scholarly journals The Measurement of Individual Differences in Cognitive Biases: A Review and Improvement

2021 ◽  
Vol 12 ◽  
Author(s):  
Vincent Berthet
Keyword(s):  
Decision Making ◽  
Individual Differences ◽  
Cognitive Biases ◽  
Empirical Work ◽  
Confirmation Bias ◽  
Generic Measures

Individual differences have been neglected in decision-making research on heuristics and cognitive biases. Addressing that issue requires having reliable measures. The author first reviewed the research on the measurement of individual differences in cognitive biases. While reliable measures of a dozen biases are currently available, our review revealed that some measures require improvement and measures of other key biases are still lacking (e.g., confirmation bias). We then conducted empirical work showing that adjustments produced a significant improvement of some measures and that confirmation bias can be reliably measured. Overall, our review and findings highlight that the measurement of individual differences in cognitive biases is still in its infancy. In particular, we suggest that contextualized (in addition to generic) measures need to be improved or developed.

Confirmation bias in decision making for fingerprints, DNA and eyewitness evidence cannot be explained by cognitive style or thinking dispositions.

2019 ◽  
Author(s):  
Daniel Edgcumbe
Keyword(s):  
Decision Making ◽  
Cognitive Style ◽  
Cognitive Biases ◽  
Confirmation Bias ◽  
Criminal Case ◽  
Court Cases ◽  
Legal Proceedings ◽  
Thinking Dispositions ◽  
Evaluation Of Evidence ◽  
Facial Composite

Pre-existing beliefs about the background or guilt of a suspect can bias the subsequent evaluation of evidence for forensic examiners and lay people alike. This biasing effect, called the confirmation bias, has influenced legal proceedings in prominent court cases such as that of Brandon Mayfield. Today many forensic providers attempt to train their examiners against these cognitive biases. Nine hundred and forty-two participants read a fictional criminal case and received either neutral, incriminating or exonerating evidence (fingerprint, eyewitness, or DNA) before providing an initial rating of guilt. Participants then viewed ambiguous evidence (alibi, facial composite, handwriting sample or informant statement) before providing a final rating of guilt. Final guilt ratings were higher for all evidence conditions (neutral, incriminating or exonerating) following exposure to the ambiguous evidence. This provides evidence that the confirmation bias influences the evaluation of evidence.

Overcoming Confirmation and Blind Spot Biases When Communicating Science

2017 ◽  
Author(s):  
Kate Kenski
Keyword(s):  
Decision Making ◽  
Cognitive Biases ◽  
Confirmation Bias ◽  
Blind Spot ◽  
Future Research ◽  
Costs And Benefits ◽  
Process Information ◽  
Bias Blind Spot

This chapter focuses on two biases that lead people away from evaluating evidence and scientific studies impartially—confirmation bias and bias blind spot. The chapter first discusses different ways in which people process information and reviews the costs and benefits of utilizing cognitive shortcuts in decision making. Next, two common cognitive biases, confirmation bias and bias blind spot, are explained. Then the literature on “debiasing” is explored. Finally, the implications of confirmation bias and bias blind spot in the context of communicating about science are examined, and an agenda for future research on understanding and mitigating these biases is offered.

scholarly journals Measuring individual differences in cognitive biases: The Cognitive Bias Inventory

2021 ◽  
Author(s):  
Vincent Berthet ◽  
Vincent de Gardelle
Keyword(s):  
Decision Making ◽  
Individual Differences ◽  
Cognitive Bias ◽  
Cognitive Biases ◽  
Temporal Stability ◽  
Real Life ◽  
Future Research ◽  
Personality Factors ◽  
Wrong Answer ◽  
Outcome Bias

This article described the behavioral measurement of six classic cognitive biases (framing, availability, anchoring, overconfidence, hindsight/outcome bias, confirmation bias). Each measure showed a satisfactory level of reliability with regard both to internal consistency (mean Cronbach’s alpha = .77) and temporal stability (mean test-retest correlation = .71). Multivariate analysis supported the hypothesis that each cognitive bias captures specific decision-making processes as the six biases: (a) were virtually uncorrelated (mean correlation = .08), thus indicating no general decision-making competence factor, (b) were moderately correlated with other relevant constructs (the A-DMC components, cognitive ability, decision-making styles, and personality factors), (c) were more related to performance on a narrow domain of decision-making (the ability to overcome an intuitive wrong answer as measured by the CRT) than to the general success in real-life decision-making as measured by the Decision Outcomes Inventory (DOI). We introduce this set of behavioral tasks as the Cognitive Bias Inventory (CBI), a psychometric tool allowing for the reliable assessment of individual differences in six common, independent cognitive shortcuts. The CBI appears as a useful tool for future research on decision-making competence and how it relates to decision errors.

scholarly journals Using Design Thinking to improve Strategic Decisions during Collaborative Sensemaking

2019 ◽  
Vol 1 (1) ◽  
Author(s):  
Mikko KORIA ◽  
Ekaterina KOTINA ◽  
Sharon PRENDEVILLE
Keyword(s):  
Decision Making ◽  
Design Thinking ◽  
Cognitive Biases ◽  
Confirmation Bias ◽  
Positive Influence ◽  
Strategic Decision ◽  
Strategic Decision Making ◽  
Strategic Decisions ◽  
Cognitive Limitations ◽  
Collaborative Sensemaking

Human cognitive limitations affect strategic decision-making. One of such effects is emergence of cognitive biases, deviations from rationality in judgment. These biases can negatively influence an organisation's capability to capture and utilize new ideas, thus inhibiting innovation. Researchers have documented different strategies for mitigating cognitive biases – and many of them overlap with the ones emphasised in design thinking. However, research so far does not offer any specific “recipes” for mitigation of cognitive biases. This paper links together research on challenges of strategic decision-making, cognitive biases and design thinking. The paper investigates the effects of applying design-thinking tool in collaborative sensemaking stage, within a small business team, aiming to mitigate confirmation bias. The study indicated that newly introduced design-thinking tools did not have the expected positive influence on decision-making. The research contributes to the field by developing a new framework on how to identify and mitigate confirmation bias in strategic decision-making.

Bibliometric analysis on the association between behavioral finance and decision making with cognitive biases such as overconfidence, anchoring effect and confirmation bias

2017 ◽  
Vol 111 (3) ◽  
pp. 1775-1799 ◽  
Author(s):  
Daniel Fonseca Costa ◽  
Francisval de Melo Carvalho ◽  
Bruno César de Melo Moreira ◽  
José Willer do Prado
Keyword(s):  
Decision Making ◽  
Bibliometric Analysis ◽  
Behavioral Finance ◽  
Cognitive Biases ◽  
Confirmation Bias ◽  
Anchoring Effect

scholarly journals How Behavioral Economics and Nudges Could Help Diminish Irrationality in Suicide-Related Decisions

2019 ◽  
Vol 15 (1) ◽  
pp. 44-61 ◽  
Author(s):  
Brian W. Bauer ◽  
Daniel W. Capron
Keyword(s):  
Decision Making ◽  
Suicide Attempt ◽  
Behavioral Economics ◽  
Bounded Rationality ◽  
Suicide Prevention ◽  
Cognitive Biases ◽  
Confirmation Bias ◽  
Computational Power ◽  
Behavioral Economic ◽  
New Evidence

People regularly make decisions that are not aligned with their own self-interests. These irrational decisions often stem from humans having bounded rationality (e.g., limited computational power), which produces reliable cognitive biases that occur outside of people’s awareness and influences the decisions people make. There are many important decisions leading up to a suicide attempt, and it is likely that these same biases exist within suicide-related decisions. This article presents an argument for the likely existence of cognitive biases within suicide-related decision making and how they may influence people to make irrational decisions. In addition, this article provides new evidence for using a behavioral economic intervention—nudges—as a potential way to combat rising suicide rates. We explore how nudges can help increase means safety, disseminate suicide prevention skills/materials, diminish well-known biases (e.g., confirmation bias), and uncover biases that may be occurring when making suicide-related decisions.

De-Biasing Legal Factfinders

2021 ◽  
pp. 395-410
Author(s):  
Frank Zenker
Keyword(s):  
Decision Making ◽  
Special Reference ◽  
Cognitive Biases ◽  
Confirmation Bias ◽  
Future Research ◽  
Research Needs ◽  
Base Rate Neglect ◽  
Human Decision ◽  
Social Biases ◽  
Evidential Basis

This chapter examines the psychological studies of biases and de-biasing measures in human decision-making with special reference to adjudicative factfinding. Research shows that factfinders are prone to cognitive biases (such as anchoring, framing, base-rate neglect, and confirmation bias) as well as social biases. Driven by this research, multiple studies have examined the extent to which those biases can be mitigated by de-biasing measures like “consider the opposite” and “give reasons.” After a brief overview of the research, the author points to the problematic evidential basis and identifies future research needs, and concludes that empirical research on de-biasing measures has so far delivered less than one would hope for.

Cognition and Expert-Level Proficiency in Intelligence Analysis

2019 ◽  
pp. 976-1000
Author(s):  
David T. Moore ◽  
Robert R. Hoffman
Keyword(s):  
Decision Making ◽  
Critical Thinking ◽  
Individual Differences ◽  
Performance Measures ◽  
Cognitive Biases ◽  
Intelligence Community ◽  
Intelligence Analysis ◽  
Robust Performance ◽  
Procedural Skills ◽  
Proficiency Level

Proficiency scaling in the domain of intelligence analysis converges on an answer to the question of what counts as expertise in this domain. Proficiency scales in the domain are based on what are called essential competencies. There are many distinct analytical roles, entailing a specialization of expertise. This chapter discusses macrocognitive models of analyst reasoning and knowledge as a function of proficiency level, including recognition-primed decision making and intuition. This chapter also considers individual differences and conceptualize the different styles to be relatively stable and distinctive approaches to critical thinking. Proficiency scaling entails the issue of whether intelligence analysts are prone to cognitive biases. Analysts must cope with the problem of indeterminate causation, that is, the understanding of events for which there is no single cause, and causal forces include human agency and motivations. Directives in the intelligence community call for robust performance measures, but measuring analyst procedural skills is non-trivial. Finally, the implications for training are discussed.

scholarly journals Confirmation Bias Estimation from Electroencephalography with Machine Learning

2019 ◽  
Vol 63 (1) ◽  
pp. 73-77
Author(s):  
Micah N. Villarreal ◽  
Alexander J. Kamrud ◽  
Brett J. Borghetti
Keyword(s):  
Machine Learning ◽  
Decision Making ◽  
Cognitive Biases ◽  
Confirmation Bias ◽  
Supervised Machine Learning ◽  
Bias Estimation ◽  
Human Decision ◽  
Behavioral Evidence ◽  
Post Hoc ◽  
The Relationship

Cognitive biases are known to affect human decision making and can have disastrous effects in the fast-paced environments of military operators. Traditionally, post-hoc behavioral analysis is used to measure the level of bias in a decision. However, these techniques can be hindered by subjective factors and cannot be collected in real-time. This pilot study collects behavior patterns and physiological signals present during biased and unbiased decision-making. Supervised machine learning models are trained to find the relationship between Electroencephalography (EEG) signals and behavioral evidence of cognitive bias. Once trained, the models should infer the presence of confirmation bias during decision-making using only EEG - without the interruptions or the subjective nature of traditional confirmation bias estimation techniques.

scholarly journals The Impact of Cognitive Biases on Professionals’ Decision-Making: A Review of Four Occupational Areas

2022 ◽  
Vol 12 ◽  
Author(s):  
Vincent Berthet
Keyword(s):  
Decision Making ◽  
Individual Differences ◽  
Cognitive Biases ◽  
Ecological Validity ◽  
Secondary Data ◽  
Primary Data ◽  
Research Gaps ◽  
Level Of Evidence ◽  
The Impact ◽  
False Idea

The author reviewed the research on the impact of cognitive biases on professionals’ decision-making in four occupational areas (management, finance, medicine, and law). Two main findings emerged. First, the literature reviewed shows that a dozen of cognitive biases has an impact on professionals’ decisions in these four areas, overconfidence being the most recurrent bias. Second, the level of evidence supporting the claim that cognitive biases impact professional decision-making differs across the areas covered. Research in finance relied primarily upon secondary data while research in medicine and law relied mainly upon primary data from vignette studies (both levels of evidence are found in management). Two research gaps are highlighted. The first one is a potential lack of ecological validity of the findings from vignette studies, which are numerous. The second is the neglect of individual differences in cognitive biases, which might lead to the false idea that all professionals are susceptible to biases, to the same extent. To address that issue, we suggest that reliable, specific measures of cognitive biases need to be improved or developed.

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