Confirmation Bias Research Articles

On the Interplay of Data and Cognitive Bias in Crisis Information Management

Humanitarian crises, such as the 2014 West Africa Ebola epidemic, challenge information management and thereby threaten the digital resilience of the responding organizations. Crisis information management (CIM) is characterised by the urgency to respond despite the uncertainty of the situation. Coupled with high stakes, limited resources and a high cognitive load, crises are prone to induce biases in the data and the cognitive processes of analysts and decision-makers. When biases remain undetected and untreated in CIM, they may lead to decisions based on biased information, increasing the risk of an inefficient response. Literature suggests that crisis response needs to address the initial uncertainty and possible biases by adapting to new and better information as it becomes available. However, we know little about whether adaptive approaches mitigate the interplay of data and cognitive biases. We investigated this question in an exploratory, three-stage experiment on epidemic response. Our participants were experienced practitioners in the fields of crisis decision-making and information analysis. We found that analysts fail to successfully debias data, even when biases are detected, and that this failure can be attributed to undervaluing debiasing efforts in favor of rapid results. This failure leads to the development of biased information products that are conveyed to decision-makers, who consequently make decisions based on biased information. Confirmation bias reinforces the reliance on conclusions reached with biased data, leading to a vicious cycle, in which biased assumptions remain uncorrected. We suggest mindful debiasing as a possible counter-strategy against these bias effects in CIM.

Librarians: It’s Time to Redesign Librarianship

The article surveys a few aspects of librarians’ work in light of current events and trends; as library collections become more digitalized than print, virtual librarianship may take the place of conventional work settings; further claims are that librarians are uniquely qualified to take on society’s information literacy problem. Potentially embedding on popular Internet platforms, librarians can help Internet users improve their information discernment skills, so they are better able to find information and identify inaccuracies in the forms of misinformation, disinformation, propaganda, and to be cognizant of confirmation bias.

The relationship between visual confirmation bias, belief consistency, and belief polarization

ABSTRACT Video evidence depicting physical altercations has polarized public opinions and courtroom decisions about social issues including race relations and police use-of-force, we believe, in part because of the way people process dynamic visual stimuli across repeated viewing opportunities. We reanalyzed two studies that covertly collected eye-tracking data to quantify and model visual confirmation bias (VCB) – the degree to which eye movements replicate previous patterns of looking across multiple viewing opportunities. We tracked the location of eye gaze when participants (N1 = 320; N2 = 212) watched the same video twice depicting an altercation between an officer and a civilian (Study 1) or a Black and a White actor (Study 2). In pilot tests, we provided evidence regarding the construct validity of statistical measures of concordance tracking similarities in where perceivers directed eye gaze across viewings as an index of VCB. In our pre-registered analytic plan, we used these metrics to probe for relationships with punishment decisions made about targets after the first and second viewings. Contrary to predictions, our pre-registered analyses found no associations between VCB, consistency, and polarization in punishment. We present exploratory analyses probing potential moderators of the association between VCB and these outcome measures. We offer practical suggestions for researchers measuring and modeling eye gaze during the presentation of dynamic stimuli across multiple viewings, particularly in the context of intergroup decision research.

Fair automated assessment of noncompliance in cargo ship networks

Cargo ships navigating global waters are required to be sufficiently safe and compliant with international treaties. Governmental inspectorates currently assess in a rule-based manner whether a ship is potentially noncompliant and thus needs inspection. One of the dominant ship characteristics in this assessment is the ‘colour’ of the flag a ship is flying, where countries with a positive reputation have a so-called ‘white flag’. The colour of a flag may disproportionately influence the inspector, causing more frequent and stricter inspections of ships flying a non-white flag, resulting in confirmation bias in historical inspection data.In this paper, we propose an automated approach for the assessment of ship noncompliance, realising two important contributions. First, we reduce confirmation bias by using fair classifiers that decorrelate the flag from the risk classification returned by the model. Second, we extract mobility patterns from a cargo ship network, allowing us to derive meaningful features for ship classification. Crucially, these features model the behaviour of a ship, rather than its static properties. Our approach shows both a higher overall prediction performance and improved fairness with respect to the flag. Ultimately, this work enables inspectorates to better target noncompliant ships, thereby improving overall maritime safety and environmental protection.

Reduced Molecular Flavins as Single-Electron Reductants after Photoexcitation.

Flavoenzymes mediate a multitude of chemical reactions and are catalytically active both in different oxidation states and in covalent adducts with reagents. The transfer of such reactivity to the organic laboratory using simplified molecular flavins is highly desirable, and such applications in (photo)oxidation reactions are already established. However, molecular flavins have not been used for the reduction of organic substrates yet, although this activity is known and well-studied for DNA photolyase enzymes. We report a catalytic method using reduced molecular flavins as photoreductants and γ-terpinene as a sacrificial reductant. Additionally, we present our design for air-stable, reduced flavin catalysts, which is based on a conformational bias strategy and circumvents the otherwise rapid reduction of O2 from air. Using our catalytic strategy, we were able to replace superstoichiometric amounts of the rare-earth reductant SmI2 in a 5-exo-trig cyclization of substituted barbituric acid derivatives. Such flavin-catalyzed reductions are anticipated to be beneficial for other transformations as well and their straightforward synthesis indicates future use in stereo- as well as site-selective transformations.

The use of deliberate reflection to reduce confirmation bias among orthopedic surgery residents

Introduction: cognitive biases might affect decision-making processes such as clinical reasoning and confirmation bias is among the most important ones. The use of strategies that stimulate deliberate reflection during the diagnostic process seems to reduce availability bias, but its effect in reducing confirmation bias needs to be evaluated.Aims: to examine whether deliberate reflection reduces confirmation bias and increases the diagnostic accuracy of orthopedic residents solving written clinical cases.Methods: experimental study comparing the diagnostic accuracy of orthopedic residents in the resolution of eight written clinical cases containing a referral diagnosis. Half of the written cases had a wrong referral diagnosis. One group of residents used deliberate reflection (RG), which stimulates comparison and contrast of clinical hypotheses in a systematic manner, and a control group (CG), was asked to provide differential diagnoses with no further instruction. The study included 55 third-year orthopedic residents, 27 allocated to the RG and 28 to the CG.Results: residents on the RG had higher diagnostic scores than the CG for clinical cases with a correct referral diagnosis (62.0±20.1 vs. 49.1±21.0 respectively; p = 0.021). For clinical cases with incorrect referral diagnosis, diagnostic accuracy was similar between residents on the RG and those on the CG (39.8±24.3 vs. 44.6±26.7 respectively; p = 0.662). We observed an overall confirmation bias in 26.3% of initial diagnoses (non-analytic phase) and 19.5% of final diagnoses (analytic phase) when solving clinical cases with incorrect referral diagnosis. Residents from RG showed a reduction in confirmation of incorrect referral diagnosis when comparing the initial diagnosis given in the non-analytic phase with the one provided as the final diagnosis (25.9±17.7 vs. 17.6±18.1, respectively; Cohen d: 0.46; p = 0.003). In the CG, the reduction in the confirmation of incorrect diagnosis was not statistically significant.Conclusions: confirmation bias was present when residents solved written clinical cases with incorrect referral diagnoses, and deliberate reflection reduced such bias. Despite the reduction in confirmation bias, diagnostic accuracy of residents from the RG was similar to those from the CG when solving the set of clinical cases with a wrong referral diagnosis.

Fake news: Why do we believe it?

Fake news dissemination has increased greatly in recent years, with peaks during the US presidential elections and the COVID-19 pandemic. Research has addressed fake news creation, consumption, sharing, and detection as well as approaches to counteract it and prevent people from believing it. This update addresses only a part of the fake news-related issues and focuses on determinants leading individuals to believe fake news, noting that rheumatology is scarcely represented. Some determinants relate to the ecosystem of media and social networks, such as the availability and rapid spread of fake news, the unselected information on platforms and the fact that consumers can become creators of fake news. Cognitive factors are important, such as confirmation bias, political partisanship, prior exposure and intuitive thinking. Low science knowledge and low educational level are also involved. Psychological factors include attraction to novelty, high emotional state, and the emotionally evocative content of fake news. High digital literacy protects against believing fake news. Sociological factors such as online communities, or echo chambers, and the role of pressure groups have been identified. The implication for practice can be deduced, including education in media literacy and warning tips, reliable journalism and fact-checking, social media regulation, partnership of media platforms’ with fact-checkers, warning messages on networks, and digital detection solutions. Health professionals need to better understand the factors that cause individuals to believe fake news. Identifying these determinants may help them in their counseling role when talking to patients about misinformation.

Confirmation bias in simulated CSA interviews: How abuse assumption influences interviewing and decision‐making processes?

AbstractPurposeResearch has shown that confirmation bias plays a role in legal and forensic decision‐making processes and, more specifically, child interviews. However, previous studies often examine confirmation bias in child interviews using non‐abuse‐related events. We enrich the literature by examining interviewers’ behaviours in simulated child sexual abuse (CSA) cases.MethodIn the present study, we used data from a series of experiments in which participants interviewed child avatars to examine how an assumption of abuse based on preliminary information influenced decision‐making and interviewing style. Interview training data (N interview = 2084) from eight studies with students, psychologists and police officers (N = 377) were included in the analyses.ResultsWe found that interviewers’ preliminary assumption of sexual abuse having taken place predicted 1) a conclusion of abuse by the interviewers after the interview; 2) higher confidence in their judgement; 3) more frequent use of not recommended question types and 4) a decreased likelihood of reaching a correct conclusion given the same number of available relevant details.ConclusionThe importance of considering how preliminary assumptions of abuse affect interview behaviour and outcomes and the implications for the training of investigative interviewers were discussed.

Dactylogyridae 2022: a meta-analysis of phylogenetic studies and generic diagnoses of parasitic flatworms using published genetic and morphological data

Dactylogyridae is one of the most studied families of parasitic flatworms with more than 1000 species and 166 genera described to date including ecto- and endoparasites. Dactylogyrid monogeneans were suggested as model organisms for host-parasite macroevolutionary and biogeographical studies due to the scientific and economic importance of some of their host lineages. Consequently, an array of phylogenetic research into different dactylogyrid lineages has been produced over the past years but the last family-wide study was published 16 years ago. Here, we provide a meta-analysis of the phylogenetic relationships of Dactylogyridae including representatives of all genera with available molecular data (n = 67). First, we investigate the systematic informativeness of morphological characters widely used to diagnose dactylogyrid genera through a parsimony analysis of the characters, character mapping, and phylogenetic comparative methods. Second, we provide an overview of the current state of the systematics of the family and its subfamilies, and summarise potentially poly- and paraphyletic genera. Third, we elaborate on the implications of taxonomic, citation, and confirmation bias in past studies. Fourth, we discuss host range, biogeographical, and freshwater-marine patterns. We found two well-supported macroclades which we assigned to the subfamilies Dactylogyrinae and Ancyrocephalinae. These subfamilies further include 16 well-supported clades with only a few synapomorphies that could be deduced from generic diagnoses in the literature. Furthermore, few morphological characters considered systematically informative at the genus level display a strong phylogenetic signal. However, the parsimony analysis suggests that these characters provide little information on the relationships between genera. We conclude that a strong taxonomic bias and low coverage of DNA sequences and regions limit knowledge on morphological and biogeographical evolutionary patterns that can be inferred from these results. We propose addressing potential citation and confirmation biases through a ‘level playing field’ multiple sequence alignment as provided by this study.

Dignity of Risk and Attributions About the Other.

Dignity and indignity, risk and safety, are pairs of concepts on a continuum, and this continuum can have fuzzy boundaries and differing interpretations. Risk is typically defined and apprehended by an actor and an observer and can shift according to time, place, context, and voice. Moreover, when the dignity of risk is considered, it typically involves the subject who is deemed to be taking the risk(s) and the other who is considering protection or safeguards and weighing in at a specific moment in time, focusing on a window of information and conceptualization. This can lead to reflexive responses and confirmatory biases. This article draws on the author's experience as a psychologist and clinical ethicist and focuses on judgments about the other, the meaning of risk, and the confounding nature of human perceptions and attributions about risk. As humans in relationship with each other, we are imperfect evaluators of risk for the other. Humility and an openness to situational factors may open up much needed space for reflection.

Confirmation bias in simulated CSA interviews: How abuse assumption influences interviewing and decision-making processes?

Confirmation bias in simulated CSA interviews: How abuse assumption influences interviewing and decision-making processes?

Soil moisture and expectations regarding future climate: evidence from panel data

The literature on belief regarding climate is extensive, with results showing that both personal characteristics and personal experience with the effects of climate change strongly influence future expectations. The vast majority of studies rely on cross-sectional data, making it difficult to ascertain the durability of expectations regarding future climate or the effect of additional environmental cues on beliefs. A few panel studies of which we are aware exploit extreme weather events to find evidence of “confirmation bias”, in which additional environmental signalling reinforces existing beliefs. In contrast, we evaluate how normal fluctuations in soil moisture causally impact expectations of future drought using a panel of New Zealand farmers. We find that environmental cues such as soil moisture scarcely affect expectations of respondents who already expected future drought to increase but that soil moisture strongly influences respondents who did not. In particular, drier soils are associated with higher expectations of future drought among these former sceptics, whether they previously believed that future drought would decrease or simply would not change. Thus, as New Zealand moves toward IPCC forecasts of more frequent and more severe drought, farmers, foresters, and growers will increasingly agree with the scientific consensus, raising the likelihood of both farm-level and public action.

A Bevy of Biases

This article is in response to and in broad support of Philip Ewell’s keynote talk, “Music Theory’s White Racial Frame,” given at the 2019 Annual Meeting of the Society for Music Theory, and essay, “Music Theory and the White Racial Frame” (".fn_cite_year($ewell_2020)."). In his address and its companion essay, Ewell notes how the repertoire we study and teach, as well as the theories we use to explain it, are manifestations of whiteness. My article will show, first, that the repertory used in the development of theories of harmony and form, as well as (and especially) music theory pedagogy comprises a small, unrepresentative corpus of pieces from the so-called “common practice period” of tonal music, mostly the music of Bach, Haydn, Mozart, and Beethoven, and only a small subset of their output. We (mis)use this repertory due to a combination ofimplicit biasesthat stem from our enculturation as practicing musicians,explicit biasesthat stem from broadly held aesthetic beliefs regarding the status of “great” composers and particular “masterworks,” andconfirmation biasesthat are manifest in our tendency to use only positive testing strategies and/or selective sampling when developing and demonstrating our theories. The theories of harmony and form developed from this small corpus further suffer fromoverfitting, whereby theoretical models are overdetermined relative to the broader norms of a musical practice, and from our tendency to conceive of our theoretic models in terms of tightly regulated “scripts” rather than looser “plans.” For these reasons, simply expanding our analytic and/or pedagogical canon will do little to displace the underlying aesthetic and cultural values that are bound up with it. We must also address the biases that underlie canon formation and valuation and the methodologies that inherently privilege certain pieces, composers, and repertoires to the detriment of others. It is thus argued that working toward greater equity, diversity, and inclusion in music theory goes hand in hand with addressing some of the problematic methodologies that have long plagued our discipline.

The breathing human infrastructure: Integrating air quality, traffic, and social media indicators

Outdoor air pollution is a complex system that is responsible for the deaths of millions of people annually, yet the integration of interdisciplinary data necessary to assess air quality's multiple metrics is still lacking. This case study integrates atmospheric indicators (concentrations of criteria pollutants including particulate matter and gaseous pollutants), traffic indicators (permanent traffic monitoring station data), and social indicators (community responses in Twitter archives) representing the interplay of the three critical pillars of the United Nations' Triple Bottom Line: environment, economy, and society. During the watershed moment of the COVID-19 pandemic lockdowns in Florida, urban centers demonstrated the gaps and opportunities for understanding the relationships, through correlations rather than causations, between urban air quality, traffic emissions, and public perceptions. The relationship between the perception and the traffic variables were strongly correlated, however no correlation was observed between the perception and actual air quality indicators, except for NO2. These observations might consequently infer that traffic serves as people's proxy for air quality, regardless of actual air quality, suggesting that social media messaging around asthma may be a way to monitor traffic patterns in areas where no infrastructure currently exists or is prohibited to build. It also indicates that people are less likely to be reliable sensors to accurately measure air quality due to bias in their observations of traffic volume and/or confirmation biases in broader social discourse. Results presented herein are of significance in demonstrating the capacity for interdisciplinary studies to consider the predictive capacities of social media and air pollution, its use as both lever and indicator of public support for air quality legislation and clean-air transitions, and its ability to overcome limitations of surface monitoring stations.

Behavioral Economics and COVID-19 Vaccine Hesitancy

This research paper will examine the relationship between behavioral economics and COVID-19 vaccine hesitancy within the United States using three heuristics: availability, confirmation bias, and framing. Each heuristic will be precisely defined, and its various mechanisms will be analyzed in great detail in order to understand the reasons behind COVID-19 vaccine hesitancy. Furthermore, the mechanisms of these heuristics will be exploited in order to formulate practical policy recommendations that stakeholders can use to combat vaccine hesitancy and encourage the American public into getting vaccinated, thus complementing the existing choice architecture. This paper will also evaluate existing policies or methods that aim to overcome these biases and increase vaccination uptake.

How Attitudes Impact the Continued Influence Effect of Misinformation: The Mediating Role of Discomfort.

Past research suggests that people continue believing retracted misinformation more when it is consistent versus inconsistent with their attitudes. However, the psychological mechanism responsible for this phenomenon remains unclear. We predicted that retractions of attitude-consistent misinformation produce greater feelings of discomfort than retractions of attitude-inconsistent misinformation and that this discomfort predicts continued belief in and use of the misinformation. We report combined analyses across 10 studies testing these predictions. Seven studies (total N = 1,323) used a mediational framework and found that the more consistent misinformation was with participants' attitudes, the more discomfort was elicited by a retraction of the misinformation. Greater discomfort then predicted greater continued belief in the misinformation, which, in turn, predicted greater use of the misinformation when participants made relevant inferences. Three additional studies (total N = 574) utilized misattribution paradigms to demonstrate that the relation between discomfort and belief in misinformation is causal in nature.

Duped by Bots: Why Some are Better than Others at Detecting Fake Social Media Personas.

We examine individuals' ability to detect social bots among Twitter personas, along with participant and persona features associated with that ability. Social media users need to distinguish bots from human users. We develop and demonstrate a methodology for assessing those abilities, with a simulated social media task. We analyze performance from a signal detection theory perspective, using a task that asked lay participants whether each of 50 Twitter personas was a human or social bot. We used the agreement of two machine learning models to estimate the probability of each persona being a bot. We estimated the probability of participants indicating that a persona was a bot with a generalized linear mixed-effects model using participant characteristics (social media experience, analytical reasoning, and political views) and stimulus characteristics (bot indicator score and political tone) as regressors. On average, participants had modest sensitivity (d') and a criterion that favored responding "human." Exploratory analyses found greater sensitivity for participants (a) with less self-reported social media experience, (b) greater analytical reasoning ability, and (c) who were evaluating personas with opposing political views. Some patterns varied with participants' political identity. Individuals have limited ability to detect social bots, with greater aversion to mistaking bots for humans than vice versa. Greater social media experience and myside bias appeared to reduce performance, as did less analytical reasoning ability. These patterns suggest the need for interventions, especially when users feel most familiar with social media.

Perceived relevance of critical thinking aspects for biology graduate students

ABSTRACT Critical thinking is one of the most important sets of cognitive abilities and dispositions required for both scientists and global citizens. In this explorative study, we examine which critical thinking aspects are perceived as relevant by biology graduate students and in what ways they found these aspects important for their scientific work. Data was collected from two cohorts of students participating in an online academic course focusing on the foundations of critical thinking. The course included weekly sessions in which different critical thinking topics were presented and discussed, followed by a seminar, in which individual students presented, reflected on, and received feedback on their biology research projects. Based on students’ responses and artefacts collected during the course, several critical thinking aspects were identified as most relevant for students’ scientific work, such as confirmation bias, methodological issues, and socio-cultural influences. Students also mentioned the value of open communication with peers when engaging in critical thinking. It is suggested that biology graduate students should have opportunities to learn about and engage with relevant aspects of critical thinking and to collaboratively reflect on their research using these aspects.

Predicting the Oil Investment Decision through Data Mining

Petroleum investment decision remains subject to economic and financial research for decades. Due to capital intensive and higher risk on oil exploration, the investment decision has become more important than ever before. This study aims to shed some light on this issue by conducting four machine learning algorithms to predict the decision applying the dataset from 2007-2019. This study includes the Decision Tree, Random Forest, Naïve Bayes, and Support Vector Machine. A comparative performance analysis is the illustrated using confusion matrix, Cohen’s Kappa value, and the accuracy of each model and Area under the ROC Curve. In this study, a machine learning approach was carried out on the oil exploration data. The findings demonstrate that Naïve Bayes has the most accurate performance for the classification (94.5%), followed by Decision Tree (92.9%), Random Forest (90.9%), and Support Vector Machine (89.6%). In practice, the selected Naïve Bayes model was applied to assess the decision using a new data test. The findings can diminish the subjective blindness and confirmation bias in the investment decision and bring about a reasonable and orderly exploration and development of petroleum reserves.

Paradigm shift for controls on basalt magmatism: Discussion with Lustrino et al on the paper I recently published in Earth-Science Reviews

I recently published “Lithosphere thickness controls the extent of mantle melting, depth of melt extraction and basalt compositions in all tectonic settings on Earth – A review and new perspectives” in this journal to demonstratively summarize a major component of my 30-year dedicated research on the basalt problem with the emphasis that the paradigm “mantle potential temperature controls the extent and pressure of mantle melting and basalt compositions” that is inconsistent with observations and experimental petrology must be abandoned. As the change from “temperature control” to “lithosphere thickness control” is fundamental and unfamiliar to many, I encourage members of the community for debate. The community interest in the theme of the paper is reflected by more than 1000 reads and 50 recommendations in RG within 10 days of its publication. In addition to a few email exchanges, the commentary by Lustrino et al. (2022) is the first written discussion with interesting comments of both breadth and depth. Overall, their commentary is more highly affirmative rather than criticism. Most of the comments are not about Niu (2021) but more general and may be shared by the scientific community. Therefore, my response is intended to be thorough, in particular on issues and concepts that I consider the community needs to be correctly informed of. My reply follows four basic principles: [1] I maintain “Objectiveness and open-mindedness (vs. ‘confirmation bias’) are requisite twins for insights and discoveries.”; [2] I express my views based on observations, experimental petrology, well-understood concepts, logical reasoning and objective analysis, rather than personal opinions to “believe” or “disbelieve”; [3] I emphasize that some misattributions may be innocent, but should be avoided because they serve no favor to our science and scientific discussion; and [4] I try to use plain language to ensure my writing readily understood by the reader. For clarity, my reply follows the same numbered questions as in the commentary and I do not discuss issues on which the commenters agree with me. Figures referenced in quotations are those in Niu (2021). For consistency, mantle potential temperature is denoted with TMP (vs. TP)