Subjective Uncertainty Research Articles

The Paradoxical Effect of Repeated Body Checking on Subjective Uncertainty.

Body checking is considered a behavioral expression of the core psychopathology of eating disorders (EDs), namely, overvaluation of body weight and shape. Compulsive checking is motivated by a desire to increase a sense of certainty regarding feared outcomes. Paradoxically, studies showed that repeated checking acts to reduce certainty, forming a vicious cycle. No previous study examined whether the same principle applies for body checking. This study filled this gap by examining the causal effect of repeated body checking on memory certainty regarding checked body parts. In a laboratory-based study, 77 female participants without an ED checked the size and shape of six body parts. Their objective memory regarding which body part was last checked, and subjective certainty about this memory were assessed. Then, one group of participants continued to engage in repeated body checking, and another group repeatedly checked a neutral object. Finally, all participants completed the six body parts checking procedure again, and their objective memory and memory certainty were re-assessed. In both checking groups, objective memory regarding the last body part checked was unaffected by the type of checking performed. Importantly, certainty about memory dropped considerably only among those in the repeated body-checking group. The findings provide the first empirical evidence of a paradoxical effect demonstrating that repeated body checking reduces certainty about checked body parts. The study implies that repeated body checking reduces the quality of information obtained through checking and, as such, could potentially motivate further checking.

Helping in Times of War: How Uncertainty Modulates Aid to Ukrainian Refugees through Compassion and Threat

Abstract The present paper focuses on the antecedents of solidarity behavior towards Ukrainian refugees, specifically examining the role of subjective uncertainty generated in public opinion by the aggression of Ukraine on feelings of compassion and perceptions of refugees as a threat. Based on pooled data from six representative samples collected in different waves during the first six months of the Russian army’s invasion of Ukraine among a representative sample of adult Italian citizens (N = 6,063), the study provided support for the intensification hypothesis, suggesting that uncertainty can act as an affective amplifier. Indeed, the results showed that uncertainty increased perceptions of refugees as a threat (acting on its emotional component, i.e., anxiety), but also feelings of compassion, which is a main driver of solidarity. Moreover, compassion seemed to reduce the (perceived) threat posed by refugees on an economic, cultural, security, or political level. The pattern of relationships tested in the model proved to be stable across different areas of the country and for the first 6 months of the Russian invasion, suggesting that the empathic concern generated by the suffering of the Ukrainian population under attack did not significantly diminish its effects over the period considered.

Smart detection of subsurface anomalies: Concept, validation and applications

Naturally formed and engineering-induced subsurface anomalies (e.g., cavities and sinkholes) jeopardize infrastructure safety and hinder urban sustainability. Here we report a smart sensing method to detect subsurface anomalies based on the physical characteristics extracted from the effective signals scattered and reflected directly from these anomalies. Potential anomalies at submeter scales can be interpreted based on a sharp variation of anomaly score relative to the background anomaly score, showing the advantage of overcoming subjective uncertainty and biases involved in the traditional geophysical methods. We find that the use of scattered and reflected waves in an intermediate frequency range is well-suited for sensing deep subsurface infrastructure at high resolutions required for civil structures. We also demonstrate that a fast and reliable detection of subsurface anomalies relies solely on the physical characteristics of seismic data in two field cases, promoting geologic hazard forecast and decision-making effectiveness.

Noise reverses the oblique effect: A horizontal effect in orientation estimation and subjective uncertainty

Noise reverses the oblique effect: A horizontal effect in orientation estimation and subjective uncertainty

Understanding uncertainty shocks and the role of black swans

Uncertainty shocks can trigger business cycles, bank runs and asset price fluctuations. But how do those shocks translate into changes in beliefs and actions? What makes people suddenly become uncertain? This paper provides an explanation for subjective uncertainty shocks, estimated on real-time GDP data, that fits puzzling features of professional forecasts. The key ingredients are that agents do not know the true model governing the distribution of macroeconomic outcomes, but they believe that distribution to be potentially skewed. When agents estimate higher probabilities of extreme tail events, their uncertainty rises. Our estimates reveal that learning about probabilities of tail events – black swans – explains much of the fluctuations in subjective uncertainty.

Neural Representations of Sensory Uncertainty and Confidence Are Associated with Perceptual Curiosity.

Humans are immensely curious and motivated to reduce uncertainty, but little is known about the neural mechanisms that generate curiosity. Curiosity is inversely associated with confidence, suggesting that it is triggered by states of low confidence (subjective uncertainty), but the neural mechanisms of this link, have been little investigated. Inspired by studies of sensory uncertainty, we hypothesized that visual areas provide multivariate representations of uncertainty, which are read out by higher-order structures to generate signals of confidence and, ultimately, curiosity. We scanned participants (17 female, 15 male) using fMRI while they performed a new task in which they rated their confidence in identifying distorted images of animals and objects and their curiosity to see the clear image. We measured the activity evoked by each image in the occipitotemporal cortex (OTC) and devised a new metric of "OTC Certainty" indicating the strength of evidence this activity conveys about the animal versus object categories. We show that, perceptual curiosity peaked at low confidence and OTC Certainty negatively correlated with curiosity, establishing a link between curiosity and a multivariate representation of sensory uncertainty. Moreover, univariate (average) activity in two frontal areas-vmPFC and ACC-correlated positively with confidence and negatively with curiosity, and the vmPFC mediated the relationship between OTC Certainty and curiosity. The results reveal novel mechanisms through which uncertainty about an event generates curiosity about that event.

Does age matter in inflation uncertainty?

This letter studies age-heterogeneous inflation uncertainty. We contrast two measures of uncertainty: The variance of the respondents' subjective belief distribution and the relatively objective rounding-based uncertainty. Inconsistency of two measures suggests that older individuals may underestimate inflation uncertainty while the young tend to overestimate it. This is further supported by the observation that older individuals have higher prediction errors. The research indicates a potential bias in subjective uncertainty assessments of different age groups.

Decision Theory, Subjective Uncertainty, and Computer Science

I argue that further integration between Decision Theory and the methods of quantifying complexity and evaluating performance in Computer Science is valuable. I review [Lanzani 2024] as an illustration of this combination.

2020 Klein Lecture—Investment and Subjective Uncertainty

AbstractA longstanding challenge in evaluating the impact of uncertainty on investment is obtaining measures of managers’ subjective uncertainty. We address this challenge by using a detailed survey measure of uncertainty collected by the U.S. Census Bureau for approximately 25,000 manufacturing plants. We find three key results. First, investment is negatively associated with higher uncertainty. Second, uncertainty is also negatively related to employment growth and overall shipments growth, which highlights the damaging impact of uncertainty. Third, rental capital and temporary workers are positively correlated with uncertainty, demonstrating that businesses switch from less flexible to more flexible inputs under uncertainty.

Variability of Uncertainty in Mental Reconstruction of Danger and Safety

Subjective images of danger and security depend on the context of uncertainty. This article introduces a mental reconstruction of danger and safety for different types of uncertainty. The authors used the methods of associative experiment, subjective ranking, and semantic differential. The empirical data were processed by averaging, ranking, factor analysis, and the Mann-Whitney criterion. The survey involved students from several Russian metropolitan and provincial universities (19–20 y.o.; n = 105; 74 females). Danger demonstrated a less complex mental structure than safety. The mental reconstruction of danger / safety included three types of uncertainty. Temporal uncertainty included period, time, and frequency of danger / safety. Objective uncertainty was connected with the place, environment, and source of danger / safety. Subjective uncertainty covered controllability, scale, and cause of danger / safety. Uncertainty proved more important for danger than for safety. The subjective level of danger grew together with objective uncertainty, especially when the source of danger was unclear, and went down with temporal uncertainty. The subjective level of security increased with temporal and subjective uncertainty and decreased with objective uncertainty. When the subjective significance of danger and safety went up, the differentiation of uncertainty in their assessment became less significant. The study identified the effect of variability of uncertainty on the mental reconstruction made by the subjects of danger / security, as well as identified some understudied areas.

Deep learning‐based grain‐size decomposition model: A feasible solution for dealing with methodological uncertainty

ABSTRACTTerrigenous clastic sediments cover a large area of the Earth's surface and provide valuable insights into the Earth's evolution and environmental change. Sediment grain‐size decomposition has been widely used as an effective approach to inferring changes in sediment sources, transport processes and depositional environments. Several algorithms, such as single sample unmixing, end‐member modelling analysis and the universal decomposition model, have been developed for grain‐size decomposition. The performance of these algorithms is highly dependent on parameter selections, introducing subjective uncertainty. This uncertainty could undermine the reliability of decomposition results, limit the application of grain‐size decomposition techniques and reduce comparability across different studies. To mitigate the methodological uncertainty, a novel deep learning‐based framework for grain‐size decomposition of terrigenous clastic sediments is proposed. First, an improved universal decomposition model is used to analyse the collected grain‐size data, in order to provide training sets for the end‐to‐end decomposers. To meet the data size requirements of supervised learning, generative adversarial networks are also trained for data augmentation. The performance of the new framework is then evaluated using a small‐scale dataset (73 393 samples from 18 sites) of three sedimentary types (loess, fluvial and lake delta deposits). The decomposed grain‐size results demonstrate high feasibility and great potential of the framework in constructing a robust grain‐size decomposition model. Finally, it is proposed that future grain‐size research should aim to establish guidelines for grain‐size data sharing and produce a big grain‐size database for deep learning.

Extrapolative Uncertainty and Household Economic Behavior

We examine the uncertainty in households’ expectations regarding macroeconomic outcomes, namely inflation and the rate of nationwide home price growth. We document that people extrapolate from the instability of their personal and local environment when assessing the future volatility of these macroeconomic variables. Consequently, there are within-person spillovers in subjective uncertainty regarding different economic outcomes. This extrapolative behavior is more pronounced among lower-numeracy individuals, and it persists throughout the business cycle. People with more uncertain macroeconomic expectations are more likely to engage in precautionary behaviors regarding consumption and equity market exposure and are more concerned about credit market access. This paper was accepted by David Simchi-Levi, finance. Supplemental Material: The data files are available at https://doi.org/10.1287/mnsc.2023.00820 .

Cognitive ability and stock market participation: evidence from China

PurposeIt is imperative for policymakers, financial institutions, and individual investors to comprehend the factors that impact stock market participation, given the growing significance of the stock market in terms of personal and national wealth. This study endeavours to explore the relationship between cognitive ability and participation in the stock market. We examine the relationship between cognitive abilities and stock market participation, and further explore the mechanism of their influence.Design/methodology/approachThe data from the China Family Panel Studies is utilized, and Tobit and Probit regressions are employed. Additionally, an instrumental variable approach (IV-estimate) is implemented to address the endogeneity issue linked to cognitive ability, and the study’s findings are resilient.FindingsThe results reveal a significant positive relationship between cognitive ability and stock market participation. Additionally, the findings suggest that households with higher cognitive ability tend to aggregate more information, expand social networks, and take more risks. A likely explanation is that individuals with higher cognitive ability are more likely to process more external information and evaluate the subjective uncertainty of stock markets based on a well-defined probability distribution. Our findings indicate that the impact of cognitive ability on stock market participation varies among families with differing education levels, genders, marital statuses, and geographical locations.Originality/valueTherefore, the roles of cognitive abilities in accelerating stock market participation should be fully considered. More information channels and sources that contain financial markets’ information (e.g. mobile applications and financial education) should be provided. Thus, the significance of cognitive ability in increasing stock market participation should be fully considered. Providing more information channels and sources, such as mobile applications and financial education, that contain financial markets’ information would be helpful. Our study contributes to promoting financial literacy and inclusion by highlighting the significant positive impact of cognitive ability, where institutions can tailor their outreach efforts and information channels to better serve individuals with different cognitive ability.

Interpersonal alignment of neural evidence accumulation to social exchange of confidence.

Private, subjective beliefs about uncertainty have been found to have idiosyncratic computational and neural substrates yet, humans share such beliefs seamlessly and cooperate successfully. Bringing together decision making under uncertainty and interpersonal alignment in communication, in a discovery plus pre-registered replication design, we examined the neuro-computational basis of the relationship between privately held and socially shared uncertainty. Examining confidence-speed-accuracy trade-off in uncertainty-ridden perceptual decisions under social vs isolated context, we found that shared (i.e. reported confidence) and subjective (inferred from pupillometry) uncertainty dynamically followed social information. An attractor neural network model incorporating social information as top-down additive input captured the observed behavior and demonstrated the emergence of social alignment in virtual dyadic simulations. Electroencephalography showed that social exchange of confidence modulated the neural signature of perceptual evidence accumulation in the central parietal cortex. Our findings offer a neural population model for interpersonal alignment of shared beliefs.

Mode choice support through an integrated Delphi-fuzzy logic model

This paper proposes a fuzzy logic mode choice model combined with a Delphi method to extract inference rules, representing the evaluation processes performed by experts. The model covers railway, road, and inland waterway networks and can handle imprecise information about the level of input variables. This fuzziness arises from the attitude and perception of decision-makers and subjective uncertainties. It extends existing models beyond optimisation and includes influential and interrelated input variables. The Rotterdam-Venlo multi-modal freight corridor in the Netherlands is selected as a case study to demonstrate the model's applicability. The model can be used to assist freight forwarders in understanding possible mode choice directions under a certain scenario, support policymakers in testing the effectiveness of designed or implemented policies (e.g. emission reduction), and give insights to infrastructure managers about performance developments by tracing possible effects of planned investments on the mode choice and possible demand shifts.

Dealing with uncertain situations

ABSTRACT There are two ways for a situation to be uncertain. Subjective uncertainty refers to not knowing facts. Objective uncertainty refers to future events that have not been determined yet. A wide ranging literature review finds that subjective uncertainty inhibits behavior, increases conserving resources and willpower, and stimulates search for information – though in crude, sometimes dysfunctional fashion. In contrast, objective uncertainty calls for action, reflected in agentic control, increased arousal, and greater willingness to take risks. Again, some responses are irrational, such as exerting more effort for less expected reward, and betting more on uncontrollable future than past events. With both kinds of uncertainty, attention is mobilized and emotion is prolonged. Our review uncovered multiple signs that some uncertainty is beneficial and heightens enjoyment as a kind of spice of life, or, in some cases, as a welcome hope that a bad outcome might still be avoided.

How does temporal blurring alter movement timing?

Subjective uncertainty arises because the estimation of the timing of an event into the future is error prone. This impact of stimulus-bound uncertainty on movement preparation has often been investigated using reaction time tasks where a warning stimulus (WS) predicts the occurrence of a 'go' signal. The timing of the 'go' signal can be chosen from a particular probability distribution with a given variance or uncertainty. It has been repeatedly shown that reaction times covary with the shape of the used 'go' signal distribution. This is interpreted as evidence for temporal preparation. Moreover, the variance of the response time should always increase with the duration of the delay between the WS and the 'go' signal. This increasing variance has been interpreted as a consequence of the temporal 'blurring' of future events (scalar expectancy).The present paper tested the validity of the temporal 'blurring' hypothesis in humans with a simple oculomotor reaction time task where subjective and stimulus-bound uncertainties were increased. Subjective uncertainty about the timing of a 'go' signal was increased by lengthening the delay between the WS and the 'go' signal. Objective uncertainty was altered by increasing the variance of 'go' signal timing. Contrary to temporal blurring hypotheses, the study has shown that increasing the delay between events did not significantly increase movement timing variability. These results suggest that temporal blurring could not be a property of movement timing in an implicit timing context.Significance StatementIt is often assumed that the estimation of the timing of a distant future event is more error prone (or variable) than the estimation of a closer one. This phenomenon is referred to as temporal 'blurring'. Metaphorically, this could be compared in the spatial domain with the blurring of a visual stimulus when perceived at an increasing distance. Surprisingly, in the current oculomotor implicit timing task, movement variability actually decreased with the increasing temporal delay between a warning and an imperative 'go' signal. Therefore, temporal blurring is not a general property but depends on the precise context of timing behaviour.

An Evaluation Model for the Influence of KOLs in Short Video Advertising Based on Uncertainty Theory

In the era of rapid growth in the short video industry, it is very important to find more accurate suitable advertising promoters, namely Key Opinion Leaders, to promote the development of short video commerce. A mathematical method is needed to grade and evaluate KOL’s abilities. Only in this way can advertisers better determine the value of KOL and determine whether it is suitable for promoting its products. Moreover, in the hierarchical evaluation of KOL, there is not only structured and quantifiable information, but also a large amount of unstructured and linguistic non-quantifiable information. Therefore, this article regards unquantifiable information as an uncertain variable and uses a comprehensive evaluation method based on uncertainty theory to handle subjective uncertainty in the evaluation process. Among them, all uncertain variables are symmetric. The main contribution of this article is the provision of a new evaluation method for KOL grading. Firstly, a two-level evaluation index system for KOL was established. Secondly, the importance and annotation of the Index set are set as uncertain variables, and the KOL evaluation model is constructed. Finally, two KOLs on TikTok were selected for comparative analysis to determine the importance ranking and KOL scores of each level of indicator, verifying the effectiveness and practicality of this method.

Quantifying subjective uncertainty in survey expectations

An increasing number of household and firm surveys ask for subjective probabilities that the inflation rate falls into various outcome ranges. We provide a new measure of the uncertainty implicit in such probabilities. The measure has several advantages over existing methods: It is robust, trivial to implement, requires no functional form assumptions, and is well-defined for all logically possible probabilities. These advantages are particularly relevant when analyzing microdata from extensive consumer surveys. We illustrate the new measure using data from the Survey of Consumer Expectations.

Evaluation of employment quality of college graduates based on interval MULTIMOORA with combination weights

PurposeThe purpose of this paper is to develop a novel interval Multi-Objective Optimization by a Ratio Analysis plus the Full Multiplicative Form(MULTIMOORA) with combination weights to evaluate the employment quality of college graduates, where the criteria are expressed by interval numbers and the weights of criteria are completely unknown.Design/methodology/approachFirstly, considering the subjective uncertainty of the weights of the criteria, the interval best worst method (I-BWM) was present to determine the subjective weights of the criteria. Secondly, by the improved interval number distance measure, an improved interval deviation maximization method (I-MDM) was introduced to detemine the objective weights. In the following, based on the I-BWM and the improved I-MDM, a combination weighting method that takes into account the subjective and objective weights is proposed. Finally, a multi-criteria decision-making method based on the interval MULTIMOORA with combination weights is present to evaluate the employment quality of college graduates, and then a comparative analysis with some of the existing distance measures of interval numberswas conducted to illustrate the flexibility.FindingsAccording to the data of the Report on Employment Quality of Chinese College Graduats released by Mycos Research Institute in 2016–2020 and 2021–2022, the proposed method was used to evaluate the employment quality of college graduates during the period before and after the COVID-19 epidemic. The results verify that the method is more reasonable because the subjective and objective weights of the criteria can be fully considered. Finally, the feasibility and practicability of the proposed method are further verified by varying parameters.Originality/valuePresent an evaluation method on the employment quality of college graduates based on the Interval MULTIMOORA with combination weights considering the subjective and objective weights. And the proposed method is proved that it can provide a more reasonable evaluation results. At the same time, it is verified that the feasibility and the practicability of the proposed method are affected by varying parameters in the paper.