Prediction is hard, especially about the future. And despite the importance people and organizations lay on having a clear view of the future, we're not very good at prediction. The authors, Tetlock and Gardner, argue that the state of prediction is similar to the state of medicine, before randomized clinical trials. Sometime forecasters are right, but mostly they're wrong, and there's no way to separate the potentially useful treatments from quackish nonsense.

But there might be a better way. Superforecasters is a write up of the authors' Good Judgement Project, an IARPA (Intelligence Advanced Research Projects Agency) effort to systemically study predictions. The Good Judgement Project smoked the competition, including in-agency experts and prediction markets. Tetlock and Gardner used their background in psychology to find out what made their top 2%, the titular superforecasters, tick better than everyone else.

The first finding is that most of us are astonishingly bad at prediction. Generally, people have three settings for probability: impossible, certain, and maybe. Kahneman's System 1, the intuitive rush to judgment, is terrible at complex problems. Perhaps the biggest step is to slow down, and engage System 2, the rational and logical side of the mind. Beyond that, people with ideological blinders are lousy predictors. If everything has to fit into Marxist dialectics, or the immortal science of Friedman-Hayek Thought, you'll overlook evidence that contradicts the theory.

The Good Judgement project provide some necessary structure. Instead of weasel words (most of, highly likely) and vague timelines (in the near future), participants are given clear factual statements with a definite endpoint. There are thousands of predictions, and participants are allowed to update their initial assessments as they do more research.

Superforecasters are adept at seeing a problem in numerous ways, rather that focusing on grand theories. They tend to be comfortable with statistics. Participants in The Good Judgement Project self-selected as more intelligent and better educated than the population at large, but superforecasters aren't notably smarter or more credentialed than their less accurate peers. Instead, they have a bulldog tendency towards research, an ability to question their own assumptions, update beliefs, and think inside-out and outside-in.

Superforecasting is a fascinating and very useful book for anyone who is thinking about the future.