Causal Artificial Intelligence

CHAPTER 2Understanding the Valueof Causal AI

One of the purposes of this book is to review the foundational aspects of causal AI and to explore and explain why causal AI is important for business leaders, subject-matter experts, data scientists, and analytics professionals to understand the value of this important evolution the field of AI. While causal AI is a technically sophisticated approach, it will have profound implications for making better business decisions. Casual AI helps managers and leaders understand how to analyze the primary causes of a problem, the effects of those factors on outcomes, and the options available to solve perplexing problems in the most efficient and effective manner possible.

In this chapter, we will discuss the principles of causal AI, its origins, and how it has evolved through improvements in infrastructure, networks, languages, data, and analytics. At this stage of development in causal AI, we have the ability to create sophisticated models and methods that can help organizations drive value from large and diverse data sets. This emerging approach is focused on understanding the cause and effect of problems and coming up with ways to transform how businesses can continue to improve outcomes.

Defining Causal AI

Judea Pearl, the father of causal inference, summed up the power of causality in his seminal book Causality: Models, Reasoning, and Inference:

The next revolution will be even more impactful upon realizing that data science is ...