Browsing by Author "Welsch, Robin"
Now showing 1 - 17 of 17
Results Per Page
Sort Options
Item Adapting Visual Complexity Based on Electrodermal Activity Improves Working Memory Performance in Virtual Reality(ACM, 2023-09-12) Chiossi, Francesco; Turgut, Yagiz; Welsch, Robin; Mayer, Sven; Department of Computer Science; Professorship Welsch Robin; Computer Science Professors; Computer Science - Human-Computer Interaction and Design (HCID); Computer Science - Engineering Psychology (ENGPSYCH); Ludwig Maximilian University of MunichBiocybernetic loops encompass users' state detection and system adaptation based on physiological signals. Current adaptive systems limit the adaptation to task features such as task difficulty or multitasking demands. However, virtual reality allows the manipulation of task-irrelevant elements in the environment. We present a physiologically adaptive system that adjusts the virtual environment based on physiological arousal, i.e., electrodermal activity. We conducted a user study with our adaptive system in social virtual reality to verify improved performance. Here, participants completed an n-back task, and we adapted the visual complexity of the environment by changing the number of non-player characters. Our results show that an adaptive virtual reality can control users' comfort, performance, and workload by adapting the visual complexity based on physiological arousal. Thus, our physiologically adaptive system improves task performance and perceived workload. Finally, we embed our findings in physiological computing and discuss applications in various scenarios.Item "AI enhances our performance, I have no doubt this one will do the same": The Placebo effect is robust to negative descriptions of AI(2024-05-11) Kloft, Agnes; Welsch, Robin; Kosch, Thomas; Villa, Steeven; Department of Computer Science; Mueller, Florian Floyd; Kyburz, Penny; Williamson, Julie R.; Sas, Corina; Wilson, Max L.; Toups Dugas, Phoebe; Shklovski, Irina; Professorship Welsch Robin; Computer Science - Engineering Psychology (ENGPSYCH); Computer Science Professors; Computer Science - Human-Computer Interaction and Design (HCID); Humboldt-Universität zu Berlin; Ludwig Maximilian University of MunichHeightened AI expectations facilitate performance in human-AI interactions through placebo effects. While lowering expectations to control for placebo effects is advisable, overly negative expectations could induce nocebo effects. In a letter discrimination task, we informed participants that an AI would either increase or decrease their performance by adapting the interface, when in reality, no AI was present in any condition. A Bayesian analysis showed that participants had high expectations and performed descriptively better irrespective of the AI description when a sham-AI was present. Using cognitive modeling, we could trace this advantage back to participants gathering more information. A replication study verified that negative AI descriptions do not alter expectations, suggesting that performance expectations with AI are biased and robust to negative verbal descriptions. We discuss the impact of user expectations on AI interactions and evaluation.Item The AI Ghostwriter Effect: When Users Do Not Perceive Ownership of AI-Generated Text But Self-Declare as Authors(ACM, 2024-02-05) Draxler, Fiona; Werner, Anna; Lehmann, Florian; Hoppe, Matthias; Schmidt, Albrecht; Buschek, Daniel; Welsch, Robin; Department of Computer Science; Professorship Welsch Robin; Computer Science - Engineering Psychology (ENGPSYCH); Computer Science Professors; Computer Science - Human-Computer Interaction and Design (HCID); Ludwig Maximilian University of Munich; University of BayreuthHuman-AI interaction in text production increases complexity in authorship. In two empirical studies (n1 = 30 & n2 = 96), we investigate authorship and ownership in human-AI collaboration for personalized language generation. We show an AI Ghostwriter Effect: Users do not consider themselves the owners and authors of AI-generated text but refrain from publicly declaring AI authorship. Personalization of AI-generated texts did not impact the AI Ghostwriter Effect, and higher levels of participants’ influence on texts increased their sense of ownership. Participants were more likely to attribute ownership to supposedly human ghostwriters than AI ghostwriters, resulting in a higher ownership-authorship discrepancy for human ghostwriters. Rationalizations for authorship in AI ghostwriters and human ghostwriters were similar. We discuss how our findings relate to psychological ownership and human-AI interaction to lay the foundations for adapting authorship frameworks and user interfaces in AI in text-generation tasks.Item Behavioral economics for AI-augmented scenarios(2024-09-16) Tuloisela, Tapio; Welsch, Robin; Perustieteiden korkeakoulu; Savioja, LauriThe applications of Artificial Intelligence (AI) are becoming increasingly prominent in the society. Therefore, it is valuable to develop a broader understanding of human decision-making in AI-augmented scenarios. For instance, independent AI agents and other advanced AI applications, such as digital assistants are becoming ubiquitous. A deep understanding of human-AI interactions is important in order to ensure that the development of AI-driven society takes into account the possible challenges that might arise from this new field of interaction. This bachelor’s thesis is a literature review exploring how humans cooperate and how these cooperative traits transition to human-AI strategic interactions. The concepts are studied using the methods of behavioral economics and game theory that have shown good results in predicting human decision-making in strategic interactions. The goal of the thesis is to inspect how human behavior changes in AI-augmented scenarios. Real-life strategic interactions can be represented with game theoretic scenarios called economic games. A common variation of these games are social dilemmas that enable researchers to study various motivations behind economic decision-making. In empirical studies on economic games, mathematical models that take into account people's preferences for fairness and cooperation tend to outperform predictions focused solely on self-interested motivations. Typically these models compare decisions by assigning utilities for different actions based on individual's social preferences and material rewards in the scenario. Examining these models is useful, because they provide insight into humans’ internal decision-making processes. The thesis concludes that in AI-augmented strategic interactions, the current social preference models are unable to predict cooperation accurately. Instead, people seem to exploit benevolent AI agents. However, social preferences tend to persist when individuals are informed that there is another human beneficiary who receives the payoffs gained by the AI. This also seems to translate to settings where humans are interacting with other AI-augmented people. Even with no human beneficiary, cooperation can be elicited by introducing cultural or emotional expressions for the AI agents. Based on the reviewed literature, the thesis presents a framework to evaluate human decision-making in strategic interactions, which also considers scenarios involving non-human agents.Item Designing User-Centric Private Conversation Methods in the Metaverse(2023-08-21) Limbago, Josephus; Welsch, Robin; Perustieteiden korkeakoulu; Di Francesco, MarioThe metaverse is an emerging medium for remote interactions, allowing users to engage in immersive experiences with others in virtual environments, such as attending concerts, business meetings, or social gatherings with friends. Private conversation is an important feature that improves the overall experience in the metaverse. This essential element of virtual interactions allows the exchange of sensitive information and promotes self-disclosure, a key factor in building interpersonal relationships. However, current methods for establishing private conversations have several limitations. In Private Talk, floating icons above the users' avatars do not feel natural and break the immersion. Meanwhile, creating private rooms and teleporting to them disrupts the flow of experience. The goal of this thesis is to design private conversations in the metaverse. First, we surveyed existing methods for establishing private conversations by assessing popular applications and online sources. Second, we developed our own application where we implemented two baseline methods for private conversations, Private Talk and private room. Next, we conducted a user study where we invited 12 participants to evaluate the baseline methods and propose their own methods. We employed questionnaires and conducted interviews to gather suggestions and valuable insights. A thematic analysis of the interview transcripts identified six themes; minimizing background noise, isolation for enhanced feeling of privacy, indicators and distinctions of privacy mode, easy and natural methods in virtual environments, and privacy concerns. From our results, we developed design implications for improving private conversation methods in the metaverse. Our findings aim to guide the design of the future metaverse.Item Feeling the Temperature of the Room : Unobtrusive Thermal Display of Engagement during Group Communication(ACM, 2023-03-28) Haliburton, Luke; Schött, Svenja Yvonne; Hirsch, Linda; Welsch, Robin; Schmidt, Albrecht; Department of Computer Science; Professorship Welsch Robin; Computer Science - Engineering Psychology (ENGPSYCH); Computer Science Professors; Computer Science - Human-Computer Interaction and Design (HCID); Ludwig Maximilian University of MunichThermal signals have been explored in HCI for emotion-elicitation and enhancing two-person communication, showing that temperature invokes social and emotional signals in individuals. Yet, extending these findings to group communication is missing. We investigated how thermal signals can be used to communicate group affective states in a hybrid meeting scenario to help people feel connected over a distance. We conducted a lab study (N=20 participants) and explored wrist-worn thermal feedback to communicate audience emotions. Our results show that thermal feedback is an effective method of conveying audience engagement without increasing workload and can help a presenter feel more in tune with the audience. We outline design implications for real-world wearable social thermal feedback systems for both virtual and in-person communication that support group affect communication and social connectedness. Thermal feedback has the potential to connect people across distances and facilitate more effective and dynamic communication in multiple contexts.Item “I Feel My Abs”: Exploring Non-standing VR Locomotion(ACM, 2023-10-04) Kontio, Reetu; Laattala, Markus; Welsch, Robin; Hämäläinen, Perttu; Department of Computer Science; Department of Art and Media; Professorship Hämäläinen Perttu; Computer Science Professors; Computer Science - Visual Computing (VisualComputing); Professorship Welsch Robin; Computer Science - Engineering Psychology (ENGPSYCH); Computer Science - Human-Computer Interaction and Design (HCID); Department of Computer ScienceVirtual Reality (VR) games and experiences predominantly have the users interact while standing or seated. However, this only represents a fraction of the full diversity of human movement. In this paper, we explore a novel non-standing approach to VR locomotion where the user performs locomotion movements in the air or only slightly touching the ground with their feet. For instance, the user may lie supine on the ground, reminiscent of the Bicycle Crunch, a core training movement common in Pilates and other forms of bodyweight exercise. Although this cannot generally replace traditional VR locomotion, it provides two benefits that we believe can be of use for specific application domains such as VR exergames: First, the user's lower body movement is not impeded by a small real-life space, allowing versatile navigation of large virtual worlds using walking, running, strafing, and jumping. Second, we allow new ways to activate parts of the body that remain passive in most existing VR interactions. We describe and discuss four different variants of the approach, and investigate two prototypes further in a qualitative user study, to better understand their strengths, weaknesses, and application potential.Item Investigating Labeler Bias in Face Annotation for Machine Learning(2024-06-05) Haliburton, Luke; Ghebremedhin, Sinksar; Welsch, Robin; Schmidt, Albrecht; Mayer, Sven; Department of Computer Science; Lorig, Fabian; Tucker, Jason; Lindstrom, Adam Dahlgren; Dignum, Frank; Murukannaiah, Pradeep; Theodorou, Andreas; Yolum, Pinar; Professorship Welsch Robin; Computer Science - Engineering Psychology (ENGPSYCH); Computer Science Professors; Computer Science - Human-Computer Interaction and Design (HCID); Ludwig Maximilian University of MunichIn a world increasingly reliant on artificial intelligence, it is more important than ever to consider the ethical implications of artificial intelligence. One key under-explored challenge is labeler bias - bias introduced by individuals who label datasets - which can create inherently biased datasets for training and subsequently lead to inaccurate or unfair decisions in healthcare, employment, education, and law enforcement. Hence, we conducted a study (N=98) to investigate and measure the existence of labeler bias using images of people from different ethnicities and sexes in a labeling task. Our results show that participants hold stereotypes that influence their decision-making process and that labeler demographics impact assigned labels. We also discuss how labeler bias influences datasets and, subsequently, the models trained on them. Overall, a high degree of transparency must be maintained throughout the entire artificial intelligence training process to identify and correct biases in the data as early as possible.Item Navigating the Virtual Gaze: Social Anxiety's Role in VR Proxemics(2024-05-11) Mello, Beatriz; Welsch, Robin; Verbokkem, Marissa; Knierim, Pascal; Dechant, Martin Johannes; Department of Computer Science; Mueller, Florian Floyd; Kyburz, Penny; Williamson, Julie R.; Sas, Corina; Wilson, Max L.; Toups Dugas, Phoebe; Shklovski, Irina; Professorship Welsch Robin; Computer Science - Engineering Psychology (ENGPSYCH); Computer Science Professors; Computer Science - Human-Computer Interaction and Design (HCID); Department of Computer Science; University of Innsbruck; University College London; University of MinhoFor individuals with Social Anxiety (SA), interacting with others can be a challenging experience, a concern that extends into the virtual world. While technology has made significant strides in creating more realistic virtual human agents (VHA), the interplay of gaze and interpersonal distance when interacting with VHAs is often neglected. This paper investigates the effect of dynamic and static Gaze animations in VHAs on interpersonal distance and their relation to SA. A Bayesian analysis shows that static centered and dynamic centering gaze led participants to stand closer to VHAs than static averted and dynamic averting gaze, respectively. In the static gaze conditions, this pattern was found to be reversed in SA: participants with higher SA kept larger distances for static-centered gaze than for averted gaze VHAs. These findings update theory, elucidate how nuanced interactions with VHAs must be designed, and offer renewed guidelines for pleasant VHA interaction design.Item Personal Space, Crowding and Safety in Populated Social Contexts(2024-03-11) Haavisto, Otso; Welsch, Robin; Perustieteiden korkeakoulu; Welsch, RobinThe environmental factors of personal space (PS) regulation, such as room size, ceiling height and crowdedness, have been studied in the past, but with inconclusive results. Notably, how these factors affect PS regulation in conjunction with each other is yet to be studied. Understanding how the combination of social and environmental factors affects PS regulation and the subjective experience can help design more comfortable spaces and experiences in both physical and virtual contexts. To investigate the socio-spatial factors of PS regulation and room perception, 33 participants were recruited for a study in a virtual reality (VR) setting and tasked to evaluate rectangular rooms of various dimensions and crowd configurations. Participants performed an active-approach stop-distance task, indicating a comfortable conversation distance to a target virtual human in each room. Additionally, participants' subjective impressions of each room configuration were gathered. The work identifies a tendency for people to accommodate others in highly populated settings despite feeling crowded. The results indicate that the equilibrium theory – the prevailing theory used to explain PS regulation – is not valid in social contexts with crowds of people. Rather than increasing their comfort distance from the approach target as distances between crowd members got shorter and their sense of crowding increased, participants partly mimicked the spatial behavior of other people. This suggests that social expectations affect distancing behavior in populated contexts. The results have implications for both physical and virtual contexts. In the physical world, settings with large numbers of people should actively manage occupancy rates to ensure the safety of attendees. While crowded scenes in mixed reality do not risk the physical safety of users, they can stimulate feelings of discomfort, both due to PS violations and spatially incompatible interaction modalities. Therefore, social spatial computing applications should consider human spatial behavior tendencies in order to deliver a comfortable user experience.Item A Pilot Study Comparing ChatGPT and Google Search in Supporting Visualization Insight Discovery(2024) He, Chen; Welsch, Robin; Jacucci, Giulio; Department of Computer Science; Soto, Axel; Zangerle, Eva; Professorship Welsch Robin; Computer Science - Engineering Psychology (ENGPSYCH); Computer Science Professors; Computer Science - Human-Computer Interaction and Design (HCID)The popularity of large language models (LLMs) provides new possibilities for deriving visualization insights, integrating human and machine intelligence. However, we have yet to understand how a contextualized LLM compares with the traditional search in supporting visualization insight discovery. To this end, we conducted a between-subjects study with 25 participants to compare user insight generation with chat/search on a CO2 Explorer. The Chat condition has ChatGPT contextualized with the data, user tasks, and interactions as programmed system prompts. Results show both systems have their merits and demerits: ChatGPT affords users to ask more diverse questions but can produce wrong answers; Search provides information sources, making the answer more reliable, but users can fail to find the answer. This study prompts us to synthesize them in a future study for reliable and efficient information retrieval.Item The placebo effect of human augmentation : Anticipating cognitive augmentation increases risk-taking behavior(Elsevier Ltd, 2023-09) Villa, Steeven; Kosch, Thomas; Grelka, Felix; Schmidt, Albrecht; Welsch, Robin; Ludwig Maximilian University of Munich; Humboldt-Universität zu Berlin; Department of Computer Science; Department of Computer ScienceHuman Augmentation Technologies improve human capabilities using technology. In this study, we investigate the placebo effect of Augmentation Technologies. Thirty naïve participants were told to be augmented with a cognitive augmentation technology or no augmentation system while conducting a Columbia Card Task. In this risk-taking measure, participants flip win and loss cards. The sham augmentation system consisted of a brain–computer interface allegedly coordinated to play non-audible sounds that increase cognitive functions. However, no sounds were played throughout all conditions. We show a placebo effect in human augmentation, where a sustained belief of improvement remains after using the sham system and an increase in risk-taking conditional on heightened expectancy using Bayesian statistical modeling. Furthermore, we identify differences in event-related potentials in the electroencephalogram that occur during the sham condition when flipping loss cards. Finally, we integrate our findings into theories of human augmentation and discuss implications for the future assessment of augmentation technologies.Item A Robot Jumping the Queue: Expectations About Politeness and Power During Conflicts in Everyday Human-Robot Encounters(2024-05-11) Babel, Franziska; Welsch, Robin; Miller, Linda; Hock, Philipp; Thellman, Sam; Ziemke, Tom; Department of Computer Science; Mueller, Florian Floyd; Kyburz, Penny; Williamson, Julie R.; Sas, Corina; Wilson, Max L.; Toups Dugas, Phoebe; Shklovski, Irina; Professorship Welsch Robin; Computer Science - Engineering Psychology (ENGPSYCH); Computer Science Professors; Computer Science - Human-Computer Interaction and Design (HCID); Linköping University; Ulm UniversityIncreasing encounters between people and autonomous service robots may lead to conflicts due to mismatches between human expectations and robot behaviour. This interactive online study (N = 335) investigated human-robot interactions at an elevator, focusing on the effect of communication and behavioural expectations on participants’ acceptance and compliance. Participants evaluated a humanoid delivery robot primed as either submissive or assertive. The robot either matched or violated these expectations by using a command or appeal to ask for priority and then entering either first or waiting for the next ride. The results highlight that robots are less accepted if they violate expectations by entering first or using a command. Interactions were more effective if participants expected an assertive robot which then asked politely for priority and entered first. The findings emphasize the importance of power expectations in human-robot conflicts for the robot’s evaluation and effectiveness in everyday situations.Item SaferHome: Interactive Physical and Digital Smart Home Dashboards for Communicating Privacy Assessments to Owners and Bystanders(ACM, 2022) Windl, Maximiliane; Hiesinger, Alexander; Welsch, Robin; Schmidt, Albrecht; Feger, Sebastian S.; Department of Computer Science; Professorship Welsch Robin; Computer Science Professors; Computer Science - Human-Computer Interaction and Design (HCID); Computer Science - Engineering Psychology (ENGPSYCH); Ludwig Maximilian University of MunichPrivate homes are increasingly becoming smart spaces. While smart homes promise comfort, they expose most intimate spaces to security and privacy risks. Unfortunately, most users today are not equipped with the right tools to assess the vulnerabilities or privacy practices of smart devices. Further, users might lose track of the devices installed in their homes or are unaware of devices placed by a partner or host. We developed SaferHome, an interactive digital-physical privacy framework, to provide smart home users with security and privacy assessments and a sense of device location. SaferHome includes a digital list view and physical and digital dashboards that map real floor plans. We evaluated SaferHome with eight households in the wild. We find that users adopted various strategies to integrate the dashboards into their understanding and interpretation of smart home privacy. We present implications for the design of future smart home privacy frameworks that are impacted by technical affinity, device types, device ownership, and tangibility of assessments.Item Society's Attitudes Towards Human Augmentation and Performance Enhancement Technologies (SHAPE) Scale(ACM, 2023-09-27) Villa, Steeven; Niess, Jasmin; Schmidt, Albrecht; Welsch, Robin; Department of Computer Science; Professorship Welsch Robin; Computer Science - Engineering Psychology (ENGPSYCH); Computer Science Professors; Computer Science - Human-Computer Interaction and Design (HCID); Ludwig Maximilian University of Munich; University of OsloHuman augmentation technologies (ATs) are a subset of ubiquitous on-body devices designed to improve cognitive, sensory, and motor capacities. Although there is a large corpus of knowledge concerning ATs, less is known about societal attitudes towards them and how they shift over time. To that end, we developed The Society's Attitudes Towards Human Augmentation and Performance Enhancement Technologies (SHAPE) Scale, which measures how users of ATs are perceived. To develop the scale, we first created a list of possible scale items based on past work on how people respond to new technologies. The items were then reviewed by experts. Next, we performed exploratory factor analysis to reduce the scale to its final length of thirteen items. Subsequently, we confirmed test-retest validity of our instrument, as well as its construct validity. The SHAPE scale enables researchers and practitioners to understand elements contributing to attitudes toward augmentation technology users. The SHAPE scale assists designers of ATs in designing artifacts that will be more universally accepted.Item Subjective evaluation of performance in AI-assisted decision-making - Analysis of the Dunning-Kruger effect in AI-assisted decision-making(2024-09-16) Nicholls, Salla; Welsch, Robin; Perustieteiden korkeakoulu; Savioja, LauriArtificial Intelligence (AI) is increasingly used as an aid in decision-making in various applications. This is called AI-assisted decision-making, in which the decision-maker utilises suggestions made by the AI, but makes the final decision himself/herself. In many applications, the correctness of the decision is judged by the decision-maker, as there might not be an objectively correct decision or the implications of the decision are manifested later. Considering this, it is important to ensure that these decision-makers are able to accurately evaluate their decisions to optimise their future behaviour. Research in psychology has revealed cognitive biases related to decision-making and the evaluation of it. The decision-making process is further complicated when an AI-assistant is present. Furthermore, the complexity of the decision-making is reflected in the subjective evaluation of the decision. Thus, research is required on how AI affects the evaluation of the decision and what cognitive biases might be present. This thesis focuses on a cognitive bias called the Dunning-Kruger effect, which research has found to be present in decision-making in a range of domains. Due to the Dunning-Kruger effect, low performing decision-makers overestimate their performance compared to their true performance. This thesis analyses if and how the addition of an AI-assistant in the decision-making process affects this cognitive bias. The foundation of this investigation is build in metacognition, one's knowledge of their own thought processes. Based on a literature review, two theoretical frameworks of the subjective evaluation of AI-assisted decision-making are formed, compared and used to explain the potential behaviour of the Dunning-Kruger effect. This effect is concluded to likely be inflated due to additional metacognitive load and the biases caused by the AI. This implies that low performing decision-makers would overestimate their performance more with an AI-assistant than without. This work encourages future research to empirically examine the Dunning-Kruger effect in the subjective evaluation of AI-assisted decision-making. The theoretical frameworks developed in this thesis provide new insights into how individual differences influence the subjective evaluation of AI-assisted decision-making and where these differences might originate from.Item Task-relevant social cues affect whole-body approach-avoidance behavior(Nature Publishing Group, 2023-05-26) Welsch, Robin; Hecht, Heiko; Stins, John; Department of Computer Science; Professorship Welsch Robin; Computer Science Professors; Computer Science - Human-Computer Interaction and Design (HCID); Computer Science - Engineering Psychology (ENGPSYCH); Johannes Gutenberg University Mainz; Vrije Universiteit AmsterdamPositively evaluated stimuli facilitate approach and negatively evaluated stimuli prompt avoidance responses, as typically measured by reaction time differences when moving a joystick toward the own body or away from it. In this study, we explore whether a whole-body response (forward and backward leaning can serve as a better indicator of approach-avoidance behavior; AA). Thirty-two subjects were presented with pictures of males and females with angry or happy facial expressions. Subjects had to perform approach or avoidance responses by leaning forward or backward, either based on the facial expression of the stimulus or the gender of the stimulus. Leaning responses were sensitive to angry faces for explicit decision cues. Here, angry facial expressions facilitated backward leaning but not when responding to the gender of the stimulus. We compare this to the established manual measure of AA and discuss our results with regard to response coding.
