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 Retention and Transfer of Cognitive Bias Mitigation Interventions: A Systematic Literature Study

2021 ◽  
Vol 12 ◽  
Author(s):  
J.E. (Hans) Korteling ◽  
Jasmin Y. J. Gerritsma ◽  
Alexander Toet
Keyword(s):  
Decision Making ◽  
Cognitive Bias ◽  
Cognitive Biases ◽  
Selection Process ◽  
Real Life ◽  
Insufficient Evidence ◽  
Human Judgment ◽  
Literature Study ◽  
Life Conditions ◽  
Over Time

Cognitive biases can adversely affect human judgment and decision making and should therefore preferably be mitigated, so that we can achieve our goals as effectively as possible. Hence, numerous bias mitigation interventions have been developed and evaluated. However, to be effective in practical situations beyond laboratory conditions, the bias mitigation effects of these interventions should be retained over time and should transfer across contexts. This systematic review provides an overview of the literature on retention and transfer of bias mitigation interventions. A systematic search yielded 52 studies that were eligible for screening. At the end of the selection process, only 12 peer-reviewed studies remained that adequately studied retention over a period of at least 14 days (all 12 studies) or transfer to different tasks and contexts (one study). Eleven of the relevant studies investigated the effects of bias mitigation training using game- or video-based interventions. These 11 studies showed considerable overlap regarding the biases studied, kinds of interventions, and decision-making domains. Most of them indicated that gaming interventions were effective after the retention interval and that games were more effective than video interventions. The study that investigated transfer of bias mitigation training (next to retention) found indications of transfer across contexts. To be effective in practical circumstances, achieved effects of cognitive training should lead to enduring changes in the decision maker's behavior and should generalize toward other task domains or training contexts. Given the small number of overlapping studies, our main conclusion is that there is currently insufficient evidence that bias mitigation interventions will substantially help people to make better decisions in real life conditions. This is in line with recent theoretical insights about the “hard-wired” neural and evolutionary origin of cognitive biases.

scholarly journals AI-Enabled Sensing and Decision-Making for IoT Systems

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Hao Qinxia ◽  
Shah Nazir ◽  
Ma Li ◽  
Habib Ullah ◽  
Wang Lianlian ◽  
...  
Keyword(s):  
Decision Making ◽  
Real Life ◽  
Research Community ◽  
Smart Sensors ◽  
Future Research ◽  
New Paradigm ◽  
Exclusion Criteria ◽  
Intelligent Devices ◽  
Research Questions

The influential stage of Internet of Things (IoT) has reformed all fields of life in general but specifically with the emergence of artificial intelligence (AI) has drawn the attention of researchers into a new paradigm of life standard. This revolution has been accepted around the globe for making life easier with the use of intelligent devices such as smart sensors, actuators, and many other devices. AI-enabled devices are more intelligent and capable of doing a specific task which saves a lot of resources and time. Different approaches are available in the existing literature to tackle diverse issues of real life based on AI and IoT systems. The role of decision-making has its own importance in the AI-enabled and IoT systems. In-depth knowledge of the existing literature is dire need of the research community to summarize the literature in effective way by which practitioners and researchers can benefit from the prevailing proofs and suggest new solutions for solving a particular problem of AI-enabled sensing and decision-making for the IoT system. To facilitate research community, the proposed study presents a systematic literature review of the existing literature, organizes the evidences in a systematic way, and then analyzes it for future research. The study reported the literature of the last 5 years based on the research questions, inclusion and exclusion criteria, and quality assessment of the selected study. Finally, derivations are drawn from the included paper for future research.

Cognitive Bias and its Relationship to Decision Making: the Case of Talented Secondary Students in Jeddah: الانحياز المعرفي وعلاقته باتخاذ القرار لدى عينة من طالبات المرحلة الثانوية الموهوبات بمدينة جدة

2020 ◽  
Vol 4 (45) ◽  
Author(s):  
Dalal Hamid Al-Dhahri, Arwa Abdullah Al-Ghamdi, Mogeda El-Sa
Keyword(s):  
Decision Making ◽  
Secondary Students ◽  
Cognitive Bias ◽  
Random Sampling ◽  
Cognitive Biases ◽  
School Administration ◽  
High Level ◽  
The Relationship ◽  
Descriptive Method

This study aims at investigating the relationship between cognitive biases and decision making from a sample of gifted secondary students. It also aims at identifying the level of students’ cognitive biases and decision making and the differences in these two areas based on different classrooms. Random sampling was used to collect data from 139 female secondary students from the gifted group. Their age ranged between (16-18) with an average of (16.6), A descriptive method was adopted in the study. The research tools used consisted of DACOBS David Assessment of Cognitive biases Scale (Vander Gaag. et al., 2000), translated and standardized by the present researchers, and Tuistra’s decision making scale for teenagers (Tuinstra, et al., 2000). The findings of the study show a negative correlation between cognitive biases and decision making. Also, there were no differences between cognitive biases and decision making scores based on different classrooms. The study also shows a low level of students’ cognitive biases and a high level of decision making. The study recommends activating the role of mentors and students' counseling, planning for the values and behaviors that need to be acquired by students by including them in the annual goals of the school administration and participating in societal awareness and education.

Frameworks and Models in Decision-Making and Judgment in Child Welfare and Protection

2020 ◽  
pp. 3-26
Author(s):  
Rami Benbenishty ◽  
John D. Fluke
Keyword(s):  
Decision Making ◽  
Information Processing ◽  
Child Welfare ◽  
False Negative ◽  
Real Life ◽  
Decision Makers ◽  
Future Research ◽  
Theoretical Perspectives ◽  
Specificity And Sensitivity ◽  
Predictive Risk

This chapter presents the basic concepts, theoretical perspectives, and areas of scholarship that bear on decisions in child welfare—making choices in decision environments characterized by high levels of uncertainty. The authors distinguish between normative models that predict what decision-makers ought to choose when faced with alternatives and descriptive models that describe how they tend to make these choices in real life. The chapter reviews those challenges that may be especially relevant in the complex context of child welfare and protection. One way in which decision-makers overcome task complexities and limitations in human information processing (bounded rationality) is by using heuristics to navigate complex tasks. The chapter reviews strategies to correct some limitations in judgment. The authors examine the relationships between workers’ predictions of what would be the outcomes of the case and the actual outcomes and describe two types of error (false positive and false negative) and the related concepts of specificity and sensitivity. These issues are followed by a description of the Lens Model and some of its implications for child welfare decision-making, including predictive risk modeling and studies on information processing models. The final section presents current theoretical models in child welfare decision-making and describes Decision-Making Ecology (DME) and Judgments and Decision Processes in Context (JUDPiC). The chapter concludes with suggestions for future research on child welfare decision-making that could contribute to our conceptual understanding and have practical utility as well.

scholarly journals Involuntary musical imagery as a component of ordinary music cognition: A review of empirical evidence

2020 ◽  
Vol 27 (6) ◽  
pp. 1195-1217
Author(s):  
Lassi A. Liikkanen ◽  
Kelly Jakubowski
Keyword(s):  
Individual Differences ◽  
Empirical Studies ◽  
Music Cognition ◽  
Future Research ◽  
Personality Factors ◽  
Extensive Literature ◽  
Musical Imagery ◽  
Mental Experience ◽  
Research Themes ◽  
Extensive Literature Search

AbstractInvoluntary musical imagery (INMI) refers to a conscious mental experience of music that occurs without deliberate efforts to initiate or sustain it. This experience often consists of the repetition of a short fragment of a melody, colloquially called an “earworm.” Here, we present the first comprehensive, qualitative review of published empirical research on INMI to date. We performed an extensive literature search and discovered, in total, 47 studies from 33 peer-reviewed articles that met the inclusion criteria for the review. In analyzing the content of these studies, we identified four major research themes, which concern the phenomenology, dynamics, individual differences, and musical features of INMI. The findings answer many questions of scientific interest—for instance, what is typical in terms of INMI frequency, duration, and content; which factors influence INMI onset; and whether demographic and personality factors can explain individual differences in susceptibility and responses to INMI. This review showcases INMI as a well-established phenomenon in light of a substantial body of empirical studies that have accumulated consistent results. Although the populations under study show an unfavorable bias towards Western, educated participants, the evidence depicts INMI as a universal psychological phenomenon, the possible function of which we do not yet fully understand. The concluding section introduces several suggestions for future research to expand on the topic.

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 The odd case when cognitive biases are more prevalent in researchers than in samples

2017 ◽  
Author(s):  
Jose D. Perezgonzalez
Keyword(s):  
Decision Making ◽  
Cognitive Bias ◽  
Strong Evidence ◽  
Cognitive Biases ◽  
Statistical Significance ◽  
The Impact ◽  
Result Interpretation

Walmsley and Gilbey (2016) reported on the impact of cognitive biases on pilots’ decision-making, concluding that there was strong evidence that cognitive bias impacted decision making thus putting pilots' lives in danger. However, their methodology was not free of the same biases they set to research and, more importantly, they relied far too much on statistical significance as the only standard for result interpretation. Consequently, while the results obtained may have been technically correct, their divorce from the underlying methodological context made them factually wrong. Therefore, the conclusions achieved also misrepresented the true impact of cognitive biases on pilots' decision-making.

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.

scholarly journals Emotional Bias Modification in Youths with Attention Deficit Hyperactivity Disorder (ADHD): New Research Vista

2020 ◽  
Vol 17 (11) ◽  
pp. 4028
Author(s):  
Zhang Melvyn ◽  
Aloysius Chow ◽  
Ranganath Vallabhajosyula ◽  
Daniel SS Fung
Keyword(s):  
Attention Deficit Hyperactivity Disorder ◽  
Cognitive Bias ◽  
Attention Deficit ◽  
Cognitive Biases ◽  
Preliminary Evidence ◽  
Cognitive Bias Modification ◽  
Emotional Dysregulation ◽  
Future Research ◽  
Hyperactivity Disorder ◽  
Bias Modification

Whilst cognitive bias modification was initially used in the treatment of anxiety disorders, it is also currently being used for the treatment of other psychopathologies. In fact, cognitive bias modification has been especially well-investigated amongst children and adolescents. A recent review suggests some evidence for the modification of interpretative biases amongst children with neurodevelopment disorders. There have since been other studies reporting of the existence of other cognitive biases, such as emotional biases, amongst individuals with attention deficit hyperactivity disorder (ADHD). This perspective article will discuss the epidemiology of ADHD and the nature of emotional biases that are present amongst individuals with ADHD. This perspective article also reviewed some of the studies that have assessed and modified emotional biases in individuals with ADHD. A total of three studies have been identified from the published literature that provide evidence for targeting emotional biases amongst individuals with ADHD. These studies provide us with preliminary evidence for the effectiveness of modifying emotional biases and how it could help in ameliorating symptoms related to emotional dysregulation. There needs to be future research in this area with further evidence supporting the effectiveness of modifying emotional biases. It is also crucial for future research to determine which of these tools is best at detecting such biases, and which of these tools are versatile enough and non-invasive that they could safely be implemented for both research and clinical needs.

scholarly journals Decision-Making Competence: More Than Intelligence?

2020 ◽  
Vol 29 (2) ◽  
pp. 186-192 ◽  
Author(s):  
Wändi Bruine de Bruin ◽  
Andrew M. Parker ◽  
Baruch Fischhoff
Keyword(s):  
Older Adults ◽  
Decision Making ◽  
Individual Differences ◽  
Fluid Intelligence ◽  
Psychological Research ◽  
Future Research ◽  
Experimental Conditions ◽  
Crystallized Intelligence ◽  
Age Related ◽  
Development And Validation

Decision-making competence refers to the ability to make better decisions, as defined by decision-making principles posited by models of rational choice. Historically, psychological research on decision-making has examined how well people follow these principles under carefully manipulated experimental conditions. When individual differences received attention, researchers often assumed that individuals with higher fluid intelligence would perform better. Here, we describe the development and validation of individual-differences measures of decision-making competence. Emerging findings suggest that decision-making competence may tap not only into fluid intelligence but also into motivation, emotion regulation, and experience (or crystallized intelligence). Although fluid intelligence tends to decline with age, older adults may be able to maintain decision-making competence by leveraging age-related improvements in these other skills. We discuss implications for interventions and future research.

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