700 research outputs found

    Affective reactions towards socially interactive agents and their computational modeling

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    Over the past 30 years, researchers have studied human reactions towards machines applying the Computers Are Social Actors paradigm, which contrasts reactions towards computers with reactions towards humans. The last 30 years have also seen improvements in technology that have led to tremendous changes in computer interfaces and the development of Socially Interactive Agents. This raises the question of how humans react to Socially Interactive Agents. To answer these questions, knowledge from several disciplines is required, which is why this interdisciplinary dissertation is positioned within psychology and computer science. It aims to investigate affective reactions to Socially Interactive Agents and how these can be modeled computationally. Therefore, after a general introduction and background, this thesis first provides an overview of the Socially Interactive Agent system used in this work. Second, it presents a study comparing a human and a virtual job interviewer, which shows that both interviewers induce shame in participants to the same extent. Thirdly, it reports on a study investigating obedience towards Socially Interactive Agents. The results indicate that participants obey human and virtual instructors in similar ways. Furthermore, both types of instructors evoke feelings of stress and shame to the same extent. Fourth, a stress management training using biofeedback with a Socially Interactive Agent is presented. The study shows that a virtual trainer can teach coping techniques for emotionally challenging social situations. Fifth, it introduces MARSSI, a computational model of user affect. The evaluation of the model shows that it is possible to relate sequences of social signals to affective reactions, taking into account emotion regulation processes. Finally, the Deep method is proposed as a starting point for deeper computational modeling of internal emotions. The method combines social signals, verbalized introspection information, context information, and theory-driven knowledge. An exemplary application to the emotion shame and a schematic dynamic Bayesian network for its modeling are illustrated. Overall, this thesis provides evidence that human reactions towards Socially Interactive Agents are very similar to those towards humans, and that it is possible to model these reactions computationally.In den letzten 30 Jahren haben Forschende menschliche Reaktionen auf Maschinen untersucht und dabei das “Computer sind soziale Akteure”-Paradigma genutzt, in dem Reaktionen auf Computer mit denen auf Menschen verglichen werden. In den letzten 30 Jahren hat sich ebenfalls die Technologie weiterentwickelt, was zu einer enormen Veränderung der Computerschnittstellen und der Entwicklung von sozial interaktiven Agenten geführt hat. Dies wirft Fragen zu menschlichen Reaktionen auf sozial interaktive Agenten auf. Um diese Fragen zu beantworten, ist Wissen aus mehreren Disziplinen erforderlich, weshalb diese interdisziplinäre Dissertation innerhalb der Psychologie und Informatik angesiedelt ist. Sie zielt darauf ab, affektive Reaktionen auf sozial interaktive Agenten zu untersuchen und zu erforschen, wie diese computational modelliert werden können. Nach einer allgemeinen Einführung in das Thema gibt diese Arbeit daher, erstens, einen Überblick über das Agentensystem, das in der Arbeit verwendet wird. Zweitens wird eine Studie vorgestellt, in der eine menschliche und eine virtuelle Jobinterviewerin miteinander verglichen werden, wobei sich zeigt, dass beide Interviewerinnen bei den Versuchsteilnehmenden Schamgefühle in gleichem Maße auslösen. Drittens wird eine Studie berichtet, in der Gehorsam gegenüber sozial interaktiven Agenten untersucht wird. Die Ergebnisse deuten darauf hin, dass Versuchsteilnehmende sowohl menschlichen als auch virtuellen Anleiterinnen ähnlich gehorchen. Darüber hinaus werden durch beide Instruktorinnen gleiche Maße von Stress und Scham hervorgerufen. Viertens wird ein Biofeedback-Stressmanagementtraining mit einer sozial interaktiven Agentin vorgestellt. Die Studie zeigt, dass die virtuelle Trainerin Techniken zur Bewältigung von emotional herausfordernden sozialen Situationen vermitteln kann. Fünftens wird MARSSI, ein computergestütztes Modell des Nutzeraffekts, vorgestellt. Die Evaluation des Modells zeigt, dass es möglich ist, Sequenzen von sozialen Signalen mit affektiven Reaktionen unter Berücksichtigung von Emotionsregulationsprozessen in Beziehung zu setzen. Als letztes wird die Deep-Methode als Ausgangspunkt für eine tiefer gehende computergestützte Modellierung von internen Emotionen vorgestellt. Die Methode kombiniert soziale Signale, verbalisierte Introspektion, Kontextinformationen und theoriegeleitetes Wissen. Eine beispielhafte Anwendung auf die Emotion Scham und ein schematisches dynamisches Bayes’sches Netz zu deren Modellierung werden dargestellt. Insgesamt liefert diese Arbeit Hinweise darauf, dass menschliche Reaktionen auf sozial interaktive Agenten den Reaktionen auf Menschen sehr ähnlich sind und dass es möglich ist diese menschlichen Reaktion computational zu modellieren.Deutsche Forschungsgesellschaf

    Human-Machine Communication: Complete Volume. Volume 3. Diffusion of Human-Machine Communication During and After the COVID-19 Pandemic

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    This is the complete volume of HMC Volume 3. Diffusion of Human-Machine Communication During and After the COVID-19 Pandemi

    If I Can\u27t Predict My Future, Why Can AI? Exploring Human Interaction with Predictive Analytics

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    This research study seeks to understand how AI-based chatbots can potentially be leveraged as a tool in a PSYOP. This study is methodologically driven as it employs validated scales concerning suggestibility and human-computer interaction to assess how participants interact with a specific AI chatbot, Replika. Recent studies demonstrate the capability of GPT-based analytics to influence user’s moral judgements, and this paper is interested in exploring why. Results will help draw conclusions regarding human interaction with predictive analytics (in this case a free GPT-based chatbot, Replika) to understand if suggestibility (how easily influenced someone generally is) impacts the overall usability of AI chatbots. This project will help assess how much of a concern predictive AI chatbots should be considered as virtual AI influencers and other bot-based propaganda modalities emerge in the contemporary media environment. This study uses the CASA paradigm, medium theory, and Boyd’s theory of conflict to explore how factors that often drive human computer interaction— like anthropomorphic autonomy and suspension of disbelief— potentially relate to suggestibility or chatbot usability. Overall, this study is interested in specifically exploring if suggestion can predict usability in AI chatbots

    Enhancing the Teleoperator’s Situation Awareness by Human-Centered HMI Design

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    Teleoperation of vehicles has the potential to serve as an approach to reap off the benefits of automated driving already in the near future when fully automated vehicles (SAE level 5 [1]) will not yet be fully operable. In teleoperated driving, a human op-erator in a remote control center boosts passenger safety and service reliability by monitoring the vehicle and taking over control when disturbances occur that the vehicle automation’s skills cannot cope with by itself. A user-centered human-machine interface (HMI) for the teleoperation of highly automated shuttles (SAE 4) by a public transport control center was generated to integrate the vehicle’s automation and hu-man remote-operation. The HMI prototype was evaluated regarding its usability, sit-uation awareness (SA) [2], acceptance, and perceived workload by transport control center professionals as an online interview study [3, 4]. Even though results supported our HMI overall, especially regarding usability, acceptance, and workload, SA ratings did not differ significantly from the scale mean, suggesting a merely average degree of SA perceived by participants. SA was measured using the Situation Awareness Rating Technique Starting (SART), a subjective self-report measure. Setting out from this particular result, the following questions arose: (1) Why did the current HMI not provide sufficient SA to the participants? What improvements need to be made in order to do so? Specifically, how did the remote setup as an online interview study influence factors such as involvedness and immersion? (2) Is the SART questionnaire-based method suitable to measure SA in this setting? If not, are there more suitable approaches to measure SA in teleoperated driving? In order to answer the first cluster of questions, a systematic analysis of the first HMI prototype’s evaluation was conducted. Both improvement suggestions from participants and additional approaches to enhance key outcome variables regarding the HMI were compiled. These include theoretical frameworks such as the Out-of-the-Loop concept in automated driving [5] as well as empirical findings on the interplay of teleoperator, environment, and operation interface characteristics on the teleopera-tor’s SA [6]. This compilation will subsequently be used to refine the HMI and then re-validate it by conducting a second evaluation study, preferably on-site using a lab-based simulator teleoperation workstation with scenarios that typically occur in tele-operated driving. To address the second cluster of questions, methods to measure SA will be systematically reviewed with a focus on objective approaches, such as the query-based Situation Awareness Global Assessment Technique (SAGAT) [7] that Endsley specifically suggested for measuring SA in teleoperation [8]. Subsequently, the SA measurement method that suits the requirements of teleoperated driving best will be selected to evaluate the refined HMI. The objectives for the focus group at the German Human Factors Summer School derive from the two central questions stated above: (1) Soliciting advise for designing the second evaluation study at the simulator teleoperation workstation and (2) discuss-ing the construct situation awareness, its usefulness in the context my research, how to measure it and what other related constructs and approaches could be considered

    Translation, interpreting, cognition

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    Cognitive aspects of the translation process have become central in Translation and Interpreting Studies in recent years, further establishing the field of Cognitive Translatology. Empirical and interdisciplinary studies investigating translation and interpreting processes promise a hitherto unprecedented predictive and explanatory power. This collection contains such studies which observe behaviour during translation and interpreting. The contributions cover a vast area and investigate behaviour during translation and interpreting – with a focus on training of future professionals, on language processing more generally, on the role of technology in the practice of translation and interpreting, on translation of multimodal media texts, on aspects of ergonomics and usability, on emotions, self-concept and psychological factors, and finally also on revision and post-editing. For the present publication, we selected a number of contributions presented at the Second International Congress on Translation, Interpreting and Cognition hosted by the Tra&Co Lab at the Johannes Gutenberg University of Mainz. Most of the papers in this volume are formulated in a particular constraint-based grammar framework, Head-driven Phrase Structure Grammar. The contributions investigate how the lexical and constructional aspects of this theory can be combined to provide an answer to this question across different linguistic sub-theories

    The way out of the box

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    Synopsis: Cognitive aspects of the translation process have become central in Translation and Interpreting Studies in recent years, further establishing the field of Cognitive Translatology. Empirical and interdisciplinary studies investigating translation and interpreting processes promise a hitherto unprecedented predictive and explanatory power. This collection contains such studies which observe behaviour during translation and interpreting. The contributions cover a vast area and investigate behaviour during translation and interpreting – with a focus on training of future professionals, on language processing more generally, on the role of technology in the practice of translation and interpreting, on translation of multimodal media texts, on aspects of ergonomics and usability, on emotions, self-concept and psychological factors, and finally also on revision and post-editing. For the present publication, we selected a number of contributions presented at the Second International Congress on Translation, Interpreting and Cognition hosted by the Tra&Co Lab at the Johannes Gutenberg University of Mainz

    Avian cognition in a changing world

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    Humans are altering the natural environment at an unprecedented rate, with profound consequences for non-human animals. However, species differ in how they respond to these ecological changes. Understanding the responses of wildlife to environmental change is vital to conserve biodiversity and mitigate anthropogenic impacts. Behaviour can often act as a rapid adaptation to ecological change, and is influenced by an organism’s ability to acquire and process information from their environment. Despite the importance of cognition in shaping behaviour, little is known about the role of cognition in allowing some species to thrive in human-dominated habitats. In this thesis, I examine how the cognitive abilities of wild jackdaws allow these birds to cope with the challenges of a rapidly changing world. Specifically, I focus on the need to navigate a dynamic social environment, and the need to learn about anthropogenic threats. Firstly, I investigate how jackdaws track their social environment by recognising conspecifics and their relationships. In Chapter 3, I demonstrate that jackdaws individually recognise the contact calls of their breeding partner, but I find no evidence of vocal discrimination beyond the pair bond. In Chapter 4, I use infidelity simulations to investigate whether jackdaws track changes to prevailing social relationships, although I find no evidence that jackdaws respond to relationship information in this experimental context. Secondly, I investigate how jackdaws’ cognitive abilities shape their behaviour during encounters with people, allowing birds to avoid danger whilst exploiting anthropogenic resources. I test the commonly-held preconception that jackdaws identify people carrying shotguns as dangerous (Chapter 5), but find no evidence that jackdaws use objects being carried by people to inform their escape decisions in this case. I also demonstrate that jackdaws learn socially about dangerous people (Chapter 6). Throughout these experiments, jackdaws differed considerably in their behaviour, which may influence individual success in anthropogenic habitats. In Chapter 7, I find that individual jackdaws differ consistently in their responses to human disturbance, but that these differences do not appear to impact reproductive success. Together, my findings highlight the importance of fundamental behavioural and cognitive research in predicting animals’ responses to environmental change.NER
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