Review: ‘The Book of Why’ Examines the Science of Cause and Effect

This lowest rung deals simply with observation — basically looking for regularities in past behavior. Professor Pearl places “present-day learning machines squarely on rung one.” While it is true that the explosion of computing power and accessible deep data sets have yielded many surprising and important results, the mechanics still operate “in much the same way that a statistician tries to fit a line to a collection of points.”

“Deep neural networks have added many layers of complexity of the fitted function, but raw data still drives the fitting process,” according to Professor Pearl. The causal revolution is what has enabled researchers to explore the higher rungs of the ladder.

The second rung of the ladder of causation moves from seeing to doing. That is, it goes from asking what happened to asking what would happen based on possible interventions. Professor Pearl notes that “many scientists have been traumatized to learn that none of the methods they learned in statistics is sufficient to articulate, let alone answer, a simple question like ‘What happens if we double the price?’” “The Book of Why” provides a detailed explanation and history of how and when a model alone can answer such questions in the absence of live experiments.

The top rung of the ladder involves something called “counterfactual” questions: What would the world be like if a different path had been taken? These are “the building blocks of moral behavior as well as scientific thought.” The ability to look backward and imagine what could have been governs our judgments on success and failure, right and wrong.

Once considered a defining characteristic of humanity, in recent decades these topics have not escaped the reach of increasingly complex modeling tools. Those tools have been applied to varied social and scientific problems, including the efficacy of medical procedures, the impact of climate change and the usefulness of social policies.