How to make better predictions

Over the weekend I argued that people are really quite good at making predictions, when you zoom out and think of all the various ways we do so in science and in everyday life. Talk about how “predictions are hard, especially about the future” tends to concentrate on a narrow band of particularly difficult topics.

But even in those cases there are ways to improve your ability to predict the future. The classic book on the subject is Phil Tetlock’s Expert Political Judgment which I recommend. And if you want the short version, and happen to have a subscription to The Financial Times you’re in luck: Tim Harford’s latest column there gives a useful summary of Tetlock’s research.

His early research basically uncovered the role of personality in forecasting accuracy. More open-minded thinkers — prone to caution and the appreciation of uncertainty, who tended to weigh multiple mental models about how the world work against each other — make more accurate predictions than other people. (They still fail to do better than even simple algorithms.)

I’ll excerpt just the last bit, which focuses on Tetlock’s latest project, an ongoing forecasting tournament (I’m participating in the current round; it’s a lot of fun and quite difficult). Here’s the nickel summary of how to be a better forecaster, beyond cultivating open-mindedness:

How to be a superforecaster

Some participants in the Good Judgment Project were given advice on how to transform their knowledge about the world into a probabilistic forecast – and this training, while brief, led to a sharp improvement in forecasting performance.

The advice, a few pages in total, was summarised with the acronym CHAMP:

● Comparisons are important: use relevant comparisons as a starting point;

● Historical trends can help: look at history unless you have a strong reason to expect change;

● Average opinions: experts disagree, so find out what they think and pick a midpoint;

● Mathematical models: when model-based predictions are available, you should take them into account;

● Predictable biases exist and can be allowed for. Don’t let your hopes influence your forecasts, for example; don’t stubbornly cling to old forecasts in the face of news.