Hirotaka Osawa

Emotional cyborg: complementing emotional labor with human-agent interaction technology

The author proposes the notion of an emotional cyborg as a new application proposal in the human-agent interaction (HAI) field. This paper is a summary of what kind of human processes maintain emotional labor and how such kind of social labor is supported by HAI technologies. The author implemented AgencyGlass, a prototype application, as a tool for realizing an emotional cyborg. The device is attached on a users face and displays the users eye gestures. The author created a prototype application for supplementing emotional labor with AgencyGlass and presented this as a video. Reactions from media and online feedback on the prototype are analyzed, and the future of HAI applications is illustrated.

E-Gaze Glasses: Simulating Natural Gazes for Blind People

Gaze and eye contact are frequently in social occasions used among sighted people. Gaze is considered as a predictor of attention and engagement between interlocutors in conversations. However, gaze signals from the sighted are not accessible for the blind person in face-to-face communication. In this paper, we present functional work-in-progress prototype, E-Gaze glasses, an assistive device based on an eye tracking system. E-Gaze simulates natural gaze for blind people, especially establishing the eye contact between blind and sighted people to enhance their engagement in face-to-face conversations. The gaze behavior is designed based on a turn-taking model, which interprets the corresponding relationship between the conclusive gaze behavior and the interlocutors conversation flow.

Future Relations between Humans and Artificial Intelligence: A Stakeholder Opinion Survey in Japan

Concern about the potential benefits and risks of artificial intelligence (AI) has given impetus to the establishment of AI research. AI requires responsible research and innovation (RRI) with the collaboration of various stakeholders, including the public, from the early stages. However, stakeholders may have different opinions about AI and human-machine relations. We aim to discuss these viewpoints by conducting a questionnaire survey, and to suggest perspectives on future collaborations among stakeholders.

Investigation of the effects of nonverbal information on werewolf

Werewolf is one of the popular communication games all over the world. It treats ambiguity of human discussion including the utterances, gestures and facial expressions in a broad sense. In this research, we pay attention to this imperfect information game werewolf. The purpose of the research is to develop an intelligent agent “AI werewolf” which is enabled to naturally play werewolf with human. This paper aims to investigate how behavior contribute to victory of own-side players by using machine learning as a first step. As the results of investigation and analysis of the playing movie, we found that nonverbal information in the game of werewolf has importance to winning or losing the game.

Development of werewolf match system for human players mediated with lifelike agents

Are You a Werewolf? is a conversation type game. We construct a Werewolf match system for humans with lifelike agents. We evaluate whether it is possible to realize conversation space of Are You a Werewolf? with the system.

Movement design of a life-like agent for the werewolf game

In this research, we target at the interactive communication game “werewolf” with a subject of research. Werewolf is a popular party game all over the world, and the relevance studies have been advanced in recent years. However, the life-like agent who does werewolf has not been developed. Therefore the purpose of this research is to analyze non-verbal information from movies which play the werewolf with face-to-face communication and to make clear the impression for others by the movements of players in the game. Moreover, we verify whether the life-like agent gives an impression like human in werewolf game by mounting the movements on a life-like agent.

E-Gaze: Create Gaze Communication for People with Visual Disability

Gaze signals are frequently used by the sighted in social interactions as visual cues. However, these signals and cues are hardly accessible for people with visual disability. A conceptual design of E-Gaze glasses is proposed, assistive to create gaze communication between blind and sighted people in face-to-face conversations. We interviewed 20 totally blind and low vision participants to envision the use of the E-Gaze. We explained four features of E-Gaze to participants using persona and use scenarios. Participants discussed the features on their usefulness, efficiency and interest. The results helped us clarify the design direction and further research.

AI Wolf Contest — Development of Game AI Using Collective Intelligence —

In this study, we specify the design of an artificial intelligence (AI) player for a communication game called “Are You a Werewolf?” (AI Wolf). We present the Werewolf game as a standard game problem in the AI field. It is similar to game problems such as Chess, Shogi, Go, and Poker. The Werewolf game is a communication game that requires several AI technologies such as multi-agent coordination, intentional reading, and understanding of the theory of mind. Analyzing and solving the Werewolf game as a standard problem will provide useful results for our research field and its applications. Similar to the RoboCup project, the goal of this project is to determine new themes while creating a communicative AI player that can play the Werewolf game with humans. As an initial step, we designed a platform to develop a game-playing AI for a competition. First, we discuss the essential factors in Werewolf with reference to other studies. We then develop a platform for an AI game competition that uses simplified rules to support the development of AIs that can play Werewolf. The paper reports the process and analysis of the results of the competition.

User-defined gestures for controlling primitive motions of an end effector

In designing and developing a gesture recognition system, it is crucial to know the characteristics of a gesture selected to control, for example, an end effector of a robot arm. We conducted an experiment to collect a set of user-defined gestures and investigate characteristics of the gestures for controlling primitive motions of an end effector in human–robot collaboration. We recorded 152 gestures from 19 volunteers by presenting virtual robotic arm movements to the participants, and then asked the participants to think about and perform gestures that would cause the motions. It was found that the hands were the parts of the body used most often for gesture articulation even when the participants were holding tools and objects with both hands: a number of participants used one- and two-handed gestures interchangeably, gestures were consistently performed by the participants across all pairs of reversible gestures, and the participants expected better recognition performance for gestures that were easy to think of and perform. These findings are expected to be useful as guidelines in creating a gesture set for controlling robotic arms according to natural user behaviors. Graphical Abstract

Constructing a Human-like agent for the Werewolf Game using a psychological model based multiple perspectives

In this paper, we focus on the Werewolf Game. The Werewolf Game is an advanced communication-game in which winning or losing is directly linked to ones success or failure in communication. Therefore, we expect exponential developments in artificial intelligence by studying the Werewolf Game. In this current study, we propose a psychological model that considers multiple perspectives to model the play of a human such as inferring the intention of the other side. As one of the psychological models, we constructed a “ones self model” that models the role of others as viewed from their own viewpoint. In addition, to determine whether ones opinion is reliable after inferring others intentions, we also constructed an “others model” that models the role of others as viewed from their viewpoints. Combining these models, we showed through experimentation that a combined approach achieved better results, i.e., higher win percentages.