Cited by 391Decision-Making and Behavioral EconomicsClinical Reasoning and Diagnostic SkillsCognitive Science and Education Research

Toward a synthesis of cognitive biases: How noisy information processing can bias human decision making.

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Hilbert, Martin·2012·Psychological Bulletin

Abstract

A single coherent framework is proposed to synthesize long-standing research on 8 seemingly unrelated cognitive decision-making biases. During the past 6 decades, hundreds of empirical studies have resulted in a variety of rules of thumb that specify how humans systematically deviate from what is normatively expected from their decisions. Several complementary generative mechanisms have been proposed to explain those cognitive biases. Here it is suggested that (at least) 8 of these empirically detected decision-making biases can be produced by simply assuming noisy deviations in the memory-based information processes that convert objective evidence (observations) into subjective estimates (decisions). An integrative framework is presented to show how similar noise-based mechanisms can lead to conservatism, the Bayesian likelihood bias, illusory correlations, biased self-other placement, subadditivity, exaggerated expectation, the confidence bias, and the hard-easy effect. Analytical tools from information theory are used to explore the nature and limitations that characterize such information processes for binary and multiary decision-making exercises. The ensuing synthesis offers formal mathematical definitions of the biases and their underlying generative mechanism, which permits a consolidated analysis of how they are related. This synthesis contributes to the larger goal of creating a coherent picture that explains the relations among the myriad of seemingly unrelated bia…

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  • Measures in accordance with (b) seem out of place because they introduce a concrete psychological aspect that sticks out from more technical and operational aspects, especially since automation bias is just one of many relevant biases, heuristics, and psychological phenomena.

    “Measures in accordance with (b), which are intended to maintain an awareness of the automation bias, seem out of place: it introduces a concrete psychological aspect that sticks out from the more technical and operational aspects outlined in the other provisions, especially considering that automation bias is just one of many relevant biases (e.g., hindsight bias, confidence bias [36, 66]), heuris”

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Authors
Hilbert, M.
Affiliations
University of Southern California (US)
Corresponding author
Hilbert, Martin
Venue
Psychological Bulletin
Published
2012-03
Volume
138
Issue
2
Pages
211-237
ISSN
  • 0033-2909 (ISSN-L)
  • 1939-1455
OpenAlex
W1990584714
Cited by
391
References
130
Citations by year
2026: 19 · 2025: 30 · 2024: 38 · 2023: 36 · 2022: 30 · 2021: 29 · 2020: 41 · 2019: 32 · 2018: 27 · 2017: 25 · 2016: 29 · 2015: 12 · 2014: 21 · 2013: 14 · 2012: 8
FWCI
7.58
Type
journal article
Language
en
Open access
Licence
cc-by-nc-sa
Locations
  • Psychological Bulletin (publishedVersion)
  • PubMed (publishedVersion)
  • eScholarship (California Digital Library) (submittedVersion, cc-by-nc-sa)
Topics
  • Social Sciences › Decision Sciences › General Decision Sciences › Decision-Making and Behavioral Economics
  • Health Sciences › Medicine › Family Practice › Clinical Reasoning and Diagnostic Skills
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Cognitive Science and Education Research
Keywords
cognitive biases, decision-making, conservatism, illusory correlation, subadditivity, confidence bias, information theory, integrative framework
MeSH terms
Decision Making, Female, Humans, Information Theory, Judgment, Male, Memory, Models, Psychological, Probability, Set, Psychology, Stochastic Processes

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