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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.