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Learning about informal fallacies and the detection of fake news: an experimental intervention
(2023)
The philosophical concept of informal fallacies–arguments that fail to provide sufficient support for a claim–is introduced and connected to the topic of fake news detection. We assumed that the ability to identify informal fallacies can be trained and that this ability enables individuals to better distinguish between fake news and real news. We tested these assumptions in a two-group between-participants experiment (N = 116). The two groups participated in a 30-minute-long text-based learning intervention: either about informal fallacies or about fake news. Learning about informal fallacies enhanced participants’ ability to identify fallacious arguments one week later. Furthermore, the ability to identify fallacious arguments was associated with a better discernment between real news and fake news. Participants in the informal fallacy intervention group and the fake news intervention group performed equally well on the news discernment task. The contribution of (identifying) informal fallacies for research and practice is discussed.
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.
Earliest autobiographical memories mark a potential beginning of our life story. However, their meaning has hardly been investigated. Against this background, participants (N = 182) were asked to think about two kinds of meaning: the meaning that the remembered event might have had in the moment of experience and the meaning that the memory of the event has for their present life situation. With respect to the meaning in the moment of experience, participants most frequently referred to situational characteristics. The meaning for the present life situation was most frequently related to aspects of the memory that told something about the person beyond the immediate context of the remembered event. Moreover, these meanings were more frequently associated with continuity than with a contrast between then and now. Apart from these overarching commonalities, our data also show that the earliest autobiographical memories of different people can tell very different stories.
Given the growing interest of corporate stakeholders in Metaverse applications, there is a need to understand accessibility of these technologies for marginalized populations such as people living with dementia to ensure inclusive design of Metaverse applications. We assessed the accessibility of extended reality technology for people living with mild cognitive impairment and dementia to develop accessibility guidelines for these technologies. We used four strategies to synthesize evidence for barriers and facilitators of accessibility: (1) Findings from a non-systematic literature review, (2) guidelines from well-researched technology, (3) exploration of selected mixed reality technologies, and (4) observations from four sessions and video data of people living with dementia using mixed reality technologies. We utilized template analysis to develop codes and themes towards accessibility guidelines. Future work can validate our preliminary findings by applying them on video recordings or testing them in experiments.
Objective
Global challenges such as climate change or the COVID‐19 pandemic have drawn public attention to conspiracy theories and citizens' non‐compliance to science‐based behavioral guidelines. We focus on individuals' worldviews about how one can and should construct reality (epistemic beliefs) to explain the endorsement of conspiracy theories and behavior during the COVID‐19 pandemic and propose the Dark Factor of Personality (D) as an antecedent of post‐truth epistemic beliefs.
Method and Results
This model is tested in four pre‐registered studies. In Study 1 (N = 321), we found first evidence for a positive association between D and post‐truth epistemic beliefs (Faith in Intuition for Facts, Need for Evidence, Truth is Political). In Study 2 (N = 453), we tested the model proper by further showing that post‐truth epistemic beliefs predict the endorsement of COVID‐19 conspiracies and disregarding COVID‐19 behavioral guidelines. Study 3 (N = 923) largely replicated these results at a later stage of the pandemic. Finally, in Study 4 (N = 513), we replicated the results in a German sample, corroborating their cross‐cultural validity. Interactions with political orientation were observed.
Conclusion
Our research highlights that epistemic beliefs need to be taken into account when addressing major challenges to humankind.
Visual stimuli are frequently used to improve memory, language learning or perception, and understanding of metacognitive processes. However, in virtual reality (VR), there are few systematically and empirically derived databases. This paper proposes the first collection of virtual objects based on empirical evaluation for inter-and transcultural encounters between English- and German-speaking learners. We used explicit and implicit measurement methods to identify cultural associations and the degree of stereotypical perception for each virtual stimuli (n = 293) through two online studies, including native German and English-speaking participants. The analysis resulted in a final well-describable database of 128 objects (called InteractionSuitcase). In future applications, the objects can be used as a great interaction or conversation asset and behavioral measurement tool in social VR applications, especially in the field of foreign language education. For example, encounters can use the objects to describe their culture, or teachers can intuitively assess stereotyped attitudes of the encounters.
Virtual reality applications employing avatar embodiment typically use virtual mirrors to allow users to perceive their digital selves not only from a first-person but also from a holistic third-person perspective. However, due to distance-related biases such as the distance compression effect or a reduced relative rendering resolution, the self-observation distance (SOD) between the user and the virtual mirror might influence how users perceive their embodied avatar. Our article systematically investigates the effects of a short (1 m), middle (2.5 m), and far (4 m) SOD between users and mirror on the perception of their personalized and self-embodied avatars. The avatars were photorealistic reconstructed using state-of-the-art photogrammetric methods. Thirty participants repeatedly faced their real-time animated self-embodied avatars in each of the three SOD conditions, where they were repeatedly altered in their body weight, and participants rated the 1) sense of embodiment, 2) body weight perception, and 3) affective appraisal towards their avatar. We found that the different SODs are unlikely to influence any of our measures except for the perceived body weight estimation difficulty. Here, the participants perceived the difficulty significantly higher for the farthest SOD. We further found that the participants’ self-esteem significantly impacted their ability to modify their avatar’s body weight to their current body weight and that it positively correlated with the perceived attractiveness of the avatar. Additionally, the participants’ concerns about their body shape affected how eerie they perceived their avatars. The participants’ self-esteem and concerns about their body shape influenced the perceived body weight estimation difficulty. We conclude that the virtual mirror in embodiment scenarios can be freely placed and varied at a distance of one to four meters from the user without expecting major effects on the perception of the avatar.
Introduction
Modern digital devices, such as conversational agents, simulate human–human interactions to an increasing extent. However, their outward appearance remains distinctly technological. While research revealed that mental representations of technology shape users' expectations and experiences, research on technology sending ambiguous cues is rare.
Methods
To bridge this gap, this study analyzes drawings of the outward appearance participants associate with voice assistants (Amazon Echo or Google Home).
Results
Human beings and (humanoid) robots were the most frequent associations, which were rated to be rather trustworthy, conscientious, agreeable, and intelligent. Drawings of the Amazon Echos and Google Homes differed marginally, but “human,” “robotic,” and “other” associations differed with respect to the ascribed humanness, consciousness, intellect, affinity to technology, and innovation ability.
Discussion
This study aims to further elaborate on the rather unconscious cognitive and emotional processes elicited by technology and discusses the implications of this perspective for developers, users, and researchers.
For formative evaluations of user experience (UX) a variety of methods have been developed over the years. However, most techniques require the users to interact with the study as a secondary task. This active involvement in the evaluation is not inclusive of all users and potentially biases the experience currently being studied. Yet there is a lack of methods for situations in which the user has no spare cognitive resources. This condition occurs when 1) users' cognitive abilities are impaired (e.g., people with dementia) or 2) users are confronted with very demanding tasks (e.g., air traffic controllers). In this work we focus on emotions as a key component of UX and propose the new structured observation method Proxemo for formative UX evaluations. Proxemo allows qualified observers to document users' emotions by proxy in real time and then directly link them to triggers. Technically this is achieved by synchronising the timestamps of emotions documented by observers with a video recording of the interaction.
In order to facilitate the documentation of observed emotions in highly diverse contexts we conceptualise and implement two separate versions of a documentation aid named Proxemo App. For formative UX evaluations of technology-supported reminiscence sessions with people with dementia, we create a smartwatch app to discreetly document emotions from the categories anger, general alertness, pleasure, wistfulness and pride. For formative UX evaluations of prototypical user interfaces with air traffic controllers we create a smartphone app to efficiently document emotions from the categories anger, boredom, surprise, stress and pride. Descriptive case studies in both application domains indicate the feasibility and utility of the method Proxemo and the appropriateness of the respectively adapted design of the Proxemo App.
The third part of this work is a series of meta-evaluation studies to determine quality criteria of Proxemo. We evaluate Proxemo regarding its reliability, validity, thoroughness and effectiveness, and compare Proxemo's efficiency and the observers' experience to documentation with pen and paper. Proxemo is reliable, as well as more efficient, thorough and effective than handwritten notes and provides a better UX to observers. Proxemo compares well with existing methods where benchmarks are available.
With Proxemo we contribute a validated structured observation method that has shown to meet requirements formative UX evaluations in the extreme contexts of users with cognitive impairments or high task demands. Proxemo is agnostic regarding researchers' theoretical approaches and unites reductionist and holistic perspectives within one method.
Future work should explore the applicability of Proxemo for further domains and extend the list of audited quality criteria to include, for instance, downstream utility. With respect to basic research we strive to better understand the sources leading observers to empathic judgments and propose reminisce and older adults as model environment for investigating mixed emotions.
In this article we offer initial insights into the fairly new interdisciplinary and international domain of robotics in Christian religious practice. We are a group of scholars in media ethics, practical theology/religious education, and human computer interaction, who have been engaged in this discourse since 2017.
A natural starting point is our study of BlessU2, a “blessing robot,” a device which received considerable recognition from the global public at the Wittenberg 500th reformation anniversary in 2017. We thus begin with the results of this study. Secondly, we will briefly address the relevant theses from Gabriele Trovato et al., as presented in their 2019 article on so-called theomorphic robots – followed by our interdisciplinary discussion of their approach. Finally, we draw conclusions for further work on the field of “religious robots.”
Somewhat more carefully: Section 1 offers starting points within the perspectives of Christian religious practice: here, the blessing robot is both cause and occasion for doing religion and theologizing in the context of existential questions (1.1). We continue with perceptions in the field of religion regarding “Discursive Design Theory” (1.2). The interaction of humans with computers as posing questions for theological standardization of religious practice is focused upon in 1.3. Section 2 reconstructs the HRI/HCI-initiative to develop theomorphic robots in a twofold manner, i.e., the idea of developing theomorphic robots (2.1) and the concept of theomorphic robots: Questions and objections (2.2). In this part of the article we raise discussion points concerning the relationship between technology and religion and the need for sharpening the understanding of religion within the research field. Section 3 closes with propositions and alternatives.
Previous research suggested that people prefer to administer unpleasant electric shocks to themselves rather than being left alone with their thoughts because engagement in thinking is an unpleasant activity. The present research examined this negative reinforcement hypothesis by giving participants a choice of distracting themselves with the generation of electric shock causing no to intense pain. Four experiments (N = 254) replicated the result that a large proportion of participants opted to administer painful shocks to themselves during the thinking period. However, they administered strong electric shocks to themselves even when an innocuous response option generating no or a mild shock was available. Furthermore, participants inflicted pain to themselves when they were assisted in the generation of pleasant thoughts during the waiting period, with no difference between pleasant versus unpleasant thought conditions. Overall, these results question that the primary motivation for the self-administration of painful shocks is avoidance of thinking. Instead, it seems that the self-infliction of pain was attractive for many participants, because they were curious about the shocks, their intensities, and the effects they would have on them.