This is super interesting. Tons of people agree that machine learning needs a better grasp of causality. Something underdiscussed is that our data doesn’t gener

This is super interesting. Tons of people agree that machine learning needs a better grasp of causality. Something underdiscussed is that our data doesn’t generally include the information needed to automate causal inference and discovery in the large. It’s the reason your A/B testing framework tracks which variables were the randomization units. Most tables don’t have that kind of provenance in a machine readable structured format. After all, a DAG connecting any rows in any tables at your company is a hell of a prospect. It’s nice to read about causality tracking systems like in the article.