Judgment under Uncertainty: Heuristics and Biases (Anchoring)
Amos Tversky & Daniel Kahneman · 1974
"When estimating an unknown quantity, people rely heavily on the first number they're exposed to, the anchor, and adjust insufficiently away from it — even when that anchor is arbitrary, irrelevant, or explicitly randomly generated."
In one of the paper's experiments, participants spun a wheel rigged to land on either 10 or 65, then were asked to estimate the percentage of African countries in the United Nations. Despite knowing the wheel was random, people who saw 65 gave estimates almost double those who saw 10 — the arbitrary number contaminated an unrelated factual judgment.
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Judgment under Uncertainty: Heuristics and Biases (Availability)
"People estimate how frequent or likely something is by how easily examples come to mind — which means vivid, recent, or heavily-reported events get judged as far more common than they actually are, while common but unremarkable events get systematically underestimated."