Why

Chapter 10. Onward

Why causality now?

The need for causality

Thousands of years after Aristotle’s seminal work on causality, hundreds of years after Hume gave us two definitions of it, and decades after automated inference became a possibility through powerful new computers, causality is still an unsolved problem. Humans are prone to seeing causality where it does not exist and our algorithms aren’t foolproof. Even worse, once we find a cause it’s still hard to use this information to prevent or produce an outcome because of limits on what information we can collect and how we can understand it. After looking at all the cases where methods haven’t worked and researchers and policy makers have gotten causality really wrong, you might wonder why you should bother.

After all, we are no longer restricted to small experiments where we must systematically change one thing at a time to uncover how a system works. We now have large-scale data on people’s shopping habits, medical records, and activities, all in a digital format. You likely carry an accelerometer and GPS with you everywhere you go in the form of a cellphone, and your online activities are tracked in a variety of ways. The nature of the Web, the spread of electronic medical records, and the ubiquity of sensors have enabled the generation of more data on more activities by more people than ever before. With so much raw material, maybe it does not matter why something works. According to some, we can mine the data for correlations ...