Seiji Yamada

National Institute of Informatics · Department of Informatics

In this study, we investigated the influence of robot beeps on trust dynamics in human-robot interaction. We designed an experimental setup in which participants engaged in a calculation task alongside a robot that alternated between successful and unsuccessful performances. Throughout the task, flat beeps were strategically expressed at different...

This paper reviews our previous trials of Nudge-XAI, an approach that introduces automatic biases into explanations from explainable AIs (XAIs) with the aim of leading users to better decisions, and it discusses the benefits and challenges. Nudge-XAI uses a user model that predicts the influence of providing an explanation or emphasizing it and att...

This paper reviews our previous trials of Nudge-XAI, an approach that introduces automatic biases into explanations from explainable AIs (XAIs) with the aim of leading users to better decisions, and it discusses the benefits and challenges. Nudge-XAI uses a user model that predicts the influence of providing an explanation or emphasizing it and att...

These days, we see different types of telepresence robots, and there has been a tremendous amount of research and development on these robots. Some telepresence robots have monitors to show the faces of remote operators and mobility to move around, but some do not have a monitor and instead have a robot face, and also they have robotic arms to do m...

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 an agent and a human in which the agent makes a mistake. To investigate significant factors for designing a robotic agent that can promote humans’ empathy, we experimentally examined...

Communication technology has improved and become diverse in terms of content and form of functions, and telepresence robots are one type of such technology. These robots are used in an expanding variety of cases. One example of an expanding application is the ability to enable even individuals with disabilities to work and go outside using telepres...

Understanding what an AI system can and cannot do is necessary for end-users to use the AI properly without being over- or under-reliant on it. Reliance calibration cues (RCCs) communicate an AI’s capability to users, resulting in optimizing their reliance on it. Previous studies have typically focused on continuously presenting RCCs, and although...

Perspective-taking, which enables individuals to consider the thoughts and objectives of another, is well established to be a successful strategy for encouraging pro-social behavior in human-computer interactions. Nowadays, perspective-taking is no longer limited to text; it is now more frequently used in virtual reality (VR). However, most previou...

This study investigated how displaying a robot's attention heatmap while the robot point gesture at it influences human trust and acceptance of its outputs. We conducted an experiment using two types of visual tasks. In these tasks, the participants were required to decide whether to accept or reject the answers of an AI or robot. The participants...

This study used XAI, which shows its purposes and attention as explanations of its process, and investigated how these explanations affect human trust in and use of AI. In this study, we generated heat maps indicating AI attention, conducted Experiment 1 to confirm the validity of the interpretability of the heat maps, and conducted Experiment 2 to...

As AI technology develops, trust in AI agents is becoming more important for more AI applications in human society. Possible ways to improve the trust relationship include empathy, success-failure series, and capability (performance). Appropriate trust is less likely to cause deviations between actual and ideal performance. In this study, we focus...

As AI technologies progress, social acceptance of AI agents, including intelligent virtual agents and robots, is becoming even more important for more applications of AI in human society. One way to improve the relationship between humans and anthropomorphic agents is to have humans empathize with the agents. By empathizing, humans act positively a...

In this paper, we conducted experiments with trip recommendation agents. The travel industry offers potential roles for robots and virtual agents. Also, product recommendation on websites is one of the themes gathering attention in the field of virtual agents. Thus, providing methods for designing trip recommendation robots or agents for websites i...

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 an agent and a human in which the agent makes a mistake. To investigate significant factors for designing a robotic agent that can promote humans empathy, we experimentally examined t...

For effective collaboration between humans and intelligent agents that employ machine learning for decision-making, humans must understand what agents can and cannot do to avoid over/under-reliance. A solution to this problem is adjusting human reliance through communication using reliance calibration cues (RCCs) to help humans assess agents' capab...

This study investigated how wait time influences trust in and reliance on a robot. Experiment 1 was conducted as an online experiment manipulating the wait time for the task partner's action from 1 to 20 seconds and the anthropomorphism of the partner. As a result, the anthropomorphism influenced trust in the partner and did not influence reliance...

This study used XAI, which shows its purposes and attention as explanations of its process, and investigated how these explanations affect human trust in and use of AI. In this study, we generated heat maps indicating AI attention, conducted Experiment 1 to confirm the validity of the interpretability of the heat maps, and conducted Experiment 2 to...

This study investigated the effects of a combination of anthropomorphic and mechanical features in a social robot on human trust, especially focusing on how beep sounds emitted by a social robot with anthropomorphic physicality influence human trust in the robot. Beep sounds were experimentally manipulated to be presented right before a robot showe...

Human knowledge can reduce the number of iterations required to learn in reinforcement learning. Though the most common approach uses trajectories, it is difficult to acquire them in certain domains. Subgoals, which are intermediate states, have been studied instead of trajectories. Subgoal-based reward shaping is a reward-shaping framework with a...

The social acceptance of AI agents, including intelligent virtual agents and physical robots, is becoming more important for the integration of AI into human society. Although the agents used in human society share various tasks with humans, their cooperation may frequently reduce the task performance. One way to improve the relationship between hu...

For effective collaboration between humans and intelligent agents that employ machine learning for decision-making, humans must understand what agents can and cannot do to avoid over/under-reliance. A solution to this problem is adjusting human reliance through communication using reliance calibration cues (RCCs) to help humans assess agents' capab...

The social acceptance of AI agents, including intelligent virtual agents and physical robots, is becoming more important for the integration of AI into human society. Although the agents used in human society share various tasks with humans, their cooperation may frequently reduce the task performance. One way to improve the relationship between hu...

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...

Perspective taking, which allows people to imagine another's thinking and goals, is known to be an effective method for promoting prosocial behaviors in human-computer interactions. However, most of the previous studies have focused on simulating human-human interactions in the real world by offering participants experiences related to various mora...

This study investigated trust in a social robot compared with that in an AI system and a human as a task partner in consideration of four types of trust: initial trust (trust before a task), early trust (trust in the beginning of a task), trust decline due to a partner's errors, and trust recovery due to a partner's performance recovery. We conduct...

We propose an AI-assisted design concept exploration tool, the “Character Space Construction” (“CSC”). Concept designers explore and articulate the target product aesthetics and semantics in language, which is expressed using “Design Concept Phrases” (“DCPs”), that is, compound adjective phrases, and contrasting terms that convey what are not their...

We propose an AI-assisted design concept exploration tool, the "Character Space Construction" ("CSC"). Concept designers explore and articulate the target product aesthetics and semantics in language, which is expressed using "Design Concept Phrases" ("DCPs"), that is, compound adjective phrases, and contrasting terms that convey what are not their...

We present an AI-assisted search tool, the "Design Concept Exploration Graph" ("D-Graph"). It assists automotive designers in creating an original design-concept phrase, that is, a combination of two adjectives that conveys product aesthetics. D-Graph retrieves adjectives from a ConceptNet knowledge graph as nodes and visualizes them in a dynamical...

Previous studies have found that nudging is key to promoting altruism in human-human interaction. However, in social robotics, there is still a lack of study on confirming the effect of nudging on altruism. In this paper, we apply two nudge mechanisms, peak-end and multiple viewpoints, to a video stimulus performed by social robots (virtual agents)...

Previous studies have found that nudging is key to promoting altruism in human-human interaction. However, in social robotics, there is still a lack of study on confirming the effect of nudging on altruism. In this paper, we apply two nudge mechanisms, peak-end and multiple viewpoints, to a video stimulus performed by social robots (virtual agents)...

The human-agent team, which is a problem in which humans and autonomous agents collaborate to achieve one task, is typical in human-AI collaboration. For effective collaboration, humans want to have an effective plan, but in realistic situations, they might have difficulty calculating the best plan due to cognitive limitations. In this case, guidan...

The human-agent team, which is a problem in which humans and autonomous agents collaborate to achieve one task, is typical in human-AI collaboration. For effective collaboration, humans want to have an effective plan, but in realistic situations, they might have difficulty calculating the best plan due to cognitive limitations. In this case, guidan...

Reinforcement learning, which acquires a policy maximizing long-term rewards, has been actively studied. Unfortunately, this learning type is too slow and difficult to use in practical situations because the state-action space becomes huge in real environments. Many studies have incorporated human knowledge into reinforcement Learning. Though human...

As AI technologies progress, social acceptance of AI agents including intelligent virtual agents and robots is getting to be even more important for more applications of AI in human society. One way to improve the relationship between humans and anthropomorphic agents is to have humans empathize with the agents. By empathizing, humans take positive...

Nowadays, a community starts to find the need for human presence in an alternative way, there has been tremendous research and development in advancing telepresence robots. People tend to feel closer and more comfortable with telepresence robots as many senses a human presence in robots. In general, many people feel the sense of agency from the fac...

Reinforcement learning, which acquires a policy maximizing long-term rewards, has been actively studied. Unfortunately, this learning type is too slow and difficult to use in practical situations because the state-action space becomes huge in real environments. The essential factor for learning efficiency is rewards. Potential-based reward shaping...

Reinforcement learning, which acquires a policy maximizing long-term rewards, has been actively studied. Unfortunately, this learning type is too slow and difficult to use in practical situations because the state-action space becomes huge in real environments. Many studies have incorporated human knowledge into reinforcement Learning. Though human...

Social navigation has been gaining attentions with the growth in machine intelligence. Since reinforcement learning can select an action in the prediction phase at a low computational cost, it has been formulated in a social navigation tasks. However, reinforcement learning takes an enormous number of iterations until acquiring a behavior policy in...

Recent advances in AI technologies are dramatically changing the world and impacting our daily life. However, human users still essentially need to cooperate with AI systems to complete tasks as such technologies are never perfect. For optimal performance and safety in human-AI cooperation, human users must appropriately adjust their level of trust...

Although the processing speed of computers has been drastically increasing year by year, users still have to wait for computers to complete tasks or to respond. To cope with this, several studies have proposed presenting certain visual information to users to change their perception of time passing as shorter, e.g., progress bars with animated ribb...

Safety and efficiency of human-AI collaboration often depend on how humans could appropriately calibrate their trust towards the AI agents. Over-trusting the autonomous system sometimes causes serious safety issues. Although many studies focused on the importance of system transparency in keeping proper trust calibration, the research in detecting...

Using robots and virtual agents as teachers in education is one of the most important fields in HAI. Many pieces of work have been published; however, little has been reported on the relationship between the subject on which a virtual teacher (VT) gives a lesson and the appearance of the VT. For example, are robot-like agents usually effective rega...

There have been few studies on cognitive bias for algorithm understanding in a human-computer cooperative situation. In the present study, we conducted an experiment with participants to investigate the cognitive process of higher level abstraction (algorithm understanding) performed in a human-computer collaboration task. The most recently used (M...

Eye gaze is considered to be a particularly important non-verbal communication cue. Gaze research is also becoming a hot topic in human–robot interaction (HRI). However, research on social eye gaze for HRI focuses mainly on human-like robots. There remains a lack of methods for functional robots, which are constrained in appearance, to show gaze-li...

Anthropomorphic agents used in online-shopping need to be trusted by users so that users feel comfortable buying products. In this paper, we propose a model for designing trustworthy agents by assuming two factors of trust, that is, emotion and knowledgeableness perceived. Our hypothesis is that when a user feels happy and perceives an agent as bei...

In this paper, we verify the effect of a VH's objective and subjective speech. We hypothesized that the effect of objective and subjective speech depends on the topics that a VH speaks about and predicted that subjective speech is effective when a VH speaks about topics that it prefers. To verify this hypothesis, we performed an experiment with two...

Today's computers are becoming ever more versatile. They are used in various applications, such as for education, entertainment, and information services. In other words, computers are often required to not only inform users of information but also communicate with them socially. Previous studies explored the design of ambient light displays and su...

In this work, we developed virtual humans (VH) designed to persuade users. We introduce the notion of distinctiveness of topics and define two kinds of persuasion strategies: "objective persuasion", which aims to persuade with only objective sentences and no expression, and "subjective persuasion", which aims to persuade with only subjective senten...

In this paper, we explore how a utility robot might express emotions via expressive lights and in-situ motions. In most previous work, methods for either modality were investigated alone, leaving a huge potential to improve the expression of emotions by combining the two modalities. We present a series of three studies, one for investigating how we...

Poor trust calibration in autonomous vehicles often degrades total system performance in safety or efficiency. Existing studies have primarily examined the importance of system transparency of autonomous systems to maintain proper trust calibration, with little emphasis on how to detect over-trust and under-trust nor how to recover from them. With...

Functional robots are generally restricted in ap- pearance, thus lacking ways to express their intent. In human- human interaction, gaze is an important cue for providing information and regulating interaction. In this pilot study, we investigate how we can implement gaze behavior in functional robots since gaze communication can allow humans to re...

A recent approach based on Bayesian inverse planning for the "theory of mind" has shown good performance in modeling human cognition. However, perfect inverse planning differs from human cognition during one kind of complex tasks due to human bounded rationality. One example is an environment in which there are many available plans for achieving a...

Artificial subtle expressions (ASEs) are machine-like expressions used to convey a system's confidence level to users intuitively. So far, auditory ASEs using beep sounds, visual ASEs using LEDs, and motion ASEs using robot movements have been implemented and shown to be effective. In this paper, we propose a novel type of ASE that uses vibration (...

Because appearance-constrained robots lack expressiveness, human users often find it hard to understand their behavior and intentions. To address this, expressive lights are considered to be an effective means for such robots to communicate with people. However, existing studies mainly focus on specific tasks or goals, leaving the knowledge of how...

This article proposes a constrained clustering algorithm with competitive performance and less computation time to the state-of-the-art methods, which consists of a constrained k-means algorithm enhanced by the boosting principle. Constrained k-means clustering using constraints as background knowledge, although easy to implement and quick, has ins...

Bioluminescence is the production and emission of light by a living organism. It, as a means of communication, is of importance for the survival of various creatures. Inspired by bioluminescent light behaviors, we explore the design of expressive lights and evaluate the effect of such expressions on a human's perception of and attitude toward an ap...

Expressive light has been explored in a handful of previous studies as a means for robots, especially appearance- constrained robots that are not able to employ human-like expressions, to convey internal states and interact with people. However, it is still unknown how different light expressions can affect a person's perception and behavior. In th...

In this paper, we verified two kinds of two-dimensional mind perception models of humanoid virtual agents and investigate the relationship between the models and effect of emotional contagion. To verify the two kinds of dimensional models, we used questionnaires from prior works and our own questionnaire. From these questionnaires, we constructed a...

Humans use two distinct cognitive strategies separately to understand and predict other humans' behavior. One is mind-reading, in which an internal state such as an intention or an emotional state is assumed to be a source of a variety of behaviors. The other is behavior-reading, in which an actor's behavior is modeled based on stimulus-response as...