Judgment Under Uncertainty: Heuristics and Biases, Studies and Experiments
Standing
Concerns Key Finding
Currently States Tversky and Kahneman identified three heuristics underlying judgment under uncertainty: representativeness, judging probability by how closely something resembles a prototype or stereotype; availability, judging frequency or probability by how easily examples come to mind; and anchoring and adjustment, estimating an unknown quantity by starting from an initial value and adjusting insufficiently away from it. Each heuristic is usually economical and effective but can produce large, systematic biases in specific, predictable circumstances.
That people rely on representativeness, availability and anchoring when judging under uncertainty, and that this reliance produces systematic, predictable deviations from formal probability in specific circumstances, is not itself disputed. What is genuinely contested, most prominently by Gerd Gigerenzer's ecological-rationality program, is whether those deviations are correctly described as biases against a single normative standard of rationality, or as heuristics that are well adapted to real-world information environments; see the dissent recorded on this fact.
Source Wikipedia: Heuristics in Judgment and Decision-Making