Crowd Within

A single estimate mixes signal with temporary noise: your current mood, framing, assumptions, and whatever happens to be salient. When you estimate again after enough time—or by a genuinely different method—some of that noise changes. Averaging the answers can then cancel errors in miniature, recreating part of the crowd advantage inside one person. The crucial ingredient is not the number of answers but their separation. If the second estimate merely repeats the first reasoning, correlated error survives the average; the benefit appears when your approaches are independent-ish enough to make different mistakes.

This is not a cure for systematic bias. If both estimates draw on the same false premise, remembered anchor, or unchanged method, averaging preserves the mistake. The Crowd Within works only to the extent that you create meaningfully different judgments—not cosmetic variations of one opinion.