Discrepancy between social and nonsocial decision-making under uncertainty following prefrontal lobe damage: the impact of an interactionist approach

Empirical evaluations of uncertainty visualizations often employ complex experimental tasks to ensure ecological validity. However, if training for such tasks is not sufficient for naïve participants, differences in performance could be due to the visualizations or to differences in task comprehension, making interpretation of findings problematic. Research has begun to assess how training is related to performance on decision-making tasks using uncertainty visualizations. This study continues this line of research by investigating how training, in general, and feedback, in particular, affect performance on a simulated resource allocation task. Additionally, we examined how this alters metacognition and workload to produce differences in cognitive efficiency. Our results suggest that, on a complex decision-making task, training plays a critical role in performance with respect to accuracy, subjective workload, and cognitive efficiency. This study has implications for improving research on complex decision making, and for designing more efficacious training interventions to assess uncertainty visualizations.

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Adaptive Modeling for Risk-Aware Decision Making

Proceedings of the AAAI Conference on Artificial Intelligence ◽

10.1609/aaai.v33i01.33019896 ◽

2019 ◽

Vol 33 ◽

pp. 9896-9897

Author(s):

Sandhya Saisubramanian

Keyword(s):

Decision Making ◽

Autonomous Agent ◽

Decision Making Under Uncertainty ◽

Risk Awareness ◽

Reasoning Under Uncertainty ◽

Adaptive Modeling ◽

Trade Off ◽

Core Capability ◽

The Impact

This thesis aims to provide a foundation for risk-aware decision making. Decision making under uncertainty is a core capability of an autonomous agent. A cornerstone for with long-term autonomy and safety is risk-aware decision making. A risk-aware model fully accounts for a known set of risks in the environment, with respect to the problem under consideration, and the process of decision making using such a model is risk-aware decision making. Formulating risk-aware models is critical for robust reasoning under uncertainty, since the impact of using less accurate models may be catastrophic in extreme cases due to overly optimistic view of problems. I propose adaptive modeling, a framework that helps balance the trade-off between model simplicity and risk awareness, for different notions of risks, while remaining computationally tractable.

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Self-reported Daily Sleep Quality Modulates the Impact of the Framing Effect on Outcome Evaluation in Decision-Making Under Uncertainty: An ERP Study

Neuropsychologia ◽

10.1016/j.neuropsychologia.2021.107864 ◽

2021 ◽

pp. 107864

Author(s):

Sihua Xu ◽

Qingqing Liu ◽

Cencen Wang

Keyword(s):

Decision Making ◽

Sleep Quality ◽

Framing Effect ◽

Outcome Evaluation ◽

Decision Making Under Uncertainty ◽

The Impact

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Uncertainty Aversion and Its Role in Travel Decision Making Under Uncertainty

International Journal of Strategic Decision Sciences ◽

10.4018/ijsds.2017010101 ◽

2017 ◽

Vol 8 (1) ◽

pp. 1-12 ◽

Cited By ~ 1

Author(s):

Zheng Li

Keyword(s):

Decision Making ◽

Travel Time ◽

Model Performance ◽

Time Variability ◽

Decision Making Under Uncertainty ◽

Uncertainty Aversion ◽

Choice Data ◽

Data Set ◽

The Impact ◽

Travel Time Variability

Travel time variability is a random phenomenon, and within the presence of it, uncertainty is associated with decision making. When a choice is made in an uncertain situation, the probability distribution is based on the subjective judgments of a decision maker. This paper introduces a psychological perspective to the concept of travel time variability, by embedding a belief-based weighting, so as to better understand decision making under uncertainty. This research argues that a subjective probability approach accounting for degrees of belief should be addressed in order to capture the impact of travel time variability on decision making. Using a simulated choice data set, the author provides an example of modelling uncertainty aversion, and illustrate its impacts on model performance.

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Experience and rationality under risk: re-examining the impact of sampling experience

Experimental Economics ◽

10.1007/s10683-019-09641-y ◽

2020 ◽

Vol 23 (4) ◽

pp. 1100-1128

Author(s):

Ilke Aydogan ◽

Yu Gao

Keyword(s):

Decision Making ◽

Expected Utility ◽

Decision Models ◽

Decision Making Under Uncertainty ◽

Probability Weighting ◽

Sampling Without Replacement ◽

Decisions Under Risk ◽

Lack Of Control ◽

The Impact ◽

Small Probabilities

Abstract A recent strand of the literature on decision-making under uncertainty has pointed to an intriguing behavioral gap between decisions made from description and decisions made from experience. This study reinvestigates this description-experience gap to understand the impact that sampling experience has on decisions under risk. Our study adopts a complete sampling paradigm to address the lack of control over experienced probabilities by requiring complete sampling without replacement. We also address the roles of utilities and ambiguity, which are central in most current decision models in economics. Thus, our experiment identifies the deviations from expected utility due to over- (or under-) weighting of probabilities. Our results confirm the existence of the behavioral gap, but they provide no evidence for the underweighting of small probabilities within the complete sampling treatment. We find that sampling experience attenuates rather than reverses the inverse S-shaped probability weighting under risk.

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Quota Women Are Threatening to Men

Swiss Journal of Psychology ◽

10.1024/1421-0185/a000195 ◽

2017 ◽

Vol 76 (3) ◽

pp. 107-116 ◽

Cited By ~ 4

Author(s):

Klea Faniko ◽

Till Burckhardt ◽

Oriane Sarrasin ◽

Fabio Lorenzi-Cioldi ◽

Siri Øyslebø Sørensen ◽

...

Keyword(s):

Decision Making ◽

Organizational Performance ◽

Gender Stereotypes ◽

Perceived Threat ◽

Preferential Treatment ◽

Public Sector Employees ◽

Different Types ◽

Low Levels ◽

Women In Decision Making ◽

The Impact

Abstract. Two studies carried out among Albanian public-sector employees examined the impact of different types of affirmative action policies (AAPs) on (counter)stereotypical perceptions of women in decision-making positions. Study 1 (N = 178) revealed that participants – especially women – perceived women in decision-making positions as more masculine (i.e., agentic) than feminine (i.e., communal). Study 2 (N = 239) showed that different types of AA had different effects on the attribution of gender stereotypes to AAP beneficiaries: Women benefiting from a quota policy were perceived as being more communal than agentic, while those benefiting from weak preferential treatment were perceived as being more agentic than communal. Furthermore, we examined how the belief that AAPs threaten men’s access to decision-making positions influenced the attribution of these traits to AAP beneficiaries. The results showed that men who reported high levels of perceived threat, as compared to men who reported low levels of perceived threat, attributed more communal than agentic traits to the beneficiaries of quotas. These findings suggest that AAPs may have created a backlash against its beneficiaries by emphasizing gender-stereotypical or counterstereotypical traits. Thus, the framing of AAPs, for instance, as a matter of enhancing organizational performance, in the process of policy making and implementation, may be a crucial tool to countering potential backlash.

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