actually learned is a bunch of very smart correlations. If users who click A also tend to click B, or if certain pixels tend to appear together in cat photos, our models will happily latch onto those patterns and exploit them. That’s powerful—and often enough for prediction—but it’s not the same as understanding what would happen if we actually changed something in the world: raised a price, changed a policy, or shipped a new feature.

Causal Inference on Han's XYZ

Causal Inference Part 1: Causation and Correlation