Preface

A Short Introduction to the Book!!

Background

Our introduction towards the topic of Causal inference and causal reasoning came from a class the both of us took together in the Summer of 2020. The class was based around working on various research topics rotating around the overall idea of Computational Skepticism.

Both of us decided to focus on the research topic of Causal Inference. We had initially thought that we would be able to bring up something novel in the field and started working with that goal in our heads. However, as we kept going through our literature survey we realized we had a massive task on our hands. Most of the literature on Causal Inference is so incredibly diverse and spread out into so many different fields that it was taking us a really long time to even grasp some of the basic concepts of Causal inference as a whole.

This is when we decided to switch paths. We decided that before we go about building something novel in the area of Causal Inference we had to compile all our learnings into one place so that it is much easier for us to refer back to in the future. Doing this would also allow us to help through this compilation of other lone wanderers who decide to step into this vast forest of Causal Inference.

Initially, both of us started documenting our understanding and experimentation in the world of Causal Inference in the form of medium articles and Google collab notebooks. Once we covered more ground, we started putting in all our findings and resources in the form of this book.

Most part of this book contains non-technical Language considering that most problems and difficulties in the field of Artificial Intelligence are more conceptual in nature.

The Goal

The goal of this book is to help anyone with the interest of exploring what causal inference is and bring them up to speed with what the current "State of The Art" is just through this one resource. We want to show how Causal Inference is not a different path towards Artificial Intelligence but an important aspect of the same pipeline that involves statistical inferences.

We hope that this book can serve as an introduction to the importance of Causal thinking in the field of Artificial Intelligence and some relevant concepts of Causal Inference!!

The Audience:

We try to target the audience which is beginning to learn about Causal Inference. This book will give you an overview starting from the origin of the field to the implementation of causal inference in the industry. The book will give you a pretty good introduction to causal Inference, which can give you a pretty good opening to the world of causality.

Pre-Requisites

• Knowledge about concepts of Artificial Intelligence and Machine Learning Models

• Understanding of Probabilistic and statistical Theories

• Interest in understanding Causal Inference.