My Top Read of the Year

“The Book of Why” is one of the most thought-provoking books I’ve read this year. Written by Judea Pearl, it delves into the concept of causality and how understanding it can revolutionize our understanding of the world and our ability to make accurate predictions.

One of the key takeaways from the book is the importance of being able to identify the true cause of an event. In many fields, including medicine and machine learning, the ability to identify cause and effect relationships is crucial to making accurate predictions and making informed decisions. In medicine, for example, being able to identify the true cause of a patient’s symptoms can lead to more effective treatments and better outcomes. Similarly, in machine learning, understanding causality allows for the creation of models that can make accurate predictions about future events.

One example the book gives is the case of a study of heart disease. For a long time, doctors believed that cholesterol was the cause of heart disease. However, it was later discovered that cholesterol is actually a symptom of heart disease, caused by other underlying factors such as genetics and lifestyle. Understanding this causal relationship led to more effective treatments for heart disease and a better understanding of the disease itself.

Another example is in the field of machine learning, where understanding causality allows for the creation of models that can make accurate predictions about future events. A model that only looks at correlation and not causality may make incorrect predictions.

Overall, The Book of Why is a must-read for anyone interested in causality and its implications in different fields, it has certainly made me think about things in a different way, and I highly recommend it to anyone looking to gain a deeper understanding of the world around them.