#1490

Mentioned in 16 episodes

The Book of Why

The New Science of Cause and Effect

Book • 2018

Dana Mackenzie Judea Pearl

In 'The Book of Why', Judea Pearl and Dana Mackenzie delve into the causal revolution, which has transformed the way we distinguish between correlation and causation.

The book introduces causal diagrams, such as Directed Acyclic Graphs (DAGs), and explains how to predict the effects of interventions.

It addresses fundamental questions about causality and its implications in fields like medicine, economics, and artificial intelligence.

The authors also discuss the potential of causal inference in enabling computers to understand counterfactuals and engage in moral decision-making.

Mentioned by

Sean M. Carroll

Robert Usazuwa Ness

Konrad Körding

Massimo Chiriatti

Paul Hünermund

Andrew Lawrence

Hugo Bowne-Anderson

Pierpaolo Hipolito

Mentioned in 16 episodes

Mentioned by

Tim Scarfe

in a discussion about causality and its role in understanding the world.

Dr. Thomas Parr - Active Inference Book

Mentioned by

George Hotz

in the context of counterfactuals and their importance in autonomous driving.

George Hotz: Comma.ai, OpenPilot, and Autonomous Vehicles

Menzionato da

Massimo Chiriatti

per la sua analisi del rapporto causa-effetto.

Umano INCOSCIENTE, Macchina INTELLIGENTE? Cogitata sul Futuro - con Massimo Chiriatti

Mentioned by

Sean M. Carroll

as a popular book from 2018 explaining the new science of cause and effect.

196 | Judea Pearl on Cause and Effect

Mentioned by Eric Topol as containing great examples of causation and correlation.

Adam Kucharski: The Uncertain Science of Certainty

Mentioned by

Robert Usazuwa Ness

as being the inspiration for his book, “Causal AI”.

909: Causal AI, with Dr. Robert Usazuwa Ness

Mentioned by Steve Sloman as a popular book containing ideas from 'Causality'.

The True Cost of Conviction

Recommended by

Lex Fridman

as an accessible book presenting key ideas from a lifetime of work.

Judea Pearl: Causal Reasoning, Counterfactuals, Bayesian Networks, and the Path to AGI

Mentioned by

Paul Hünermund

as a book that drives home the importance of causal inference.

Causal inference

Mentioned by

Helge Tennø

in relation to causal diagrams and understanding relationships between data points.

#114 - Bringing Customers Back to the Heart of Business - with Helge Tennø

Mentioned by

Andrew Lawrence

as a narrative book that puts causality concepts into context.

Causal AI, Modularity & Learning || Andrew Lawrence || Causal Bandits Ep. 002 (2023)

Mentioned by

Hugo Bowne-Anderson

as a recommended resource for learning about causal inference.

Episode 12: Your Machine Learning Solves The Wrong Problem

Mentioned by

Paul Hünermund

as a book that created a lot of attention in the industry about causal AI and causal machine learning techniques.

#168 Causal AI in Business with Paul Hünermund, Assistant Professor, Copenhagen Business School

Mentioned by

Robert Ness

as inspiration for writing his book on causal AI.

#137 Causal AI & Generative Models, with Robert Ness

Mentioned by

Chris Wiggins

when discussing causal inference.

Episode 7: What Lies Beyond Machine Learning and AI: Decision Systems and the Future of Data Teams

Mentioned by

Jill Nephew

, referencing an unnamed woman whose work on causality was unrecognized.

PUBLIC SHADOW #2 w/ Jill Nephew

Recommended by

Konrad Körding

as an accessible introduction to causal inference.

469: Learning Deep Learning Together

Mentioned by

Curt Jaimungal

as an author of a book on causation, with some objections from

Tim Maudlin

.

Tim Maudlin on Quantum Realism, Bell's Theorem, Pilot Wave, and Interpretations of Quantum Mechanics

Mentioned by

Pierpaolo Hipolito

as a good starting point for understanding causal reasoning and paradoxes in data science.

Navigating Common Pitfalls in Data Science: Lessons from Pierpaolo Hipolito - ML 183

Recommended by

Gary Marcus

as a resource for understanding causal reasoning in AI.

Rebooting AI: What's Missing, What's Next with Gary Marcus - TWIML Talk #298

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