That's why the climatologists had been using vague language about probability—they didn't feel they could draw on the rigorous language of percentages to describe what were essentially subjective judgments. At issue was our intuitive distinction between two kinds of probability, which might be described as "statistical" and "subjective." We might say, in the statistical sense, that the chance of rolling snake eyes on a pair of dice is about 3 percent; subjective probabilities, by contrast, come into play whenever we make a personal judgment based on available evidence. On Sunday morning I used my marginal knowledge of football to determine that the Bears would win the Super Bowl. Jurors use courtroom testimony to decide how likely it is that a defendant is guilty of a crime. And climatologists use scientific evidence to decide how likely it is that we're heating up the Earth.
We haven't always been hung up on distinguishing between statistical judgments of chance and subjective ones. In the 18th century, magistrates were expected to assess the probability of a defendant's guilt by calculating the sum of the testimony against him. Meanwhile, a tribunal that convicted by a 2-to-1 margin could be taken to imply that the verdict had a 67 percent chance of being correct. The elements of probability weren't teased apart until 1837, when Siméon-Denis Poisson divided it into the dual concepts of statistical frequency (called "chance") and subjective judgment (sometimes referred to as "raison de croire").
Poisson's distinction has persisted, more or less, until today. In general, we use numbers and percentages when we're talking about statistical probability, and we use phrases like "doubtful" or "almost certain" when we're talking about subjective judgments. That doesn't mean you can't quantify belief. In fact, most of us have a pretty consistent intuition about how the language of uncertainty relates to numerical values. According to a famous study from 1990, if you ask people to translate the phrase likely or probable into a percentage, most will give a number between 63 percent and 78 percent. Very likely yields a rating of 80 percent to 90 percent. Something that's certain is 98 percent or 99 percent.
But further research revealed that these meanings are stable only when the words are presented without context. In a report on climate change, by contrast, there's no reliable way to know if one policy-maker will ascribe the same percentage to the word likely as another.
That's where the uncertainty cops come in. They tell the scientists to turn their opinions—as the best-informed experts in the world—into numbers. The process of mapping judgments to percentages has two immediate benefits. First, there's no ambiguity of meaning; politicians and journalists aren't left to make their own judgments about the state of the science on climate change. Second, a consistent use of terms makes it possible to see the uptick in scientific confidence from one report to the next; since 2001, we've gone from "likely" to "very likely," and from 66 percent to 90 percent.
But the new rhetoric of uncertainty has another effect—one that provides less clarity instead of more. By tagging subjective judgments with percent values, the climatologists erode the long-standing distinction between chance and raison de croire. As we read the report, we're likely to assume that a number represents a degree of statistical certainty, rather than an expert's confidence in his or her opinion. We're misled by our traditional understanding of percentages and their scientific meaning.
The uncertainty cops argue that in the face of global warming—and the spin campaign to discredit it—we must do whatever it takes to boost the credibility of the experts. If the public is more inclined to believe in percentages, then the experts should give them percentages. It's a reasonable argument and one that could help us to address the precipitous rise in greenhouse-gas emissions. But we have to acknowledge that the new headline-grabbing rhetoric of climate change has elements of propaganda. However valid its conclusions, the report toys with our intuitions about science—that a number is more precise than a word, that a statistic is more accurate than a belief.