The effects of disappointment on hindsight bias for real-world outcomes

Application of Uncertainty Thought Environment in Judicial Adjudication Based on Cognitive Psychology

The uncertainty of judicial decision-making has a deep and extensive theoretical foundation. Theoretical analysis starts with a reflection on legal rationalism that challenges the legal certainty before delving deeply into the case's facts and the entire legal system. In light of this, this paper explores a novel approach to enhance the reasoning mechanism of trial documents from the viewpoint of modern cognitive psychology, concentrating on the parties' and the public's cognitive processes to justice. It is suggested to use an inert hierarchical multilabel classification algorithm. In order to predict the category of invisible examples, the extended multilabel training set is first searched for adjacent samples of invisible examples, and the classification weight and confidence of each category are then determined in accordance with these adjacent samples. The group of invisible examples is then anticipated. Experimental comparison demonstrates that this algorithm outperforms other prediction techniques; the macro accuracy, macro recall, and macro F1 of this method are, respectively, 0.896, 0.871, and 0.814. It has some advantages in many multilabel evaluation indexes when compared to other multilabel algorithms.

How Will the Occupation End? A Real-World Exploration of Hindsight Bias and Retroactive Pessimism Concerning Antigovernment Protests in Bulgaria

We explored hindsight bias and retroactive pessimism related to the occupation of Sofia University in 2013–2014, using a memory design. We found partial evidence for hindsight bias for predictions of whether the occupation would achieve its goal (the government's resignation) but not for specific events related to the occupation, which were deemed unlikely from the start and later perceived not to have occurred. We did not find evidence for retroactive pessimism: Hindsight bias indices for the prediction of the government's resignation were not reliably associated with support for the occupation and disappointment with its outcome. We propose using a recall/reconstruct measure as a more rigorous test for retroactive pessimism, which has so far been demonstrated through reassessment.

Older and younger adults' hindsight bias after positive and negative outcomes

After learning about facts or outcomes of events, people overestimate in hindsight what they knew in foresight. Prior research has shown that this hindsight bias is more pronounced in older than in younger adults. However, this robust finding is based primarily on a specific paradigm that requires generating and recalling numerical judgments to general knowledge questions that deal with emotionally neutral content. As older and younger adults tend to process positive and negative information differently, they might also show differences in hindsight bias after positive and negative outcomes. Furthermore, hindsight bias can manifest itself as a bias in memory for prior given judgments, but also as retrospective impressions of inevitability and foreseeability. Currently, there is no research on age differences in all three manifestations of hindsight bias. In this study, younger (N = 46, 18-30 years) and older adults (N = 45, 64-90 years) listened to everyday-life scenarios that ended positively or negatively, recalled the expectation they previously held about the outcome (to measure the memory component of hindsight bias), and rated each outcome's foreseeability and inevitability. Compared with younger adults, older adults recalled their prior expectations as closer to the actual outcomes (i.e., they showed a larger memory component of hindsight bias), and this age difference was more pronounced for negative than for positive outcomes. Inevitability and foreseeability impressions, however, did not differ between the age groups. Thus, there are age differences in hindsight bias after positive and negative outcomes, but only with regard to memory for prior judgments.

Hindsight Bias and Electoral Outcomes: Satisfaction Counts More Than Winner-Loser Status

The tendency to perceive outcomes as more foreseeable once they are available is a well-known phenomenon. However, research on the cognitive and motivational factors that induce individuals to overestimate the foreseeability of an electoral outcome has yielded inconsistent findings. In three studies based on large-scale electoral surveys (ITANES, Italian National Election Studies), we argued that the tendency to perceive an electoral outcome as foreseeable is positively and consistently associated with satisfaction with the outcome. Across all studies, satisfaction with the outcome was significantly and positively associated with retrospective foreseeability, above and beyond voters’ preference for a “winning” or “losing” party. In Study 3, a measure of memory distortion of pre-electoral forecasts was included, which was only weakly associated with retrospective foreseeability, but not with satisfaction for the outcome, supporting the notion of different levels of hindsight bias associated with different cognitive and motivational factors.

Hindsight Bias

Hindsight bias occurs when people feel that they "knew it all along," that is, when they believe that an event is more predictable after it becomes known than it was before it became known. Hindsight bias embodies any combination of three aspects: memory distortion, beliefs about events' objective likelihoods, or subjective beliefs about one's own prediction abilities. Hindsight bias stems from (a) cognitive inputs (people selectively recall information consistent with what they now know to be true and engage in sensemaking to impose meaning on their own knowledge), (b) metacognitive inputs (the ease with which a past outcome is understood may be misattributed to its assumed prior likelihood), and (c) motivational inputs (people have a need to see the world as orderly and predictable and to avoid being blamed for problems). Consequences of hindsight bias include myopic attention to a single causal understanding of the past (to the neglect of other reasonable explanations) as well as general overconfidence in the certainty of one's judgments. New technologies for visualizing and understanding data sets may have the unintended consequence of heightening hindsight bias, but an intervention that encourages people to consider alternative causal explanations for a given outcome can reduce hindsight bias.