With the recent shift from conventional industrial robots to more collaborative Human-Robot Interaction (HRI) robots11In this paper, the term ‘HRI robot’ is used to underscore the significance of the interaction between robots and humans, rather than focusing on the type of robot involved (e.g., cobot, social robot) or the nature of the interaction (e.g., instruction-based, social interaction-based), when we refer to HRI robots we refer to any type of robot a person/s may interact or engage directly with during a task. within industries such as the agriculture sector, it has become essential to understand the challenges associated with the adoption of these robots to ensure a smooth integration with minimal resistance. As with all new technologies, there is often push-back when changing approaches and initiating new pathways within company operations, which can cause hesitation and even halt the adoption process. This paper draws from interviews with agricultural companies that have previously attempted to implement robots requiring direct human interaction, focusing on individuals within those companies who had decision-making capabilities during the implementation process. From these interviews, a set of action principles has been developed based on transferable knowledge found within the participating companies. The main results of this user study highlight that previous implementation attempts, whether positive or negative, influence future adoption. The study also identifies the multitude of barriers surrounding the agricultural sector's adoption of these technologies and suggests potential actions for companies to take to minimize the issues associated with implementing HRI robots. By identifying common successes and failures and contextualizing them for other companies to follow, this study aims to utilize lessons learned from past implementation attempts to shorten the learning curve and reduce hesitation in adopting HRI robots within the agricultural sector.

The integration and adoption of Human-Robot Interaction (HRI) technologies present numerous challenges and opportunities, with adoption referring to the stage in which they are initially selected for use, and integration referring to a sense of acceptance and transparency within the user environment once they’ve been adopted. As we move towards a hybrid society where we must coexist with agents such as robots, issues such as privacy concerns, ethical considerations, and the potential displacement of human workers by robots need to be addressed. However, the opportunities are equally compelling, including improved efficiency, enhanced safety in hazardous environments, and the potential for robots to as- sist in tasks that are physically demanding or repetitive for humans. We propose to run a workshop on the challenges and opportuni- ties that the adoption and integration of HRI technologies pose in the creation of this hybrid society as a crucial platform for re- searchers, developers, and other stakeholders to collaborate, share insights, and address these opportunities and challenges collectively. By fostering interdisciplinary dialogue, our workshop can catal- yse innovation by fostering discussion, establishing best practices, and informing policies surrounding the responsible integration of robots into society and Industry. Furthermore, the community stands to gain invaluable knowledge, networking opportunities, and the chance to shape the future of HRI technologies while con- sidering the technological and social factors that play a crucial role in the adoption and integration of such technologies. With this workshop, our main objective is to create a welcoming environ- ment to discuss the issues surrounding the adoption and integration of Human-Robot Interaction technologies in different topic areas, as well as to explore together with attendees the potential ways forward to improve this.

As robotics, particularly in agriculture, become more prevalent, understanding the role that different factors play on the trust levels that users have in these robots becomes crucial to facilitate their adoption and integration into the industry. In this paper we present the results of a within-subjects study that included between-subject factors exploring how prior experience with robotics and different interaction styles with a mobile manipulator robot may affect trust levels in said robot before and after the completion of an agriculture-related manipulation task. The results show that interacting with the robot helps improve trust levels, particularly for those without prior experience with robotics, who present a higher trust improvement score, and that an interaction style involving physical human-robot interaction (pHRI), more specifically Learning by Demonstration, was favoured versus less direct interaction styles. We found that incorporating Text-to-Speech (TTS) can be a good design choice when trying to improve trust, and that the improvement score for trust before and after interaction with the robot was significantly higher for older age groups, with these participants being more conservative with their reported trust level before the interaction. Overall, these results offer insights into different interaction styles and their effect on trust levels for an agriculture-related manipulation task, and open the door to future work exploring further interaction styles and task variations.

Increasingly, robots are adopted for routine tasks such as cleaning and disinfection of public spaces, raising questions about attitudes and trust of professional cleaners who might in future have robots as teammates, and whether the general public feels reassured when disinfection is carried out by robots. In this paper, we present the results of a mixed-methods user study exploring how trust and reassurance by both professional cleaners and members of the public is affected by the use of a UV-C disinfection robot and information about its performance after disinfecting a simulated classroom. The results show a range of insights for those designing and wishing to deploy UV-C robots: we found that trust and reassurance are affected by information about the UV-C robot’s task performance, with more information coinciding with significantly more agreement to be able to judge that the robot is doing a good job. However, care should be taken when designing information about task performance to avoid misinterpretation. Overall, the results suggest a generally positive picture regarding the use of UV-C disinfecting robots and that cleaning professionals would be happy to have them as their teammates; however, there were also some concerns regarding the effect on less-skilled jobs. Taken together, our results provide considerations to make UV-C robots welcomed by cleaning teams as well as to provide reassurance to space users.

Human Factors play a significant role in the development and integration of avionic systems to ensure that they are trusted and can be used effectively. As Unoccupied Aerial Vehicle (UAV) technology becomes increasingly important to the aviation domain this holds true. This study aims to gain an understanding of UAV operators’ trust requirements when piloting UAVs by utilising a popular aviation interview methodology (Schema World Action Research Method), in combination with key questions on trust identified from the literature. Interviews were conducted with six UAV operators, with a range of experience. This identified the importance of past experience to trust and the expectations that operators hold. Recommendations are made that target training to inform experience, in addition to the equipment, procedures and organisational standards that can aid in developing trustworthy systems. The methodology that was developed shows promise for capturing trust within human-automation interactions.

Virtual human technologies are now being widely explored as therapy tools for mental health disorders including depression and anxiety. These technologies leverage the ability of the virtual agents to engage in naturalistic social interactions with a user to elicit behavioural expressions which are indicative of depression and anxiety. Research efforts have focused on optimising the human-like expressive capabilities of the virtual human, but less attention has been given to investigating the effect of virtual human mediation on the expressivity of the user. In addition, it is still not clear what an optimal task is or what task characteristics are likely to sustain long term user engagement. To this end, this paper describes the design and evaluation of virtual human-mediated tasks in a user study of 56 participants. Half the participants complete tasks guided by a virtual human, while the other half are guided by text on screen. Self-reported PHQ9 scores, biosignals and participants' ratings of tasks are collected. Findings show that virtual-human mediation influences behavioural expressiveness and this observation differs for different depression severity levels. It further shows that virtual human mediation improves users' disposition towards tasks.

Access to healthcare advice is crucial to promote healthy societies. Many factors shape how access might be constrained, such as economic status, education or, as the COVID-19 pandemic has shown, remote consultations with health practitioners. Our work focuses on providing pre/post-natal advice to maternal women. A salient factor of our work concerns the design and deployment of embodied conversation agents (ECAs) which can sense the (health) literacy of users and adapt to scaffold user engagement in this setting. We present an account of a Wizard of Oz user study of 'ALTCAI', an ECA with three modes of interaction (i.e., adaptive speech and text, adaptive ECA, and non-adaptive ECA). We compare reported engagement with these modes from 44 maternal women who have differing levels of literacy. The study shows that a combination of embodiment and adaptivity scaffolds reported engagement, but matters of health-literacy and language introduce nuanced considerations for the design of ECAs.