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Ownership and usage of personal voice assistant devices like Amazon Echo or Google Home have increased drastically over the last decade since their market launch. This thesis builds upon existing computers are social actors (CASA) and media equation research that is concerned with humans displaying social reactions usually exclusive to human-human interaction when interacting with media and technological devices. CASA research has been conducted with a variety of technological devices such as desktop computers, smartphones, embodied virtual agents, and robots. However, despite their increasing popularity, little empirical work has been done to examine social reactions towards these personal stand-alone voice assistant devices, also referred to as smart speakers. Thus, this dissertation aims to adopt the CASA approach to empirically evaluate social responses to smart speakers. With this goal in mind, four laboratory experiments with a total of 407 participants have been conducted for this thesis. Results show that participants display a wide range of social reactions when interacting with voice assistants. This includes the utilization of politeness strategies such as the interviewer-bias, which led to participants giving better evaluations directly to a smart speaker device compared to a separate computer. Participants also displayed prosocial behavior toward a smart speaker after interdependence and thus a team affiliation had been induced. In a third study, participants applied gender stereotypes to a smart speaker not only in self-reports but also exhibited conformal behavior patterns based on the voice the device used. In a fourth and final study, participants followed the rule of reciprocity and provided help to a smart speaker device that helped them in a prior interaction. This effect was also moderated by subjects’ personalities, indicating that individual differences are relevant for CASA research. Consequently, this thesis provides strong empirical support for a voice assistants are social actors paradigm. This doctoral dissertation demonstrates the power and utility of this research paradigm for media psychological research and shows how considering voice assistant devices as social actors lead to a more profound understanding of voice-based technology. The findings discussed in this thesis also have implications for these devices that need to be carefully considered both in future research as well as in practical design.
With the continuous development of artificial intelligence, there is an effort to let the expressed mind of robots resemble more and more human-like minds. However, just as the human-like appearance of robots can lead to feelings of aversion to such robots, recent research has shown that the apparent mind expressed by machines can also be responsible for their negative evaluations. This work strives to explore facets of aversion evoked by machines with human-like mind (uncanny valley of mind) within three empirical projects from a psychological point of view in different contexts, including the resulting consequences.
In Manuscript #1, the perspective of previous work in the research area is reversed and thus shows that humans feel eeriness in response to robots that can read human minds, a capability unknown from human-human interaction. In Manuscript #2, it is explored whether empathy for a robot being harmed by a human is a way to alleviate the uncanny valley of mind. A result of this work worth highlighting is that aversion in this study did not arise from the manipulation of the robot’s mental capabilities but from its attributed incompetence and failure. The results of Manuscript #3 highlight that status threat is revealed if humans perform worse than machines in a work-relevant task requiring human-like mental capabilities, while higher status threat is linked with a higher willingness to interact, due to the machine’s perceived usefulness.
In sum, if explanatory variables and concrete scenarios are considered, people will react fairly positively to machines with human-like mental capabilities. As long as the machine’s usefulness is palpable to people, but machines are not fully autonomous, people seem willing to interact with them, accepting aversion in favor of the expected benefits.
Manifestations of aggressive driving, such as tailgating, speeding, or swearing, are not trivial offenses but are serious problems with hazardous consequences—for the offender as well as the target of aggression. Aggression on the road erases the joy of driving, affects heart health, causes traffic jams, and increases the risk of traffic accidents. This work is aimed at developing a technology-driven solution to mitigate aggressive driving according to the principles of Persuasive Technology. Persuasive Technology is a scientific field dealing with computerized software or information systems that are designed to reinforce, change, or shape attitudes, behaviors, or both without using coercion or deception.
Against this background, the Driving Feedback Avatar (DFA) was developed through this work. The system is a visual in-car interface that provides the driver with feedback on aggressive driving. The main element is an abstract avatar displayed in the vehicle. The feedback is transmitted through the emotional state of this avatar, i.e., if the driver behaves aggressively, the avatar becomes increasingly angry (negative feedback). If no aggressive action occurs, the avatar is more relaxed (positive feedback). In addition, directly after an aggressive action is recognized by the system, the display is flashing briefly to give the driver an instant feedback on his action.
Five empirical studies were carried out as part of the human-centered design process of the DFA. They were aimed at understanding the user and the use context of the future system, ideating system ideas, and evaluating a system prototype. The initial research question was about the triggers of aggressive driving. In a driver study on a public road, 34 participants reported their emotions and their triggers while they were driving (study 1). The second research question asked for interventions to cope with aggression in everyday life. For this purpose, 15 experts dealing with the treatment of aggressive individuals were interviewed (study 2). In total, 75 triggers of aggressive driving and 34 anti-aggression interventions were identified. Inspired by these findings, 108 participants generated more than 100 ideas of how to mitigate aggressive driving using technology in a series of ideation workshops (study 3). Based on these ideas, the concept of the DFA was elaborated on. In an online survey, the concept was evaluated by 1,047 German respondents to get a first assessment of its perception (study 4). Later on, the DFA was implemented into a prototype and evaluated in an experimental driving study with 32 participants, focusing on the system’s effectiveness (study 5). The DFA had only weak and, in part, unexpected effects on aggressive driving that require a deeper discussion.
With the DFA, this work has shown that there is room to change aggressive driving through Persuasive Technology. However, this is a very sensitive issue with special requirements regarding the design of avatar-based feedback systems in the context of aggressive driving. Moreover, this work makes a significant contribution through the number of empirical insights gained on the problem of aggressive driving and wants to encourage future research and design activities in this regard.
Intuitive Benutzung wird in dieser Arbeit definiert als das Ausmaß, mit dem ein Produkt mental effizient und effektiv genutzt wird, was mit einem starken metakognitiven Gefühl von Flüssigkeit einhergeht. Aktuelle Methoden verfügen nicht über eine ausreichend hohe zeitliche Anwendungseffizienz, um im Industrieprojekt 3D-GUIde effektiv zur Evaluation von Interaktionspatterns für 3D-Creation-Oriented-User-Interfaces (3D-CUIs) eingesetzt werden zu können. Diese Interaktionspatterns beschreiben strukturiert, wie 3D-CUIs als User Interfaces zur Erstellung von dreidimensionalen Inhalten gestaltet werden müssen, um intuitive Benutzung zu unterstützen. In dieser Arbeit werden daher zwei neue Evaluationsmethoden vorgeschlagen: 1) IntuiBeat-F als formative Evaluationsmethode und 2) IntuiBeat-S als summative Evaluationsmethode. Basierend auf Default-Interventionist-Theorien und bestehenden Definitionen intuitiver Benutzung werden die mentale Beanspruchung als zentrales objektives, das metakognitive Gefühl von Flüssigkeit als zentrales subjektives und die Effektivität als zentrales pragmatisches mit intuitiver Benutzung assoziiertes Merkmal identifiziert. Die Evaluation intuitiver Benutzung mithilfe von IntuiBeat-F und IntuiBeat-S ist vielversprechend, da es sich bei beiden Methoden um Inhibition basierende Rhythmuszweitaufgaben handelt und diese somit mentale Beanspruchung objektiv erfassen können. Das Potential beider Methoden wird im Hinblick auf vorherige Forschungsarbeiten zur zeitlich effizienten Evaluation von 3D-CUIs aus der Mensch-Computer-Interaktion und der Psychologie diskutiert. Aus dieser Diskussion werden empirische Forschungsfragen abgeleitet. Die erste Forschungsfrage untersucht die wissenschaftliche Güte von IntuiBeat-S. Im ersten, zweiten und dritten Experiment werden Paare von 3D-CUIs miteinander summativ verglichen (d.h. weniger vs. stärker intuitiv benutzbare User Interfaces). Dabei wird die wissenschaftliche Güte von IntuiBeat-S hinsichtlich der Hauptgütekriterien Objektivität, Reliabilität und Validität beurteilt. Die Ergebnisse zeigen, dass IntuiBeat-S eine hohe wissenschaftliche Güte bei der summativen Evaluation besitzt. Zudem macht es bei der Anwendung von IntuiBeat-S keinen Unterschied, ob der Rhythmus über die Ferse oder den Fußballen eingeben wird, und ob als Stichproben Studierende mit höherer oder geringerer Vorerfahrung bezüglich der Nutzung von 3D-CUIs verwendet werden. Die zweite Forschungsfrage untersucht die wissenschaftliche Güte von IntuiBeat-F. Im vierten, fünften, sechsten und siebten Experiment werden 3D-CUIs einzeln formativ evaluiert (d.h. entweder ein weniger oder stärker intuitiv benutzbares User Interface). Dabei wird die wissenschaftliche Güte von IntuiBeat-F hinsichtlich der Hauptgütekriterien Gründlichkeit, Gültigkeit und Zuverlässigkeit beurteilt. Die Ergebnisse zeigen, dass IntuiBeat-F eine hohe wissenschaftliche Güte bei der formativen Evaluation besitzt. Diese liegt bei strikter Anwendung der Methode (d.h. Berücksichtigung ausschließlich mit der Methode entdeckter Nutzungsprobleme) zwar höher, ist aber bei wenig strikter Anwendung der Methode (d.h. Berücksichtigung auch unabhängig von der Methode entdeckter Nutzungsprobleme) noch ausreichend hoch. Jedoch konnte erst die Entwicklung und Einführung einer zusätzlichen Analysesoftware im Zuge des sechsten und siebten Experiments die wissenschaftliche Güte von IntuiBeat-F hinsichtlich aller drei Hauptgütekriterien demonstrieren, da ohne deren Unterstützung IntuiBeat-F vom Evaluator nicht ausreichend gründlich angewendet wird. Die dritte Forschungsfrage untersucht, wie hoch die zeitliche Anwendungseffizienz beider Methoden als wichtiger Aspekt praktischer Güte im Vergleich zu bereits vorhandenen Evaluationsmethoden für intuitive Benutzung ist. Bezüglich der summativen Evaluation wird im zweiten Experiment eine höhere zeitliche Anwendungseffizienz von IntuiBeat-S im Vergleich zum aktuellen summativen Benchmark, der CHAI-Methode, sowohl bei der Evaluation von weniger als auch bei der von stärker intuitiv benutzbaren 3D-CUIs demonstriert. Auch bezüglich der formativen Evaluation konnten die Ergebnisse der letzten vier Experimente zeigen, dass die zeitliche Anwendungseffizienz von IntuiBeat-F im Vergleich zum aktuellen formativen Benchmark, dem Nutzertest mit retrospektivem Think-Aloud- Protokoll, sowohl bei der Evaluation von weniger als auch stärker intuitiv benutzbaren 3D-CUIs höher liegt. Dieser Unterschied bleibt bestehend, egal ob eine zusätzliche Analysesoftware vom Evaluator verwendet wird oder nicht. Als Ergebnis aller Experimente lässt sich feststellen, dass die wissenschaftliche Güte und die zeitliche Anwendungseffizienz beider Methoden zur Evaluation intuitiver Benutzung von 3D-CUIs mehr als zufriedenstellend beurteilt werden kann. Die Arbeit wird mit einer Diskussion des geleisteten Forschungsbeitrags geschlossen. Dabei werden Anregungen für künftige Forschung aus theoretischer (z.B. Berücksichtigung des Gefühls von Flüssigkeit bei der Evaluation), praktischer (z.B. Untersuchung der Anwendbarkeit beider Methoden in anderen Domänen) und methodischer (z.B. Beurteilung der praktischen Güte beider Methoden anhand anderer Kriterien) Perspektive gegeben.
The field of human-computer interaction (HCI) strives for innovative user interfaces. Innovative and novel user interfaces are a challenge for a growing population of older users and endanger older adults to be excluded from an increasingly digital world. This is because older adults often have lower cognitive abilities and little prior experiences with technology.
This thesis aims at resolving the tension between innovation and age-inclusiveness by developing user interfaces that can be used regardless of cognitive abilities and technology-dependent prior knowledge.
The method of image-schematic metaphors holds promises for innovative and age-inclusive interaction design. Image-schematic metaphors represent a form of technology-independent prior knowledge. They reveal basic mental models and can be gathered in language (e.g. bank account is container from "I put money into my bank account").
Based on a discussion of previous applications of image-schematic metaphors in HCI, the present work derives three empirical research questions regarding image-schematic metaphors for innovative and age-inclusive interaction design.
The first research question addresses the yet untested assumption that younger and older adults overlap in their technology-independent prior knowledge and, therefore, their usage of image-schematic metaphors. In study 1, a total of 41 participants described abstract concepts from the domains of online banking and everyday life. In study 2, ten contextual interviews were conducted. In both studies, younger and older adults showed a substantial overlap of 70% to 75%, indicating that also their mental models overlap substantially.
The second research question addresses the applicability and potential of image-schematic metaphors for innovative design from the perspective of designers. In study 3, 18 student design teams completed an ideation process with either an affinity diagram as the industry standard, image-schematic metaphors or both methods in combination and created paper prototypes. The image-schematic metaphor method alone, but not the combination of both methods, was readily adopted and applied just as a well as the more familiar standard method.
In study 4, professional interaction designers created prototypes either with or without image-schematic metaphors. In both studies, the method of image-schematic metaphors was perceived as applicable and creativity stimulating.
The third research question addresses whether designs that explicitly follow image-schematic metaphors are more innovative and age-inclusive regarding differences in cognitive abilities and prior technological knowledge. In two experimental studies (study 5 and 6) involving a total of 54 younger and 53 older adults, prototypes that were designed with image-schematic metaphors were perceived as more innovative compared to those who were designed without image-schematic metaphors. Moreover, the impact of prior technological knowledge on interaction was reduced for prototypes that had been designed with image-schematic metaphors. However, participants' cognitive abilities and age still influenced the interaction significantly.
The present work provides empirical as well as methodological findings that can help to promote the method of image-schematic metaphors in interaction design. As a result of these studies it can be concluded that the image-schematic metaphors are an applicable and effective method for innovative user interfaces that can be used regardless of prior technological knowledge.