Studies have repeatedly shown that mere exposure to ideas makes those ideas seem more true, a finding referred to as the “illusory truth” effect. This feature of cognition may heighten existing concerns surrounding the spread of misinformation. Recent studies have shown that the effect extends to fake news headlines and may increase the likelihood that someone shares misinformation. But is this evidence that mere exposure can affect our beliefs? The two leading accounts of the illusory truth effect argue that after initial exposure, participants sense a feeling of familiarity or “fluency” at test that they use as a sign the statement is true. Beliefs however, extend further than just truth ratings. Beliefs also guide actions and imply other beliefs. Three pre-registered experiments were conducted to examine whether mere exposure to statements induces genuine beliefs by first examining if participants draw implications from mere exposure in Study 1. Surprisingly, results indicated that exposure to “premise” statements affect participants’ truth ratings for novel “implied” statements, which cannot be explained by the familiarity or fluency accounts of the illusory truth effect. Study 2 replicated results from Study 1 and ruled out consistency pressure as an explanation for prior findings. Finally, Study 3 replicated results from Studies 1 and 2 and ensured they were not due to demand characteristics by conducting separate analysis for suspicious and non-suspicious participants. Since these findings cannot be explained by the predominant accounts of the illusory truth effect, the authors believe this is evidence of a new effect the “illusory implication” effect. More importantly, these findings suggest that the consequences of misinformation may be larger than previously thought and warrants further study into potential mechanisms driving the illusory implication effect.

Risk assessments are key legal tools that can inform a number of legal decisions regarding parole sentencing and predict recidivism rates. Due to assessments being historically performed by humans, they can be prone to bias and have come under various amounts of scrutiny. The increased capability and application of machine learning technology has lead the justice system to incorporate algorithms and codes to increase accuracy and reliability. This study researched laypersons’ attitudes towards these algorithms and how they would change when exposed to an algorithm that made errors in the risk assessment process. Participants were tasked with reading two vignettes and answering a series of questions to assess the differences in their perceptions towards machine learning and clinician-based risk assessments. The research findings showed that individuals lent more trust to clinicians and had more confidence in their assessments when compared to machines, but were not significantly more punitive when it came to attributing blame and judgement for the consequences of an incorrect risk assessment. Participants had a significantly more positive attitude towards clinician-based risk assessments, noting their assessments as being more reliable, informed, and trustworthy. Participants were also asked to come to a parole decision using the assessment of either a clinician or machine learning algorithm at the end of the study and rate their own confidence in their decision. Results found that participants were only significantly less confident in their decision when exposed to previous instances of risk assessments with error, but that there was no significant difference in their confidence based solely on who conducted the assessment.

Cyberbullying has become increasingly prevalent, difficult to detect, and harmful to its victims. Whereas correlates of cyberbullying victimization and perpetration have been studied extensively, there has been less research on the critical role that bystanders to cyberbullying instances can play. This study explored the extent to which Big Five personality traits, social dominance orientation, narcissism, moral disengagement, self-control, and cyberbullying severity level are related to bystander behavior in cyberbullying situations. Adults in the U.S. took part in an online survey in which they were presented with a series of 12 simulated social media interactions in the form of screenshots that involved exchanges between two social media users. Each screenshot depicted one of three distinct levels of cyberbullying severity: none, low severity, and high severity. For each screenshot, participants were asked to report the likelihood that they would respond in a range of ways as a bystander. Participants then completed a series of individual difference scales. The results indicated that as the severity of the cyberbullying depicted in a screenshot increased, bystanders were more likely to support the victim, flag the post, and confront the bully, and less likely to be passive observers or support the bully. Higher levels of extraversion, conscientiousness, and agreeableness were associated with a lower likelihood of remaining a passive observer, while social dominance orientation and moral disengagement were positively correlated with bystander interaction in support of the bully. Additionally, agreeableness and extraversion were positively correlated with the likelihood of supporting the victim; and agreeableness was positively correlated with the likelihood of confronting the bully. No significant relationship was discovered between self-control, narcissism, and cyberbystander behavior. This research offers experimental validation for the predictive value of both cyberbullying severity and individual differences for understanding diverse forms of cyberbystander behavior.

As any group-work member can attest, conveying information, and confirming understanding among group members can be a challenging first step in problem-solving. Despite being a ubiquitous strategy employed in many educational and organizational settings, there are collaborations that fall flat while others succeed. Recent strides have been made in the psycholinguistic approach to communication, evaluating the extent to which speakers align across lexical, syntactic, and semantic usages of language within various task environments, but gaps remain in understanding the role of language in open-ended, emergent problem-solving spaces. Study 1 examines the specific trends and functions of lexical, syntactic, and semantic alignment among speakers in a complex, creative problem-solving effort. As collaborators work through their tasks, lexical alignment decreases as semantic alignment increases and syntactic re-use decreases. These findings suggest alignment may be a sensitive mechanism that hinges on time spent in a collaborative environment and the influencing factor of goal type. More research is needed to understand the varying mechanisms across unique problem-solving spaces that vary in complexity, silence of referents, and cognitive load placed upon performers. Follow-up analyses explore how speakers use specific terms in their collaborative dialogues, assessing the roles of cognition- and action-related language. The use of thinking words (e.g. “think”, “wonder”) predicts when participants may hit an impasse in their collaborations. One interpretation suggests that cognition-related language tends to be involved when groups struggle to convey ideas. Findings from the current work have implications for interventions in organizational and educational domains, along with potential artificial intelligence applications.