Overconfidence effects in category learning: A comparison of connectionist and exemplar memory models.

Sieck, Winston R.; Yates, JoAnne

doi:10.1037/0278-7393.27.4.1003

Cited by 40 publications

(54 citation statements)

References 69 publications

(96 reference statements)

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“…Also, numerous distinct attempts to reduce overconfidence have been made in various task settings, and with varying degrees of theoretical motivation (e.g. Arkes, Christensen, Lai, & Blumer, 1987;Griffin & Buehler, 1999;Koriat, Lichtenstein, & Fischhoff, 1980;Sieck & Yates, 2001). However, several of the proposed manipulations have met with only mixed success.…”

Section: Introductionmentioning

confidence: 99%

The recalcitrance of overconfidence and its contribution to decision aid neglect

Sieck

Arkes

2005

Behavioral Decision Making

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102

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Three experiments tested the hypothesis that people's overconfidence in the quality of their intuitive judgment strategies contributes to their reluctance to use helpful actuarial judgment aids. Participants engaged in a judgment task that required them to use five cues to decide whether a prospective juror favored physician-assisted suicide. Participants had the opportunity to examine the judgments of a statistical equation that correctly classified 77% of the prospective jurors. In all experiments, participants infrequently examined the equation, performed worse than the equation, and were highly overconfident. In Experiments 1 and 2, outcome feedback and calibration feedback failed to reduce overconfidence. In Experiment 3, enhanced calibration feedback reduced overconfidence and increased reliance on the equation, thus leading to improved judgment performance.

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Section: Introductionmentioning

confidence: 99%

The recalcitrance of overconfidence and its contribution to decision aid neglect

Sieck

Arkes

2005

Behavioral Decision Making

Self Cite

102

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“…An example of work at the computational level would be investigations that attempt to document the existence of unconscious cognitive biases that emerge during the financial decision making process, such as the overconfidence effect (Sieck & Yates, 2001) and delay discounting (Shamosh et al, 2008). Research at the third (and most basic) level of analysis examines the biological basis of financial and economic decisions.…”

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confidence: 99%

Impact of retirement worry on information processing.

Gutierrez¹,

Hershey²

2013

Journal of Neuroscience, Psychology, and Economics

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Clinically anxious individuals have been shown to process psychologically threatening words (e.g., worry) more slowly than words that are unrelated to their disorder (e.g., hammer). In the present investigation, working adults (N ϭ 87) with different levels of financially linked retirement anxiety were investigated using the Emotional Stroop Task (EST). The EST involves presenting financially relevant retirement threat words (e.g., poverty) on a computer screen in addition to nonretirement neutral words (e.g., sailboat). Words were presented individually in 1 of 4 different colors of ink. Respondents' task was to identify the ink color for each word as rapidly as possible. It was hypothesized that individuals with high levels of retirement anxiety would generate slower response latencies when naming the color of retirement threat words relative to neutral words. No such processing delay was predicted for nonanxious participants. ANOVA findings revealed a 2-way interaction that was consistent with a priori predictions. The data suggest working adults with retirement anxiety experienced information processing disruptions that stem from the negative emotional content linked to retirement concepts in long-term memory. From an applied perspective, these processing disruptions may represent a significant obstacle that needs to be surmounted when encouraging individuals with retirement anxiety to plan and save for the future.

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“…Another approach could involve an extension of the present task to category learning (Sieck & Yates, 2001) or multiple-cue probability learning (MCPL) tasks (White & Koehler, 2004), involving probabilistic as opposed to discrete informational cues. Indeed, White and Koehler (2004) developed and tested alternative models for dealing with missing information in a MCPL medical diagnosis task.…”

Section: Discussionmentioning

confidence: 99%

Aggregating conclusive and inconclusive information: Data and a model based on the assessment of threat

Baranski¹,

Petrusic²

2009

Behavioral Decision Making

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This study examined the process of combining conclusive and inconclusive information using a Naval threat assessment simulation. On each of 36 trials, participants interrogated 10 pieces of information (e.g., speed, direction, bearing, etc.) about ''targets'' in a simulated radar space. The number of hostile, peaceful, and inconclusive cues was factorially varied across targets. Three models were developed to understand how inconclusive information is used in the judgment of threat. According to one model, inconclusive information is ignored and the judgment of threat is based only on the conclusive information. According to a second model, the amount of dominant conclusive information is normalized by all of the available information. Finally, according to a third model, inconclusive information is partitioned under the assumption that it equally represents both dominant and non-dominant evidence. In Experiment 1, the data of novices (i.e., civilians) were best described by a model that assumes a partitioning of inconclusive evidence. This result was replicated in a second experiment involving variation of the global threat context. In a third experiment involving experts (i.e., Canadian Navy officers), the data of half of the participants were best described by the partitioning model and the data of the other half were best described by the normalizing model. In Experiments 1 and 2, the presence of inconclusive information produced a ''dilution effect'', whereby hostile (peaceful) targets were judged as less hostile (peaceful) than the predictions of the Partitioning model. The dilution effect was not evident in the judgments of the Navy officers. # 2009 Crown in the right of Canada. key words inconclusive information; threat assessment; subjective probability; confidence; balance of evidence; dilution effect

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Overconfidence effects in category learning: A comparison of connectionist and exemplar memory models.

Cited by 40 publications

References 69 publications

The recalcitrance of overconfidence and its contribution to decision aid neglect

The recalcitrance of overconfidence and its contribution to decision aid neglect

Impact of retirement worry on information processing.

Aggregating conclusive and inconclusive information: Data and a model based on the assessment of threat

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