Institut Mensch - Computer - Medien
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Social patterns and roles can develop when users talk to intelligent voice assistants (IVAs) daily. The current study investigates whether users assign different roles to devices and how this affects their usage behavior, user experience, and social perceptions. Since social roles take time to establish, we equipped 106 participants with Alexa or Google assistants and some smart home devices and observed their interactions for nine months. We analyzed diverse subjective (questionnaire) and objective data (interaction data). By combining social science and data science analyses, we identified two distinct clusters—users who assigned a friendship role to IVAs over time and users who did not. Interestingly, these clusters exhibited significant differences in their usage behavior, user experience, and social perceptions of the devices. For example, participants who assigned a role to IVAs attributed more friendship to them used them more frequently, reported more enjoyment during interactions, and perceived more empathy for IVAs. In addition, these users had distinct personal requirements, for example, they reported more loneliness. This study provides valuable insights into the role-specific effects and consequences of voice assistants. Recent developments in conversational language models such as ChatGPT suggest that the findings of this study could make an important contribution to the design of dialogic human–AI interactions.
In the context of medical device training, e-Learning can address problems like unstandardized content and different learning paces. However, staff and students value hands-on activities during medical device training. In a blended learning approach, we examined whether using a syringe pump while conducting an e-Learning program improves the procedural skills needed to operate the pump compared to using the e-Learning program only. In two experiments, the e-Learning only group learned using only the e-Learning program. The e-Learning + hands-on group was instructed to use a syringe pump during the e-Learning to repeat the presented content (section “Experiment 1”) or to alternate between learning on the e-Learning program and applying the learned content using the pump (section “Experiment 2”). We conducted a skills test, a knowledge test, and assessed confidence in using the pump immediately after learning and two weeks later. Simply repeating the content (section “Experiment 1”) did not improve performance of e-Learning + hands-on compared with e-Learning only. The instructed learning process (section “Experiment 1”) resulted in significantly better skills test performance for e-Learning + hands-on compared to the e-Learning only. Only a structured learning process based on multi-media learning principles and memory research improved procedural skills in relation to operating a medical device.
When interacting with sophisticated digital technologies, people often fall back on the same interaction scripts they apply to the communication with other humans—especially if the technology in question provides strong anthropomorphic cues (e.g., a human-like embodiment). Accordingly, research indicates that observers tend to interpret the body language of social robots in the same way as they would with another human being. Backed by initial evidence, we assumed that a humanoid robot will be considered as more dominant and competent, but also as more eerie and threatening once it strikes a so-called power pose. Moreover, we pursued the research question whether these effects might be accentuated by the robot’s body size. To this end, the current study presented 204 participants with pictures of the robot NAO in different poses (expansive vs. constrictive), while also manipulating its height (child-sized vs. adult-sized). Our results show that NAO’s posture indeed exerted strong effects on perceptions of dominance and competence. Conversely, participants’ threat and eeriness ratings remained statistically independent of the robot’s depicted body language. Further, we found that the machine’s size did not affect any of the measured interpersonal perceptions in a notable way. The study findings are discussed considering limitations and future research directions.
The relevance of user experience in safety–critical domains has been questioned and lacks empirical investigation. Based on previous studies examining user experience in consumer technology, we conducted an online survey on positive experiences with interactive technology in acute care. The participants of the study consisted of anaesthesiologists, nurses, and paramedics (N = 55) from three German cities. We report qualitative and quantitative data examining (1) the relevance and notion of user experience, (2) motivational orientations and psychological need satisfaction, and (3) potential correlates of hedonic, eudaimonic, and extrinsic motivations such as affect or meaning. Our findings reveal that eudaimonia was the most salient aspect in these experiences and that the relevance of psychological needs is differently ranked than in experiences with interactive consumer technology. We conclude that user experience should be considered in safety–critical domains, but research needs to develop further tools and methods to address the domain-specific requirements.
The current condition of (Western) academic psychology can be criticized for various reasons. In the past years, many debates have been centered around the so-called “replication crisis” and the “WEIRD people problem”. However, one aspect which has received relatively little attention is the fact that psychological research is typically limited to currently living individuals, while the psychology of the past remains unexplored. We find that more research in the field of historical psychology is required to capture both the similarities and differences between psychological mechanisms both then and now. We begin by outlining the potential benefits of understanding psychology also as a historical science and explore these benefits using the example of stress. Finally, we consider methodological, ideological, and practical pitfalls, which could endanger the attempt to direct more attention toward cross-temporal variation. Nevertheless, we suggest that historical psychology would contribute to making academic psychology a truly universal endeavor that explores the psychology of all humans.
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 increasing adaptability and complexity of advisory artificial intelligence (AI)-based agents, the topics of explainable AI and human-centered AI are moving close together. Variations in the explanation itself have been widely studied, with some contradictory results. These could be due to users’ individual differences, which have rarely been systematically studied regarding their inhibiting or enabling effect on the fulfillment of explanation objectives (such as trust, understanding, or workload). This paper aims to shed light on the significance of human dimensions (gender, age, trust disposition, need for cognition, affinity for technology, self-efficacy, attitudes, and mind attribution) as well as their interplay with different explanation modes (no, simple, or complex explanation). Participants played the game Deal or No Deal while interacting with an AI-based agent. The agent gave advice to the participants on whether they should accept or reject the deals offered to them. As expected, giving an explanation had a positive influence on the explanation objectives. However, the users’ individual characteristics particularly reinforced the fulfillment of the objectives. The strongest predictor of objective fulfillment was the degree of attribution of human characteristics. The more human characteristics were attributed, the more trust was placed in the agent, advice was more likely to be accepted and understood, and important needs were satisfied during the interaction. Thus, the current work contributes to a better understanding of the design of explanations of an AI-based agent system that takes into account individual characteristics and meets the demand for both explainable and human-centered agent systems.
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.
Emotional shifts are often a fundamental part of the narrative experience and engrained into the schematic structures of stories. Recent theoretical work suggests that these shifts are key for narrative influence and are interconnected with transportation, a known mechanism of narrative effects. Empirical research examining this proposition is still scarce, inconclusive, and lacking measures that assess the experience of emotional shifts throughout a narrative to explain effects. This thesis aims to contribute to this research lacuna and investigates the link between emotional shifts, transportation, and story-consistent outcomes using different methods to measure emotional shifts in the moment they occur (Manuscript #1 and #2), and using various narrative stimuli (audiovisual, written, auditive).
Manuscript #1 uses real-time-response (RTR) measurement to examine the relationship of valence shifts experienced during film viewing with transportation and post-exposure self-reported emotional flow. Manuscript #2 reports a pilot study and two experiments in which a self-probed emotional retrospection task is used to measure the number and intensity of emotional shifts during reading. I investigate the effect of reviews on transportation, the link between transportation and emotional shifts, and their respective associations with story-consistent attitudes, social sharing intentions, and donation behavior. In Manuscript #3, narrative structures are manipulated. Two experiments examine the effects of audio stories with shifting (positive-negative-positive) vs. positive-only emotional trajectories on the experience of happiness- and sadness-shifts, transportation, and post-exposure emotional flow.
Transportation was positively linked to valence shifts (M#1), and the number and intensity of emotional shifts (M#2), and emotional flow (M#1, M#3). In M#3, transportation was predicted by shifts in happiness, but not sadness. Emotional flow was linked to shifts in happiness, sadness, and RTR valence (M#1, M#3). Emotional shifts and transportation were associated with social sharing intentions, but only transportation was linked to some story-consistent attitudes (affective attitudes in particular).
Humans have long used external memory aids to support remembering. However, modern digital technologies could facilitate recording and remembering personal information in an unprecedented manner. The present research sought to understand the potential impact of these technologies on autobiographical memory based on interviews with users of smart journaling apps. In Study 1 (N = 12), participants who had no prior experience with smart journaling apps tested the app Day One for 2 weeks and were interviewed about their subjective perceptions afterwards. In order to cross-validate the obtained findings, Study 2 (N = 4) was based on in-depth interviews with long-time users of different smart journaling apps. Taken together, the two studies provide insights into the way autobiographical remembering may change in the digital age – but also into the opportunities and risks potentially associated with the use of technologies that allow creating a detailed and multimedia-based record of one's life.