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This study investigates user experiences of interactions with two types of robots: Pepper, a social humanoid robot, and Double 3, a self-driving telepresence robot. Conducted in a controlled setting with a specific participant group, this research aims to understand how the design and functionality of these robots influence user perception, interaction patterns, and emotional responses. The findings reveal diverse participant reactions, highlighting the importance of adaptability, effective communication, autonomy, and perceived credibility in robot design. Participants showed mixed responses to human-like emotional displays and expressed a desire for robots capable of more nuanced and reliable behaviors. Trust in robots was influenced by their perceived functionality and reliability. Despite limitations in sample size, the study provides insights into the ethical and social considerations of integrating AI in public and professional spaces, offering guidance for enhancing user-centered designs and expanding applications for social and telepresence robots in society.

This paper presents a taxonomy of agents’ embodiment in physical and virtual environments. It categorizes embodiment based on five entities: the agent being embodied, the possible mediator of the embodiment, the environment in which sensing and acting take place, the degree of body, and the intertwining of body, mind, and environment. The taxonomy is applied to a wide range of embodiment of humans, artifacts, and programs, including recent technological and scientific innovations related to virtual reality, augmented reality, telepresence, the metaverse, digital twins, and large language models. The presented taxonomy is a powerful tool to analyze, clarify, and compare complex cases of embodiment. For example, it makes the choice between a dualistic and non-dualistic perspective of an agent’s embodiment explicit and clear. The taxonomy also aided us to formulate the term “embodiment by proxy” to denote how seemingly non-embodied agents may affect the world by using humans as “extended arms”. We also introduce the concept “off-line embodiment” to describe large language models’ ability to create an illusion of human perception.

The recent development of large language models (LLMs) and improvements in speech recognition have made it realistic to envision AI-driven robots replace humans in debates, or even debating with each other. One application area is politics, where debating robots could support human politicians and, in principle, they could also debate on their own. However, political debating are highly complex and is often guided by values and ideologies, rather than rational decisions based on explicit facts.

In this paper we discuss how introducing appropriate bias into an LLM can be a way to accomplish this. As a simple proof of concept, we present a novel system of three robots conducting verbal debates on selectable topics. The robots are driven by the LLM GPT-3.5, and the desired political view, level of knowledge, and speaking style of each robot are configurable. The results demonstrate how LLMs may be used to argue both for and against different standpoints in debates, and how the output arguments depend on a programmed bias reflecting desired values and ideological principles.

The Umeå Student Conference in Computing Science (USCCS) is an annual event organized as part of a course offered by the Department of Computing Science at Ume ̊a University. The primary aim of the course is to provide students with a hands-on introduction to independent research, scientific writing, and oral presentation. 

A student who participates in the course selects a topic in computing science and related areas and formulates a research question. The course revolves around three significant milestones. The first milestone requires students to write a lit- erature overview with an annotated bibliography, demonstrating not only their academic proficiency but also grounding their research into existing literature - standing on the shoulder of giants. The second milestone involves the actual research and its description in a scholarly manner, demonstrating a commitment to academic excellence, rigour and adherence to high standards. The third milestone encompasses the analysis and discussion of the obtained results, ensuring a thorough and objective examination. 

These three milestones are supported by three peer-review group meetings, consisting of 4-5 students each. During these sessions, each ongoing draft or milestone is efficiently and critically discussed aiming at guidance and improvement of the draft. This process provides valuable training in both giving and receiving constructive criticism. 

In addition, four lectures support the students’ learning and progress in the incremental development and refinement of a scientific paper, and timely discusssions on research ethics and quality. 

Each scientific paper is submitted to USCCS through EasyChair, an on-line submission system, and receives anonymous reviews from experts in the field. Based on the reviews and the editor’s assessment a decision of acceptance is made. Reviewers’ comments are incorporated, and the revised manuscripts undergo a final review before being included in these proceedings. The review process and conference format aim to simulate realistic settings for publishing processes and participation in scientific conferences. 

The conference is the highlight of the course, and this year, we received 14 submissions out of a possible 16, each thoroughly reviewed by experts listed on the following page. As a result, 8 submissions have been accepted for presentation at the conference. We extend our gratitude to the reviewers for their efforts within a tight timeframe and busy schedules. 

We also thank all authors for their dedication and outstanding final results, which will be presented during the conference. We wish all participants interesting exchange of ideas and stimulating discussions throughout USCCS. 

We investigate interaction patterns for humans interacting with explainable and non-explainable robots. Non-explainable robots are here robots that do not explain their actions or non-actions, neither do they give any other feedbackduring interaction, in contrast to explainable robots. We video recorded and analyzed human behavior during a board game, where 20 humans verbally instructed either an explainable or non-explainable Pepper robot to move objects on the board. The transcriptions and annotations of the videos were transformed into transactions for association rule mining. Association rules discovered communication patterns in the interaction between the robots and the humans, and the most interesting rules were also tested with regular chi-square tests. Some statistically significant results are that there is a strong correlation between men and non-explainable robots and women and explainable robots, and that humans mirror some of the robot’s modality. Our results also show that it is important to contextualize human interaction patterns, and that this can be easily done using association rules as an investigative tool. The presented results are important when designing robots that should adapt their behavior to become understandable for the interacting humans.

One important aspect when designing understandable robots is how robots should communicate with a human user to be understood in the best way. In elder care applications this is particularly important, and also difficult since many older adults suffer from various kinds of impairments. In this paper we present a solution where communication modality and communication parameters are adapted to fit both a user profile and an environment model comprising information about light and sound conditions that may affect communication. The Rasa dialogue manager is complemented with necessary functionality, and the operation is verified with a Pepper robot interacting with several personas with impaired vision, hearing, and cognition. Several relevant ethical questions are identified and briefly discussed, as a contribution to the WARN workshop.

The Umeå Student Conference in Computing Science (USCCS) is organized annually as part of a course given by the Computing Science department at Umeå University. The objective of the course is to give the students a practical introduction to independent research, scientific writing, and oral presentation. A student who participates in the course first selects a topic and a research question that they are interested in. If the topic is accepted, the student outlines a paper and composes an annotated bibliography to give a survey of the research topic. The main work consists of conducting the actual research that answers the question asked, and convincingly and clearly reporting the results in a scientific paper. Another major part of the course is multiple internal peer review meetings in which groups of students read each others’ papers and give feedback to the author. This process gives valuable training in both giving and receiving criticism in a constructive manner. Altogether, the students learn to formulate and develop their own ideas in a scientific manner, in a process involving internal peer reviewing of each other’s work and under supervision of the teachers, and incremental development and refinement of a scientific paper. Each scientific paper is submitted to USCCS through an on-line submission system, and receives two reviews. Based on the review, the editors of the conference proceedings issue a decision of preliminary acceptance of the paper to each author. If, after final revision, a paper is accepted, the student is given the opportunity to present the work at the conference. The review process and the conference format aims at mimicking realistic settings for publishing and participation at scientific conferences.

The increasing demands of society in terms of communication, monitorization and assistance, which have been recently exacerbated by the COVID-19 pandemic, are driving the consolidation of a new social model. This model involves a strong presence of technology in daily life settings; thus, robotics is one of the disciplines most drastically affected by this shift. Robots working in a social context should incorporate social parameters in their behaviour in order to maximize adherence. Depending on the particular use case and application area, these social parameters affect navigation, interaction and task planning. Their implementation therefore requires a multidisciplinary approach, including new skills and procedures in the cognitive architecture of the robot, and an evaluation of the robot’s performance in terms of functionality, acceptability, utility and accessibility. This Special Issue will provide thorough use case specifications, a description of technical solutions and analysis of user experience in support of the application of social robots in different domains, including: education, telepresence, monitoring, security, assistance, healthcare, service, therapy, caregiving, small retail automation or industrial co-working.