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on human decision making. They explained that people rely on emotional shortcuts, called “heuristics,” to make choices. The more uncertainty, the more shortcuts. And the shortcuts, while very useful, lead to a slew of predictable errors. For example, in one study, they found that a majority of subjects judged a deadly flood triggered by a California earthquake to be more likely than an equally deadly flood occurring somewhere else in North America on its own. The notion of a California earthquake resonated more than the prospect of a flood—and so it was assigned a higher probability by the people in the study.

In fact, the chances of a flood occurring for some other reason is far greater. But that kind of workaday flood—the kind that kills people every year—does not trigger the same cascading series of emotional shortcuts. It is less scary for a reason, which isn’t to say that it’s rational.

At first, Kahneman and Tversky were labeled pessimists. At a time when most Americans were enchanted by technology, they had concluded that people were in fact irrational. They were attacked for exaggerating the flaws of the human brain. More than one critic pointed to the fact that man had walked on the moon. How could a species that has evolved to walk on the moon be plagued by irrationality? But their work forever altered the study of risk. In 2002, six years after Tversky’s death, Kahneman was awarded the Nobel Prize in Economics for their work.

Today, most people who study decision making agree that human beings are not rational. “We don’t go around like risk assessors—doing calculations, multiplying probabilities. That’s been disproved,” says Paul Slovic, a psychology professor at the University of Oregon and one of the world’s most respected experts on risk. Instead, people rely on two different systems: the intuitive and the analytical. The intuitive system is automatic, fast, emotional, and swayed heavily by experiences and images. The analytical system is the ego to the brain’s id: logical, contemplative, and pragmatic.

One system can override the other, depending on the situation. For example, consider this question:

A coffee and a donut cost $1.10 in total. The coffee costs $1 more than the donut. How much does the donut cost?

If your first answer was ten cents, that’s your intuitive system talking. If you then caught yourself and came to the correct answer (five cents), that’s your analytical system policing your intuition.

Notice how deft the intuitive system is! It moved at lightning speed, and if the question were a mountain lion about to lunge at your throat, it might have saved your life—or at least distracted the lion for a minute.

But it was also wrong. And this is where we come to the truth-telling moment: we all make mistakes when we judge risk. Our risk formula, especially when it comes to disasters, almost never looks this rational:

Risk = Probability × Consequence

No, if we could reduce our risk calculation to a simple formula, it might look more like this:

Risk = Probability × Consequence × Dread/Optimism

Dread. Rarely does a label used by scientists so aptly fit the emotion it describes. Think of dread as humanity in a word. It represents all of our evolutionary fears, hopes, lessons, prejudices, and distortions wrapped up in one dark X factor.

After talking about dread with risk experts, I started to imagine it as a sum of many other, powerful factors. Dread had its own equation. Each factor in the equation could raise or reduce the sensation of dread, depending on the situation. It seemed important to break dread into its parts in order to understand its imperfections. So here, with apologies to those experts for reducing their findings to a formula, is what I think the equation for dread might look like:

Dread = Uncontrollability + Unfamiliarity + Imaginability + Suffering + Scale of Destruction + Unfairness

Chances are the thing that most terrifies you is high in several of these factors. Dread explains why we fear plane crashes so much more than we fear heart disease or car