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Evaluating information quality online is increasingly important for healthy decision‐making. People assess information quality using visual interfaces (e.g., computers, smartphones) with visual cues like aesthetics. Yet, voice interfaces lack critical visual cues for evaluating information because there is often no visual display. Without ways to assess voice‐based information quality, people may overly trust or misinterpret information which can be challenging in high‐risk or sensitive contexts. This paper investigates voice information uncertainty in one high‐risk context—health information seeking. We recruited 30 adults (ages 18–84) in the United States to participate in scenario‐based interviews about health topics. Our findings provide evidence of information uncertainty expectations with voice assistants, voice search preferences, and the audio cues they use to assess information quality. We contribute a nuanced discussion of how to inform more critical information ecosystems with voice technologies and propose ways to design audio cues to help people more quickly assess content quality. [ABSTRACT FROM AUTHOR]

Abstract: In managing various threats to biodiversity, it is important to prioritize multiple management actions and the levels of effort to apply. However, a spatial conservation prioritization framework that integrates these key aspects, and can be generalized, is still missing. Moreover, assessing the robustness of prioritization frameworks to uncertainty in species responses to management is critical to avoid misallocation of limited resources. Yet, the impact of information uncertainty on prioritization of management effort remains unknown. We present an approach for prioritizing alternative levels of conservation management effort to multiple actions, based on the ecological responses of species to management. We estimated species responses through a structured email‐based expert elicitation process, where we also captured the uncertainty in individual experts' assessments. We identified priority locations and associated level of management of effort of four actions to abate threats to freshwater‐dependent fauna, using a northern Australia case study, and quantified sensitivity of the proposed solution to uncertainty in the answers of each individual expert. Achievement of conservation targets for freshwater‐dependent fauna in the Daly River catchment would require 9.4 million AU$ per year, for a total of approximately 189 million AU$ investment over 20 years. We suggest that this could be best achieved through a mix of aerial shooting of buffalos and pigs, riparian fencing and chemical spraying of weeds, applied at varying levels of management effort in key areas of the catchment. Uncertainty in experts' estimation of species responses to threats causes 60% of the species to achieve 80% of their conservation targets, which was consistent across target levels. Synthesis and applications. Our prioritization approach facilitates the planning of conservation management at fine spatial scales and is applicable to terrestrial, freshwater and marine realms. Plan implementation may require policy instruments ranging from landowner stewardship agreements, market‐based mechanisms and low‐intensity land use management schemes, to regulation of commercial activities within portions of marine protected areas. However, assessing plan sensitivity to uncertainty in species response to management and finding ways of dealing with it in the prioritization rather than ignoring it, as often done, remains vital for effective achievement of conservation objectives. [ABSTRACT FROM AUTHOR]

Fault diagnosis is of great significance in maintaining the safe and stable operation of a system. Fast and precise location of faults is important for restoring power supply systems. In this paper, considering the interference of information uncertainty to fault diagnosis under different weather conditions, a fault diagnosis model based on Bayesian network is proposed. The model inherits the capability of processing uncertain information of a Bayesian network and divides the information into historical information and evidence information. The uncertainty of historical information is reduced by modifying the parameters through improving parameter learning formulas, while that of evidence information can be reduced by logical judgment. A fault simulation model based on Monte Carlo method is used to generate simulation data for parameter learning, and a case study confirms the correctness of the proposed fault diagnosis and fault simulation models. © 2018 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc. [ABSTRACT FROM AUTHOR]

Subjective time dilation is an effect discovered using the oddball paradigm, where expanding visual stimuli, but not shrinking ones, induce a prolongation of subjective temporal perception compared to static stimuli. This disparity is often seen as another demonstration of humans' evolved reaction to approaching threats, since visual expansion resembles approaching potential threats and warrants extra attention. In this study, we show that by manipulating the relative sizes of stimuli, both expanding and shrinking stimuli can induce prolongation of subjective time in an oddball paradigm. We propose an alternative explanation based on information theory, linking subjective temporal perception to entropy, an objective property of stimulus that is information uncertainty. Temporal function as a logistic function thus serves as the framework inside which content functions like information processing are able to operate coherently. [ABSTRACT FROM AUTHOR]

The uncertainty of alarm information in power grids can lead to incorrect diagnosis of faults. The authors propose a method for diagnosing power grid faults that considers the uncertainty of alarm information using intuitionistic fuzzy logic. To consider the influence of the uncertainty of alarm information in fault diagnosis, an intuitionistic fuzzy set is used to represent the certainty and the uncertainty of alarm information. Using topological analysis and the logical relationships among electrical devices, protective actions, and circuit breaker trips, the authors establish a diagnostic model for power systems based on intuitionistic fuzzy Petri nets. The certainty and the uncertainty of electrical device fault events are calculated using the reasoning method for intuitionistic fuzzy Petri nets. The results for some test cases show that this method can effectively diagnose complex faults in power systems when multiple components operate incorrectly in the complicated data environment and the information is not trusted. [ABSTRACT FROM AUTHOR]

Does political uncertainty affect whether lobbyists contact government officials? We suggest that the answer depends on the type of uncertainty introduced. Distinguishing between policy objective uncertainty—where organized interests and lobbyists are uncertain about the policy intentions of decision makers—and issue information uncertainty—where policymakers are uncertain about the technical details of issues—we hypothesize that whereas an increase in policy objective uncertainty leads to a decrease in lobbying, a rise in issue information uncertainty leads to more lobbying. We test the hypotheses with longitudinal data from the Canadian Lobbyists Registry measuring change in the number of times lobbyists have contacted government ministries each month from 2008 to 2018. The results suggest that lobbying intensity does respond differently to these types of uncertainty. Whereas events introducing issue information uncertainty have a statistically significant positive relationship with lobbying, events introducing policy objective uncertainty do not. [ABSTRACT FROM AUTHOR]

Product development efforts now more than ever are in need of methodologies that can address the challenges of increased system complexities, shortening time to market, increased demands in mass customization, market instabilities, geographical barriers, improved innovation, and adaptability to emerging technologies. To address these challenges most companies will need to make key decisions early in the product development life‐cycle. In this early phase there are high levels of information uncertainty and information ambiguity. Under these circumstances many companies will converge too early to a point design (Point Based Design—PBD) which will lead to increased cost and schedule delays due to reworking the design later in the product development life cycle. To overcome these challenges many researchers have proposed the Set‐Based Design (SBD) methodology. However, there has been limited guidance on how to define, reason, and narrow sets while improving the level of abstraction of the design. To address such concerns, a literature review was conducted. The contributions of this research include: (1) aggregated literature from over 100 sources on quantitative methods (QM) that has not been considered SBD but does support set‐based thinking, (2) consolidated body of knowledge on QM to help industrial practitioners implement SBD, (3) ​defined gaps and opportunities for future research, and (4) defined strengths and limitations of QM and techniques to define, reason and narrow sets. [ABSTRACT FROM AUTHOR]

An emerging infectious disease event like the coronavirus (COVID‐19) pandemic demands careful communication of public health messages to diverse audiences. However, misinformation is easily generated and amplified when a rapidly evolving epidemiological situation is coupled with gaps in scientific knowledge about a novel pathogen. Groups involved in health policy research, advocacy, implementation, and enforcement must be aware of three key challenges as they develop and apply communication strategies during emergencies: (i) information overload, (ii) information uncertainty, and (iii) misinformation. These challenges can be countered by accurately communicating core messages to specific audiences, being transparent about the evidence base for recommendations and open about the likelihood that guidelines may change as scientific discoveries are made, and identifying which myths and conspiracy theories circulating on social media are so harmful that they must be directly countered. Data analytics can assist with the process of monitoring and evaluating the impact of organizational communications. [ABSTRACT FROM AUTHOR]

The scale and complexity associated with the coordinated response to natural disasters inevitably produce human errors. However, little is known about the frequency and distribution of human error at different levels of coordination during disasters. The purpose of this research was to explore this phenomenon for selected catastrophic bushfires in Australia. To accomplish this, we used the Human Factors Analysis and Classification System that has been widely applied to accidents but is untested with respect to the complexity and temporality of disasters. The results identified that decision errors made during these disasters differed depending upon the level of coordination but were associated with information uncertainty, fatigue, coordination complexities, procedural violations, and degraded personal interactions. [ABSTRACT FROM AUTHOR]

Objective While previous studies document racial discrimination in Major League Baseball, few have considered statistical discrimination, and how racial bias may spill over into related markets. Investigating rookie card (RC) values at their initial release, we exploit the role of information uncertainty to separately identify the influence of racial discrimination and statistical discrimination. Methods Using ordinary least squares (OLS) and Tobit models, we examine 6,026 cards released from 1986 to 1993. After documenting race-based differentials in MLB achievement, we explore the determinants of prices in certain and uncertain environments. Results RCs of black players carry a 14-20 percent premium at their initial release. Race does not influence card values once careers are finished. Finally, given comparable career performance, prices for black players decline significantly more over time. Collectively, this suggests statistical discrimination influences consumers in this market. Conclusion Racial discrimination in an upstream market can lead to spillover effects on related downstream markets. [ABSTRACT FROM AUTHOR]