The construct of state-level suspicion: a model and research agenda for automated and information technology (IT) contexts

Longitudinal Associations Between Interpersonal Distrust and Social Aggression During College: Disentangling the Within-Person Process from Stable Between-Person Differences

There is a dearth of information on the relationship between interpersonal distrust and social aggression in the youth, although both may lead to negative interpersonal relationships. Furthermore, scholars have not explored whether interpersonal distrust influences later social aggression over time at the within-person level. This study used five wave longitudinal data to investigate the longitudinal association between interpersonal distrust and social aggression and the role of hostile attribution bias in this relationship; notably, it used a relatively rigorous approach-the random intercept cross-lagged panel model-to disentangle within-person processes from stable between-person differences. The final number of participants included 1053 undergraduate students (677 female students and 376 male students), and 64.3% were female students, with a mean age of 18.45 years (SD = 0.95) at first measurement. Participants completed assessments for interpersonal distrust, hostile attribution bias, and social aggression at five time points across 6-month intervals. At the within-person level, the results revealed that interpersonal distrust was a predictor of later social aggression and that hostile attribution bias acted as a longitudinal mediator in this relationship. This result indicates that to enhance interpersonal harmony and reduce individual hostility and aggression toward others, intervention programs should aim to reduce interpersonal distrust.

Suspicion About Suspicion Probes: Ways Forward

Suspicion probes are the traditional tool employed to assess the extent to which participants suspect intentional misdirection or deception within the research context. A primary reason psychologists use deception in research settings is to prevent participants from altering their behavior in light of knowing what is being studied, which could undermine internal validity as well as threaten the generalizability of findings to the real world (i.e., external validity). The present article elucidates a number of challenges with suspicion probes. A definition and framework for conceptualizing the construct of suspicion in research settings are proposed. Following a literature review, an analysis of existing evidence, and new data on the prevalence of using and reporting suspicion probes, we conclude that suspicion is a likely problem in research practice. We provide a decision guide to help researchers navigate the numerous choices involved in addressing potential suspicion and call for a combination of (a) renewed research leading to empirically supported tools and best practices and (b) systemic changes to editorial policies, funding practices, professional standards, and research training that would increase rigor and focus on this aspect of research methodology.

Trusting Automation: Designing for Responsivity and Resilience

OBJECTIVE

This paper reviews recent articles related to human trust in automation to guide research and design for increasingly capable automation in complex work environments.

BACKGROUND

Two recent trends-the development of increasingly capable automation and the flattening of organizational hierarchies-suggest a reframing of trust in automation is needed.

METHOD

Many publications related to human trust and human-automation interaction were integrated in this narrative literature review.

RESULTS

Much research has focused on calibrating human trust to promote appropriate reliance on automation. This approach neglects relational aspects of increasingly capable automation and system-level outcomes, such as cooperation and resilience. To address these limitations, we adopt a relational framing of trust based on the decision situation, semiotics, interaction sequence, and strategy. This relational framework stresses that the goal is not to maximize trust, or to even calibrate trust, but to support a process of trusting through automation responsivity.

CONCLUSION

This framing clarifies why future work on trust in automation should consider not just individual characteristics and how automation influences people, but also how people can influence automation and how interdependent interactions affect trusting automation. In these new technological and organizational contexts that shift human operators to co-operators of automation, automation responsivity and the ability to resolve conflicting goals may be more relevant than reliability and reliance for advancing system design.

APPLICATION

A conceptual model comprising four concepts-situation, semiotics, strategy, and sequence-can guide future trust research and design for automation responsivity and more resilient human-automation systems.

A Multidisciplinary Survey and Framework for Design and Evaluation of Explainable AI Systems

The need for interpretable and accountable intelligent systems grows along with the prevalence of artificial intelligence ( AI ) applications used in everyday life. Explainable AI ( XAI ) systems are intended to self-explain the reasoning behind system decisions and predictions. Researchers from different disciplines work together to define, design, and evaluate explainable systems. However, scholars from different disciplines focus on different objectives and fairly independent topics of XAI research, which poses challenges for identifying appropriate design and evaluation methodology and consolidating knowledge across efforts. To this end, this article presents a survey and framework intended to share knowledge and experiences of XAI design and evaluation methods across multiple disciplines. Aiming to support diverse design goals and evaluation methods in XAI research, after a thorough review of XAI related papers in the fields of machine learning, visualization, and human-computer interaction, we present a categorization of XAI design goals and evaluation methods. Our categorization presents the mapping between design goals for different XAI user groups and their evaluation methods. From our findings, we develop a framework with step-by-step design guidelines paired with evaluation methods to close the iterative design and evaluation cycles in multidisciplinary XAI teams. Further, we provide summarized ready-to-use tables of evaluation methods and recommendations for different goals in XAI research.

A Bifactor Model of Trait Trust, Distrust, and Suspicion

Abstract. We explored competing models using bifactor item response theory (IRT) analyses to determine the relationship between trait measures of trust, distrust, and suspicion. The model with a general factor for all three scales fits the data best. We explored the relationship of the emergent general factor by correlating it with two latent traits: Agreeableness and the Trust facet of Agreeableness. The exploratory findings showed evidence that the general factor from the best-fitting model was practically identical to the Trust facet of Agreeableness. We concluded that trait trust, distrust, and suspicion reside on a continuum represented by the general factor, which is dispositional trust.

Being suspicious in the workplace: the role of suspicion and negative views of others in the workplace in the perception of abusive supervision

Purpose

Research reported in this manuscript focuses on the relationship between trait suspicion and the perception of abusive supervision. Based on previous research, the authors assume that suspicion is positively related to the perception of abusive supervision. The role implicit theories play in this relationship is examined.

Design/methodology/approach

Two studies are presented to examine the relationship between trait suspicion and the perception of abusive supervision as moderated by implicit leadership theories. The first study is a survey study, and the second study is an experimental vignette study.

Findings

Results of both studies indicate that suspicion is positively related to the perception of abusive supervision and that implicit leadership theories moderate the relationship between suspicion and the perception of abusive supervision.

Research limitations/implications

Results are interpreted in terms of biases in leadership perception as well as the reversing-the-lens perspective.

Originality/value

While there is progress in taking into account follower characteristics and the resulting perceptual biases in the study of constructive leadership phenomena such as transformational leadership, less is know about the follower perception aspect of destructive leadership phenomena. With this research, the authors extend research into the influence of follower characteristics on the perception of abusive supervision and also look at boundary conditions of this relationship by including implicit leadership theories as a moderator.

Incidental Emotions and Hedonic Forecasting: The Role of (Un)certainty

The impact of incidental emotions on decision making is well established. Incidental emotions can be differentiated on several appraisal dimensions, including certainty–uncertainty. The present research investigates the effect of certainty–uncertainty of incidental emotions on hedonic forecasting. The results of four experimental studies indicate that uncertainty-associated incidental emotions, such as fear and hope, compared with certainty emotions, such as anger and happiness, amplify predicted utility. This amplification effect is confirmed for opposite utility types; uncertainty-associated emotions, when compared with their certainty counterparts, lead to an overprediction of positive utilities and to an underprediction of negative utilities. This effect is mediated by the prediction task uncertainty, providing evidence for a carryover process of the incidental emotion. The effect of task uncertainty on predicted utility is, in turn, partly mediated by attention to the task, suggesting that an affective adaptation process lies behind the amplification of forecasts. Taken together, these findings extend the impact of certainty–uncertainty to the context of hedonic forecasting and further corroborate the impact of incidental emotions in judgment and decision making.

Exploring the Unique and Shared Variance of Propensity to Trust and Suspicion Propensity

Abstract. Across two studies, we explored the relationship of propensity to trust – a general willingness to trust others ( Mayer, Davis, & Schoorman, 1995 ) – and suspicion propensity – a disposition toward being suspicious ( Calhoun et al., 2017 ) – to determine if the constructs are distinct and account for unique variance in relevant outcomes. We used exploratory structural equation modeling to investigate whether propensity to trust and suspicion propensity are separate constructs. Then, we investigated the unique predictive validity of each trait on criteria of interest. We found some evidence that propensity to trust and suspicion propensity are unique, yet related, constructs with unique predictive validity. Theoretical and practical implications, as well as limitations, of this research are discussed.

Trust and the Compliance-Reliance Paradigm: The Effects of Risk, Error Bias, and Reliability on Trust and Dependence

OBJECTIVE

This study provides a theoretical link between trust and the compliance-reliance paradigm. We propose that for trust mediation to occur, the operator must be presented with a salient choice, and there must be an element of risk for dependence.

BACKGROUND

Research suggests that false alarms and misses affect dependence via two independent processes, hypothesized as trust in signals and trust in nonsignals. These two trust types manifest in categorically different behaviors: compliance and reliance.

METHOD

Eighty-eight participants completed a primary flight task and a secondary signaling system task. Participants evaluated their trust according to the informational bases of trust: performance, process, and purpose. Participants were in a high- or low-risk group. Signaling systems varied by reliability (90%, 60%) within subjects and error bias (false alarm prone, miss prone) between subjects.

RESULTS

False-alarm rate affected compliance but not reliance. Miss rate affected reliance but not compliance. Mediation analyses indicated that trust mediated the relationship between false-alarm rate and compliance. Bayesian mediation analyses favored evidence indicating trust did not mediate miss rate and reliance. Conditional indirect effects indicated that factors of trust mediated the relationship between false-alarm rate and compliance (i.e., purpose) and reliance (i.e., process) but only in the high-risk group.

CONCLUSION

The compliance-reliance paradigm is not the reflection of two types of trust.

APPLICATION

This research could be used to update training and design recommendations that are based upon the assumption that trust causes operator responses regardless of error bias.

Organizational Conspiracy Beliefs: Implications for Leadership Styles and Employee Outcomes

PURPOSE

Belief in conspiracy theories about societal events is widespread among citizens. The extent to which conspiracy beliefs about managers and supervisors matter in the micro-level setting of organizations has not yet been examined, however. We investigated if leadership styles predict conspiracy beliefs among employees in the context of organizations. Furthermore, we examined if such organizational conspiracy beliefs have implications for organizational commitment and turnover intentions.

DESIGN/METHODOLOGY/APPROACH

We conducted a survey among a random sample of the US working population (N = 193).

FINDINGS

Despotic, laissez-faire, and participative leadership styles predicted organizational conspiracy beliefs, and the relations of despotic and laissez-faire leadership with conspiracy beliefs were mediated by feelings of job insecurity. Furthermore, organizational conspiracy beliefs predicted, via decreased organizational commitment, increased turnover intentions.

IMPLICATIONS

Organizational conspiracy beliefs matter for how employees perceive their leaders, how they feel about their organization, and whether or not they plan to quit their jobs. A practical implication, therefore, is that it would be a mistake for managers to dismiss organizational conspiracy beliefs as innocent rumors that are harmless to the organization.

ORIGINALITY/VALUE

Three novel conclusions emerge from this study. First, organizational conspiracy beliefs occur frequently among employees. Second, participative leadership predicts decreased organizational conspiracy beliefs; despotic and laissez-faire leadership predict increased organizational conspiracy beliefs due to the contribution of these destructive leadership styles to an insecure work environment. Third, organizational conspiracy beliefs harm organizations by influencing employee commitment and, indirectly, turnover intentions.

Using Noninvasive Brain Measurement to Explore the Psychological Effects of Computer Malfunctions on Users during Human-Computer Interactions

In today’s technologically driven world, there is a need to better understand the ways that common computer malfunctions affect computer users. These malfunctions may have measurable influences on computer user’s cognitive, emotional, and behavioral responses. An experiment was conducted where participants conducted a series of web search tasks while wearing functional near-infrared spectroscopy (fNIRS) and galvanic skin response sensors. Two computer malfunctions were introduced during the sessions which had the potential to influence correlates of user trust and suspicion. Surveys were given after each session to measure user’s perceived emotional state, cognitive load, and perceived trust. Results suggest that fNIRS can be used to measure the different cognitive and emotional responses associated with computer malfunctions. These cognitive and emotional changes were correlated with users’ self-report levels of suspicion and trust, and they in turn suggest future work that further explores the capability of fNIRS for the measurement of user experience during human-computer interactions.