This article is an excerpt from the Shortform book guide to "Superforecasting" by Philip E. Tetlock. Shortform has the world's best summaries and analyses of books you should be reading.
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What is probabilistic thinking? How do probabilistic thinkers approach problems differently from an average person?
Probabilistic thinking is essentially an approach to predicting an outcome of a situation or the likelihood of a future event. Most people tend to estimate probabilities in terms of “yes” or “no” options. In contrast, probabilistic thinkers think in terms of percentages.
Keep reading to learn about the psychology of probabilistic thinking.
What Is Probabilistic Thinking?
If you were asked to predict whether a certain event would happen in the future, you’d probably respond with one of three answers: yes, no, or maybe. Most people’s mental “probability dial” has three distinct settings. By contrast, probabilistic thinkers have an unlimited number of settings. They’re more likely to answer questions in terms of percentages rather than “yes” or “no.”
The Two- (or Three-) Setting Dial
There is a good reason that most of us are not natural probabilistic thinkers. For most of human history, the three-setting dial was reduced even further to two settings (“yes” or “no”). For our ancestors, this was an advantage. Early humans lived in a world where predators were a constant threat—but our brains and bodies aren’t designed for perpetual vigilance, and stress wears us down over time. Snap judgments became an evolutionary life hack: While the probabilistic thinkers were fretting over the likelihood that a strange noise came from a predator, the concrete thinkers had already landed on an answer and responded accordingly.
Whether there is a real threat present or not, a correct guess has a distinct advantage. If the sound did come from a predator, the concrete thinkers have more time to prepare to fight or flee; If the sound didn’t come from a predator, they can lay back, relax, and conserve the cognitive resources their probabilistic peers spend on worrying. Even a false positive is relatively harmless. Only in the case of a miss (there is a predator, but you decide there isn’t) would the concrete thinkers be in trouble.
But what about “maybe”? For life-or-death decisions, “maybe” is not particularly helpful. Most of us use “maybe” as a last resort, only when the odds are roughly even and the stakes are low. The uncertainty that comes with a “maybe” answer is intuitively unsettling, possibly because we have evolved to associate uncertainty with danger. We settle for maybe only when we’re forced to—usually for probabilities roughly between 40% and 60%. Anything higher is “yes,” anything lower is “no.”
Does this sound wrong or overly reductive? There’s a reason for that. We do much better when we encounter probabilities as abstractions (random numbers with no context, like the 40% and 60% in the paragraph above). But in real-life situations, most of us revert to that intuitive two-setting dial. For example, when you check the weather forecast and see “80% chance of rain,” do you think about the 20% chance of clear skies? Or do you grab your umbrella and carry on with your day assuming that it will rain?
Probabilistic Thinking and Uncertainty
Human minds crave certainty. Uncertainty creates anxiety—somewhere deep in the brain, we still interpret uncertainty as the chance that a lion is right behind us. Researchers have tested this by asking parents how much they would hypothetically pay for a treatment that would reduce their child’s risk of contracting a serious illness from 10% to 5% or from 5% to 0%. Even though the reduction is the same magnitude for both cases, parents were willing to pay up to three times more to reduce the risk from 5% to 0%. Certainty is priceless.
The problem is that certainty is also very rare. Few things have either a 0% or 100% chance of happening. But claims of certainty are common and powerfully compelling. If someone claims that something will definitely happen or that a treatment will definitely work, we equate that confidence with accuracy (there is a small positive correlation between the two, but we estimate it to be much larger). This means we’re much more likely to trust confident people—but because certainty is so rare, they’re also much more likely to be wrong.
This skewed perspective impacts the way we think about science. Many people think of science as the ultimate pillar of truth and that scientific facts are facts, full stop. In this worldview, scientists are the ultimate heroes in the fight against uncertainty. We tend to forget that at one point, the scientific community was certain the Earth was flat.
(Scientists themselves are partly to blame here, as they often do speak in terms of certainties. They can do this because, among scientists, there is a general understanding that “this is fact” should be taken to mean “this is the conclusion that the evidence supports, but there is still a tiny possibility that it could be wrong.” But among laypeople, the word “fact” means an absolute truth.)
Two- and three-setting mental dials helped our species survive into the modern era, and they are still helpful when snap decisions are necessary. But thankfully, most of the judgments we make on a daily basis are not immediate, life-or-death decisions. For everything else, the most accurate answer is “maybe.” This is where probabilistic thinkers shine—they see “maybe” not as an answer in itself but as an infinite range of possible answers.
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