Superforecasting: The Art and Science of Prediction

“always predict no change” or “predict the recent rate of change.” Still,

commanders were to tell subordinates what their goal is but not how to achieve it.

There is also dress-to-impress forecasting

The rate of the development of science is not the rate at which you make observations alone but, much more important, the rate at which you create new things to test.

No model captures the richness of human nature. Models are supposed to simplify things, which is why even the best are flawed. But they’re necessary. Our minds are full of models. We couldn’t function without them. And we often function pretty well because some of our models are decent approximations of reality. “All models are wrong,” the statisti

future accurately, but that’s often not the goal, or at least not the sole goal. Sometimes forecasts are meant to entertain.

But there’s a much bigger collaboration I’d like to see. It would be the Holy Grail of my research program: using forecasting tournaments to depolarize unnecessarily polarized policy debates and make us collectively smarter.

aggregating the judgments of an equal number of people who know lots about lots of different things is most effective because the collective pool of information becomes much bigger.

he created a database containing hundreds of information sources—from the New York Times to obscure blogs—that are tagged by their ideological orientation, subject matter, and geographical origin, then wrote a program that selects what he should read next using criteria that emphasize diversity.

System 1 comes first. It is fast and constantly running in the background. If a question is asked and you instantly know the answer, it sprang from System 1. System 2 is charged with interrogating that answer. Does it stand up to scrutiny? Is it backed by evidence?