When we think about individual outcomes we usually think about independent causal structures. A car accident happened because a person was switching their Spotify playlist and accidently ran a red light. A person stole from a grocery store because they had poor moral character which came from a poor cultural upbringing. A build-up of electrical potential from the friction of two air masses rushing past each other caused a lightning strike.
When we think about larger systems and structures we usually think about more interconnected and somewhat random outcomes that we don’t necessarily observe on a case by case basis, but instead think about in terms of likelihoods and conditions which create the possibilities for a set of events and outcomes. Increasing technological capacity in smartphones with lagging technological capacity in vehicles created a tension for drivers who wanted to stream music while operating vehicles, increasing the chances of a driver error accident. A stronger US dollar made it more profitable for companies to employ workers in other countries, leading to a decline in manufacturing jobs in US cities and people stealing food as they lost their paychecks. Earth’s tilt toward the sun led to a difference in the amount of solar energy that northern continental landmasses experienced, creating a temperature and atmospheric gradient which led to lightning producing storms and increased chances of lightning in a given region.
What I am trying to demonstrate in the two paragraphs above is a tension between thinking statistically versus thinking causally. It is easy to think causally on a case by case basis, and harder to move up the ladder to think about statistical likelihoods and larger outcomes over entire complex systems. Daniel Kahneman presents these two types of thought in his book Thinking Fast and Slow writing:
“Statistical base rates are facts about a population to which a case belongs, but they are not relevant to the individual case. Causal base rates change your view of how the individual case came to be.”
It is more satisfying for us to assign agency to a single individual than to consider that individual’s actions as being part of a large and complex system that will statistically produce a certain number of outcomes that we observe. We like easy causes, and dislike thinking about statistical likelihoods of different events.
“Statistical base rates are generally underweighted, and sometimes neglected altogether, when specific information about the case at hand is available.
Causal base rates are treated as information about the individual case and are easily combined with other case-specific information.”
The base rates that Kahneman describes can be thought of as the category or class to which we assign something. We can use different forms of base rates to support different views and opinions. Shifting the base rate from a statistical base rate to a causal base rate may change the way we think about whether a person is deserving of punishment, or aid, or indifference. It may change how we structure society, design roads, and conduct cost-benefit analyses for changing programs or technologies. Looking at the world through a limited causal base rate will give us a certain set of outcomes that might not generalize toward the rest of the world, and might cause us to make erroneous judgments about the best ways to organize ourselves to achieve the outcomes we want for society.