Cognitive Biases and Decision Making in Gambling

2010 ◽  
Vol 107 (1) ◽  
pp. 15-24 ◽  
Author(s):  
Mariano Chóliz
Keyword(s):  
Decision Making ◽  
Cognitive Bias ◽  
Cognitive Biases ◽  
Structural Characteristics ◽  
Illusion Of Control ◽  
Games Of Chance

Heuristics and cognitive biases can occur in reasoning and decision making. Some of them are very common in gamblers (illusion of control, representativeness, availability, etc.). Structural characteristics and functioning of games of chance favor the appearance of these biases. Two experiments were conducted with nonpathological gamblers. The first experiment was a game of dice with wagers. In the second experiment, the participants played two bingo games. Specific rules of the games favored the appearance of cognitive bias (illusion of control) and heuristics (representativeness and availability) and influence on the bets. Results and implications for gambling are discussed.

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.

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 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.

Cognitive Biases

2018 ◽  
pp. 214-235
Keyword(s):  
Decision Making ◽  
Cognitive Bias ◽  
Cognitive Biases ◽  
Legal Education ◽  
Decision Making Process ◽  
Strategic Decisions

This chapter will describe some implications of using cognitive biases in the decision-making process in social areas such as economic, legal, education, and political. The cognitive bias would be a pattern of deviation in judgment, in which the inferences that we make about other people and/or situations can be illogical. Moreover, different studies have found that even strategic decisions that affect the society can be influenced by these biases. Therefore, it is important to be aware of them to try to detect and reduce them. Above all, it is necessary to teach how to detect them in order to reduce them in public professionals.

Exploring Cognitive Biases, Groupthink, and Polythink Syndrome in Security Decisions and Business Outcomes

2021 ◽  
pp. 47-61
Author(s):  
Luisa Dall'Acqua
Keyword(s):  
Decision Making ◽  
Group Dynamics ◽  
Group Decision Making ◽  
Cognitive Bias ◽  
Cognitive Biases ◽  
The Other ◽  
Key Factors ◽  
Business Decisions ◽  
Business Outcomes ◽  
Clear Cut

Cognitive bias among workers can undermine security work and lead to critical misinterpretations of data. Understanding cognitive biases can improve understanding of how employees make decisions. This work analyzes key factors to better understand, predict, and obviate the detrimental bias symptoms, focusing on groupthink and polythink phenomena occurring in security and business decisions. It intends to provide support for the strategic versus tactical hypothesis in a strategic group decision-making, confirming how even in a clear-cut decision, following a groupthink or polythink dynamic, implementation becomes difficult due to a group dynamics at the other end of the decision-making continuum.

scholarly journals Cognitive bias: how understanding its impact on antibiotic prescribing decisions can help advance antimicrobial stewardship

2020 ◽  
Vol 2 (4) ◽  
Author(s):  
Bradley J Langford ◽  
Nick Daneman ◽  
Valerie Leung ◽  
Dale J Langford
Keyword(s):  
Decision Making ◽  
Cognitive Bias ◽  
Cognitive Biases ◽  
Healthcare Setting ◽  
Hyperbolic Discounting ◽  
Antibiotic Prescribing ◽  
Support Tools ◽  
Human Decision

Abstract The way clinicians think about decision-making is evolving. Human decision-making shifts between two modes of thinking, either fast/intuitive (Type 1) or slow/deliberate (Type 2). In the healthcare setting where thousands of decisions are made daily, Type 1 thinking can reduce cognitive load and help ensure decision making is efficient and timely, but it can come at the expense of accuracy, leading to systematic errors, also called cognitive biases. This review provides an introduction to cognitive bias and provides explanation through patient vignettes of how cognitive biases contribute to suboptimal antibiotic prescribing. We describe common cognitive biases in antibiotic prescribing both from the clinician and the patient perspective, including hyperbolic discounting (the tendency to favour small immediate benefits over larger more distant benefits) and commission bias (the tendency towards action over inaction). Management of cognitive bias includes encouraging more mindful decision making (e.g., time-outs, checklists), improving awareness of one’s own biases (i.e., meta-cognition), and designing an environment that facilitates safe and accurate decision making (e.g., decision support tools, nudges). A basic understanding of cognitive biases can help explain why certain stewardship interventions are more effective than others and may inspire more creative strategies to ensure antibiotics are used more safely and more effectively in our patients.

Cognitive Bias: The Downside of Shared Decision Making

2018 ◽  
pp. 1-10 ◽  
Author(s):  
Semra Ozdemir ◽  
Eric Andrew Finkelstein
Keyword(s):  
Decision Making ◽  
Shared Decision Making ◽  
Cognitive Bias ◽  
Cognitive Biases ◽  
Patient Treatment ◽  
Shared Decision ◽  
Undue Influence ◽  
Treatment Choices ◽  
Patients With Cancer ◽  
Future Selves

This narrative review presents theoretical and empirical evidence of common cognitive biases that are likely to influence treatment choices of patients with cancer and other illnesses. We present an overview of common cognitive biases that result from how and when information is presented to patients. We supplement these descriptions with cancer-specific examples or those from other health fields if no cancer-specific examples are available. The results provide compelling evidence that patient treatment choices are subconsciously influenced by both known and unknown biases. Shared decision making is ideal in theory, but in reality, it is fraught with risks resulting from cognitive biases and undue influence of even the best-intentioned physicians and family members. Efforts should be made to minimize these concerns and to help patients to make decisions that their future selves are least likely to regret.

The Role of Cognitive Bias in Breast Radiology Diagnostic and Judgment Errors

2020 ◽  
Vol 2 (4) ◽  
pp. 382-389
Author(s):  
Vilert A Loving ◽  
Elizabeth M Valencia ◽  
Bhavika Patel ◽  
Brian S Johnston
Keyword(s):  
Decision Making ◽  
Cognitive Bias ◽  
Cognitive Biases ◽  
Organizational Level ◽  
Individual Level ◽  
Gambler’S Fallacy ◽  
Satisfaction Of Search ◽  
Human Decision ◽  
The Individual

Abstract Cognitive bias is an unavoidable aspect of human decision-making. In breast radiology, these biases contribute to missed or erroneous diagnoses and mistaken judgments. This article introduces breast radiologists to eight cognitive biases commonly encountered in breast radiology: anchoring, availability, commission, confirmation, gambler’s fallacy, omission, satisfaction of search, and outcome. In addition to illustrative cases, this article offers suggestions for radiologists to better recognize and counteract these biases at the individual level and at the organizational level.

scholarly journals Human Cognitive Bias Identification for Generating Safety Requirements in Safety Critical Systems

2020 ◽  
Vol 8 (6) ◽  
pp. 5749-5758
Keyword(s):  
Decision Making ◽  
Cognitive Bias ◽  
Human Error ◽  
Cognitive Biases ◽  
Human Potential ◽  
Economic Damage ◽  
Critical Systems ◽  
Safety Requirements ◽  
Safety Critical ◽  
Safety Critical Systems

Safety critical systems are systems whose failure could result loss of life, economic damage, incidents, accidents or undesirable outcome, but it is not doubt that critical system safety has improved greatly under the development of the technology as the number of hardware and software induced accidents has been definitely reduced, but number of human deviations in their decision making found in each accident range remains more. We deeply reviewed traditional human error approaches and their limitations and propose approach of Human Cognitive Bias Identification Technique (H-CoBIT) that identifies, mitigates human potential cognitive biases and generates safety requirements during the initial phase of system Design. This proposed method, analyses the design of safety critical systems from a human factors perspective. It contributes system analyst, designers, and software engineers to identify potential cognitive biases (metal deviations in operator’s decision-making process) during the system use. To ensure the validity of the proposed method, we conducted an empirical experiment to validate the method for accuracy and reliability comparing different experimental outcomes using signal detection theorem.

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.

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