Agent Trust Research Articles

Multi-Mobile Agent Trust Framework for Mitigating Internal Attacks and Augmenting RPL Security.

Recently, the Internet of Things (IoT) has emerged as an important way to connect diverse physical devices to the internet. The IoT paves the way for a slew of new cutting-edge applications. Despite the prospective benefits and many security solutions offered in the literature, the security of IoT networks remains a critical concern, considering the massive amount of data generated and transmitted. The resource-constrained, mobile, and heterogeneous nature of the IoT makes it increasingly challenging to preserve security in routing protocols, such as the routing protocol for low-power and lossy networks (RPL). RPL does not offer good protection against routing attacks, such as rank, Sybil, and sinkhole attacks. Therefore, to augment the security of RPL, this article proposes the energy-efficient multi-mobile agent-based trust framework for RPL (MMTM-RPL). The goal of MMTM-RPL is to mitigate internal attacks in IoT-based wireless sensor networks using fog layer capabilities. MMTM-RPL mitigates rank, Sybil, and sinkhole attacks while minimizing energy and message overheads by 25–30% due to the use of mobile agents and dynamic itineraries. MMTM-RPL enhances the security of RPL and improves network lifetime (by 25–30% or more) and the detection rate (by 10% or more) compared to state-of-the-art approaches, namely, DCTM-RPL, RBAM-IoT, RPL-MRC, and DSH-RPL.

Using fNIRS to Identify Transparency- and Reliability-Sensitive Markers of Trust Across Multiple Timescales in Collaborative Human-Human-Agent Triads.

Intelligent agents are rapidly evolving from assistants into teammates as they perform increasingly complex tasks. Successful human-agent teams leverage the computational power and sensory capabilities of automated agents while keeping the human operator's expectation consistent with the agent's ability. This helps prevent over-reliance on and under-utilization of the agent to optimize its effectiveness. Research at the intersection of human-computer interaction, social psychology, and neuroergonomics has identified trust as a governing factor of human-agent interactions that can be modulated to maintain an appropriate expectation. To achieve this calibration, trust can be monitored continuously and unobtrusively using neurophysiological sensors. While prior studies have demonstrated the potential of functional near-infrared spectroscopy (fNIRS), a lightweight neuroimaging technology, in the prediction of social, cognitive, and affective states, few have successfully used it to measure complex social constructs like trust in artificial agents. Even fewer studies have examined the dynamics of hybrid teams of more than 1 human or 1 agent. We address this gap by developing a highly collaborative task that requires knowledge sharing within teams of 2 humans and 1 agent. Using brain data obtained with fNIRS sensors, we aim to identify brain regions sensitive to changes in agent behavior on a long- and short-term scale. We manipulated agent reliability and transparency while measuring trust, mental demand, team processes, and affect. Transparency and reliability levels are found to significantly affect trust in the agent, while transparency explanations do not impact mental demand. Reducing agent communication is shown to disrupt interpersonal trust and team cohesion, suggesting similar dynamics as human-human teams. Contrasts of General Linear Model analyses identify dorsal medial prefrontal cortex activation specific to assessing the agent's transparency explanations and characterize increases in mental demand as signaled by dorsal lateral prefrontal cortex and frontopolar activation. Short scale event-level data is analyzed to show that predicting whether an individual will trust the agent, with data from 15 s before their decision, is feasible with fNIRS data. Discussing our results, we identify targets and directions for future neuroergonomics research as a step toward building an intelligent trust-modulation system to optimize human-agent collaborations in real time.

Effectiveness of “Neither-Good-Nor-Bad” Information on User's Trust in Agents in Presence of Numerous Options

Effectiveness of “Neither-Good-Nor-Bad” Information on User's Trust in Agents in Presence of Numerous Options

Supporting Artificial Social Intelligence With Theory of Mind.

In this paper, we discuss the development of artificial theory of mind as foundational to an agent's ability to collaborate with human team members. Agents imbued with artificial social intelligence will require various capabilities to gather the social data needed to inform an artificial theory of mind of their human counterparts. We draw from social signals theorizing and discuss a framework to guide consideration of core features of artificial social intelligence. We discuss how human social intelligence, and the development of theory of mind, can contribute to the development of artificial social intelligence by forming a foundation on which to help agents model, interpret and predict the behaviors and mental states of humans to support human-agent interaction. Artificial social intelligence will need the processing capabilities to perceive, interpret, and generate combinations of social cues to operate within a human-agent team. Artificial Theory of Mind affords a structure by which a socially intelligent agent could be imbued with the ability to model their human counterparts and engage in effective human-agent interaction. Further, modeling Artificial Theory of Mind can be used by an ASI to support transparent communication with humans, improving trust in agents, so that they may better predict future system behavior based on their understanding of and support trust in artificial socially intelligent agents.

Designing Empathic Virtual Agents: Manipulating Animation, Voice, Rendering, and Empathy to Create Persuasive Agents.

Designers of virtual agents have a combinatorically large space of choices for the look and behavior of their characters. We conducted two between-subjects studies to explore the systematic manipulation of animation quality, speech quality, rendering style, and simulated empathy, and its impact on perceptions of virtual agents in terms of naturalness, engagement, trust, credibility, and persuasion within a health counseling domain. In the first study, animation was varied between manually created, procedural, or no animations; voice quality was varied between recorded audio and synthetic speech; and rendering style was varied between realistic and toon-shaded. In the second study, simulated empathy of the agent was varied between no empathy, verbal-only empathic responses, and full empathy involving verbal, facial, and immediacy feedback. Results show that natural animations and recorded voice are more appropriate for the agent's general acceptance, trust, credibility, and appropriateness for the task. However, for a brief health counseling task, animation might actually be distracting from the persuasive message, with the highest levels of persuasion found when the amount of agent animation is minimized. Further, consistent and high levels of empathy improve agent perception but may interfere with forming a trusting bond with the agent.

Pengaruh Kualitas Layanan Petugas Agen Brilink (PAB) Terhadap Loyalitas Agen Brilink

This study aims to analyze the effect of the service quality of BRILink Agent Officers (PAB) on the level of satisfaction, trust and loyalty of BRILink Agents in order to achieve the BRILink Agent transaction volume target. This study used a questionnaire with a five-point Likert scale. Questionnaires were submitted to 300 respondents, namely BRILink agents who were used as samples, which were located in West Jakarta, Banten and West Kalimantan. Respondent requirements are BRILink Agents who have been BRI Agents for a minimum of 6 months and the number of transactions is under 200 transactions per month. Questionnaires were distributed by BRI employees, namely the Resident Auditor Unit (RAU) in the local area. There were 274 questionnaires that were returned and were completely filled out. The data analysis technique uses the Structural Equation Model (SEM) method and uses Lisrel 8.72 software to analyze the casual relationship between service quality, satisfaction, trust and loyalty of BRILink agents, and to evaluate hypotheses regarding the relationship between model construction. The results of this study indicate that all Service Quality indicators have a significant effect on BRIink Agent Satisfaction, BRILink Agent Satisfaction has a significant effect on BRILink Agent Trust and Loyalty. What greatly affects the satisfaction, trust and loyalty of BRILink Agents is the frequency of PAB visits to BRILink Agents, PAB's ability to motivate BRILink Agents, and BRI must improve the quality of the system and network. Keywords: loyalty, service quality, satisfaction, trust, SEM

The Antecedents to the Actual Use of Digital Currencies in Ghana

This study investigates the antecedents to the use of digital currencies in a developing country. In the digital currency literature, behavioral and technological antecedents that affect individuals' behavior towards the use of digital currencies remain scanty. Drawing on Bitcoin, mobile money, and perfect money as some types of digital currencies, this research adopts the technology organization environment (TOE) framework and the prospect theory. Based on 520 questionnaire responses, this research employs the partial least square structural equation modeling (PLS-SEM) technique. Results from the analysis reveal that technology competence, service, and agent trust, perceived risk, and cost have positive influences on the intention to use digital currencies. Behavioral intention influences the actual use of the technology. However, a country's regulatory environment does not influence the intention to adopt digital currencies. The research provides important analytical advances and presents practical and economic consequences for the implementation of digital currencies.

Testing the validity of the modified vaccine attitude question battery across 22 languages with a large-scale international survey dataset: within the context of COVID-19 vaccination

ABSTRACT In this study, we tested the validity of the modified version of the Vaccine Attitude Question Battery (VAQB) across 22 different languages. Validity test was conducted with a large-scale international survey dataset, COVIDiSTRESSII Global Survey, collected from 20,601 participants from 62 countries. We employed exploratory and confirmatory factor analysis, measurement invariance test, and measurement alignment for internal validity test. Moreover, we examined correlation between the VAQB score, vaccination intent, compliance with preventive measures, and trust in public health-related agents. The results reported that the modified VAQB, which included five items, showed good validity across 22 languages with measurement alignment. Furthermore, the VAQB score showed negative association with vaccination intent, compliance, and trust as expected. The findings from this study provide additional evidence supporting the validity of the modified VAQB in 22 languages for future large-scale international research on COVID-19 and vaccination.

Trust in the scientific research community predicts intent to comply with COVID-19 prevention measures: An analysis of a large-scale international survey dataset.

In the present study, I explored the relationship between people's trust in different agents related to the prevention of the spread of coronavirus disease 2019 (COVID-19) and their compliance with pharmaceutical and non-pharmaceutical preventive measures. The COVIDiSTRESSII Global Survey dataset, which was collected from international samples, was analysed to examine the aforementioned relationship across different countries. For data-driven exploration, network analysis and Bayesian generalised linear model (GLM) analysis were performed. The result from network analysis demonstrated that trust in the scientific research community was most central in the network of trust and compliance. In addition, the outcome from Bayesian GLM analysis indicated that the same factor, trust in the scientific research community, was most fundamental in predicting participants' intent to comply with both pharmaceutical and non-pharmaceutical preventive measures. I briefly discussed the implications of the findings, the importance of trust in the scientific research community in explaining people's compliance with a measure to prevent the spread of COVID-19.

Budget transparency as an important condition for strengthening the financial self-sufficiency of territorial communities

The article characterizes theoretical principles of the impact of budget transparency on ensuring the financial self-sufficiency of territorial communities determined by the ability of their authorities to finance in full the spending powers for solving social and cultural needs of the daily life of both individual residents and the community in general at the expense of the financial resources formed in local budgets. The content of a number of interrelated key characteristics (transparency, openness, timeliness, accountability, credibility) and types of budget transparency (political, economic, procedural, public, regulatory, institutional) is highlighted and revealed, taking into account the key areas of their manifestation. Attention is focused on the main problems of budgetary transparency of territorial communities: a decrease in trust and respect for the authorities on the part of citizens, a lack of open dialogue with representatives of the authorities, and a low level of readiness of society to participate in the decision-making process for solving local problems. The article justifies that ensuring the accountability of authorities and effective involvement of the community in the budget process requires the development and implementation of an effective communication strategy at the level of territorial communities, the creation of expert platforms, the spread of the practice of forming local budgets on a participatory basis, the development and launch of complex public finance management systems, and comprehensive evaluation of budget transparency, which would cover all local budgets. Particular attention is paid to highlighting the forms of citizen involvement in managing the finances of territorial communities in terms of the stages of the budget cycle and the possible effects of such participation. The article offers the following directions for strengthening the financial self-sufficiency of the budgets of territorial communities based on the increase in the level of budget transparency - increasing the loyalty and trust of economic agents in the activities of subnational governments, activating the financing of investment projects of local importance due to the increase in participation in the process of planning, formation, and use of local budget baskets, and optimization of the budgetary resources spending due to the growing interest of members of the territorial community in solving issues of local importance.

Recycled water reuse: what factors affect public acceptance?

SummaryGlobally, water resources are under immense and increasing pressure. This, coupled with the threat of climate change, has increased global interest in water reuse. However, global water reuse remains limited because of public opposition. This paper thus examines public perceptions and attitudes to water reuse across the world. It finds that results from studies of water reuse acceptance have tended to be context specific, although claims can be made about the universal relevance of some predictors, underscoring the need for individual water reuse schemes to carefully consider their local context. Disgust remains a constant in the public psyche, while public trust in delivery agents as well as how water reuse is communicated vis-à-vis perceptions about the quality and safety of recycled water are also critical. The latter particularly highlights public concerns about the indeterminate health risks associated with water reuse.

Currency Depreciation Nexus Country's Export: Evidence from Georgia

The recent shocks in demand and supply caused by Covid-19 influence and the current depreciation of the Georgian Lari (GEL) reduced the trust of economic agents in currency. There is no objective macroeconomic reason that would change their attitude to the future of currency for the better. Depreciation of a currency impacts all the components of GDP, leading to myriad problems in economic growth. The depreciation of the national currency is generally perceived as positively affecting the country's export. The study analyzes the impact of Georgian Lari's exchange rate depreciation on Georgia's export using monthly GEL exchange rate data from May 2006 to April 2020. The paper employs Autoregressive Distributed Lag Model (ARDL) for its advantages of measuring cointegration, usefulness in the small samples, and being unbiased in measuring a long-run relationship between variables. Outcomes indicate that the exchange rate depreciation has an inverse long-run impact on export in the long-run period. The exchange rate impact on Georgia's export shows inelastic demand for Georgia's export goods. The study contributes to the literature while providing the implication of currency depreciation on exports of the Georgian economy. The estimated value of the exchange rate has been found to exert no direct pressure on the amount of export. In the paper, possible reasons for such implications are also examined. Paper found that the control variable interest rate also has an inverse impact on Georgia's export performance in the long-run as well as in the short-run. International reserves positively influence the export in the long-run with a high significance level. The paper also discusses possible ways of stabilization of national currency.

Investigating the Impact of Visual Environmental Uncertainty on Human-Agent Teaming

Uncertainty in Human-Agent interactions is often studied in terms of transparency and understandability of agent actions. Less work, however, has focused on how Visual Environmental Uncertainty (VEU) that restricts or occludes visual information affects the Human-Agent Teaming (HAT) in terms of trust, reliance, performance, cognitive load and situational awareness. We conducted a mixed-design experiment (n=96) where participants interacted with an agent during a collaborative aiming task under four different types of VEUs involving global and dynamic occlusions. Our results show that while environmental uncertainties led to increases in perceived trust, they induced differences in reliance and performance. Counter to intuition, when participants trusted the agent the most, they relied on the agent more, but performed worst. These findings highlight how trust in agents is also influenced by external environmental conditions and suggest that reported trust in HAT scenarios may not always generalize beyond the environmental factors in which they were studied.

A comparison between chatbot and human service: customer perception and reuse intention

PurposeChatbot users’ communication experience with disembodied conversational agents was compared with instant messaging (IM) users’ communication experience with human conversational agents. The purpose of this paper is to identify what affects users’ intention to reuse and whether they perceive any difference between the two.Design/methodology/approachA conceptual model was developed based on computer-mediated communication (CMC) and interpersonal communication theories. Data were collected online from four different continents (North America, Europe, Asia and Australia). Partial least squares structural equation modeling was applied to examine the research model.FindingsThe findings mainly reveal that media richness and social presence positively influence trust and reuse intention through task attraction and social attraction; IM users reported significantly higher scores in terms of communication experience, perceived attractiveness of the conversational agent, and trust than chatbot users; users’ trust in the conversational agents is mainly determined by perceived task attraction.Research limitations/implicationsCustomers’ evaluation of the communication environment is positively related to their perceived competence of the conversational agent which ultimately affect their intention to reuse chatbot/IM. The findings reveal determinants of chatbot/IM adoption which have rarely been mentioned by previous work.Practical implicationsPractitioners should note that consumers in general still prefer to interact with human conversational agents. Practitioners should contemplate how to combine chatbot and human resources effectively to deliver the best customer service.Originality/valueThis study goes beyond the Computer as Social Actor paradigm and Technology Acceptance Model to understand chatbot and IM adoption. It is among one of the first studies that compare chatbot and IM use experience in the tourism and hospitality literature.

Above the Scam: Moral Elevation Reduces Gullibility

Consumers are increasingly exposed to scams and questionable marketing practices. The current work examines how consumers’ emotional states influence their gullibility (a belief or compliance with a request that most people would consider naïve). Across four studies, we show that the emotional experience of moral elevation reduces susceptibility to believe dubious claims or comply with suspicious requests. While past research showed that moral elevation enhances nurturance behavior (and support of a requester), the current work suggests that elevation may also play a protective function (that is, reduce gullibility). We show that decreased trust in a persuasion agent mediates the influence of elevation on gullibility, and demonstrate this effect in the context of health and financial domains.

Interactive effects of advising strength and brand familiarity on users' trust and distrust in online recommendation agents

PurposeThis paper investigates the effects of advising strength of a recommendation agent on users' trust and distrust beliefs and how the effects are moderated by perceived brand familiarity.Design/methodology/approachA research model is evaluated using a laboratory experiment with 149 participants.FindingsResults reveal that a strong advising tone leads to higher trust in terms of users' credibility and benevolence beliefs and lower distrust in terms of their discredibility beliefs (the trustor's concerns regarding the trustee's dishonesty and competence in engaging in harmful behavior) when perceived brand familiarity is high. By contrast, when brand familiarity is low, strong advising tone results in low trust in terms of users' credibility belief and high distrust in terms of their beliefs in discredibility and malevolence (concerns regarding the trustee's conduct in terms of a malicious intention that can hurt the trustor's welfare).Originality/valueThis paper contributes to the trust and distrust literature by studying how each of the dimensions of trust and distrust can be affected by an RA's design feature. It extends the attribution theory to the RA context by studying the moderating role of brand familiarity in determining the effects of the advising strength of an RA. It provides actionable guidelines for practitioners regarding the adoption of an RA's appropriate advising strength to promote different types of products.

Investigating Trust in Interaction with Inconsistent Embodied Virtual Agents

Embodied Virtual Agents (EVAs) are used today as interfaces for social robots, educational tutors, game counterparts, medical assistants, as well as companions for the elderly and individuals with psychological or behavioral conditions. Forming a reliable and trustworthy interaction is critical to the success and acceptability of this new form of interaction. In this paper, we report on a study investigating how trust is influenced by the cooperativeness of an EVA as well as an individuals prior experience with other agents. Participants answered two sets of multiple choice questions, working with a different agent in each set. Two types of agent behaviors were possible: Cooperative and Uncooperative. In addition to participants achieving significantly higher performance and having higher trust for the cooperative agent, we found that participants’ trust for the cooperative agent was significantly higher if they interacted with an uncooperative agent in one of the sets, compared to working with cooperative agents in both sets. Furthermore, we found that participants may still decide to choose agent’s suggested answer (which can be incorrect) over theirs, even if they are fairly certain their own answer is the correct one. The results suggest that trust for an EVA is relative and it is dependent on user’s history of interaction with different agents in addition to current agent’s behavior. The findings provide insight into important considerations for creating trustworthy EVAs.

The Effect of Value Similarity on Trust in the Automation Systems: A Case of Transportation and Medical Care

ABSTRACT Trustworthy automation systems can be beneficial in transportation and medical care, thus resulting in broader acceptance of such systems. This study examines the determinants of trust, focusing on the salient value similarity model, which proposed that perceived value similarity increases trust in agents. We have adopted a scenario method and explored whether the automation systems would be trusted when their moral judgments are similar to a participants’ desired values. Experiment 1 (N = 270) showed that moral value similarity affected trust in autonomous cars. Experiment 2 (N = 605) aimed to generalize these findings to the medical domain, wherein trust in a medical system was promoted when the moral values of a system and participant were similar. Moreover, the automation systems were trusted less than human agents in both experiments. Finally, we discuss some theoretical and practical implications of the findings.

Trust and Team Performance in Human–Autonomy Teaming

ABSTRACT This study aims to better understand trust in human–autonomy teams, finding that trust is important for team performance. A Wizard of Oz approach was used to simulate an autonomous agent team member, in a remotely piloted aircraft system research environment, to study the relationship between trust and team performance in human–autonomy teams. Results show that (1) there are lower levels of trust in the autonomous agent in low-performing teams compared with medium- or high-performing teams; (2) there is a loss of trust in the autonomous agent over time across low-, medium-, and high-performing teams; and (3) both low- and medium-performing teams indicated lower levels of trust in their human team members. These findings indicate that trust in a teammate (autonomous or human) is associated with team performance and that trust may evolve over time irrespective of team performance.

Conditions under which “Neither-Good-Nor-Bad” Information Works Effectively on User’s Trust in Agents

Conditions under which “Neither-Good-Nor-Bad” Information Works Effectively on User’s Trust in Agents