Discussing

Impede the Motion of Data and You Impede Innovation

The original article can be found here. Impede the Motion of Data and You Impede Innovation by Ravi Naik Why that is, and what to do about it. Data drives innovation. At scale, innovation does not happen in isolation. Without finely tuned, smartly orchestrated...

Professor Judea Pearl’s tweets

Glad you asked. I have been in this business for 3 decades and have not found anything clearer, more rigorous or friendlier than Chapter 4 of Primer. Here is a free link https://t.co/Sf5yw328zl. Enjoy, and don't let the mystics tell you counterfacuals...

Tweets by Judea Pearl

Tweets by yudapearl

Causal Inference in Machine Learning

Ricardo Silva Department of Statistical Science and Centre for Computational Statistics and Machine Learning [email protected]   Researchers reviewed 47 nutrition studies and concluded that children and adolescents who ate breakfast had better...

Causal inference in AI

Causal inference in AI refers to the process of drawing a conclusion based on the causal connection amongst the conditions of the occurrence of an effect. The main goal of causal inference is to analyze the response of the effect variable when the cause...

Causal inference without graphs

In a recent posting on this blog, Elias and Bryant described how graphical methods can help decide if a pseudo-randomized variable, Z, qualifies as an instrumental variable, namely, if it satisfies the exogeneity and exclusion requirements associated...

A Crash Course in Good and Bad Control

Carlos Cinelli, Andrew Forney and Judea Pearl Introduction If you were trained in traditional regression pedagogy, chances are that you have heard about the problem of “bad controls”. The problem arises when we need to decide whether the addition...

Lord’s Paradox: The Power of Causal Thinking

Background This post aims to provide further insight to readers of “Book of Why” (BOW) (Pearl and Mackenzie, 2018) on Lord’s paradox and the simple way this decades-old paradox was resolved when cast in causal language. To recap, Lord’s paradox...

Graphical Models and Instrumental Variables

At the request of readers, we re-post below a previous comment from Bryant and Elias (2014) concerning the use of graphical models for determining whether a variable is a valid IV. Dear Conrad,Following your exchange with Judea, we would like to present...