A researcher on LessWrong is documenting a personal diary on causal discovery and model comparison. The author uses a diabetes dataset to test how variables connect. This informal exploration targets the technical gap in how AI understands causality. Practitioners can track these experiments to see how causal inference improves model interpretability.