Social robots are a lesser known technology with uncertain but seemingly very powerful potential, which for decades has been portrayed in cultural artifacts as threats to human primacy. Research on people’s relationships to non-robotic technology, however, indicates that people will treat robots socially and assimilate them into their lives in ways that may disrupt existing norms but still fulfill a fundamental human need. Through the theoretical lenses of media equation and apparatgiest, this dissertation examines facets of robot humanization, defined as how people think of robots as social and human-like entities through perceptions of liking, human-likeness, and rights’ entitlement. In a 2 (gender) x 2 (physical humanness) x 3 (status) between-subjects online experiment, this dissertation explores the influence of fixed technological traits (the robot’s gender, physical humanness, and described status) and participants’ individual differences on humanization perceptions. Findings show that the robots’ features mattered less than participants’ individual traits, which explained the most variance in humanizing perceptions of social robots. Of those, participants’ prior robot exposure (both in real life and mediated) and efficacy traits were the strongest predictors of robot liking, perceived human-likeness, and perceptions of rights entitlement. Specifically, those with more real-life exposure and who perceived themselves as more technologically competent were more likely to humanize robots, while those with higher internal loci of control and negative mediated views of robots were less inclined to humanize robots. Theoretically, this study’s findings suggest that technological affordances matter less than the ontological understanding that social robots as a category may have in people’s humanizing perceptions. Looking forward, these findings indicate that there is an opportunity in the design of social robots to set precedents now that are prosocial and reflective of the world people strive for and want to inhabit in the future.

UX-designperspektivet är väsentlig vid utvärdering av interaktion med alla typer av robotar, men särskilt sociala robotar. Då dessa utvecklas för att utföra viktiga uppgifter i samhället såsom att vara sällskapsrobotar inom äldrevården, skolor med mera. User Experience Design-området har en bred samling av utvärderingsmetoder som människa-robotinteraktion-området kan dra nytta av. Denna studie syftar till att förbättra upplevelse vid interaktion med en social robot. För detta syfte har bland annat litteraturstudier genomförts där identifierades UX-aspekter som är relevanta att fokusera på vid utvärdering av förutsättningarna för engagemang i interaktionen mellan människa och social robot samt att det identifierades en kunskapslucka av tillgängliga analytiska utvärderingsmetoder inom människa-robotinteraktion (MRI). För att ta fram en ny analytisk utvärderingsmetod för att främja engagemang med en social robot användes en metodansats som är etablerad för att utveckla just utvärderingsmetoder. Designprocessen av den nya metoden bestod av fem iterativa faser som resulterade Analytisk utvärderingsmetod av engagemang vid interaktion med social sällskapsrobotar (AUEIS). AEUIS är designad för att utvärdera förutsättningarna för att uppnå engagemang vid interaktion med en social robot. Stort fokus lades på den femte fasen där versioner av AUEIS testades av flera UX-designers utifrån kriterierna att AUEIS ska ha hög validitet, vara användbar och ha bra lärbarhet. Testningen genomfördes med fyra UX-designer med olika erfarenheter inom MRI. Resultatet av testningen visade att en UX-designer utan tidigare erfarenhet av att utvärdera MRI kan använda AUEIS utan större problematik. Samtidigt, de framtagna aspekterna för att genomföra utvärderingen med var omfattande för att identifiera problem vid interaktion med en social robot. Det slutliga resultatet av detta är arbete är en komplett analytisk utvärderingsmetod. AUEIS består av sju aspekter som studerar föreutsättningarna för engagemang med en social robot. För att genomföra utvärdering med AUEIS finns det tre faser: Förberedelse, utvärdering och analys. Varje fas har några aktiviteter som följas för att få fram ett resultat om förutsättningarna av engagemang vid interaktionen med en social robot. Resultatet av utvärderingen med AUEIS kommer att bestå av kvalitativa och kvantitativa data. Den kvalitativa data som resulteras kan analyseras för att få en lista med vilka aspekter av engagemang som ej uppfylls av den sociala roboten. Den kvantitativa data kan ge en snabb överblick över vilka aspekter som har flest problem och vilka problem är mest allvarliga. AUEIS utvärderar förutsättningar för engagemang vid interaktion med en social robot och är begränsad till detta på grund av att den utvärderar om den sociala roboten uppfyller de förutsättningarna för engagemang. Därför användarensupplevelse av engagemang utvärderas enbart på ett mindre sätt utifrån hur mycket den sociala roboten uppfyller de förutsättningarna för engagemang. En framtida forskning och utveckling av AUEIS hade varit intressant och behövs för att AEUIS ska kunna utvärdera om användaren är engagerad och i vilken omfattning är hen engagerad. En annan aspekt som kan studeras är användarens engagemang under lång tidsinteraktion, korttidsinteraktion eller olika faser av engagemang. Exempelvis hur utvärderas att användaren påbörjar engagemang med en social robot och hur ska det utvärderas att engagemanget hålls och fortsätter eller om den avbryter och varför utifrån användarensperspektiv. I kapitel 5 (Slutresultat AUEIS-metoden) presenteras metoden samt detaljerade instruktioner över genomförandet presenters i Bilaga 7. / The user experience design (UX) perspective is essential when evaluating interaction with all types of robots, but especially social robots. As these are developed to perform important tasks in society such as being companion robots in geriatric care, schools and more. The User Experience Design area has a wide collection of evaluation methods that the human-robot interaction area can benefit from. This study aims to improve the experience of interacting with a social robot. For this purpose, literature studies have been conducted where UX aspects were identified that are relevant to focus on when evaluating the conditions for engagement in the interaction between human and social robot. A knowledge gap was identified of limited available analytical evaluation methods in human-robot interaction (HRI). In order to develop a new analytical evaluation method to promote engagement with a social robot, a methodological approach was used to develop evaluation methods. The design process of the new method consisted of five iterative phases that resulted in an Analytical evaluation method of engagement in interaction with social companion robots (AUEIS). AEUIS is designed to evaluate the conditions for achieving engagement when interacting with a social robot. Great focus was placed on the fifth phase where versions of AUEIS were tested by several UX designers based on the criteria that AUEIS should have high validity, be useful and have good learnability. The testing was performed with four UX designers with different experiences in HRI. The results of the testing showed that a UX designer without previous experience in evaluating HRI can use AUEIS without problems. At the same time, the aspects developed to carry out the evaluation were comprehensive to identify problems when interacting with a social robot. The result of this is work is a complete analytical evaluation method. AUEIS consists of seven aspects that study the conditions for engagement with a social robot. To evaluate with AUEIS, there are three phases: Preparation, evaluation, and analysis. Each phase has some activities that are followed to obtain a result about the conditions of engagement in the interaction with a social robot. The result of the evaluation with AUEIS will consist of qualitative and quantitative data. The qualitative data that is obtained can be analyzed to get a list of which aspects of engagement are not fulfilled by the social robot. The quantitative data can provide a quick overview of which aspects have the most problems and which problems are most serious. AUEIS evaluates the conditions for engagement when interacting with a social robot and is limited to this because it evaluates whether the social robot meets those conditions for engagement. Therefore, the user experience of engagement is evaluated only in a minor way based on how much the social robot meets the conditions for engagement. Future research and development of AUEIS would have been interesting and needed for AEUIS to be able to evaluate whether the user is engaged and to what extent is. Another interesting aspect to study can be the user experience of engagement whether it is during long-term interaction, short-term interaction, or different phases of an engagement. For example, how to evaluate that the user begins engagement with a social robot and how should it be evaluated that the engagement is maintained and continues or if it interrupts and why from a user perspective? Chapter 5 (End result the AUEIS method) presents the method and detailed instructions on implementation are presented in Appendix 7.

Les travaux de recherche de la thèse portent sur l'étude et la formalisation des interactions émotionnelles Humain-Machine. Au delà d’une détection d'informations paralinguistiques (émotions, disfluences,...) ponctuelles, il s'agit de fournir au système un profil interactionnel et émotionnel de l'utilisateur dynamique, enrichi pendant l’interaction. Ce profil permet d’adapter les stratégies de réponses de la machine au locuteur, et il peut également servir pour mieux gérer des relations à long terme. Le profil est fondé sur une représentation multi-niveau du traitement des indices émotionnels et interactionnels extraits à partir de l'audio via les outils de détection des émotions du LIMSI. Ainsi, des indices bas niveau (variations de la F0, d'énergie, etc.), fournissent des informations sur le type d'émotion exprimée, la force de l'émotion, le degré de loquacité, etc. Ces éléments à moyen niveau sont exploités dans le système afin de déterminer, au fil des interactions, le profil émotionnel et interactionnel de l'utilisateur. Ce profil est composé de six dimensions : optimisme, extraversion, stabilité émotionnelle, confiance en soi, affinité et domination (basé sur le modèle de personnalité OCEAN et les théories de l’interpersonal circumplex). Le comportement social du système est adapté en fonction de ce profil, de l'état de la tâche en cours, et du comportement courant du robot. Les règles de création et de mise à jour du profil émotionnel et interactionnel, ainsi que de sélection automatique du comportement du robot, ont été implémentées en logique floue à l'aide du moteur de décision développé par un partenaire du projet ROMEO. L’implémentation du système a été réalisée sur le robot NAO. Afin d’étudier les différents éléments de la boucle d’interaction émotionnelle entre l’utilisateur et le système, nous avons participé à la conception de plusieurs systèmes : système en Magicien d’Oz pré-scripté, système semi-automatisé, et système d’interaction émotionnelle autonome. Ces systèmes ont permis de recueillir des données en contrôlant plusieurs paramètres d’élicitation des émotions au sein d’une interaction ; nous présentons les résultats de ces expérimentations, et des protocoles d’évaluation de l’Interaction Humain-Robot via l’utilisation de systèmes à différents degrés d’autonomie. / Analysing and formalising the emotional aspect of the Human-Machine Interaction is the key to a successful relation. Beyond and isolated paralinguistic detection (emotion, disfluences…), our aim consists in providing the system with a dynamic emotional and interactional profile of the user, which can evolve throughout the interaction. This profile allows for an adaptation of the machine’s response strategy, and can deal with long term relationships. A multi-level processing of the emotional and interactional cues extracted from speech (LIMSI emotion detection tools) leads to the constitution of the profile. Low level cues ( F0, energy, etc.), are then interpreted in terms of expressed emotion, strength, or talkativeness of the speaker. These mid-level cues are processed in the system so as to determine, over the interaction sessions, the emotional and interactional profile of the user. The profile is made up of six dimensions: optimism, extroversion, emotional stability, self-confidence, affinity and dominance (based on the OCEAN personality model and the interpersonal circumplex theories). The information derived from this profile could allow for a measurement of the engagement of the speaker. The social behaviour of the system is adapted according to the profile, and the current task state and robot behaviour. Fuzzy logic rules drive the constitution of the profile and the automatic selection of the robotic behaviour. These determinist rules are implemented on a decision engine designed by a partner in the project ROMEO. We implemented the system on the humanoid robot NAO. The overriding issue dealt with in this thesis is the viable interpretation of the paralinguistic cues extracted from speech into a relevant emotional representation of the user. We deem it noteworthy to point out that multimodal cues could reinforce the profile’s robustness. So as to analyse the different parts of the emotional interaction loop between the user and the system, we collaborated in the design of several systems with different autonomy degrees: a pre-scripted Wizard-of-Oz system, a semi-automated system, and a fully autonomous system. Using these systems allowed us to collect emotional data in robotic interaction contexts, by controlling several emotion elicitation parameters. This thesis presents the results of these data collections, and offers an evaluation protocol for Human-Robot Interaction through systems with various degrees of autonomy.

As people respond strongly to faces and facial features, both consciously and subconsciously, faces are an essential aspect of social robots. Robotic faces and heads until recently belonged to one of the following categories: virtual, mechatronic or animatronic. As an original contribution to the field of human-robot interaction, I present the R-PAF technology (Retro-Projected Animated Faces): a novel robotic head displaying a real-time, computer-rendered face, retro-projected from within the head volume onto a mask, as well as its driving software designed with openness and portability to other hybrid robotic platforms in mind. The work constitutes the first implementation of a non-planar mask suitable for social human-robot interaction, comprising key elements of social interaction such as precise gaze direction control, facial expressions and blushing, and the first demonstration of an interactive video-animated facial mask mounted on a 5-axis robotic arm. The LightHead robot, a R-PAF demonstrator and experimental platform, has demonstrated robustness both in extended controlled and uncontrolled settings. The iterative hardware and facial design, details of the three-layered software architecture and tools, the implementation of life-like facial behaviours, as well as improvements in social-emotional robotic communication are reported. Furthermore, a series of evaluations present the first study on human performance in reading robotic gaze and another first on user’s ethnic preference towards a robot face.

Humans are very good at conveying when something is lost or misinterpreted in communication by using social cues like facial expressions or changes in prosody. However, these methods are usually not applicable for most robots, which are appearance constrained and vocality constrained. This is also one of the key factors that restrain the efficiency of Human-Robot Interaction (HRI). In this project, we explore a novel paradigm for enhancing the perception of the robot’s internal states using augmented reality (AR). A series of visualization interfaces augmenting either the environment, robot, or target object are implemented and evaluated through a user study. We found that AR visualization improved efficiency and motion predictability over a control group in which there is no visualization. The project shows not only the potential of AR visualizing as a bridge coordinating human and robot, but also a promising future of applications visualising robot’s internal states. / Människor är mycket bra på att förmedla när något går förlorat eller tolkas felaktigt i kommunikationen genom att använda sociala ledtrådar som ansiktsuttryck eller förändringar i prosodi. Dessa metoder är dock vanligtvis inte tillämpliga för de flesta robotar, vilka är begränsade till utseendet och begränsad vokalitet. Detta är också en av nyckelfaktorerna som begränsar effektiviteten i Human-Robot Interaction (HRI). I detta projekt utforskar vi ett nytt paradigm för att förbättra uppfattningen om robotens interna tillstånd med hjälp av augmented reality (AR). En serie visualiseringsgränssnitt som förstärker antingen miljön, roboten eller målobjektet implementeras och utvärderas genom en användarstudie. Vi fann att AR-visualisering förbättrade effektiviteten och rörelsesförutsägbarheten över en kontrollgrupp där det inte finns någon visualisering. Projektet visar inte bara potentialen för AR- visualisering som en bro som koordinerar människa och robot utan också en lovande framtid för applikationer som visualiserar robotens interna tillstånd.

I detta arbete genomfördes en enkätundersökning för att se hur upplevelsen av en furhatrobot ändrades efter att ha implementerat felhantering och mer användarinitiativ. Genom enkätformatet Godspeed undersöktes kategorierna människolikhet och upplevd intelligens. Roboten står placerad på ett museum och har som syfte att problematisera kring dagens teknologiska utveckling. Arbetet utfördes genom att modifiera en existerande skill för att undersöka hur ovan nämnda aspekter påverkar besökares upplevelse av roboten. Enkätstudien visade ej på någon större skillnad i hur roboten uppfattades efter modifikation. Framtida arbete skulle kunna undersöka om mer användarinitiativ i form av möjlighet att avbryta roboten eller småprata med den leder till en ökad upplevd intelligens eller människolikhet.

A primary design goal of companion social robots is to increase a user's perceived level of companionship. One way to examine perceived companionship is through parasocial presence. In the scope of human-technology interactions, parasocial presence can be defined as the extent to which the technology promotes, whether as a medium or by itself, the perception of understanding, social connection, engagement, and intimacy. One specific aspect of parasocial relationships which has been explored in human-robot interaction is para-friendship, or the sense of self-disclosure and social support a person perceives in a parasocial relationship. The present research examined how the relationship between a user's personality and the perceived personality of a companion social robot influences the relationship of intimacy, understanding, enjoyability, and involvement on para-friendship. This research also investigated whether the user and robot's personalities affect para-friendship and the intention to use the robot as a social companion. Due to their designed goal of serving as social companions, understanding the relationship of a user's personality and perceived robot personality on parasocial presence, parasocial friendship, and use intention is one important link to improve Human-Robot Interaction design (HRI) and increase the marketability of social robots. Results showed that personality similarity predicted parasocial presence, but may not be as critical as perceived robot personality. Additionally, while parasocial presence predicted parasocial friendship, this effect was limited for parasocial involvement. Finally, higher feelings of parasocial presence promoted greater use intention. Implications for robot development, personality aspects of robot friendship formation, and opinions of human-robot relationships are discussed.

The work presented in this study is based on the long-term goal of developing a social robot that can be involved in leading a conversation in a language café. In detail, the study has investigated whether it is possible to classify involvement with a conversation participant based on its facial expression and gaze two factors that previous studies have shown to be central to human engagement. To perform the assessment, the software Openface has extracted said parameters from a previous field study which has then been processed with the machine learning model Support Vector Machine. After a lot of hyperparameter tuning, the final model managed to predict engagement on a three-point scale with 54.5% accuracy. Furthermore, the study has also examined the potential of the new technological paradigm that the social robot represents. The potential has been analyzed on the basis of Dosi’s four dimensions: technological possibilities, appropriability of innovation, cumulativeness of technical advances and properties of the knowledge base. The analysis clarifies that the paradigm has the potential to revolutionize a number of industries as a result of its technological opportunities and worldwide stakeholders, but also faces challenges in the form of technical and ethical difficulties. / Arbetet som presenteras i den här studien grundar sig i det långsiktiga målet att utveckla en social robot som kan vara med och leda samtalssessioner på ett språkcafé. I detalj har studien undersökt om det går att klassificera engagemang hos en samtalsdeltagare utifrån dess ansiktsuttryck och blickriktning – två faktorer som tidigare studier visat sig vara centrala för människans engagemang. För att utföra bedömningen har mjukvaran Openface extraherat nämnda parametrar från en tidigare fältstudie vilka sedan har processats med maskininlärningsmodellen Support Vector Machine. Efter gedigna försök att finna optimala värden på hyperparametrar till modellen lyckades den slutligen predicera engagemang på en tregradig skala med 54,5% accuracy. Vidare har studien också undersökt potentialen för det nya teknologiska paradigmet som den sociala roboten utgör. Potentialen har analyserats med utgångspunkt i Dosis fyra dimensioner: teknologiska möjligheter, möjliga vinster från innovation, kumulativ höjd på teknologiska framsteg och egenskaper i kunskapsbasen. Analysen klargör att paradigmet har förutsättningar att revolutionera ett flertal industrier till följd av dess teknologiska möjligheter och världsomfattande intressenter, men står också inför utmaningar i form av tekniska och etiska svårigheter.

The Computers are Social Actors (CASA) paradigm was proposed more than two decades ago to understand humans’ interaction with computer technologies. Today, as emerging media technologies including social robots and smartphones become more personal and persuasive, questions of how users respond to them socially, what individual factors leverage the relationship, and what constitutes the social influence of these technologies need to be addressed. As an expansion of the CASA paradigm, the Media are Social Actors (MASA) paradigm was applied in the current dissertation to understand users’ social perception, social attitudes, and social behavior in their interactions with humanoid social robots and smartphones. Two lab experiments with between-subjects factorial design were conducted. A total of 110 participants were asked to interact with a humanoid social robot and a smartphone respectively in a socio-emotional context and a task-oriented context. Four pairs of social cues were compared to understand their influence on users’ anthropomorphism of the technologies. Multivariate analyses and textual analyses were conducted. Results suggested that users developed more trust in the social robot with a human voice than with a synthetic voice. Users also developed more intimacy and more interest in the social robot when the robot was paired with humanlike gestures. However, individual differences such as users’ attitudes toward robots, robot use experiences, and suspension of disbelief affected users’ psychological responses to the social robot. Although users’ responses to the smartphone did not vary based on the language styles and the modalities, factors such as individuals’ intensive smartphone use, mobile use habits, and their source orientation and re-orientation moderated the social influence of the smartphone. The dissertation has theoretical value in expanding the CASA paradigm to social robots and smartphones. It also tests the validity of the propositions of the MASA paradigm. The results can lead to more comprehensive, nuanced, and exciting discoveries of the social implications, ethical implications, and practical guides of using these emerging media technologies in the future. / Media & Communication

This paper examines the ‘robotic moment’, as defined by Sherry Turkle (2011), in the light of general theories of human-technology relations, notably the theoretical framework founded by Jacques Ellul (1954). Potential psychological, cultural, and technical consequences of human-technology interaction, especially human interaction with so-called ‘social-robots’, are explored. It is demonstrated that the ‘robotic moment’ may reasonably be understood as a result of the formation of pseudo-social anthropo-technological circuits, and as a result of cultural disintegration and an increasingly prevalent societal impulse to incorporate everything that is commonly not understood to be technological (i.e. even the biological, the social, and the spiritual) into the technological order. It is demonstrated that the category ‘social robot’ may reasonably be understood, depending on how the robot is used, as a technique humaine, as a magical practice, or as a complex hybrid practice. Assumptions concerning the nature of technologies, the extent to which technologies are useful, and the impact of technologies on society are questioned. The extent to which a society’s worldview may determine or influence how its inhabitants relate to technologies is explored. It is suggested that, as societies demystify the universe and develop mature techno-secular worldviews, means-to-ends (i.e. technologies) are being mystified; the ensuing quasi-religious techno-secular worldviews, which fail to recognise the limitations of technologies, may in turn be responsible for much of the irrational use of technologies in technological societies. The essay suggests that the ‘robotic moment’ can be explained not only in terms of vulnerabilities inherent in human nature and in terms of properties inherent in technological society, but also in terms of the notions of the sacred that prevail in technically advanced societies and a society’s practice of science, engineering, magic, and faith.