Discussing

The Causal Revolution as the Summit of Scientific-Technological-Industrial Revolutions

Judea Pearl is the author of The Book of Why: The New Science of Cause and Effect lead Causal Revolution. He is also the recipient of the 2020 World Leader in AI World Society and leads the section Modern Causal Inference of AIWS.net.   It is common...

Can Bayesian Networks provide answers when Machine Learning comes up short? It’s a question of probabilities

Machine Learning gets all the marketing hype, but are we overlooking Bayesian Networks? Here’s a deeper look at why “Bayes Nets” are underrated – especially when it comes to addressing probability and causality. In commercial...

Why machine learning struggles with causality

When you look at the following short video sequence, you can make inferences about causal relations between different elements. For instance, you can see the bat and the baseball player’s arm moving in unison, but you also know that it is the player’s...

The Domestication of Causal Reasoning

1. Introduction On Wednesday December 23 I had the honor of participating in “AI Debate 2”, a symposium organized by Montreal AI, which brought together an impressive group of scholars to discuss the future of AI. I spoke on “The Domestication...

Causally Colored Reflections on Leo Breiman’s “Statistical Modeling: The Two Cultures” (2001) https://projecteuclid.org/download/pdf_1/euclid.ss/1009213726

Enticed by a recent seminar on this subject, I have re-read Breiman’s influential paper and would like to share with readers a re-assessment of its contributions to the art of statistical modeling. When the paper first appeared, in 2001, I had the impression...

Radical Empiricism and Machine Learning Research

A speaker at a lecture that I have attended recently summarized the philosophy of machine learning this way: “All knowledge comes from observed data, some from direct sensory experience and some from indirect experience, transmitted to us either culturally...

Data versus Science: Contesting the Soul of Data-Science

SummaryThe post below is written for the upcoming Spanish translation of The Book of Why, which was announced today. It expresses my firm belief that the current data-fitting direction taken by “Data Science” is temporary (read my lips!), that the...

Race, COVID Mortality, and Simpson’s Paradox (by Dana Mackenzie)

Summary This post reports on the presence of Simpson’s paradox in the latest CDC data on coronavirus. At first glance, the data may seem to support the notion that coronavirus is especially dangerous to white, non-Hispanic people. However, when we take...

Artificial intelligence: The dark matter of computer vision

What makes us humans so good at making sense of visual data? That’s a question that has preoccupied artificial intelligence and computer vision scientists for decades. Efforts at reproducing the capabilities of human vision have so far yielded results...