By Daniel Kahneman, The New York Times
The word “bias” commonly appears in conversations about mistaken judgments and unfortunate decisions. We use it when there is discrimination, for instance against women or in favor of Ivy League graduates. But the meaning of the word is broader: A bias is any predictable error that inclines your judgment in a particular direction. For instance, we speak of bias when forecasts of sales are consistently optimistic or investment decisions overly cautious.
Society has devoted a lot of attention to the problem of bias — and rightly so. But when it comes to mistaken judgments and unfortunate decisions, there is another type of error that attracts far less attention: noise.
To see the difference between bias and noise, consider your bathroom scale. If on average the readings it gives are too high (or too low), the scale is biased. If it shows different readings when you step on it several times in quick succession, the scale is noisy. (Cheap scales are likely to be both biased and noisy.) While bias is the average of errors, noise is their variability.