Accuracy Motivation Research Articles

Effects of Health-related Deepfakes on Misperceptions: Moderating Effects of Issue Relevance and Accuracy Motivation

ABSTRACT Among its many applications, artificial intelligence (AI) can be used to manipulate audiovisual content for malicious intents. Such manipulations – which are commonly known as deepfakes – present a significant obstacle to maintaining truth in sectors that serve the public interest, and it is necessary to take proactive fact-checking actions to respond to the threat they pose. The current study conducted an online experiment focusing on the topic of cancer prevention. In this experiment, we further examined the influence of individual differences, such as issue relevance and motns, in health information consumption. When compared to textual disinformation, health-related audiovisual deepfakes were found to have a significant effect on increasing misperceptions but no such effect on fact-checking intentions. We also found that exposure to such deepfakes discouraged individuals with high issue relevance from engaging in fact-checking. Deepfakes were also shown to have a particularly potent effect on increasing misperceptions among individuals with high (illusory) accuracy motivations. These findings underscore the need for increased awareness regarding the detrimental effects of health deepfakes in particular and the urgent importance of further elucidating individual variations to ultimately develop more comprehensive approaches to combat deepfakes.

Why do Citizens Choose to Read Fact-Checks in the Context of the Russian War in Ukraine? The Role of Directional and Accuracy Motivations in Nineteen Democracies

The recent surge of false information accompanying the Russian invasion of Ukraine has re-emphasized the need for interventions to counteract disinformation. While fact-checking is a widely used intervention, we know little about citizen motivations to read fact-checks. We tested theoretical predictions related to accuracy-motivated goals (i.e., seeking to know the truth) versus directionally-motivated goals (i.e., seeking to confirm existing beliefs) by analyzing original survey data ( n = 19,037) collected in early April to late May 2022 in nineteen countries, namely Austria, Belgium, Brazil, Czech Republic, Denmark, France, Germany, Greece, Hungary, Italy, Netherlands, Poland, Romania, Serbia, Spain, Sweden, Switzerland, UK, and USA. Survey participants read ten statements about the Russian war in Ukraine and could opt to see fact-checks for each of these statements. Results of mixed models for three-level hierarchical data (level 1: statements, level 2: individuals, and level 3: countries) showed that accuracy motivations were better explanations than directional motivations for the decision to read fact-checks about the Russian war in Ukraine.

Increasing accuracy motivations using moral reframing does not reduce Republicans’ belief in false news

In a pre-registered survey experiment with 2,009 conservative Republicans, we evaluated an intervention that presents having accurate beliefs as consistent with conservative political identity and values (e.g., patriotism, respect for tradition, and religious purity). The intervention caused participants to report placing greater value on accuracy, and placing greater value on accuracy was correlated with successfully rating true headlines as more accurate than false headlines. Yet, the intervention had no significant effect on accuracy judgments. These results suggest that moral reframing, and perhaps interventions based on connecting accuracy motivation with political identity more generally, may not be promising for combatting belief in misinformation.

Attitudinal and behavioral correlates of algorithmic awareness among German and U.S. social media users

Abstract With the increase in algorithms on social media, scholarship is increasingly focused on “algorithmic literacy,” or users’ understanding of algorithms. Algorithmic literacy is multi-faceted (knowledge, attitudes, and behavior), and researchers are still uncovering how these facets are connected. This article presents a preregistered survey of social media users from two western countries: the United States (n = 990) and Germany (n = 1117). Results show key predictors of algorithmic awareness—age, education, frequency of social media use—are the same in both countries. Nevertheless, U.S. social media users show higher algorithmic awareness and more positive attitudes toward algorithms than German social media users, likely due to their higher overall social media usage. Results also indicate that algorithmic awareness predicts attitudes about filtering algorithms depending on users’ defense motivations or accuracy motivations and behaviors to counteract filtering. These patterns have implications for literacy interventions and for increasing algorithmic transparency.

Deliberative panels as a source of public knowledge: A large-sample test of the Citizens' Initiative Review.

Evolving US media and political systems, coupled with escalating misinformation campaigns, have left the public divided over objective facts featured in policy debates. The public also has lost much of its confidence in the institutions designed to adjudicate those epistemic debates. To counter this threat, civic entrepreneurs have devised institutional reforms to revitalize democratic policymaking. One promising intervention is the Citizens' Initiative Review (CIR), which has been adopted into law in Oregon and tested in several other states, as well as Switzerland and Finland. Each CIR gathers a demographically stratified random sample of registered voters to form a deliberative panel, which hears from pro and con advocates and neutral experts while assessing the merits of a ballot measure. After four-to-five days of deliberation, each CIR writes an issue guide for voters that identifies key factual findings, along with the most important pro and con arguments. This study pools the results of survey experiments conducted on thirteen CIRs held from 2010 to 2018, resulting in a dataset that includes 67,120 knowledge scores collected from 10,872 registered voters exposed to 82 empirical claims. Analysis shows that reading the CIR guide had a positive effect on voters' policy knowledge, with stronger effects for those holding greater faith in deliberation. We found little evidence of directional motivated reasoning but some evidence that reading the CIR statement can spark an accuracy motivation. Overall, the main results show how trust in peer deliberation provides one path out of the maze of misinformation shaping voter decisions during elections.

Not all skepticism is “healthy” skepticism: Theorizing accuracy- and identity-motivated skepticism toward social media misinformation

Fostering skepticism has been seen as key to addressing misinformation on social media. This article reveals that not all skepticism is “healthy” skepticism by theorizing, measuring, and testing the effects of two types of skepticism toward social media misinformation: accuracy- and identity-motivated skepticism. A two-wave panel survey experiment shows that when people’s skepticism toward social media misinformation is driven by accuracy motivations, they are less likely to believe in congruent misinformation later encountered. They also consume more mainstream media, which in turn reinforces accuracy-motivated skepticism. In contrast, when skepticism toward social media misinformation is driven by identity motivations, people not only fall for congruent misinformation later encountered, but also disregard platform interventions that flag a post as false. Moreover, they are more likely to see social media misinformation as favoring opponents and intentionally avoid news on social media, both of which form a vicious cycle of fueling more identity-motivated skepticism.

Breaking the mold: examining the effectiveness of techniques to reduce motivated reasoning

ABSTRACT Extensive research in the social sciences has shown that people tend to engage in motivated reasoning when processing information. However, one area of inquiry that has been lacking is examining the effectiveness of different strategies that aim to decrease motivated reasoning. In this paper, we examine three strategies that have been shown to decrease motivated reasoning: accuracy motivation, the common ingroup identity model, and self-affirmation. We begin by replicating previous findings examining the effectiveness of each of these strategies in reducing motivated reasoning. We then extend this line of inquiry by comparing the effects of these three strategies against one another to determine if one of them is more effective at reducing motivated reasoning. To test our hypotheses, we used an experimental design and recruited participants from Prolific.

Managerial advice‐taking—Sharing responsibility with (non)human advisors trumps decision accuracy

AbstractOrganizations are increasingly implementing algorithmic decision aids to advise managerial decision‐making. We study managers' motives behind using advice (human and nonhuman), particularly sharing responsibility versus increasing decision accuracy motives. We conduct an online experiment with experienced managers in a sales forecasting setting and find that managers focus on increasing decision accuracy (sharing responsibility) when they are unable (able) to share responsibility with advisors. Moreover, managers prefer to share responsibility with blamable human advisors over nonhuman advisors unless they perceive algorithms as socially competent. Consequently, the results show that managers are not solely motivated to minimize forecast errors but also to reduce personal responsibility when taking advice. We contribute to the literature by highlighting the opportunistic motives of managers when taking (non)human advice. Our findings also bear important implications for practice. Specifically, firms should be aware of managers' opportunistic advice‐taking motives when implementing algorithmic decision aids.

Accuracy and social motivations shape judgements of (mis)information

The extent to which belief in (mis)information reflects lack of knowledge versus a lack of motivation to be accurate is unclear. Here, across four experiments (n = 3,364), we motivated US participants to be accurate by providing financial incentives for correct responses about the veracity of true and false political news headlines. Financial incentives improved accuracy and reduced partisan bias in judgements of headlines by about 30%, primarily by increasing the perceived accuracy of true news from the opposing party (d = 0.47). Incentivizing people to identify news that would be liked by their political allies, however, decreased accuracy. Replicating prior work, conservatives were less accurate at discerning true from false headlines than liberals, yet incentives closed the gap in accuracy between conservatives and liberals by 52%. A non-financial accuracy motivation intervention was also effective, suggesting that motivation-based interventions are scalable. Altogether, these results suggest that a substantial portion of people’s judgements of the accuracy of news reflects motivational factors.

Sincere or motivated? Partisan bias in advice-taking

Abstract Political divisions have become a central feature of modern life. Here, we ask whether these divisions affect advice-taking from co- and counter-partisans in a nonpolitical context. In an incentivized task assessing the accuracy of nonpolitical news headlines, we find partisan bias in advice-taking: Democratic participants are less swayed by (accurate) information that comes from Republicans compared to the same information from Democrats (Republican participants display no such bias). We then adjudicate between two possible mechanisms for this biased advice-taking: a preference-based account, where participants are motivated to take less advice from counter-partisans because doing so is unpleasant; versus a belief-based account, where participants sincerely believe co-partisans are more competent at the task (even though this belief is incorrect). To do so, we examine the impact of a substantial increase in the stakes, which should increase accuracy motivations (and thereby reduce the relative impact of partisan motivations). We find that increasing the stakes does not reduce biased advice-taking, hence no evidence to support the bias is driven by preference. Consistent with the belief-based account, we find that Democratic participants (incorrectly) believe their co-partisans are better at the task, and this incorrect belief is much less severe among Republican participants. Further supporting the notion that the stated beliefs are sincere, raising the stakes of the belief elicitation of relative partisan competence does not affect the stated beliefs. Finally, participants—instead of ignoring the feedback—actually substantially update in favor of their counter-partisans given feedback that suggests counter-partisans are competent.

Heuristic Thinking and Credibility of Organic Advertising Claims: The Role of Knowledge and Motivations

Consumers are often overexposed to sustainability symbols and claims on food product packages and find it difficult to accurately judge their meaning when making purchase decisions. Based on the heuristic-systematic model (HSM), this paper aims to identify cognitive mechanisms to reduce the heuristic credibility of organic advertising claims and to increase the motivation for searching for more reliable information when making product judgements. Particularly, we hypothesize that knowledge and defense and accuracy motivations affect organic claim credibility, which in turn is related to organic product judgement. Data collected from an experimental between-subject study with a sample of 412 Spanish undergraduates was analyzed using partial least squares. The results indicated that claim credibility was directly related to the attribution of organic properties to products, and was affected by defense motivation especially when appropriate knowledge was not available. Improving consumers’ knowledge reduced organic claim credibility and triggered a positive effect of accuracy motivation on credibility. The findings stress the importance of improving the regulation of ambitious advertising claims and developing specific educational campaigns to empower consumers and prevent biased purchase decisions of organic products.

A Uniter and a Divider: American Presidential Campaigns and Partisan Perceptions of the National Economy

Do American presidential campaigns polarize or unify partisan perceptions? I propose that they do both, where the balance of these countervailing forces varies by context. Campaign messages enable partisan differences, especially in battleground states, but campaigns also promote social contexts that foster accuracy motives and reduce the effects of partisan biases nationwide. After documenting panel data evidence of campaign trends toward unity, further tests compare the national effects of campaign engagement with the local effects of campaign intensity using daily survey data on national economic evaluations. In support of the countervailing forces framework, national engagement in presidential campaigns generally increased levels of cross-partisan agreement by campaign’s end, but local campaign intensity enhanced partisan differences in rate of responsiveness to the campaign. Although targeted campaigns reduced unifying effects in many states, presidential campaigns typically have a net unifying effect on American economic perceptions, thereby strengthening economic voting.

Competitive Frames and Accuracy Motivations

Abstract. To examine the psychological mechanisms involved in value framing effects, the present study extends previous research on competitive frames and tests the mediating role of ambivalence in value framing effects. The current research delves into the nuances of value framing effects and helps explain processes such as applicability. Two web-based experiments were conducted using value frames related to two different issues, civil liberties and gay rights. Findings from moderated-mediation models indicate that when individuals are exposed to competitive frames they feel ambivalent. Because of this ambivalence, participants were more willing to seek information and showed increased online information-seeking behavior. However, these findings are true only in cases of individuals who are motivated to process the information. Implications are discussed.

Susceptibility to mis- and disinformation and the effectiveness of fact-checkers: Can misinformation be effectively combated?

The online dissemination of mis- and disinformation may pose vexing problems on democracy. The factual basis of (political) information may be challenged by opposed partisans or issue publics, and misinformation may impact decision-making as confirmation biases may outweigh accuracy motivations. In this setting, fact-checkers that refute the false claims of misinformation may be regarded as an important tool to combat misinformation. Yet, the effectiveness of corrective information may be contingent upon partisan lenses, or the framing used in misinformation. In this study, the effectiveness of fact-checkers that refute different forms of misinformation on the polarizing issue of crime rates related to anti-immigration framing was assessed in the US and Netherlands. The main findings indicate that exposure to fact-checkers can correct misperceptions on immigration, and lowers the credibility of misinformation. Fact-checkers are more effective in the Netherlands than the US. These findings have important ramifications for understanding citizens’ susceptibility to (partisan) misinformation and rebuttals.

Motivated reconstruction: The effect of brand commitment on false memories.

Across 5 studies, we examine the effect of prior brand commitment on the creation of false memories about product experience after reading online product reviews. We find that brand commitment and the valence of reviews to which consumers are exposed, interact to affect the incidence of false memories. Thus, highly committed consumers are more susceptible to the creation of false experience memories on exposure to positive versus negative reviews, whereas low commitment consumers exhibit similar levels of false memories in response to both positive and negative reviews. Further, these differences across brand commitment are attenuated when respondents are primed with an accuracy motivation, suggesting that the biasing effects of commitment are likely because of the motivation to defend the committed brand. Finally, we find that differences in false memories subsequently lead to differences in intentions to spread word-of-mouth (e.g., recommend the product to friends), suggesting that the consequences of false product experience memories can be significant for marketers and consumers. Our findings contribute to the literatures in false memory and marketing by documenting a motivated bias in false memories because of brand commitment. (PsycINFO Database Record

The illusion of transparency in performance appraisals: When and why accuracy motivation explains unintentional feedback inflation

The present research shows that managers communicate negative feedback ineffectively because they suffer from transparency illusions that cause them to overestimate how accurately employees perceive their feedback. We propose that these illusions emerge because managers are insufficiently motivated to engage in effortful thinking, which reduces the accuracy with which they communicate negative feedback to employees. Six studies (N=1883) using actual performance appraisals within an organization and role plays with MBA students, undergraduates, and online participants show that transparency illusions are stronger when feedback is negative (Studies 1–2), that they are not driven by employee bias (Study 3), and occur because managers are insufficiently motivated to be accurate (Studies 4a–c). In addition, these studies demonstrate that transparency illusions are driven by more indirect communication by the manager and how different interventions can be used to mitigate these effects (Studies 4a–c). An internal meta-analysis including 11 studies from the file drawer (N=1887) revealed a moderate effect size (d=0.43) free of publication bias.

A Metacognitive Model of the Effects of Susceptibility to Persuasion Self-Beliefs on Advertising Effects

This study postulates that people's beliefs about their own susceptibility to persuasion efforts can influence advertising effects. It thus represents the first explication of the process by which self-beliefs determine advertising effects, through their influence on the subjective experience of the ease of being persuaded. Integrating three research streams (metacognition, persuasion knowledge, and cognitive correction), the current study proposes a model of three influence patterns, which are contingent on whether people perceive the advertising message to be high in manipulative intent and whether people are motivated to be accurate in their judgments. If advertising messages are low in manipulative intent, such that the persuasion seems acceptable, susceptibility self-beliefs influence people's attitudes toward the advertised products or issues (i.e., expected effects). If advertising messages are high in manipulative intent, such that persuasion seems unacceptable, people exhibit suppression (no effects) if they have weak accuracy motives, but they exhibit overcorrection (opposite effects) if they are strongly motivated to be accurate. Five studies test these predictions and reveal some demographic characteristics associated with self-beliefs about susceptibility to persuasion. The findings thus have important implications for advertising practitioners.

The anchoring bias reflects rational use of cognitive resources.

Cognitive biases, such as the anchoring bias, pose a serious challenge to rational accounts of human cognition. We investigate whether rational theories can meet this challenge by taking into account the mind's bounded cognitive resources. We asked what reasoning under uncertainty would look like if people made rational use of their finite time and limited cognitive resources. To answer this question, we applied a mathematical theory of bounded rationality to the problem of numerical estimation. Our analysis led to a rational process model that can be interpreted in terms of anchoring-and-adjustment. This model provided a unifying explanation for ten anchoring phenomena including the differential effect of accuracy motivation on the bias towards provided versus self-generated anchors. Our results illustrate the potential of resource-rational analysis to provide formal theories that can unify a wide range of empirical results and reconcile the impressive capacities of the human mind with its apparently irrational cognitive biases.

Considering diversity and accuracy simultaneously for ensemble pruning

Diversity among individual classifiers is widely recognized to be a key factor to successful ensemble selection, while the ultimate goal of ensemble pruning is to improve its predictive accuracy. Diversity and accuracy are two important properties of an ensemble. Existing ensemble pruning methods always consider diversity and accuracy separately. However, in contrast, the two closely interrelate with each other, and should be considered simultaneously. Accordingly, three new measures, i.e., Simultaneous Diversity & Accuracy, Diversity-Focused-Two and Accuracy-Reinforcement, are developed for pruning the ensemble by greedy algorithm. The motivation for Simultaneous Diversity & Accuracy is to consider the difference between the subensemble and the candidate classifier, and simultaneously, to consider the accuracy of both of them. With Simultaneous Diversity & Accuracy, those difficult samples are not given up so as to further improve the generalization performance of the ensemble. The inspiration of devising Diversity-Focused-Two stems from the cognition that ensemble diversity attaches more importance to the difference among the classifiers in an ensemble. Finally, the proposal of Accuracy-Reinforcement reinforces the concern about ensemble accuracy. Extensive experiments verified the effectiveness and efficiency of the proposed three pruning measures. Through the investigation of this work, it is found that by considering diversity and accuracy simultaneously for ensemble pruning, well-performed selective ensemble with superior generalization capability can be acquired, which is the scientific value of this paper.

What’s in Your Wallet? Psychophysical Biases in the Estimation of Money

AbstractThe denomination effect (Raghubir and Srivastava 2009) suggests that individuals are less likely to spend when money is in the form of a single large denomination (e.g., a $10 bill) relative to many smaller denominations (e.g., ten $1 bills). We explore the idea that consumers are reluctant to break large bills because smaller denominations are less easy to monitor and keep track of relative to larger denominations. This increases the likelihood of spending with smaller denominations. In estimating the contents of one’s wallet, money is more difficult to recall, and recalled less accurately the smaller the denomination, and the more the number of units of any denomination. Study 1 demonstrates the biases in a memory-based task, study 2 adds a stimulus-based task, study 3 explores the effect of accuracy motivation and task difficulty, and study 4 links the biases to actual spending. We develop a descriptive psychophysical model of how individuals estimate contents of their wallet and fit the model ...