Bayesian Updating
Start from a base rate, update incrementally on evidence in proportion to how diagnostic it is; the best forecasters do this and most people either ignore the prior or over-react to the latest data point.
An everyday example
A single glowing reference moving a hiring decision from 30% to 90%.
What it can cost you
Over-updating on vivid evidence, under-updating on dull evidence, and being fed evidence designed to move you.
Warning signs
- One fact flipped my view.
- I had no starting estimate.
One thing to do
For any new fact ask two questions: how likely is this if I am right, and how likely if I am wrong? Move only by the ratio.
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