This workshop aims to support early-career researchers in the field of Human-Agent Interaction (HAI), especially those from non-native English-speaking backgrounds. Despite increasing global engagement, many talented researchers face challenges in presenting their work internationally due to language barriers and limited opportunities. By providing a platform to present research in English in a supportive and peer-driven environment, this workshop will foster accessibility, visibility, and confidence among participants. Presentations will be followed by extended and moderated Q&A sessions to encourage inclusive discussion. The workshop also invites guest talks from early-career researchers who exemplify innovative HAI research, promoting role models for the next generation. Overall, the workshop seeks to lower entry barriers and empower underrepresented voices in the global HAI community.

As AI and robots become increasingly integrated into daily life, fostering trust in robots is essential for establishing long-term human-robot relationships. Enhancing people’s trust in robots can help mitigate anxiety and aversion toward them. While previous research has primarily focused on trust in robots based on their performance and achievements, this study explores the impact of robots appearing to trust humans on human decision-making. In this study, a robot performed the Prisoner’s Dilemma task three times with participants. We examined whether participants’ choices in the game were influenced by the robot’s eye color (blue, red), the robot’s behavior (available, not available), and before/after the task using a three-factor mixed design. The first experiment assessed whether the robot appeared to trust participants using a questionnaire. The second measured participants’ trust in the robot after the interaction. Analysis results indicated that as the number of Prisoner’s Dilemma interactions increased, participants were more likely to betray the robot. However, trust in the robot increased after the task, suggesting that participants felt more trusted by the robot, which in turn enhanced their own trust in it. This study introduces a novel perspective on human-robot relationships, highlighting how making people feel trusted by a robot can foster greater trust toward it.

As AI technology develops, the relationship between people and agents is becoming increasingly important as more agents are used in human society. One way to improve this relationship is to increase empathy for the agent. In this study, to increase empathy toward the agent, an agent was envisioned that assists participants in reflecting on traffic safety. Focusing on the agent’s attitude and behavior modification, three hypotheses were investigated through experimental testing. The results of experiment showed an interaction between the agent’s behavior modification and the before/after factors, indicating that a positive behavior modification maintains empathy for the agent. This research reveals an approach that promotes the social use of agents by people, which is necessary for the social coexistence of people and agents.

As anthropomorphic agents (AI and robots) are increasingly used in society, empathy and trust between people and agents are becoming increasingly important. A better understanding of agents by people will help to improve the problems caused by the future use of agents in society. In the past, there has been a focus on the importance of self-disclosure and the relationship between agents and humans in their interactions. In this study, we focused on the attributes of self-disclosure and the relationship between agents and people. An experiment was conducted to investigate hypotheses on trust and empathy with agents through six attributes of self-disclosure (opinions and attitudes, hobbies, work, money, personality, and body) and through competitive and cooperative relationships before a robotic agent performs a joint task. The experiment consisted of two between-participant factors: six levels of self-disclosure attributes and two levels of relationship with the agent. The results showed that the two factors had no effect on trust in the agent, but there was statistical significance for the attribute of self-disclosure regarding a person’s empathy toward the agent. In addition, statistical significance was found regarding the agent’s ability to empathize with a person as perceived by the person only in the case where the type of relationship, competitive or cooperative, was presented. The results of this study could lead to an effective method for building relationships with agents, which are increasingly used in society.

This study investigated whether human trust in a social robot with anthropomorphic physicality is similar to that in an AI agent or in a human in order to clarify how anthropomorphic physicality influences human trust in an agent. We conducted an online experiment using two types of cognitive tasks, calculation and emotion recognition tasks, where participants answered after referring to the answers of an AI agent, a human, or a social robot. During the experiment, the participants rated their trust levels in their partners. As a result, trust in the social robot was basically neither similar to that in the AI agent nor in the human and instead settled between them. The results showed a possibility that manipulating anthropomorphic features would help assist human users in appropriately calibrating trust in an agent.

One way to improve the relationship between humans and anthropomorphic agents is to have humans empathize with the agents. In this study, we focused on a task between agents and humans. We experimentally investigated hypotheses stating that task difficulty and task content facilitate human empathy. The experiment was a two-way analysis of variance (ANOVA) with four conditions: task difficulty (high, low) and task content (competitive, cooperative). The results showed no main effect for the task content factor and a significant main effect for the task difficulty factor. In addition, pre-task empathy toward the agent decreased after the task. The ANOVA showed that one category of empathy toward the agent increased when the task difficulty was higher than when it was lower. This indicated that this category of empathy was more likely to be affected by the task. The task itself used can be an important factor when manipulating each category of empathy.