The DOI matches its Crossref record, with a small difference in title or year; 11 of the 11 references it cites were found in a registry or an index.
Toward a synthesis of cognitive biases: How noisy information processing can bias human decision making.
Open accessAbstract
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), 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”
From On the Quest for Effectiveness in Human Oversight: Interdisciplinary Perspectives (2024) · cites this paper as [36]
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“While Chaudhary (2013) argued that behavioral finance explains why investors make irrational financial decisions, Hilbert (2012) demonstrated that behavioral biases—such as herding, overconfidence, and reinforcement bias—exert a stronger influence on individual investors than on institutional…”
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“Likewise, there is strong multidisciplinary evidence that human decision-makers — regardless of expertise — are subject to a variety of biases that distort their judgment and undermine the fairness and validity of decisions (Hilbert, 2012; Kahneman, 2013).”
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“People are subject to cognitive biases such as salience bias, recency bias, and subadditivity bias (Hilbert, 2012; Sunstein, 2019).”
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“The findings are similar to the ones that (Hilbert, 2012),cite in the study since the latter authors emphasized the role of demographic characteristics in the process of how the information is processed and to which extent people are prone to the effects of the cognitive bias.”
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“Researchers consider a decision to be biased when there is deviation from what is normatively predicted by classical probability and utility theory to be the optimal outcome based on the information or options available (Hilbert 2012).”
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“These deviations from norms and rationality when making (errors in) judgment are referred to as biases (Hilbert 2012; Shafir et al. 2002; Kappes 2020).”
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“Beliefs are also subject to systematic and predictable processes that are termed cognitive biases or heuristics that simplify and speed information processing and may contribute to psychological well-being (Gilovich, 1991; Hilbert, 2012).”
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“Recent literature has extensively examined cognitive biases (Blumenthal-Barby & Krieger, 2015; Das & Teng, 1999; Haselton et al., 2015; Hilbert, 2012); however, with a few exceptions, moral biases have primarily been characterized as distortions of our moral behavior driven by self-interest (Croson…”
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“Some researchers focus on mediating/moderating factors and correlations between the three (e.g. Field, Beeson, Jones 2015), while others focus on gaps (Kahneman, Tversky 1996; Hilbert 2012).”
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Metadata
- Authors
- Hilbert, M.
- Affiliations
- University of Southern California (US)
- Corresponding author
- Hilbert, Martin
- ORCID
- 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
- green
- escholarship.org
- 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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