scholarly journals Debiasing Decisions

2015 ◽  
Vol 2 (1) ◽  
pp. 129-140 ◽  
Author(s):  
Carey K. Morewedge ◽  
Haewon Yoon ◽  
Irene Scopelliti ◽  
Carl W. Symborski ◽  
James H. Korris ◽  
...  
Keyword(s):  
Decision Making ◽  
Computer Game ◽  
Blind Spot ◽  
Bias Reduction ◽  
Private Life ◽  
Instructional Video ◽  
Training Intervention ◽  
Intelligence Analysis ◽  
Training Interventions ◽  
Bias Blind Spot

From failures of intelligence analysis to misguided beliefs about vaccinations, biased judgment and decision making contributes to problems in policy, business, medicine, law, education, and private life. Early attempts to reduce decision biases with training met with little success, leading scientists and policy makers to focus on debiasing by using incentives and changes in the presentation and elicitation of decisions. We report the results of two longitudinal experiments that found medium to large effects of one-shot debiasing training interventions. Participants received a single training intervention, played a computer game or watched an instructional video, which addressed biases critical to intelligence analysis (in Experiment 1: bias blind spot, confirmation bias, and fundamental attribution error; in Experiment 2: anchoring, representativeness, and social projection). Both kinds of interventions produced medium to large debiasing effects immediately (games ≥ −31.94% and videos ≥ −18.60%) that persisted at least 2 months later (games ≥ −23.57% and videos ≥ −19.20%). Games that provided personalized feedback and practice produced larger effects than did videos. Debiasing effects were domain general: bias reduction occurred across problems in different contexts, and problem formats that were taught and not taught in the interventions. The results suggest that a single training intervention can improve decision making. We suggest its use alongside improved incentives, information presentation, and nudges to reduce costly errors associated with biased judgments and decisions.

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.

Serious Efforts at Bias Reduction

2018 ◽  
Vol 30 (1) ◽  
pp. 16-28 ◽  
Author(s):  
Adrienne Shaw ◽  
Kate Kenski ◽  
Jennifer Stromer-Galley ◽  
Rosa Mikeal Martey ◽  
Benjamin A. Clegg ◽  
...  
Keyword(s):  
Learning Outcomes ◽  
Cognitive Processes ◽  
Serious Games ◽  
Cognitive Biases ◽  
Digital Games ◽  
Blind Spot ◽  
Bias Reduction ◽  
Effective Learning ◽  
Training Video ◽  
Bias Blind Spot

Abstract. As research on serious games continues to grow, we investigate the efficacy of digital games to train enhanced decision making through understanding cognitive biases. This study investigates the ability of a 30-minute digital game as compared with a 30-minute video to teach people how to recognize and mitigate three cognitive biases: fundamental attribution error, confirmation bias, and bias blind spot. We investigate the effects of character customization on learning outcomes as compared with an assigned character. We use interviews to understand the qualitative differences between the conditions. Experimental results suggest that the game was more effective at teaching and mitigating cognitive biases than was the training video. Although interviews suggest players liked avatar customization, results of the experiment indicate that avatar customization had no significant effect on learning outcomes. This research provides information future designers can use to choose the best medium and affordances for the most effective learning outcomes on cognitive processes.

scholarly journals Debiasing Training Improves Decision Making in the Field

2019 ◽  
Vol 30 (9) ◽  
pp. 1371-1379 ◽  
Author(s):  
Anne-Laure Sellier ◽  
Irene Scopelliti ◽  
Carey K. Morewedge
Keyword(s):  
Decision Making ◽  
Space Shuttle ◽  
Confirmation Bias ◽  
Business Case ◽  
Private Life ◽  
Professional Programs ◽  
Training Interventions ◽  
Space Shuttle Challenger ◽  
Natural Variance ◽  
To Receive

The primary objection to debiasing-training interventions is a lack of evidence that they improve decision making in field settings, where reminders of bias are absent. We gave graduate students in three professional programs ( N = 290) a one-shot training intervention that reduces confirmation bias in laboratory experiments. Natural variance in the training schedule assigned participants to receive training before or after solving an unannounced business case modeled on the decision to launch the Space Shuttle Challenger. We used case solutions to surreptitiously measure participants’ susceptibility to confirmation bias. Trained participants were 19% less likely to choose the inferior hypothesis-confirming solution than untrained participants. Analysis of case write-ups suggests that a reduction in confirmatory hypothesis testing accounts for their improved decision making in the case. The results provide promising evidence that debiasing-training effects transfer to field settings and can improve decision making in professional and private life.

scholarly journals Bilinguals are less susceptible to the bias blind spot in their second language

2021 ◽  
Author(s):  
Paweł Niszczota ◽  
Magdalena Pawlak ◽  
Michal Bialek
Keyword(s):  
Decision Making ◽  
Second Language ◽  
Foreign Language ◽  
Mixed Model ◽  
Blind Spot ◽  
Main Hypothesis ◽  
Attenuation Effect ◽  
Bias Blind Spot ◽  
Processing Information ◽  
Blind Spots

Extant research suggests that processing information in a second language (L2) affects decision making, possibly by affecting metacognition. We hypothesized that processing in L2 will reduce the bias blind spot effect, whereby people (on average) erroneously think that they are less susceptible to biases than others. In Experiment 1, participants assessed their susceptibility and the susceptibility of others to 13 psychological and 7 economic biases, in either L1 (Polish) or L2 (English). In Experiment 2, participants assessed the 7 most severe bias blind spots from Experiment 1. We recruited 500 participants for each experiment via Prolific (832 overall, after exclusions). The main hypothesis and moderators were tested via mixed-model regressions. In Experiment 1, participants showed an overall bias blind spot, which decreased in the L2 condition, but only for psychological biases. In Experiment 2, we replicated the L2-bias blind spot attenuation effect. An exploratory analysis suggests that the effect of L2 is the result of both lower ratings of other-susceptibility and higher ratings of self-susceptibility. Our study provides unique insights on how L2 affects metacognition. We are the first to study how use of L2 can attenuate the bias blind spot. Our findings provide rare support for the psychological distancing (‘birds-eye view’) explanation for the foreign language effect. Bilinguals using L2 showed some resilience to the bias blind spot, suggesting metacognition is language-dependent. Using L2 can be considered as a debiasing technique.

Errors in Surgical Neuropathology and the Influence of Cognitive Biases: The Psychology of Intelligence Analysis

2006 ◽  
Vol 130 (5) ◽  
pp. 613-616 ◽  
Author(s):  
Roger E. McLendon
Keyword(s):  
Decision Making ◽  
Cognitive Psychology ◽  
Medical Decision Making ◽  
Cognitive Biases ◽  
Correct Diagnosis ◽  
Data Sources ◽  
Medical Decision ◽  
Intelligence Analysis ◽  
First Impression ◽  
Decision Making Processes

Abstract Context.—A significant difficulty that pathologists encounter in arriving at a correct diagnosis is related to the way information from various sources is processed and assimilated in context. Objective.—These issues are addressed by the science of cognitive psychology. Although cognitive biases are the focus of a number of studies on medical decision making, few if any focus on the visual sciences. Data Sources.—A recent publication authored by Richards Heuer, Jr, The Psychology of Intelligence Analysis, directly addresses many of the cognitive biases faced by neuropathologists and anatomic pathologists in general. These biases include visual anticipation, first impression, and established mindsets and subconsciously influence our critical decision-making processes. Conclusions.—The book points out that while biases are an inherent property of cognition, the influence of such biases can be recognized and the effects blunted.

The Bias Blind Spot Across Childhood

2018 ◽  
Vol 36 (6) ◽  
pp. 671-708 ◽  
Author(s):  
Sara Hagá ◽  
Kristina R. Olson ◽  
Leonel Garcia-Marques
Keyword(s):  
Blind Spot ◽  
Bias Blind Spot

Training for Decision Making in Aircraft Inspection

1993 ◽  
Vol 37 (18) ◽  
pp. 1267-1271 ◽  
Author(s):  
Anand K. Gramopadhye ◽  
Colin G. Drury ◽  
Joseph Sharit
Keyword(s):  
Decision Making ◽  
Visual Inspection ◽  
Human Factor ◽  
Preliminary Results ◽  
Training Interventions ◽  
Training Scheme ◽  
Civil Aircraft ◽  
Inspection And Maintenance ◽  
Inspection Task

Research on civil aircraft inspection and maintenance has shown the potential for employing human factor interventions in improving performance. A series of training experiments was developed to understand the effects of different training interventions in the visual inspection domain. This paper reports on preliminary results obtained in applying a combined active and progressive part training scheme in improving the decision making performance for a visual inspection task. The task was a computer simulated airframe visual inspection task.

scholarly journals Advanced Deep Learning Model

2021 ◽  
Author(s):  
Yew Kee Wong
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Decision Making ◽  
Deep Learning ◽  
Learning Algorithms ◽  
Learning Model ◽  
Intelligence Analysis ◽  
Basic Parameters ◽  
Deep Learning Model ◽  
Learning Sets

Deep learning is a type of machine learning that trains a computer to perform human-like tasks, such as recognizing speech, identifying images or making predictions. Instead of organizing data to run through predefined equations, deep learning sets up basic parameters about the data and trains the computer to learn on its own by recognizing patterns using many layers of processing. This paper aims to illustrate some of the different deep learning algorithms and methods which can be applied to artificial intelligence analysis, as well as the opportunities provided by the application in various decision making domains.

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