In my undergraduate and graduate studies I had a few statistics classes and I remember the challenge of learning probability. Probability, odds, and statistics are not always easy to understand and interpret. There are some concepts that are pretty straightforward, and others that seem to contradict what we would expect if we had not gone through the math and if we had not studied the concepts in depth. To contrast the difficult and sometimes counter-intuitive nature of statistics, we can think about causality, which is a challenging concept, but unlike statistics, is something we are able to intuit from very young age.
In The Book of Why Judea Pearl writes, “In both a cognitive and a philosophical sense, the idea of cause and effect is much more fundamental than probability. We begin learning causes and effects before we understand language and before we understand mathematics.”
As Pearl explains, we see causality naturally and experience causality as we move through our lives. From a young child who learns that if they cry they receive attention to a nuclear physicist who learns what happens when two atoms collide at high energy levels, our minds are constantly looking at the world and looking for causes. It begins by making observations of phenomena around us and continues as we predict what outcomes would happen based on certain system inputs. Eventually, our minds reach a point where we can understand why our predictions are accurate or inaccurate, and we can imagine new ways to bring about certain outcomes. Even if we cannot explain all of this, we can still understand causation at a fundamental and intuitive level.
However, many of us deny that we can see and understand the world in a causal way. I am personally guilty of thinking in a purely statistical way and ignoring the causal. The classes I took in college helped me understand statistics and probability, but also told me not to trust my intuitive causal thinking. Books like Kahneman’s Thinking Fast and Slow cemented this mindset for me. Rationality, we believe, requires that we think statistically and discount our intuitions for fear of bias. Modern science says we can only trust evidence when it is backed by randomized controlled trials and directs us to think of the world through correlations and statistical relationships, not through a lens of causality.
Pearl pushes back against this notion. By arguing that causality is fundamental to the human mind, he implies that our causal reasoning can and should be trusted. Throughout the book he demonstrates that a purely statistical way of thinking leaves us falling short of the knowledge we really need to improve the world. He demonstrates that complex tactics to remove variables from equations in statistical methods are often unnecessary, and that we can accept the results of experiments and interventions even when they are not fully randomized controlled trials. For much of human history our causal thinking nature has lead us astray, but I think that Pearl argues that we have overcorrected in modern statistics and science, and that we need to return to our causal roots to move forward and solve problems that statistics tells us are impossible to solve.