Group trust dynamics during a risky driving experience in a Tesla Model X.

The growing concern about the risk and safety of autonomous vehicles (AVs) has made it vital to understand driver trust and behavior when operating AVs. While research has uncovered human factors and design issues based on individual driver performance, there remains a lack of insight into how trust in automation evolves in groups of people who face risk and uncertainty while traveling in AVs. To this end, we conducted a naturalistic experiment with groups of participants who were encouraged to engage in conversation while riding a Tesla Model X on campus roads.

Customizing virtual interpersonal skills training applications may not improve trainee performance.

While some theoretical perspectives imply that the context of a virtual training should be customized to match the intended context where those skills would ultimately be applied, others suggest this might not be necessary for learning. It is important to determine whether manipulating context matters for performance in training applications because customized virtual training systems made for specific use cases are more costly than generic "off-the-shelf" ones designed for a broader set of users. Accordingly, we report a study where military cadets use a virtual platform to practice their negotiation skills, and are randomly assigned to one of two virtual context conditions: military versus civilian.

Designing Man's New Best Friend: Enhancing Human-Robot Dog Interaction through Dog-Like Framing and Appearance.

To understand how to improve interactions with dog-like robots, we evaluated the importance of "dog-like" framing and physical appearance on interaction, hypothesizing multiple interactive benefits of each. We assessed whether framing Aibo as a puppy (i.e.

Lessons Learned About Designing and Conducting Studies From HRI Experts.

The field of human-robot interaction (HRI) research is multidisciplinary and requires researchers to understand diverse fields including computer science, engineering, informatics, philosophy, psychology, and more disciplines. However, it is hard to be an expert in everything. To help HRI researchers develop methodological skills, especially in areas that are relatively new to them, we conducted a virtual workshop, Workshop Your Study Design (WYSD), at the 2021 International Conference on HRI.

Spiritual over physical formidability determines willingness to fight and sacrifice through loyalty in cross-cultural populations.

Across 11 studies involving six countries from four continents ( = 3,285), we extend insights from field investigations in conflict zones to offline and online surveys to show that personal spiritual formidability-the conviction and immaterial resources (values, strengths of beliefs, character) of a person to fight-is positively associated with the will to fight and sacrifice for others. The physical formidability of groups in conflict has long been promoted as the primary factor in human decisions to fight or flee in times of conflict. Here, studies in Spain, Iraq, Lebanon, Palestine, and Morocco reveal that personal spiritual formidability, a construct distinct from religiosity, is more strongly associated with the willingness to fight and make costly self-sacrifices for the group than physical formidability.

Measurement of Trust in Automation: A Narrative Review and Reference Guide.

With the rise of automated and autonomous agents, research examining Trust in Automation (TiA) has attracted considerable attention over the last few decades. Trust is a rich and complex construct which has sparked a multitude of measures and approaches to study and understand it. This comprehensive narrative review addresses known methods that have been used to capture TiA.

Robot Authority in Human-Robot Teaming: Effects of Human-Likeness and Physical Embodiment on Compliance.

The anticipated social capabilities of robots may allow them to serve in authority roles as part of human-machine teams. To date, it is unclear if, and to what extent, human team members will comply with requests from their robotic teammates, and how such compliance compares to requests from human teammates. This research examined how the human-likeness and physical embodiment of a robot affect compliance to a robot's request to perseverate utilizing a novel task paradigm.

Factors that affect younger and older adults' causal attributions of robot behaviour.

Stereotypes are cognitive shortcuts that facilitate efficient social judgments about others. Just as causal attributions affect perceptions of people, they may similarly affect perceptions of technology, particularly anthropomorphic technology such as robots. In a scenario-based study, younger and older adults judged the performance and capability of an anthropomorphised robot that appeared young or old.

Trust and Distrust of Automated Parking in a Tesla Model X.

Objective: The present study aims to evaluate driver intervention behaviors during a partially automated parking task.

Background: Cars with partially automated parking features are becoming widely available. Although recent research explores the use of automation features in partially automated cars, none have focused on partially automated parking.

Learning From the Slips of Others: Neural Correlates of Trust in Automated Agents.

With the rise of increasingly complex artificial intelligence (AI), there is a need to design new methods to monitor AI in a transparent, human-aware manner. Decades of research have demonstrated that people, who are not aware of the exact performance levels of automated algorithms, often experience a mismatch in expectations. Consequently, they will often provide either too little or too much trust in an algorithm.

From 'automation' to 'autonomy': the importance of trust repair in human-machine interaction.

Modern interactions with technology are increasingly moving away from simple human use of computers as tools to the establishment of human relationships with autonomous entities that carry out actions on our behalf. In a recent commentary, Peter Hancock issued a stark warning to the field of human factors that attention must be focused on the appropriate design of a new class of technology: highly autonomous systems. In this article, we heed the warning and propose a human-centred approach directly aimed at ensuring that future human-autonomy interactions remain focused on the user's needs and preferences.

A Little Anthropomorphism Goes a Long Way.

Objective: We investigated the effects of exogenous oxytocin on trust, compliance, and team decision making with agents varying in anthropomorphism (computer, avatar, human) and reliability (100%, 50%).

Background: Authors of recent work have explored psychological similarities in how people trust humanlike automation compared with how they trust other humans. Exogenous administration of oxytocin, a neuropeptide associated with trust among humans, offers a unique opportunity to probe the anthropomorphism continuum of automation to infer when agents are trusted like another human or merely a machine.

Almost human: Anthropomorphism increases trust resilience in cognitive agents.

We interact daily with computers that appear and behave like humans. Some researchers propose that people apply the same social norms to computers as they do to humans, suggesting that social psychological knowledge can be applied to our interactions with computers. In contrast, theories of human–automation interaction postulate that humans respond to machines in unique and specific ways.

An fMRI and effective connectivity study investigating miss errors during advice utilization from human and machine agents.

As society becomes more reliant on machines and automation, understanding how people utilize advice is a necessary endeavor. Our objective was to reveal the underlying neural associations during advice utilization from expert human and machine agents with fMRI and multivariate Granger causality analysis. During an X-ray luggage-screening task, participants accepted or rejected good or bad advice from either the human or machine agent framed as experts with manipulated reliability (high miss rate).

Building resilience with the Stress Resilience Training System: Design validation and applications.

Background: Resilience to stress is critical in today's military service. Past work has shown that experts handle stress in more productive ways compared to novices. Training that specifically addresses stress regulation, such as the Graduated Stress Exposure paradigm, can build individual and unit resilience as well as adaptability so that stressors trigger effective stress coping skills rather than stress injury.

Team performance in networked supervisory control of unmanned air vehicles: effects of automation, working memory, and communication content.

Objective: Assess team performance within a net-worked supervisory control setting while manipulating automated decision aids and monitoring team communication and working memory ability.

Background: Networked systems such as multi-unmanned air vehicle (UAV) supervision have complex properties that make prediction of human-system performance difficult. Automated decision aid can provide valuable information to operators, individual abilities can limit or facilitate team performance, and team communication patterns can alter how effectively individuals work together.

Statistical modelling of networked human-automation performance using working memory capacity.

This study examines the challenging problem of modelling the interaction between individual attentional limitations and decision-making performance in networked human-automation system tasks. Analysis of real experimental data from a task involving networked supervision of multiple unmanned aerial vehicles by human participants shows that both task load and network message quality affect performance, but that these effects are modulated by individual differences in working memory (WM) capacity. These insights were used to assess three statistical approaches for modelling and making predictions with real experimental networked supervisory performance data: classical linear regression, non-parametric Gaussian processes and probabilistic Bayesian networks.

Dopamine beta hydroxylase genotype identifies individuals less susceptible to bias in computer-assisted decision making.

Computerized aiding systems can assist human decision makers in complex tasks but can impair performance when they provide incorrect advice that humans erroneously follow, a phenomenon known as "automation bias." The extent to which people exhibit automation bias varies significantly and may reflect inter-individual variation in the capacity of working memory and the efficiency of executive function, both of which are highly heritable and under dopaminergic and noradrenergic control in prefrontal cortex. The dopamine beta hydroxylase (DBH) gene is thought to regulate the differential availability of dopamine and norepinephrine in prefrontal cortex.

Oxytocin selectively increases perceptions of harm for victims but not the desire to punish offenders of criminal offenses.

The neuropeptide oxytocin functions as a hormone and neurotransmitter and facilitates complex social cognition and approach behavior. Given that empathy is an essential ingredient for third-party decision-making in institutions of justice, we investigated whether exogenous oxytocin modulates empathy of an unaffected third-party toward offenders and victims of criminal offenses. Healthy male participants received intranasal oxytocin or placebo in a randomized, double-blind, placebo-controlled, between-subjects design.

Distractions N' Driving: video game simulation educates young drivers on the dangers of texting while driving.

The proliferation of portable communication and entertainment devices has introduced new dangers to the driving environment, particularly for young and inexperienced drivers. Graduate students from George Mason University illustrate a powerful, practical, and cost-effective program that has been successful in educating these drivers on the dangers of texting while driving, which can easily be adapted and implemented in other communities.

A meta-analysis of factors affecting trust in human-robot interaction.

Objective: We evaluate and quantify the effects of human, robot, and environmental factors on perceived trust in human-robot interaction (HRI).

Background: To date, reviews of trust in HRI have been qualitative or descriptive. Our quantitative review provides a fundamental empirical foundation to advance both theory and practice.

Detecting threat-related intentional actions of others: effects of image quality, response mode, and target cuing on vigilance.

Three experiments examined the vigilance performance of participants watching videos depicting intentional actions of an individual's hand reaching for and grasping an object--involving transporting or using either a gun or a hairdryer--in order to detect infrequent threat-related actions. Participants indicated detection of target actions either manually or by withholding response. They also rated their subjective mental workload before and after each vigilance task.