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So far, sustainable HCI has mainly focused on the domestic context, but there is a growing body of work looking at the organizational context. As in the domestic context, these works still rest on psychological theories for behaviour change used for the domestic context. We supplement this view with an organizational theory-informed approach that adopts organizational roles as a key element. We will show how a role-based analysis could be applied to uncover information needs and to give em-ployee’s eco-feedback, which is linked to their tasks at hand. We illustrate the approach on a qualitative case study that was part of a broader, ongoing action research conducted in a German production company.
Focus on what matters: improved feature selection techniques for personal thermal comfort modelling
(2022)
Occupants' personal thermal comfort (PTC) is indispensable for their well-being, physical and mental health, and work efficiency. Predicting PTC preferences in a smart home can be a prerequisite to adjusting the indoor temperature for providing a comfortable environment. In this research, we focus on identifying relevant features for predicting PTC preferences. We propose a machine learning-based predictive framework by employing supervised feature selection techniques. We apply two feature selection techniques to select the optimal sets of features to improve the thermal preference prediction performance. The experimental results on a public PTC dataset demonstrated the efficiency of the feature selection techniques that we have applied. In turn, our PTC prediction framework with feature selection techniques achieved state-of-the-art performance in terms of accuracy, Cohen's kappa, and area under the curve (AUC), outperforming conventional methods.
UX-Professionals stehen vor der Aufgabe ihre Fertigkeiten und Kenntnisse kontinuierlich auszubauen. Eine Möglichkeit dies zu tun sind Communities of Practice, also Gemeinschaften von Personen mit ähnlichen Aufgaben und Schwerpunkten sowie einem gemeinsamen Interesse an Lösungen. Sie agieren weitgehend selbstorganisiert und dienen dem Austausch und der gegenseitigen Unterstützung. So entstehen ein gemeinsamer Wissensschatz sowie ein Netzwerk zwischen allen UX-Interessierten. Der Aufbau einer Community of Practice für UX-Professionals wurde in einem mittelständigen Unternehmen über 18 Monate begleitet und ausgewertet. Die Ergebnisse führten zu Handlungsempfehlungen, um Hindernisse beim Aufbau zu reduzieren und einen Mehrwert für alle Beteiligten herbeizuführen.
In Software development, the always beta principle is used to successfully develop innovation based on early and continuous user feedback. In this paper we discuss how this principle could be adapted to the special needs of designing for the Smart Home, where we do not just take care of the software, but also release hardware components. In particular, because of the 'materiality' of the Smart Home one could not just make a beta version available on the web, but an essential part of the development process is also to visit the 'beta' users in their home, to build trust, to face the real world issues and provide assistance to make the Smart Home work for them. After presenting our case study, we will then discuss the challenges we faced and how we dealt with them.
Critical consumerism is complex as ethical values are difficult to negotiate, appropriate products are hard to find, and product information is overwhelming. Although recommender systems offer solutions to reduce such complexity, current designs are not appropriate for niche practices and use non-personalized intransparent ethics. To support critical consumption, we conducted a design case study on a personalized food recommender system. Therefore, we first conducted an empirical pre-study with 24 consumers to understand value negotiations and current practices, co-designed the recommender system, and finally evaluated it in a real-world trial with ten consumers. Our findings show how recommender systems can support the negotiation of ethical values within the context of consumption practices, reduce the complexity of finding products and stores, and strengthen consumers. In addition to providing implications for the design to support critical consumption practices, we critically reflect on the scope of such recommender systems and its appropriation.
In 1991 the researchers at the center for the Learning Sciences of Carnegie Mellon University were confronted with the confusing question of “where is AI” from the users, who were interacting with AI but did not realize it. Three decades of research and we are still facing the same issue with the AItechnology users. In the lack of users’ awareness and mutual understanding of AI-enabled systems between designers and users, informal theories of the users about how a system works (“Folk theories”) become inevitable but can lead to misconceptions and ineffective interactions. To shape appropriate mental models of AI-based systems, explainable AI has been suggested by AI practitioners. However, a profound understanding of the current users’ perception of AI is still missing. In this study, we introduce the term “Perceived AI” as “AI defined from the perspective of its users”. We then present our preliminary results from deep-interviews with 50 AItechnology users, which provide a framework for our future research approach towards a better understanding of PAI and users’ folk theories.
Bisherige Versuche der HCI-Community die Lebensmittelverschwendung oder den CO2-Fußabdruck zu reduzieren, basierten meist auf Persuasive Design Ansätzen. Diese werden jedoch kritisiert, die Alltagswelten und Konsumpraktiken für eine Langzeitwirkung nur unzureichend zu berücksichtigen. Das Problem aufgreifend, untersucht dieser Beitrag die Rolle (digitaler) Medien im Übergang zu einer veganen Ernährungspraktik. Hierfür wurden semi-strukturierte Interviews mit 9 VeganerInnen geführt und vor dem Hintergrund der Praxistheorie analysiert. Die Ergebnisse deuten dabei auf eine intensive Nutzung (digitaler) Medien, insbesondere in der frühen Phase der Änderung der Konsumpraktik. Statt Gamification oder Persuasive Design, zeigt sich Mediennutzung in Form von Irritation, Informationsbereitstellung zur Ausbildung eines vegan-spezifischen Konsumwissens sowie als Vermittler zwischen Gleichgesinnten.
For most people, using their body to authenticate their identity is an integral part of daily life. From our fingerprints to our facial features, our physical characteristics store the information that identifies us as "us." This biometric information is becoming increasingly vital to the way we access and use technology. As more and more platform operators struggle with traffic from malicious bots on their servers, the burden of proof is on users, only this time they have to prove their very humanity and there is no court or jury to judge, but an invisible algorithmic system. In this paper, we critique the invisibilization of artificial intelligence policing. We argue that this practice obfuscates the underlying process of biometric verification. As a result, the new "invisible" tests leave no room for the user to question whether the process of questioning is even fair or ethical. We challenge this thesis by offering a juxtaposition with the science fiction imagining of the Turing test in Blade Runner to reevaluate the ethical grounds for reverse Turing tests, and we urge the research community to pursue alternative routes of bot identification that are more transparent and responsive.
Smart home systems are becoming an integral feature of the emerging home IT market. Under this general term, products mainly address issues of security, energy savings and comfort. Comprehensive systems that cover several use cases are typically operated and managed via a unified dashboard. Unfortunately, research targeting user experience (UX) design for smart home interaction that spans several use cases or covering the entire system is scarce. Furthermore, existing comprehensive and user-centered longterm studies on challenges and needs throughout phases of information collection, installation and operation of smart home systems are technologically outdated. Our 18-month Living Lab study covering 14 households equipped with smart home technology provides insights on how to design for improving smart home appropriation. This includes a stronger sensibility for household practices during setup and configuration, flexible visualizations for evolving demands and an extension of smart home beyond the location.
Usability und User Experience (UX) haben als Design-Aspekte in der Produktentwicklung zunehmend an Bedeutung gewonnen. Daher ist es sinnvoll, die organisationale Kompetenz zur Entwicklung von Produkten mit einer positiven UX zu stärken. Veränderungen in Organisationen sind jedoch mit großem Aufwand verbunden. Deshalb müssen Organisationen entscheiden, welche Aktivitäten zur Veränderung der eigenen Kompetenz durchgeführt werden sollen und welche nicht. Die bisherige Forschung hat sich weitgehend auf die Anwendbarkeit bestimmter Methoden im Projekt- und Produktkontext konzentriert. Um geeignete Aktivitäten zur Verbesserung der organisationalen UX-Kompetenz zu identifizieren, wurden 17 UX-Professionals befragt. Diese UX-Professionals haben mindestens zehn Jahre Erfahrung durch die Arbeit in mehreren Unternehmen und durch die Übernahme einer Führungsrolle im Bereich UX gesammelt. Aus diesen Interviews wurden 13 mögliche Maßnahmen zur Steigerung der UX-Kompetenz von Organisationen abgeleitet. Dazu gehören beispielsweise die Erhöhung der Kompetenz einzelner Mitarbeiter, das Teilen von UX-Erfolgsgeschichten oder das Ermöglichen von User Research.
AI (artificial intelligence) systems are increasingly being used in all aspects of our lives, from mundane routines to sensitive decision-making and even creative tasks. Therefore, an appropriate level of trust is required so that users know when to rely on the system and when to override it. While research has looked extensively at fostering trust in human-AI interactions, the lack of standardized procedures for human-AI trust makes it difficult to interpret results and compare across studies. As a result, the fundamental understanding of trust between humans and AI remains fragmented. This workshop invites researchers to revisit existing approaches and work toward a standardized framework for studying AI trust to answer the open questions: (1) What does trust mean between humans and AI in different contexts? (2) How can we create and convey the calibrated level of trust in interactions with AI? And (3) How can we develop a standardized framework to address new challenges?
Die Entwicklung intelligenter Technologien zur Unterstützung im Alltag und in den eigenen vier Wänden begleitet unsere Gesellschaft schon seit dem Zeitalter des Personal Computers. Mit dem Aufkommen des Internet der Dinge und begünstigt durch immer kleiner und günstiger werdende Hardware ergeben sich neue Potenziale, die das Thema Smart Home attraktiver als je zuvor werden lassen. Eine Vielzahl der aktuell im Markt verfügbaren Lösungen adressiert die Bedürfnisse Komfort, Sicherheit und effiziente Energienutzung. Die versprochene Intelligenz – smartness, wie sie der Begriff selbst suggeriert – wird vor allem bei Lösungen im privaten Nachrüstbereich überwiegend durch die Interaktion der Nutzer selbst und entsprechende regelbasierte Konfigurationen erzeugt. Diese notwendige Art der Interaktion und die damit verbundenen Aufwände sind jedoch von starker Bedeutung für das gesamte Nutzungserlebnis Smart Home und führen nicht selten zu Frustration oder gar Resignation in der Nutzung.
Getrieben durch kleiner und günstiger werdende Sensoren und der damit verbundenen Messbarmachung immer weiter reichender Teile des Alltages, hat sich die Gestaltung von Verbrauchsvisualisierunen bzw. Verbrauchsfeedbacksystemen zur Unterstützung von nachhaltigem Verhalten zu einem sehr aktiven Forschungsfeld entwickelt.
Die im Jahre 2013 begonnene Workshop-Reihe „Usability in der betrieblichen Praxis“ auf der Mensch und Computer wird mit diesem Workshop als Aktivität des Mittelstand 4.0-Kompetenzzentrums Usability des BMWi fortgesetzt. Unter dem Stichwort „Digitalisierung“ ergeben sich neue Herausforderungen der Umsetzung von Usability und positiver User Experience (UUX) in der betrieblichen Praxis kleiner und mittelständischer Unternehmen (UUX-Praxis). Diese werden in vier Schwerpunktthemen im Workshop behandelt: „UUX - Erfolgsfaktor für Innovation und Zukunft der Arbeit“, „UUX und digitale Nutzerforschung“, „UUX und Agilität“ sowie „UUX - Unterstützung mittelständischer Unternehmensnetzwerke“. Der Workshop richtet sich an Entwicklungs- und UUX-Praktiker aus Softwareentwicklungs-, Anwendungs- und UUX-Beratungsunternehmen sowie Wissenschaftler, die sich mit Umsetzung der UUX-Praxis in Unternehmen beschäftigen.
Intelligentes Carsharing zur Förderung der urbanen Mobilität - Einfach Teilen : Schlussbericht
(2019)
Autonomous driving enables new mobility concepts such as shared-autonomous services. Although significant re-search has been done on passenger-car interaction, work on passenger interaction with robo-taxis is still rare. In this paper, we tackle the question of how passengers experience robo-taxis as a service in real-life settings to inform the interaction design. We conducted a Wizard of Oz study with an electric vehicle where the driver was hidden from the passenger to simulate the service experience of a robo-taxi. 10 participants had the opportunity to use the simulated shared-autonomous service in real-life situations for one week. By the week's end, 33 rides were completed and recorded on video. Also, we flanked the study conducting interviews before and after with all participants. The findings provided insights into four design themes that could inform the service design of robo-taxis along the different stages including hailing, pick-up, travel, and drop-off.
Eco-InfoVis at Work
(2020)
Die Globalisierung führt zu immer komplexeren, für die Einzelnen kaum nachvollziehbaren Wertschöpfungsketten in der Lebensmittelindustrie. Zugleich eröffnet die Digitalisierung neue Möglichkeiten, Informationen entlang der Kette zu sammeln, und so mehr Transparenz und Vertrauen für den Verbraucherbeziehungsweise die Verbraucherin zu schaffen. Jedoch finden Verbraucherinformations-Apps wie fTRACE bisher nur eine geringe Verbreitung. Daher haben wir in einer qualitativen Studie mit 16 Teilnehmer/-innen Bedürfnisse und Nutzungshürden von Verbraucher/-innen im Zusammenhang mit Verbraucherinformations-Apps analysiert. Es zeigt sich, dass das Vertrauen in die Informationen, sowie der einfache Zugang dazu für Verbraucher/-innen zentral sind. Durch die gut sichtbare Bereitstellung der Informationen am Point-of-Sale, sowie der automatisierten Informationsversorgung z. B. mittels digitaler Kassenzettel in Kombination mit weiteren Verbraucher-Services kann die Bekanntheit und Akzeptanz von Rückverfolgbarkeitssystemen weiter gesteigert werden.
Designing consumption feedback to support sustainable behavior is an active research topic. In recent years, relevant work has suggested a variety of possible design strategies. Addressing the more recent developments in this field, this paper presents a structured literature review, providing an overview of current information design approaches and highlighting open research questions. We suggest a literature-based taxonomy of used strategies, data source and output media with a special focus on design. In particular, we analyze which visual forms are used in current research to reach the identified strategy goals. Our survey reveals that the trend is towards more complex and contextualized feedback and almost every design within sustainable HCI adopts common visualization forms. Furthermore, adopting more advanced visual forms and techniques from information visualization research is helpful when dealing with ever-increasing data sources at home. Yet so far, this combination has often been neglected in feedback design.
Improved Thermal Comfort Model Leveraging Conditional Tabular GAN Focusing on Feature Selection
(2024)
The indoor thermal comfort in both homes and workplaces significantly influences the health and productivity of inhabitants. The heating system, controlled by Artificial Intelligence (AI), can automatically calibrate the indoor thermal condition by analyzing various physiological and environmental variables. To ensure a comfortable indoor environment, smart home systems can adjust parameters related to thermal comfort based on accurate predictions of inhabitants’ preferences. Modeling personal thermal comfort preferences poses two significant challenges: the inadequacy of data and its high dimensionality. An adequate amount of data is a prerequisite for training efficient machine learning (ML) models. Additionally, high-dimensional data tends to contain multiple irrelevant and noisy features, which might hinder ML models’ performance. To address these challenges, we propose a framework for predicting personal thermal comfort preferences, combining the conditional tabular generative adversarial network (CTGAN) with multiple feature selection techniques. We first address the data inadequacy challenge by applying CTGAN to generate synthetic data samples, incorporating challenges associated with multimodal distributions and categorical features. Then, multiple feature selection techniques are employed to identify the best possible sets of features. Experimental results based on a wide range of settings on a standard dataset demonstrated state-of-the-art performance in predicting personal thermal comfort preferences. The results also indicated that ML models trained on synthetic data achieved significantly better performance than models trained on real data. Overall, our method, combining CTGAN and feature selection techniques, outperformed existing known related work in thermal comfort prediction in terms of multiple evaluation metrics, including area under the curve (AUC), Cohen’s Kappa, and accuracy. Additionally, we presented a global, model-agnostic explanation of the thermal preference prediction system, providing an avenue for thermal comfort experiment designers to consciously select the data to be collected.