Guessing and Predicting
Guessing an unknown past fact and forecasting a future event both require estimates from incomplete information. Taleb uses the comparison to warn against expressing more certainty than the evidence supports.
THE IDEA
Guessing and Predicting
There is no effective difference between my guessing a variable that is not random, but for which my information is partial or deficient, such as the number of lovers who transited through the bed of Catherine II of Russia, and predicting a random one, like tomorrow’s unemployment rate or next year’s stock market. In this sense, guessing (what I don’t know, but what someone else may know) and predicting (what has not taken place yet) are the same thing.
To further appreciate the connection between guessing and predicting, assume that instead of trying to gauge the number of lovers of Catherine of Russia, you are estimating the less interesting but, for some, more important question of the population growth for the next century, the stockmarket returns, the social-security deficit, the price of oil, the results of your great-uncle’s estate sale, or the environmental conditions of Brazil two decades from now. Or, if you are the publisher of Yevgenia Krasnova’s book, you may need to produce an estimate of the possible future sales. Both kinds of estimate can sound more certain than the available information warrants.
When to use it
When estimating the potential sales of a new product, recognize that your guess is subject to the same biases as forecasting the stock market.
In historical research, treat estimates of past events with the same caution as predictions of future trends.
When evaluating expert predictions, consider that professionals may be overconfident due to their domain knowledge.
FROM THEORY TO EVERYDAY LIFE
In practice
Guessing the number of Catherine II's lovers
Estimating the number of lovers of Catherine II is a guess about a fixed but unknown past fact, similar to predicting a future variable like tomorrow's unemployment rate.
Forecasting book sales
A publisher estimating future sales of a book must confront the same cognitive biases as someone guessing a historical fact.
A MOMENT TO REFLECT
Put it to work.
Think of a time you made a prediction about the future. What biases influenced your estimate?
How might you treat a guess about a past event and a prediction about the future as equivalent in terms of uncertainty?
How could you compare a professional forecast with a simple baseline to assess whether expertise improves its accuracy?
CONTINUE THE CONVERSATION
Source texts
- The Black Swan The Impact of the Highly Improbable With a new section On Robustness and Fragility (Nassim Nicholas Taleb)