Causal Artificial Intelligence

CHAPTER 1Setting the Stage for Causal AI

The ability to understand information in the context of solving complex problems is not new. From the earliest days of artificial intelligence, scientists and mathematicians have tried to find new ways to understand the world through models and data. The promise of artificial intelligence (AI) is to reach the point where machines could think and provide answers to some of the most challenging problems of our world. There are a huge number of sophisticated analytics tools that provide significant help in understanding what has occurred in the past and predict a possible future from that data. However, one element that has been missing from the analyses is understanding the cause and effect of the observed and unobserved interactions. The dynamic of understanding why events happen and what can be done to change the outcomes is the power and opportunity of causal AI. This chapter will put causal AI in perspective and set the stage for our exploration of the evolution of the field of AI.

Why Causality Is a Game Changer

Why is there a sudden explosion in interest in causal AI? The answer is both complex and simple. Causal AI enables us to move beyond the predictive modeling capabilities of traditional AI to understand and predict causal relationships between variables in a system. Here are some of the most salient topics that outline the value of causal AI:

• Understanding causality: Traditional AI models can make predictions based on observed ...