Judgment under Uncertainty¶
Tversky, A., & Kahneman, D. (1974). Judgment under Uncertainty: Heuristics and Biases. Science, 185(4157), 1124-1131.
Cited by¶
23 citations across 23 artifacts.
Each citation links to the sentence it supports in the citing article.
Primes¶
- Anchoring
- Anchoring is the systematic influence of an initial numerical value or reference point on subsequent judgments, evaluations, and decisions, such that final answers are drawn toward the anchor stimulus even when the anchor is arbitrary, uninformative, or explicitly disclosed as irrelevant.
This sourceFounding paper of the heuristics-and-biases program; Section on adjustment-and-anchoring reports the wheel-of-fortune experiment (spinner landing on 10 vs. 65; median UN-Africa estimates 25% vs. 45%) and names anchoring as a systematic judgment bias.
Supported in partVerified against the publisher's abstract
The abstract backs anchoring as an adjustment heuristic that yields systematic, predictable errors, but describes it as used when a relevant value is available, not for arbitrary or disclosed-irrelevant anchors.
“adjustment from an anchor, which is usually employed in numerical prediction when a relevant value is available. These heuristics are highly economical and usually effective, but they lead to systematic and predictable errors.”
- Anchoring is the systematic influence of an initial numerical value or reference point on subsequent judgments, evaluations, and decisions, such that final answers are drawn toward the anchor stimulus even when the anchor is arbitrary, uninformative, or explicitly disclosed as irrelevant.
- Belief Formation
- It enables path-sensitivity analysis: the process is path-dependent (order and framing of inputs shifts the final belief even with the same total evidence), so the reasoner can predict that two agents exposed to the same evidence in different sequences will end up at different posteriors — a finding Tversky and Kahneman (1974) embedded in their analysis of anchoring and order effects on judgment under uncertainty.
This sourceDocuments representativeness, availability, and anchoring-and-adjustment as systematic departures from coherent probabilistic reasoning.
Supported in partVerified against the publisher's abstract
The abstract confirms the 1974 paper documents anchoring-and-adjustment as a heuristic yielding systematic, predictable errors in judgment under uncertainty, but says nothing about evidence order producing different posteriors.
“adjustment from an anchor, which is usually employed in numerical prediction when a relevant value is available. These heuristics are highly economical and usually effective, but they lead to systematic and predictable errors.”
- It enables path-sensitivity analysis: the process is path-dependent (order and framing of inputs shifts the final belief even with the same total evidence), so the reasoner can predict that two agents exposed to the same evidence in different sequences will end up at different posteriors — a finding Tversky and Kahneman (1974) embedded in their analysis of anchoring and order effects on judgment under uncertainty.
- Bias
- These are not random errors; they push judgment the same way across people and occasions.
This sourceFounding paper of the heuristics-and-biases program; documents representativeness, availability, and anchoring as systematic, reproducible departures from coherent probabilistic reasoning (including base-rate neglect) — directional distortions that push judgment the same way across people and occasions.
Supported in partVerified against the publisher's abstract
The abstract states the heuristics 'lead to systematic and predictable errors', which backs the non-random half of the claim but not its 'same way across people and occasions' clause.
“These heuristics are highly economical and usually effective, but they lead to systematic and predictable errors.”
- These are not random errors; they push judgment the same way across people and occasions.
- Bounded Rationality
- Confirmation Bias
- .
This sourceFounding heuristics-and-biases paper documenting representativeness, availability, and anchoring as systematic DEPARTURES from coherent probabilistic reasoning. Does NOT establish that confirmation behavior is rational Bayesian updating — it is a non-supporting (indeed contrary) anchor for the specific T5 claim it sits on (see non-supporting flag).
- .
- Heuristic
- Cognitive heuristics canonical triad.
This sourceFounding paper of the heuristics-and-biases program; documents representativeness, availability, and anchoring as systematic departures from coherent probabilistic reasoning, including base-rate neglect and inverse-fallacy errors.
SupportedVerified against the publisher's abstract
The paper describes "three heuristics that are employed in making judgments under uncertainty": representativeness, used in judging whether an object or event belongs to a class or process; availability of instances or scenarios, used in assessing the frequency of a class or the plausibility of a development; and adjustment from an anchor, used in numerical prediction. Those three are the canonical triad the sentence names.
“This article described three heuristics that are employed in making judgments under uncertainty: (i) representativeness, which is usually employed when people are asked to judge the probability that an object or event A belongs to class or process B; (ii) availability of instances or scenarios, which is often employed when people are asked to assess the frequency of a class or the plausibility of a particular …”
- Cognitive heuristics canonical triad.
- Mental Model
- In both, mental-model diagnosis enables targeted intervention.
This sourceFounding paper of the heuristics-and-biases program; documents representativeness, availability, and anchoring as systematic departures from coherent probabilistic reasoning, including base-rate neglect and inverse-fallacy errors.
- In both, mental-model diagnosis enables targeted intervention.
- Probability
- Medicine and public health apply it to diagnostic probabilities (sensitivity, specificity, positive and negative predictive value), epidemiological models, clinical-trial design, and risk stratification. Engineering reliability treats system failure as a probabilistic event, with Weibull and exponential lifetime models driving maintenance schedules and warranty design. Finance applies it to derivatives pricing under risk-neutral measures, value-at-risk computation, and stress testing. Cognitive science and behavioral economics measure how human probability judgment systematically departs from coherence — Tversky and Kahneman's (1974) heuristics-and-biases program documented base-rate neglect, conjunction errors, and representativeness substitution.
This sourceFounding paper of the heuristics-and-biases program; documents representativeness, availability, and anchoring as systematic departures from coherent probabilistic reasoning, including base-rate neglect and inverse-fallacy errors.
Supported in partVerified against the publisher's abstract
The abstract names representativeness as a heuristic and says these heuristics yield systematic and predictable errors, backing the general claim but not the named biases.
“These heuristics are highly economical and usually effective, but they lead to systematic and predictable errors.”
- Medicine and public health apply it to diagnostic probabilities (sensitivity, specificity, positive and negative predictive value), epidemiological models, clinical-trial design, and risk stratification. Engineering reliability treats system failure as a probabilistic event, with Weibull and exponential lifetime models driving maintenance schedules and warranty design. Finance applies it to derivatives pricing under risk-neutral measures, value-at-risk computation, and stress testing. Cognitive science and behavioral economics measure how human probability judgment systematically departs from coherence — Tversky and Kahneman's (1974) heuristics-and-biases program documented base-rate neglect, conjunction errors, and representativeness substitution.
- Regression to the Mean
- Additional canonical references in this cluster: , , , , ,
This sourceFounding paper of the heuristics-and-biases program; documents representativeness, availability, and anchoring as systematic departures from coherent probabilistic reasoning, including base-rate neglect and inverse-fallacy errors.
- Additional canonical references in this cluster: , , , , ,
- Stereotyping
- As Tversky and Kahneman (1974) demonstrated in their canonical analysis of heuristics and biases, the question is not whether to compress but how to monitor and correct for compression bias.
This sourceFounding paper of the heuristics-and-biases program; documents representativeness, availability, and anchoring as systematic departures from coherent probabilistic reasoning, including base-rate neglect and inverse-fallacy errors.
Supported in partVerified against the publisher's abstract
The abstract supports Tversky & Kahneman as the canonical account of systematic heuristic bias and of correcting it, but says nothing about compression, so it backs the framing only.
“These heuristics are highly economical and usually effective, but they lead to systematic and predictable errors. A better understanding of these heuristics and of the biases to which they lead could improve judgments and decisions in situations of uncertainty.”
- As Tversky and Kahneman (1974) demonstrated in their canonical analysis of heuristics and biases, the question is not whether to compress but how to monitor and correct for compression bias.
Domain-specific¶
- Base Rate
- Interviewer Leading
- Anchoring: numerical questions that mention any figure — even an explicitly arbitrary one — shift respondents' estimates toward it
This sourceThe third of three judgment heuristics, "adjustment from an anchor", "usually employed in numerical prediction when a relevant value is available", with the heuristics leading to "systematic and predictable errors".
Supported in partVerified against the publisher's abstract
“adjustment from an anchor, which is usually employed in numerical prediction when a relevant value is available”
- Anchoring: numerical questions that mention any figure — even an explicitly arbitrary one — shift respondents' estimates toward it
Mechanisms¶
- Blind Independent Valuation Review
- Its strength is that it neutralizes the most powerful bias in any valuation: anchoring
This sourceShows that numerical judgments are biased toward an initial number supplied before the estimate.
- Its strength is that it neutralizes the most powerful bias in any valuation: anchoring
- Disciplinary Guideline
- Its failure mode runs through anchoring: a recommended range, even one stamped "advisory," silently pulls decisions toward its midpoint, so the guideline quietly makes the choice it claims to leave open.
This sourceDemonstrates that an initial numerical value anchors later estimates even when it is arbitrary, so an advisory range can systematically pull decisions toward the values it presents.
- Its failure mode runs through anchoring: a recommended range, even one stamped "advisory," silently pulls decisions toward its midpoint, so the guideline quietly makes the choice it claims to leave open.
- Duplicate or Blind Remeasurement Check
- It catches anchoring bias — the pull of a first answer on a second
This sourceDefines anchoring as estimates remaining biased toward an initial value.
- It catches anchoring bias — the pull of a first answer on a second
- Feasible Option Inventory
- There is also an anchoring risk
This sourceIdentifies adjustment from an initial value as an anchoring heuristic that can systematically bias judgment.
- There is also an anchoring risk
- Incident Pattern Review
- It surfaces the failures that actually recur rather than the ones that are fun to imagine, it corrects intuition with base rates, and it mines near misses — cheap, plentiful, and predictive — for warning signs that would otherwise be discovered only after the next incident.
This sourceShows that intuitive probability judgments often neglect outcome base rates when representativeness dominates.
- It surfaces the failures that actually recur rather than the ones that are fun to imagine, it corrects intuition with base rates, and it mines near misses — cheap, plentiful, and predictive — for warning signs that would otherwise be discovered only after the next incident.
- Pattern Fit Scoring Rubric
- … (a crisp number laid over squishy judgements), weight-fiddling to reach a desired total (the classic run-backwards abuse), and compensatory aggregation letting surface matches mask a structural miss — the representativeness trap, where resemblance to a prototype inflates the felt fit while base rates are ignored.
This sourceRepresentativeness judgments can substitute resemblance to a prototype for probabilistic reasoning and neglect prior probabilities or base rates.
- … (a crisp number laid over squishy judgements), weight-fiddling to reach a desired total (the classic run-backwards abuse), and compensatory aggregation letting surface matches mask a structural miss — the representativeness trap, where resemblance to a prototype inflates the felt fit while base rates are ignored.
- Reweighted Update Log
- This is disciplined updating in the Bayesian spirit — a posterior derived from a prior and a stated adjustment — and it specifically guards against anchoring, where an initial number sticks and subsequent "adjustment" is chronically insufficient.
This sourceShows that people anchor on an initial value and typically adjust away from it insufficiently.
- This is disciplined updating in the Bayesian spirit — a posterior derived from a prior and a stated adjustment — and it specifically guards against anchoring, where an initial number sticks and subsequent "adjustment" is chronically insufficient.
- Rolling Forecast Review
- Its most common quiet failure is anchoring: a "review" that merely tweaks last period's forecast a few percent rather than rebuilding it
This sourceDefines anchoring-and-adjustment as estimating from an initial value and shows that adjustment is often insufficient.
- Its most common quiet failure is anchoring: a "review" that merely tweaks last period's forecast a few percent rather than rebuilding it
- Silent-Start Estimation Round
- Its direct target is anchoring
This sourceIdentifies adjustment from an anchor as a heuristic used in numerical prediction when an initial value is available.
- Its direct target is anchoring
- Similarity Dimension Rubric
- A rubric can look rigorous while over-weighting a salient but irrelevant dimension — false precision laundering a resemblance judgment that is really the representativeness heuristic in a spreadsheet.
This sourceIdentifies spreadsheet precision that launders a resemblance judgment as the representativeness heuristic.
- A rubric can look rigorous while over-weighting a salient but irrelevant dimension — false precision laundering a resemblance judgment that is really the representativeness heuristic in a spreadsheet.
- Threat Claim Triage
- Its failure mode is treating a vivid, easily-pictured story as if it were high-quality evidence — base-rate neglect, where the memorability of a scenario is mistaken for its likelihood.
This sourceShows that judgments can neglect base rates and overweigh the availability or imaginability of vivid scenarios when estimating likelihood.
- Its failure mode is treating a vivid, easily-pictured story as if it were high-quality evidence — base-rate neglect, where the memorability of a scenario is mistaken for its likelihood.
Verification¶
Does it exist? Confirmed. This work's DOI resolves to a registered record, which fixes its identity. That is all it fixes.
Does it back the claim? Read against the text for 7 of 23 citations: 1 supported, 6 supported in part. Each verdict is shown under its citation below, with what in the work backs the sentence.
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