Judging Truth.

Deceptive claims surround us, embedded in fake news, advertisements, political propaganda, and rumors. How do people know what to believe? Truth judgments reflect inferences drawn from three types of information: base rates, feelings, and consistency with information retrieved from memory. First, people exhibit a bias to accept incoming information, because most claims in our environments are true. Second, people interpret feelings, like ease of processing, as evidence of truth. And third, people can (but do not always) consider whether assertions match facts and source information stored in memory. This three-part framework predicts specific illusions (e.g., truthiness, illusory truth), offers ways to correct stubborn misconceptions, and suggests the importance of converging cues in a post-truth world, where falsehoods travel further and faster than the truth.

Recollection of "true" feedback is better than "false" feedback independently of a priori beliefs: an investigation from the perspective of dual-recollection theory.

The processes underlying memory for truth and falsity have been explored and discussed in experimental psychology for over thirty years now. Psychologists have often referred to the Spinozan and Cartesian models about truth-value information "tagging" but, so far, experimental results have been inconsistent. This paper investigates memory for truth and falsity from the new perspective of the dual-recollection theory. We conducted two experiments using the conjoint recognition paradigm and multinomial modelling as a measurement model. Both our experiments confirmed a satisfactory goodness of fit of the data to the dual-recollection multinomial model. In Experiment 1, the context recollection parameter representing memory for feedback information was significantly higher for true than for false statements. This finding was replicated in the second experiment, which controlled the potential impact of participants' previous knowledge on memory performance. Experiment 2 indicated that the target recollection parameter representing memory for the sentence itself was significantly higher for true than for false sentences solely when participants believed this sentence to be true but not when they perceived it as false before the memory experiment. Our research was the first attempt to look at memory for truth and falsity from the perspective of the recently developed dual-recollection theory.

More evidence against the Spinozan model: Cognitive load diminishes memory for "true" feedback.

We tested two competing models on the memory representation of truth-value information: the Spinozan model and the Cartesian model. Both models assume that truth-value information is represented with memory "tags," but the models differ in their coding scheme. According to the Cartesian model, true information is stored with a "true" tag, and false information is stored with a "false" tag. In contrast, the Spinozan model proposes that only false information receives "false" tags. All other (i.e., untagged) information is considered as true by default. Hence, in case of cognitive load during feedback encoding, the latter model predicts a load effect on memory for "false" feedback, but not on memory for "true" feedback. To test this prediction, participants studied trivia statements (Experiment 1) or nonsense statements that allegedly represented foreign-language translations (Experiment 2). After each statement, participants received feedback on the (alleged) truth value of the statement. Importantly, half of the participants experienced cognitive load during feedback processing. For the trivia statements of Experiment 1, we observed a load effect on memory for both "false" and "true" feedback. In contrast, for the nonsense statements of Experiment 2, we found a load effect on memory for "true" feedback only. Both findings clearly contradict the Spinozan model. However, our results are also only partially in line with the predictions of the Cartesian model. For this reason, we suggest a more flexible model that allows for an optional and context-dependent encoding of "true" tags and "false" tags.

The source of the truth bias: Heuristic processing?

People believe others are telling the truth more often than they actually are; this is called the truth bias. Surprisingly, when a speaker is judged at multiple points across their statement the truth bias declines. Previous claims argue this is evidence of a shift from (biased) heuristic processing to (reasoned) analytical processing. In four experiments we contrast the heuristic-analytic model (HAM) with alternative accounts. In Experiment 1, the decrease in truth responding was not the result of speakers appearing more deceptive, but was instead attributable to the rater's processing style. Yet contrary to HAMs, across three experiments we found the decline in bias was not related to the amount of processing time available (Experiments 1-3) or the communication channel (Experiment 2). In Experiment 4 we found support for a new account: that the bias reflects whether raters perceive the statement to be internally consistent.

Trust or distrust? Neither! The right mindset for confronting disinformation.

A primary explanation for why individuals believe disinformation is the truth bias, a predisposition to accept information as true. However, this bias is context-dependent, as research shows that rejection becomes the predominant process in a distrust mindset. Consequently, trust and distrust emerge as pivotal factors in addressing disinformation. The current review offers a more nuanced perspective by illustrating that whereas distrust may act as an antidote to the truth bias, it can also paradoxically serve as a catalyst for belief in disinformation. The review concludes that mindsets other than those rooted solely in trust (or distrust), such as an evaluative mindset, may prove to be more effective in detecting and refuting disinformation.

Plausibility matters: A challenge to Gilbert's "Spinozan" account of belief formation.

Most of the claims we encounter in real life can be assigned some degree of plausibility, even if they are new to us. On Gilbert's (1991) influential account of belief formation, whereby understanding a sentence implies representing it as true, all new propositions are initially accepted, before any assessment of their veracity. As a result, plausibility cannot have any role in initial belief formation on this account. In order to isolate belief formation experimentally, Gilbert, Krull, and Malone (1990) employed a dual-task design: if a secondary task disrupts participants' evaluation of novel claims presented to them, then the initial encoding should be all there is, and if that initial encoding consistently renders claims 'true' (even where participants were told in the learning phase that the claims they had seen were false), then Gilbert's account is confirmed. In this pre-registered study, we replicate one of Gilbert et al.'s (1990) seminal studies ("The Hopi Language Experiment") while additionally introducing a plausibility variable. Our results show that Gilbert's 'truth bias' does not hold for implausible statements - instead, initial encoding seemingly renders implausible statements 'false'. As alternative explanations of this finding that would be compatible with Gilbert's account can be ruled out, it questions Gilbert's account.

Did You Just Lie to Me? Deception Detection in Face to Face versus Computer Mediated Communication.

Individuals' deception detection ability during either a face-to-face (FtF) interaction or through computer-mediated communication (CMC) was explored under more naturalistic conditions where they were not forewarned that deception may be involved. Participants discussed a social issue either in a room together or by instant messaging from separate rooms. Prior to discussion, some participants were asked to deceive their partner regarding their actual opinion on the issue. Results showed that mode of communication did not influence participants' deception detection accuracy rate, nor their truth bias. Regardless of mode of communication, deceptive participants experienced the same level of physiological arousal as the non-deceivers. In contrast, deceivers reported experiencing higher levels of anxiety but only in the FtF condition. Findings highlight how for different communication modalities, a multitude of interactive factors may influence deception detection.

How humans impair automated deception detection performance.

BACKGROUND: Deception detection is a prevalent problem for security practitioners. With a need for more large-scale approaches, automated methods using machine learning have gained traction. However, detection performance still implies considerable error rates. Findings from different domains suggest that hybrid human-machine integrations could offer a viable path in detection tasks. METHOD: We collected a corpus of truthful and deceptive answers about participants' autobiographical intentions (n = 1640) and tested whether a combination of supervised machine learning and human judgment could improve deception detection accuracy. Human judges were presented with the outcome of the automated credibility judgment of truthful or deceptive statements. They could either fully overrule it (hybrid-overrule condition) or adjust it within a given boundary (hybrid-adjust condition). RESULTS: The data suggest that in neither of the hybrid conditions did the human judgment add a meaningful contribution. Machine learning in isolation identified truth-tellers and liars with an overall accuracy of 69%. Human involvement through hybrid-overrule decisions brought the accuracy back to chance level. The hybrid-adjust condition did not improve deception detection performance. The decision-making strategies of humans suggest that the truth bias - the tendency to assume the other is telling the truth - could explain the detrimental effect. CONCLUSIONS: The current study does not support the notion that humans can meaningfully add the deception detection performance of a machine learning system. All data are available at https://osf.io/45z7e/.

How Information on a Motive to Lie Influences CBCA-Based Ratings and Veracity Judgments.

We investigated how information on a motive to lie impacts on the perceived content quality of a statement and its subsequent veracity rating. In an online study, 300 participants rated a statement about an alleged sexual harassment on a scale based on Criteria-based Content Analysis (CBCA) and judged its veracity. In a 3 × 3 between-subjects design, we varied prior information (motive to lie, no motive to lie, and no information on a motive), and presented three different statement versions of varying content quality (high, medium, and low). In addition to anticipating main effects of both independent variables (motive information and statement version), we predicted that the impact of motive information on both ratings would be highest for medium quality statements, because their assessment is especially ambiguous (interaction effect). Contrary to our hypotheses, results showed that participants were unaffected by motive information and accurately reproduced the manipulated quality differences between statement versions in their CBCA-based judgments. In line with the expected interaction effect, veracity ratings decreased in the motive-to-lie group compared to controls, but only when the medium- and the low-quality statements were rated (truth ratings dropped from approximately 80 to 50%). Veracity ratings in both the no-motive-to-lie group and controls did not differ across statement versions (≥82% truth ratings). In sum, information on a motive to lie thus encouraged participants to consider content quality in their veracity judgments by being critical only of statements of medium and low quality. Otherwise, participants judged statements to be true irrespective of content quality.

Impact of Adult Attachment Anxiety on Deception Judgments: Examining the Moderating Effect of Motivation.

Several psychologists have paid attention to individual differences in deception detection, but only a few studies have found significant results. The present study aimed to explore the relationship between attachment anxiety and deception judgment when there are no obvious cues to distinguish lies from truth, and to examine the moderating effect of motives. Participants were instructed to judge each of 10 audios on whether they were true or false. Subsequently, the attachment anxiety of participants was assessed using the Experiences in Close Relationships questionnaire. Results revealed that, compared with people who had low attachment anxiety, those with high attachment anxiety tend to have higher truth biases in the low-motive condition and lower accuracy in the high-motive condition.

Aligning Spinoza with Descartes: An informed Cartesian account of the truth bias.

There is a bias towards believing information is true rather than false. The Spinozan account claims there is an early, automatic bias towards believing. Only afterwards can people engage in an effortful re-evaluation and disbelieve the information. Supporting this account, there is a greater bias towards believing information is true when under cognitive load. However, developing on the Adaptive Lie Detector (ALIED) theory, the informed Cartesian can equally explain this data. The account claims the bias under load is not evidence of automatic belief; rather, people are undecided, but if forced to guess they can rely on context information to make an informed judgement. The account predicts, and we found, that if people can explicitly indicate their uncertainty, there should be no bias towards believing because they are no longer required to guess. Thus, we conclude that belief formation can be better explained by an informed Cartesian account - an attempt to make an informed judgment under uncertainty.

Detecting deceptive behaviour after the fact.

This study examined whether people can detect deception after the fact if they initially accept someone's behaviour at face value but then learn that they have been duped. Fifty-four groups composed of four to six mutual friends engaged in a group discussion with a financial incentive for arriving at a correct decision. One member of each group was secretly assigned to sabotage the decision. Although none of the participants noticed the deception when it was committed, they showed substantial accuracy in identifying the saboteur once they were told that a deception had occurred. Nevertheless, interrogation did not increase the accuracy of their detection of deception. Participants showed a significant positive relationship between confidence and accuracy. Finally, participants also showed better-than-chance accuracy in their judgments of who believed them during the interrogation and who did not. These results suggest that the detection of deception might often be accomplished using information gained after the fact to reinterpret behaviours that were not initially suspected.