Personality in Healthcare Human Robot Interaction (H-HRI): A Literature Review and Brief Critique

Robots are becoming an important way to deliver health care, and personality is vital to understanding their effectiveness. Despite this, there is a lack of a systematic overarching understanding of personality in health care human robot interaction (H-HRI). To address this, the authors conducted a review that identified 18 studies on personality in H-HRI. This paper presents the results of that systematic literature review. Insights are derived from this review regarding the methodologies, outcomes, and samples utilized. The authors of this review discuss findings across this literature while identifying several gaps worthy of attention. Overall, this paper is an important starting point in understanding personality in H-HRI.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/156252/1/Esterwood and Robert 2020.pdfDescription of Esterwood and Robert 2020.pdf : ArticleSEL

Is Silent External Human–Machine Interface (eHMI) Enough? A Passenger-Centric Study on Effective eHMI for Autonomous Personal Mobility Vehicles in the Field

Density functional quantum mechanical research yield a comprehensive theoretical approach on the selected organic molecule of 9,9-dihydroxynanoic acid. The DFT approach is implemented to optimise the molecular structure. The geometrical parameters of molecule were calculated. The vibrational spectrum studies were done with FT-IR and FT-Raman and their results were investigated. VEDA software is utilised to simulate PED for the basic vibrational frequencies in order to find all the vibration modes. UV–Vis analysis is performed for the gaseous phase and on solvent phases such as water, ethanol, ethyl ethanoate, acetone, and DMSO by TD-DFT-B3LYP with 6-311++G (d,p), and band gap energies are calculated. FMO investigations reported analysing the compound energy gap, softness, hardness, and electrophilicity index in gaseous phase along with a variety solvent phase. To further understand the molecule\u27s reactive areas, Mulliken atomic charge evaluation, Fukui functions, and dual descriptors were conceptually investigated. The electro static MEP map of the compound in distinct solvent phases is provided in order to comprehend the molecular shape, size, and reactive region. The molecule\u27s hyperpolarizability is observed to be 201.8 a.u for gas, 146.6 a.u for acetone, 138.9 a.u for DMSO, 136.3 a.u for water, and 169.8 a.u for ethyl ethanoate, will supports the molecule is good NLO material. The donor acceptor interaction has been explored so as to explain the intramolecular hyper conjugative interaction and stability. To understand the topology Multiwfn analysis like ELF, LOL and ALIE were done. The E.coli proteins are downloaded from the PDB database and fictitiously docked with our selected ligand molecule using Auto Dock software to determine hydrogen bonding and binding energy

Is Silent External Human–Machine Interface (eHMI) Enough? A Passenger-Centric Study on Effective eHMI for Autonomous Personal Mobility Vehicles in the Field

Autonomous personal mobility vehicle (APMV) is a miniaturized autonomous vehicle designed for short-distance mobility to everyone. Due to its open design, APMV’s passengers are exposed to communications between the external human-machine interface (eHMI) on APMV and pedestrians. Therefore, effective eHMI designs for APMV need to consider potential impacts of APMV-pedestrian interactions on passengers’ subjective feelings. This study from the perspective of APMV passengers discussed three eHMI designs: (1) graphical user interface (GUI)-based eHMI with text message (eHMI-T), (2) multimodal user interface (MUI)-based eHMI with neutral voice (eHMI-NV), and (3) MUI-based eHMI with affective voice (eHMI-AV). In a riding field experiment (N = 24), eHMI-T made passengers feel awkward during the “silent time” when eHMI-T conveyed information exclusively to pedestrians, not passengers. MUI-based eHMIs with voice cues showed advantages, with eHMI-NV excelling in pragmatic quality and eHMI-AV in hedonic quality. Considering passengers’ personalities and genders in APMV eHMI design is also highlighted

A Review of Personality in Human Robot Interactions

Personality has been identified as a vital factor in understanding the quality of human robot interactions. Despite this the research in this area remains fragmented and lacks a coherent framework. This makes it difficult to understand what we know and identify what we do not. As a result our knowledge of personality in human robot interactions has not kept pace with the deployment of robots in organizations or in our broader society. To address this shortcoming, this paper reviews 83 articles and 84 separate studies to assess the current state of human robot personality research. This review: (1) highlights major thematic research areas, (2) identifies gaps in the literature, (3) derives and presents major conclusions from the literature and (4) offers guidance for future research.Comment: 70 pages, 2 figure

개발 초기 단계에서의 소셜 AI 개인비서 평가 모델 개발

학위논문(박사) -- 서울대학교대학원 : 공과대학 산업공학과, 2022.2. 윤명환.This dissertation aims to propose a user evaluation model to evaluate social AI personal assistants in the early stage of product development. Due to the rapid development of personal devices, data generated from personal devices are increasing explosively, and various personal AI services and products using these data are being launched. However, compared to the interest in AI personal assistant products, its market is still immature. In this case, it is important to understand consumer expectations and perceptions deeply and develop a product that can satisfy them to spread the product and allow general consumers to easily accept the product promptly. Accordingly, this dissertation proposes and validates a user evaluation model that can be used in the early stage of product development. Prior to proposing this methodology, main characteristics of social AI personal assistants, the importance of user evaluation in the early stage of product development and the limitations of the existing user evaluation model were investigated in Chapter 2. Various technology acceptance models and evaluation models for social AI personal assistant products have been proposed, evaluation models that can be applied in the initial stage of product development were insufficient, however. Moreover, it was found that commonly used evaluation measures for assessment of hedonic value were much fewer compared to measures for utilitarian value. These were used as starting points of this dissertation. In Chapter 3, the evaluation measures used in previous studies related to social AI personal assistant were collected and carefully reviewed. Through systematic review of 40 studies, the evaluation measures used in the past and limitation of related research were investigated. As a result, it was found that it was not easy to develop a prototype for evaluation, so it was possible to make the most of the products that have already been commercialized. In addition, all evaluation items used in previous studies were collected and used as the basis for the evaluation model to be proposed later. As a result of the analysis, considering the purpose of the social AI personal assistant, the role as supporting the user emotionally through social interaction with the user is important, but it was found that the evaluation measures related to hedonic value that are commonly used were still insufficient. In Chapter 4, evaluation measures that can be used in the initial stage of product development for social AI personal assistant were selected. Selected evaluation measures were used to evaluate three types of social robots and relationship among evaluation factors were induced through this evaluation. A process was proposed to understand to various opinions related to social robots and to derive evaluation items, and a case study was conducted in which a total of 230 people evaluated three social robots concept images using the evaluation items finally selected through this process. As a result, it is shown that consumers’ attitude toward products was built through the utilitarian dimension and the hedonic dimension. In addition, there is positive relationship between ease of use and utility in the utilitarian dimension, and among aesthetic pleasure, attractiveness of personality, affective value in the hedonic dimension. Moreover, it is confirmed that the evaluation model derived from this study showed superior explanatory power compared to the previously proposed technology acceptance model. In Chapter 5, the model was validated again by applying the evaluation measure and the relationship among evaluation factors derived in Chapter 4 to other products. 100 UX experts with expertise in the field of social AI personal assistants and 100 users who use the voice assistant service often, watched two concept videos of the voice assistant service to help users in the onboarding situation of mobile phones and evaluated these concepts. As a result of the evaluation, there is no significant difference in the evaluation results between the UX expert and the real user group, so the structural equation model analysis was conducted using all the data obtained from the UX expert and the real user group. As a result, results similar to those in Chapter 4 are obtained, and it is expected that the model could be generalized to social AI personal assistant products and applied for future research. This dissertation proposes evaluation measure and relationship among evaluation factors that can be applied when conducting user evaluation in the initial stage of social AI personal assistant development. In addition, case studies using social AI personal assistant products and services were conducted to validate it. With the findings of this study, it is expected that researchers who need to conduct user evaluation to clarify product concepts in the early stages of product development will be able to apply evaluation measures effectively. It is expected that the significance of this dissertation will become clearer if further research is conducted comparing the finished product of social AI personal assistants with the video type stimulus in the early stage of development.본 논문은 최근 빠르게 발전하고 있는 social AI personal assistant의 개발 초기 단계에 활용 가능한 사용자 평가 항목을 개발하고 평가 항목 간의 관계를 검증하는 것을 목표로 한다. 개인 디바이스의 발달로 인해, 각 디바이스에서 생성되는 데이터가 폭발적으로 증가하고 있고, 이를 활용한 개인용 AI 서비스 및 제품이 다양하게 제안되고 있다. 하지만 그 관심에 비해, social AI personal assistant 제품의 실제 시장은 아직 성숙하지 않은 단계이다. 이러한 상황에서 제품을 빠르게 확산시키고 일반 소비자들이 쉽게 제품을 수용할 수 있게 하기 위해서는, 소비자의 기대와 인식을 충분히 이해하고 그를 충족시킬 수 있는 제품을 개발하는 것이 중요하다. 이에 따라 본 연구에서는 제품 개발 초기 단계에 활용할 수 있는 사용자 평가 항목을 제안하고 평가 항목 간 관계를 도출하는 것을 목표로 한다. 먼저 2장에서는 social AI personal assistant의 특징, 제품 개발 초기 단계에서 이루어지는 사용자 평가의 중요성 및 기존 사용자 평가 모델의 한계점을 조사하였다. 기존에 기술 수용 모델 및 AI personal assistant 제품의 평가 모델들이 다양하게 제안되어 왔으나, 제품 개발 초기 단계에 활용할 수 있는 평가 모델은 부족하였고, 제품 전반을 평가할 수 있는 평가 모델의 부재로 대부분의 기존 연구에서는 두 가지 이상의 평가 모델을 결합, 수정하여 사용한 것을 알 수 있었다. 3장에서는 AI personal assistant 관련 기존 연구에서 활용된 평가 항목을 검토하였다. 총 40개의 연구를 리뷰하여, 기존에 활용되고 있는 평가 항목의 종류 및 한계점을 알아보았다. 그 결과, 평가를 위한 프로토타입 개발이 쉽지 않기에 이미 상용화된 제품들을 최대한 활용하는 것을 알 수 있었으며, 제품 전반을 평가한 사례는 부족함을 알 수 있었다. 또한 기존 연구들이 사용한 평가 항목을 모두 수집 및 정리하여 이후 제안할 평가 모델의 기반 자료로 활용하였다. 분석 결과, social AI personal assistant의 목적을 고려해보았을 때, 사용자와의 사회적 인터랙션을 통해 사용자의 감정적인 면을 채워주는 역할이 중요하지만, 공통적으로 활용하고 있는 감정적 가치 관련 평가 항목이 부족한 것으로 나타났다. 4장에서는 social AI personal assistant 제품 개발 초기 단계에서 활용 가능한 평가 항목을 수집 및 제안하고, 평가 항목을 활용하여 social robots을 평가한 뒤 이를 통해 평가 항목 간의 관계를 도출하였다. Social robots 관련 의견을 다양하게 청취하고 평가 항목을 도출하는 프로세스를 제안하였으며, 본 프로세스를 통해 최종 선정된 평가 항목을 이용하여, 총 230명이 세 가지 social robots 컨셉 영상을 평가하는 사례 연구를 진행하였다. 평가 결과, 제품에 대한 소비자 태도는 Utilitarian dimension과 Hedonic dimension을 통해 형성되었고, Utilitarian dimension 내 사용성 및 제품 효용성, Hedonic dimension에 포함되는 심미적 만족도, 성격의 매력도, 감성적 가치 각각은 서로 긍정적인 상관관계를 지님을 알 수 있었다. 또한 기존에 제안된 기술 수용 모델 대비 본 연구에서 도출한 평가 모델이 우수한 설명력을 보임을 확인하였다. 5장에서는 4장에서 도출된 평가 모델을 타 제품에 적용하여 모델을 다시 한번 검증하였다. 해당 분야에 전문성을 지닌 UX 전문가 100명 및 음성 비서 서비스를 실제 사용하는 실사용자 100명이, 휴대폰 온보딩 상황에서 사용자를 도와주는 음성 비서 서비스의 컨셉 영상 두 가지를 보고 컨셉에 대한 평가를 진행하였다. 평가 결과 UX 전문가와 실사용자 그룹 간에는 평가 결과에 유의미한 차이를 보이지 않았기 때문에, UX 전문가와 실사용자 그룹에서 얻은 데이터 전체를 활용하여 구조 방정식 모델 분석을 진행하였다. 그 결과 5장과 유사한 수준의 결과를 얻었고, 추후 해당 모델을 social AI personal assistant 제품에 일반화하여 활용할 수 있을 것으로 판단하였다. 본 논문은 social AI personal assistant 관련 제품 및 서비스의 개발 초기 단계에서 사용자 평가를 진행할 때 활용 가능한 평가 항목 및 평가 항목 간의 관계를 도출하였다. 또한 이를 검증하기 위하여 social AI personal assistant 제품 및 서비스를 활용한 사례연구를 진행하였다. 본 연구 결과는 추후 제품 개발 초기 단계에서 제품의 컨셉을 명확히 하기 위한 사용자 평가를 실시해야 하는 연구진이 효율적으로 활용할 수 있을 것으로 기대된다. 추후 이 부분의 검증을 위해, social AI personal assistants의 완제품과 개발 초기 단계의 video type stimulus를 비교하는 추가 연구가 이루어진다면 본 연구의 의미를 보다 명확하게 제시할 수 있을 것으로 생각된다.Chapter 1 Introduction 1 1.1 Background and motivation 1 1.1 Research objectives 5 1.2 Dissertation outline 7 Chapter 2 Literature review 9 2.1 Social AI personal assistant 9 2.2 User centered design process 13 2.3 Technology acceptance models 16 2.4 Evaluation measures for social AI personal assistant 22 2.5 Existing evaluation methodologies for social AI personal assistant 27 Chapter 3 Collection of existing evaluation measures for social AI personal assistants 40 3.1 Background 40 3.2 Methodology 43 3.3 Result 51 3.4 Discussion 60 Chapter 4 Development of an evaluation model for social AI personal assistants 63 4.1 Background 63 4.2 Methodology 66 4.2.1 Developing evaluation measures for social AI personal assistants 68 4.2.2 Conducting user evaluation for social robots 74 4.3 Result 77 4.3.1 Descriptive statistics 77 4.3.2 Hypothesis development and testing 80 4.3.3 Comparison with existing technology acceptance models 88 4.4 Discussion 93 Chapter 5 Verification of an evaluation model with voice assistant services 95 5.1 Background 95 5.2 Methodology 98 5.2.1 Design of evaluation questionnaires for voice assistant services 99 5.2.2 Validation of relationship among evaluation factors 103 5.3 Result 108 5.3.1 Descriptive statistics 108 5.3.2 Hypothesis development and testing 111 5.3.3 Comparison with existing technology acceptance models 118 5.4 Discussion 121 Chapter 6 Conclusion 124 6.1 Summary of this study 124 6.2 Contribution of this study 126 6.3 Limitation and future work 128 Bibliography 129 Appendix A. Evaluation measures for social AI personal assistant collected in Chapter 4 146 Appendix B. Questionnaires for evaluation of social robots 154 Appendix C. Questionnaires for evaluation of voice assistant service 166박

Building Embodied Conversational Agents:Observations on human nonverbal behaviour as a resource for the development of artificial characters

"Wow this is so cool!" This is what I most probably yelled, back in the 90s, when my first computer program on our MSX computer turned out to do exactly what I wanted it to do. The program contained the following instruction: COLOR 10(1.1) After hitting enter, it would change the screen color from light blue to dark yellow. A few years after that experience, Microsoft Windows was introduced. Windows came with an intuitive graphical user interface that was designed to allow all people, so also those who would not consider themselves to be experienced computer addicts, to interact with the computer. This was a major step forward in human-computer interaction, as from that point forward no complex programming skills were required anymore to perform such actions as adapting the screen color. Changing the background was just a matter of pointing the mouse to the desired color on a color palette. "Wow this is so cool!". This is what I shouted, again, 20 years later. This time my new smartphone successfully skipped to the next song on Spotify because I literally told my smartphone, with my voice, to do so. Being able to operate your smartphone with natural language through voice-control can be extremely handy, for instance when listening to music while showering. Again, the option to handle a computer with voice instructions turned out to be a significant optimization in human-computer interaction. From now on, computers could be instructed without the use of a screen, mouse or keyboard, and instead could operate successfully simply by telling the machine what to do. In other words, I have personally witnessed how, within only a few decades, the way people interact with computers has changed drastically, starting as a rather technical and abstract enterprise to becoming something that was both natural and intuitive, and did not require any advanced computer background. Accordingly, while computers used to be machines that could only be operated by technically-oriented individuals, they had gradually changed into devices that are part of many people’s household, just as much as a television, a vacuum cleaner or a microwave oven. The introduction of voice control is a significant feature of the newer generation of interfaces in the sense that these have become more "antropomorphic" and try to mimic the way people interact in daily life, where indeed the voice is a universally used device that humans exploit in their exchanges with others. The question then arises whether it would be possible to go even one step further, where people, like in science-fiction movies, interact with avatars or humanoid robots, whereby users can have a proper conversation with a computer-simulated human that is indistinguishable from a real human. An interaction with a human-like representation of a computer that behaves, talks and reacts like a real person would imply that the computer is able to not only produce and understand messages transmitted auditorily through the voice, but also could rely on the perception and generation of different forms of body language, such as facial expressions, gestures or body posture. At the time of writing, developments of this next step in human-computer interaction are in full swing, but the type of such interactions is still rather constrained when compared to the way humans have their exchanges with other humans. It is interesting to reflect on how such future humanmachine interactions may look like. When we consider other products that have been created in history, it sometimes is striking to see that some of these have been inspired by things that can be observed in our environment, yet at the same do not have to be exact copies of those phenomena. For instance, an airplane has wings just as birds, yet the wings of an airplane do not make those typical movements a bird would produce to fly. Moreover, an airplane has wheels, whereas a bird has legs. At the same time, an airplane has made it possible for a humans to cover long distances in a fast and smooth manner in a way that was unthinkable before it was invented. The example of the airplane shows how new technologies can have "unnatural" properties, but can nonetheless be very beneficial and impactful for human beings. This dissertation centers on this practical question of how virtual humans can be programmed to act more human-like. The four studies presented in this dissertation all have the equivalent underlying question of how parts of human behavior can be captured, such that computers can use it to become more human-like. Each study differs in method, perspective and specific questions, but they are all aimed to gain insights and directions that would help further push the computer developments of human-like behavior and investigate (the simulation of) human conversational behavior. The rest of this introductory chapter gives a general overview of virtual humans (also known as embodied conversational agents), their potential uses and the engineering challenges, followed by an overview of the four studies

Building Embodied Conversational Agents:Observations on human nonverbal behaviour as a resource for the development of artificial characters

"Wow this is so cool!" This is what I most probably yelled, back in the 90s, when my first computer program on our MSX computer turned out to do exactly what I wanted it to do. The program contained the following instruction: COLOR 10(1.1) After hitting enter, it would change the screen color from light blue to dark yellow. A few years after that experience, Microsoft Windows was introduced. Windows came with an intuitive graphical user interface that was designed to allow all people, so also those who would not consider themselves to be experienced computer addicts, to interact with the computer. This was a major step forward in human-computer interaction, as from that point forward no complex programming skills were required anymore to perform such actions as adapting the screen color. Changing the background was just a matter of pointing the mouse to the desired color on a color palette. "Wow this is so cool!". This is what I shouted, again, 20 years later. This time my new smartphone successfully skipped to the next song on Spotify because I literally told my smartphone, with my voice, to do so. Being able to operate your smartphone with natural language through voice-control can be extremely handy, for instance when listening to music while showering. Again, the option to handle a computer with voice instructions turned out to be a significant optimization in human-computer interaction. From now on, computers could be instructed without the use of a screen, mouse or keyboard, and instead could operate successfully simply by telling the machine what to do. In other words, I have personally witnessed how, within only a few decades, the way people interact with computers has changed drastically, starting as a rather technical and abstract enterprise to becoming something that was both natural and intuitive, and did not require any advanced computer background. Accordingly, while computers used to be machines that could only be operated by technically-oriented individuals, they had gradually changed into devices that are part of many people’s household, just as much as a television, a vacuum cleaner or a microwave oven. The introduction of voice control is a significant feature of the newer generation of interfaces in the sense that these have become more "antropomorphic" and try to mimic the way people interact in daily life, where indeed the voice is a universally used device that humans exploit in their exchanges with others. The question then arises whether it would be possible to go even one step further, where people, like in science-fiction movies, interact with avatars or humanoid robots, whereby users can have a proper conversation with a computer-simulated human that is indistinguishable from a real human. An interaction with a human-like representation of a computer that behaves, talks and reacts like a real person would imply that the computer is able to not only produce and understand messages transmitted auditorily through the voice, but also could rely on the perception and generation of different forms of body language, such as facial expressions, gestures or body posture. At the time of writing, developments of this next step in human-computer interaction are in full swing, but the type of such interactions is still rather constrained when compared to the way humans have their exchanges with other humans. It is interesting to reflect on how such future humanmachine interactions may look like. When we consider other products that have been created in history, it sometimes is striking to see that some of these have been inspired by things that can be observed in our environment, yet at the same do not have to be exact copies of those phenomena. For instance, an airplane has wings just as birds, yet the wings of an airplane do not make those typical movements a bird would produce to fly. Moreover, an airplane has wheels, whereas a bird has legs. At the same time, an airplane has made it possible for a humans to cover long distances in a fast and smooth manner in a way that was unthinkable before it was invented. The example of the airplane shows how new technologies can have "unnatural" properties, but can nonetheless be very beneficial and impactful for human beings. This dissertation centers on this practical question of how virtual humans can be programmed to act more human-like. The four studies presented in this dissertation all have the equivalent underlying question of how parts of human behavior can be captured, such that computers can use it to become more human-like. Each study differs in method, perspective and specific questions, but they are all aimed to gain insights and directions that would help further push the computer developments of human-like behavior and investigate (the simulation of) human conversational behavior. The rest of this introductory chapter gives a general overview of virtual humans (also known as embodied conversational agents), their potential uses and the engineering challenges, followed by an overview of the four studies