Institut für Verbraucherinformatik (IVI)
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AI-powered systems pose unknown challenges for designers, policymakers, and users, making it more difficult to assess potential harms and outcomes. Although understanding risks is a requirement for building trust in technology, users are often excluded from risk assessments and explanations in policy and design. To address this issue, we conducted three workshops with 18 participants and discussed the EU AI Act, which is the European proposal for a legal framework for AI regulation. Based on results of these workshops, we propose a user-centered conceptual model with five risk dimensions (Design and Development, Operational, Distributive, Individual, and Societal) that includes 17 key risks. We further identify six criteria for categorizing use cases. Our conceptual model (1) contributes to responsible design discourses by connecting the risk assessment theories with user-centered approaches, and (2) supports designers and policymakers in more strongly considering a user perspective that complements their own expert views.
Consumers are using online reviews to decide which products to purchase. Cybercriminals produce fake reviews to influence unknowing consumers into buying products of lower quality, which can lead to financial, emotional and physical damage. We have little under-standing of how consumers make decisions about the veracity of online reviews, or incorpo-rate online reviews into purchasing decisions, especially outside of the laboratory. Therefore, in this study using a grounded theory approach we elaborate on how consumers determine the veracity and trustworthiness of online user reviews. Twenty-five interviews with Dutch and German consumers were held to identify deception cues, thought processes and other markers of online shopping behaviour. The results show that consumers use online reviews differently depending on context. Our new theory proposes that consumers process reviews in at least two steps. First, they scan the review for relevance and then they determine the trustworthiness, credibility, and veracity. Additionally, we identified different deception cues that are used. Together, these findings lead the way into a new understanding of human fake review detection online.
People must perform bureaucratic, administrative work in daily life, such as applying for official documents, concluding contracts, organizing purchases, managing pension plans, etc. This work is time-consuming and unequally distributed in the household. At its best, it is perceived as boring; at its worst, it is mentally and emotionally stressful, leaving people overwhelmed and unable to fulfill their obligations. People can benefit from the digitalization of domestic bureaucracy automating repetitive tasks, reducing mental effort, and saving time for leisure activities. In recent years, there has been a need for more empirical knowledge about the use of technology or the working environment for this purpose. This paper presents insights from an online survey with 617 socio-demographically distributed participants highlighting the devices, tools, special software, and common places people favor for accomplishing these office-like household chores. Our results provide a solid empirical basis that not only quantifies previous qualitative results now using the German adult population but also offers orientation for further in-depth research as well as design.
Effective information security policies are crucial for organisations to mitigate information security threats and risks. However, poorly designed information security policies can lead to hidden costs and decreased compliance in daily work routines. While behavioural factors like social norms, positive attitudes, and knowledge are well known to influence compliance, the usability of information security policies, which takes the context of use seriously, remains understudied,. To address this, we introduce the Information Security Policy Usability Scale (ISPUS), an adaptation of the widely recognised System Usability Scale (SUS). ISPUS assesses the usability of information security policies. Thereby, it supports both companies and works councils in ensuring the fit of the work context, individual skills, tools and the policy. By applying ergonomic principles, ISPUS aims to enhance information security policy design and support organisational security efforts.
Diese Arbeit untersucht Entwicklungspraktiken im Kontext professioneller Softwareentwicklung für Augmented und Virtual Reality (XR) Anwendungen. Die Verbindung einer Design Science Linse mit praxeologischen Ansätzen ermöglicht einen umfassenden Einblick in existierende und aufkommende Entwicklungsprozesse in der aufstrebenden XR-Softwareindustrie. Angesichts des aktuellen Mangels an Design Guidelines, Entwicklungs- und Technologiestandards sowie unterstützenden Entwicklungswerkzeugen bietet die Arbeit einen ganzheitlichen Überblick und entwickelt mögliche Lösungsansätze sowie Designvorschläge zur (softwarebasierten) Unterstützung professioneller XR-Entwickler in interdisziplinären Teams.
Merger-und-Acquisitions-Prozesse gelten als ein wesentliches Thema der strategischen Unternehmensausrichtung und haben erhebliche Auswirkungen auf die betroffenen Unternehmen. Aufgrund der gestiegenen Relevanz von kollaborativen Cloud-Services in den letzten Jahren untersucht dieser Beitrag anhand von Experteninterviews die Auswirkungen von Merger-und-Acquisition-Prozesse auf die kollaborativen Cloud-Services. Im Rahmen dieses Beitrags wird eine Übersicht über die Hintergründe zu Mergers und Acquisitions, kollaborativen Cloud-Services sowie der Herausforderungen bei der Integration gegeben. Die Ergebnisse zeigen praxisnah, welche Auswirkungen ein Merger-und-Acquisition-Prozess auf kollaborative Cloud-Services hat. Dabei werden insbesondere das Vorgehen, die Migration sowie Benutzer und Stakeholder betrachtet.
Das Feld des Verbraucherschutzes unterliegt einem permanenten Wandel. Hatten sich in der Vergangenheit im Bereich der Rechts- oder der Ernährungswissenschaften Ausbildungsgänge oder Spezialisierungsmöglichkeiten für dieses komplexe Berufsfeld entwickelt, so stehen die Akteure angesichts der beschleunigten Marktveränderungen doch immer wieder vor neuen Herausforderungen, die etwa heute auch Kompetenzanforderungen im Bereich des Hackens oder der Algorithmenkontrolle umfassen. Vor diesem Hintergrund gilt es über Verbraucherschutz als Beruf und Berufung genauer nachzudenken und insbesondere die Grenzen und Möglichkeiten der Professionalisierung in diesem Feld zu reflektieren.
Die Reihe "Jahrbuch Konsum & Verbraucherwissenschaften" präsentiert neben einem Schwerpunktthema neue Erkenntnisse aus Forschung und Praxis. Erstmals werden im diesem Jahrbuch die Beiträge der Preisträger der "Förderpreise Konsum & Verbraucherwissenschaften" präsentiert.
Das Feld des Verbraucherschutzes unterliegt einem permanenten Wandel. Hatten sich in der Vergangenheit im Bereich der Rechts- oder der Ernährungswissenschaften Ausbildungsgänge oder Spezialisierungsmöglichkeiten für dieses komplexe Berufsfeld entwickelt, so stehen die Akteure angesichts der beschleunigten Marktveränderungen doch immer wieder vor neuen Herausforderungen, die etwa heute auch Kompetenzanforderungen im Bereich des Hackens oder der Algorithmenkontrolle umfassen. Vor diesem Hintergrund gilt es über Verbraucherschutz als Beruf und Berufung genauer nachzudenken und insbesondere die Grenzen und Möglichkeiten der Professionalisierung in diesem Feld zu reflektieren.
This research paper investigates the temporal and mental workload as well as work satisfaction regarding bureaucratic, administrative household labor, with a focus on socio-demographic differences. The study utilizes a paid online survey with 617 socio-demographically distributed participants. The results show significant differences in the temporal workload of different chore categories and in the quality of work, whereby satisfaction and mental workload are examined. In addition, the influences of gender, age, and education are analyzed, revealing differences in temporal and mental workload as well as work satisfaction. Our findings confirm prevailing literature showing that women have lower work satisfaction and a higher workload. In addition, we also discovered that younger people and groups of people with higher incomes have a higher level of satisfaction and a higher workload. In our study, a perceived high mental workload does not necessarily go hand in hand with a low level of satisfaction. This study contributes to the understanding of the bureaucratic burden on adults in their households and the variety of activities to manage private life.
Enlarged Education – Exploring the Use of Generative AI to Support Lecturing in Higher Education
(2024)
The rapid progress in sensor technology has empowered smart home systems to efficiently monitor and control household appliances. AI-enabled smart home systems can forecast household future energy demand so that the occupants can revise their energy consumption plan and be aware of optimal energy consumption practices. However, deep learning (DL)-based demand forecasting models are complex and decisions from such black-box models are often considered opaque. Recently, eXplainable Artificial Intelligence (XAI) has garnered substantial attention in explaining decisions of complex DL models. The primary objective is to enhance the acceptance, trust, and transparency of AI models by offering explanations about provided decisions. We propose ForecastExplainer, an explainable deep energy demand forecasting framework that leverages Deep Learning Important Features (DeepLIFT) to approximate Shapley values to map the contribution of different appliances and features with time. The generated explanations can shed light to explain the prediction highlighting the impact of energy consumption attributes corresponding to time, such as responsible appliances, consumption by household areas and activities, and seasonal effects. Experiments on household datasets demonstrated the effectiveness of our method in accurate forecasting. We designed a new metric to evaluate the effectiveness of the generated explanations and the experiment results indicate the comprehensibility of the explanations. These insights might empower users to optimize energy consumption practices, fostering AI adoption in smart applications.
As voice assistants (VAs) become more advanced leveraging Large Language Models (LLMs) and natural language processing, their potential for accountable behavior expands. Yet, the long-term situational effectiveness of VAs’ accounts when errors occur remains unclear. In our 19-month exploratory study with 19 households, we investigated the impact of an Alexa feature that allows users to inquire about the reasons behind its actions. Our findings indicate that Alexa's accounts are often single, decontextualized responses that led to users’ alternative repair strategies over the long term, such as turning off the device, rather than initiating a dialogue about what went wrong. Through role-playing workshops, we demonstrate that VA interactions should facilitate explanatory dialogues as dynamic exchanges that consider a range of speech acts, recognizing users’ emotional states and the context of interaction. We conclude by discussing the implications of our findings for the design of accountable VAs.
Explaining AI Decisions: Towards Achieving Human-Centered Explainability in Smart Home Environments
(2024)
The air quality in many German cities does not comply with EU-wide standards. Vehicle emissions, in particular, have been identified as an important cause of air pollution. As a result, driving bans for diesel vehicles with critical pollutant groups have been imposed by courts in many places in recent history. Against the backdrop of the growth of major German cities over the last few years, the question has become whether and how a change in the modal split in favor of more environmentally and climate-friendly public transport sector can be achieved. The Federal City of Bonn is one of five model cities that is testing measures to reduce traffic-related nitrogen dioxide emissions through a Climate Ticket as a mobility flat rate for one year for 365 €, which is part of the two-year "Lead City" project funded by the federal government. A quantitative survey (n = 1,315) of Climate Ticket users as well as the logistic regression carried out confirm that a change in individual mobility behavior in favor of public transport is possible by subsidizing the ticket price. The results show that individual traffic could be saved on the city's main congestion axes. In order to achieve a sustainable improvement in air quality, such a Climate Ticket must be granted on a permanent basis, with a well-designed mobility offer and must be generous in terms of the group of authorized persons and the area of validity.
Verbraucherinformatik
(2024)
In einer Zeit, in der digitale Technologien nahezu jeden Aspekt unseres Lebens durchdringen, ist es unerlässlich, die tieferen Zusammenhänge des digitalen Konsums zu verstehen. Erstmalig bietet dieses open access-Lehrbuch einen Wegweiser durch die vielfältigen Facetten der Digitalisierung des Konsums. Dabei verbindet es die Disziplinen der angewandten Informatik und Verbraucherwissenschaften.
Die Leserinnen und Leser erhalten Einblick in die digitale Konsumlandschaft, ausgehend von der historischen Entwicklung des (digitalen) Konsums. Dazu vermittelt das Lehrbuch zentrale Grundbegriffe und Themen der Verbraucherinformatik und stellt verschiedene Konsumtheorien aus den Disziplinen Wirtschaftswissenschaften, Psychologie und Sozialwissenschaften vor. Praxisnahe Beispiele aus der Digitalisierung bieten Einsichten in unterschiedliche Perspektiven, während vertiefende Textboxen und Selbstreflexionsfragen das Verständnis fördern.
Inhaltlich decken die Autorinnen und Autoren Themen von Datenschutz bis zur Sharing Economy ab und geben insbesondere auch praktische Ansätze für Themen wie Verbraucherschutz und Nachhaltigkeit mit auf den Weg. Die Anwendungs- und Querschnittsthemen der Verbraucherinformatik reichen von der Digitalisierung der Haushalte und Märkte über Fragen des digitalen Verbraucherschutzes bis hin zu zentralen gesellschaftlichen Fragestellungen rund um die Themen Fairness, Verantwortung und Nachhaltigkeit bei der Gestaltung von digitalen Technologien.
Das Buch bietet einen umfassenden Überblick, der sowohl für Studierende der Wirtschafts- und Sozialwissenschaften als auch der angewandten Informatik von bedeutendem Wert ist.
Einordnung und Hintergrund
(2024)
Digitale Produkte und Dienstleistungen sind integraler Bestandteil des Alltags. Mobile Geräte sind in jedem Bereich präsent, vom Finanzmanagement bis zur Gesundheitsversorgung. Die Art des Konsums hat sich mit der Digitalisierung des Alltags der Verbraucher:innen grundlegend gewandelt, was neben Fragen nach Geschäftsmodellen auch solche nach Verbraucherschutz und Nachhaltigkeit aufwirft. Die Verbraucherinformatik untersucht diese Entwicklungen und ihre Auswirkungen auf Gesellschaft und Individuen. Dieses Kapitel gibt eine Einführung in die Disziplin und skizziert die Entwicklung des digitalen Konsums sowie die damit verbundenen Veränderungen für die Verbraucher:innen von der Verbreitung der ersten Heimcomputer bis heute. Zudem stellt es zentrale Grundbegriffe vor und gibt einen Überblick über das didaktische Konzept sowie die Inhalte der weiteren Kapitel des Lehrbuchs.
In diesem Kapitel werden wichtige theoretische Konsumtheorien und ihr Bezug zur Verbraucherinformatik besprochen. Hierzu gehören Markttheorien, die die Verbraucher:in als rationalen Marktakteur verstehen, und psychologische Ansätze, die das individuelle Konsumverhalten auf Basis von Bedürfnissen, Kognition und Emotionen zu erklären versuchen. Darüber hinaus werden gesellschafts- und kulturwissenschaftliche Ansätze vorgestellt, welche die gesellschaftliche Prägung und symbolische Bedeutung des Konsums betonen. Ein Fokus liegt dabei auf praxistheoretischen Ansätzen, die vor allem die materielle Ebene, die performative Ausgestaltung und die Routinehaftigkeit von Konsum in den Blick nehmen. Ziel des Kapitels ist es, die verschiedenen Ansätze mit ihren jeweiligen Stärken und Schwächen vorzustellen und Leser:innen Orientierungswissen mit an die Hand zu geben, welche theoretische Linse für welche Fragestellung geeignet ist, da die Wahl eines bestimmten Ansatzes von der konkreten Forschungsfrage abhängt.
Digitaler Haushalt und Markt
(2024)
In diesem Kapitel werden die Perspektive des Privathaushalts und die Perspektive des Marktes erörtert. Ein:e Verbraucher:in, welche:r innerhalb eines Haushalts zur Bedürfnisbefriedigung wirtschaftet, erledigt dabei Hausarbeit durch Kochen, Putzen, Waschen, tätigt den Abschluss von Verträgen, die Pflege von Einkaufslisten oder eine Finanzplanung. Dabei haben Verbraucher:innen unterschiedliche Praktiken und Bewältigungsstrategien entwickelt, die es in der Verbraucherinformatik zu analysieren gilt. Physische Hausarbeit wird bereits im Smart-Home-Kontext durch intelligente Maschinen (oft Roboter genannt) ausgelagert. Kognitive Hausarbeit im alltäglichen Handeln (bspw. bei Verträgen) kann und wird in Zukunft durch Software wie auch Intermediäre unterstützt werden. Digitale Märkte stellen eine häufige Form der Intermediation dar, die Besonderheiten und Effekten unterliegt, welche das Verbraucherverhalten beeinflussen können. So gewinnen zum Beispiel einige wenige Anbieter mithilfe von Netzwerkeffekten, Skaleneffekten und Lock-in-Effekten zunehmend an Marktdominanz und verdrängen kleinere Anbieter, was zu Quasimonopolen führen kann. Digitale Märkte zeichnen sich zudem durch ihre Vertrauensfunktion in der Internet-Ökonomie aus.
Digitaler Verbraucherschutz
(2024)
Verbraucher:innen hinterlassen Spuren in nahezu allen Bereichen und Lebensräumen. Besonders der stetig wachsende digitale Lebensraum ist voll von Informationen und Daten. Durch die Allgegenwärtigkeit datensammelnder Dienste und Geräte wie das Smartphone durchdringen diese immer tiefer auch die analogen Bereiche des Lebens. In diesem Kapitel geht es um Privatsphäre, Verbraucherdaten und die resultierende Cyberkriminalität. Es werden Wege aufgezeigt, wie Verbraucher:innen sensibilisiert und befähigt werden können, um sich selbst, ihre Privatsphäre und ihre Daten zu schützen. Außerdem geben wir einen Überblick, welche Arten von Cyberkriminalität es gibt und was darunter verstanden wird. Hierbei wird auf Verbraucherschutz, Privatsphäre und die verschiedenen Arten des Onlinebetrugs eingegangen. Wir bieten einen Einblick in die „digitale Resilienz“ von Verbraucher:innen und erfassen die verschiedenen Präventions- und Bewältigungsstrategien, die Opfer anwenden.
Digitale Verantwortung
(2024)
Die Verbreitung digitaler Systeme beeinflusst Entscheidungen, Gesetze, Verhalten und Werte in unserer Gesellschaft. Dies wirkt sich auf Konsumgewohnheiten, Marktbeziehungen, Machtverteilung, Privatsphäre und IT-Sicherheit aus. Damit einhergehende Veränderungen haben direkte Auswirkungen auf unser Leben, was im Bereich der Technikfolgenabschätzung bzw. der angewandten Informatik unter dem Stichwort ELSI diskutiert wird. Dieses Kapitel fokussiert auf entsprechende Fragestellungen bezüglich ethischer Auswirkungen. Insbesondere rückt Fairness im Kontext automatisierter Entscheidungen in den Fokus, da Verbraucher:innen diesen zunehmend ausgesetzt sind. Zudem wird im Rahmen der gestiegenen Besorgnis über ökologische Auswirkungen das Thema Nachhaltigkeit am Beispiel von „Sharing Economy“ und „Shared Mobility“ weiter vertieft.
Digitale Gestaltung
(2024)
Die digitale Gestaltung in der Verbraucherinformatik stellt den Menschen und seine Konsumpraktiken in den Gestaltungsmittelpunkt. Dieses Kapitel erläutert gängige Designansätze und -vorgehen in der Software-Artefaktgestaltung und diskutiert die nutzer:innenzentrierten Kriterien und Ziele, die durch die Gebrauchstauglichkeit (Usability) und das Nutzungserlebnis (UX) maßgeblich bestimmt werden. Mit Rückbezug auf soziale Praktiken werden diese und die gesellschaftliche Partizipation im Allgemeinen als Designmaterial vorgestellt. Abschließend werden in zwei Design Case Studies explorative Designansätze zur Gestaltung neuer Technologien exemplarisch erläutert und diskutiert.
Dark Patterns are deceptive designs that influence a user's interactions with an interface to benefit someone other than the user. Prior work has identified dark patterns in WIMP interfaces and ubicomp environments, but how dark patterns can manifest in Augmented and Virtual Reality (collectively XR) requires more attention. We therefore conducted ten co-design workshops with 20 experts in XR and deceptive design. Our participants co-designed 42 scenarios containing dark patterns, based on application archetypes presented in recent HCI/XR literature. In the co-designed scenarios, we identified ten novel dark patterns in addition to 39 existing ones, as well as ten examples in which specific characteristics associated with XR potentially amplified the effect dark patterns could have on users. Based on our findings and prior work, we present a classification of XR-specific properties that facilitate dark patterns: perception, spatiality, physical/virtual barriers, and XR device sensing. We also present the experts’ assessments of the likelihood and severity of the co-designed scenarios and highlight key aspects they considered for this evaluation, for example, technological feasibility, ease of upscaling and distributing malicious implementations, and the application's context of use. Finally, we discuss means to mitigate XR dark patterns and support regulatory bodies to reduce potential harms.
The digitization of financial activities in consumers' lives is increasing, and the digitalization of invoicing processes is expected to play a significant role, although this area is not well understood regarding the private sector. Human-Computer Interaction (HCI) and Computer Supported Cooperative Work (CSCW) research have a long history of analyzing the socio-material and temporal aspects of work practices that are relevant for the domestic domain. The socio-material structuring of invoicing work and the working styles of consumers must be considered when designing effective consumer support systems. In this ethnomethodologically-informed, design-oriented interview study, we followed 17 consumers in their daily practices of dealing with invoices to make the invisible administrative work involved in this process visible. We identified and described the meaningful artifacts that were used in a spatial-temporal process within various storage locations such as input, reminding, intermediate (for postponing cases) buffers, and archive systems. Furthermore, we identified three different working styles that consumers exhibited: direct completion, at the next opportunity, and postpone as far as possible. This study contributes to our understanding of household economics and domestic workplace studies in the tradition of CSCW and has implications for the design of electronic invoicing systems.
In recent years, eXtended Reality (XR) technology like Augmented Reality and Virtual Reality became both technically feasible as well as affordable which lead to a drastic demand of professionally designed and developed applications. However, this demand combined with a rapid pace of innovation revealed a lack of design tool support for professional interaction designers as well as a knowledge gap regarding their approaches and needs. To address this gap, this thesis engages with the work of professional XR interaction designers in a qualitative research into XR interaction design approach. Therefore, this thesis applies two complementary lenses stemming from scientific design and social practice theory discourses to observe, describe, analyze, and understand professional XR interaction designers' challenges and approaches with a focus on application prototyping.
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.
Vehicle emissions have been identified as a cause of air pollution and one of the major reasons why air quality in many large German cities such as Berlin, Bonn, Hamburg, Cologne or Munich does not meet EU-wide limits. As a result, in the recent past, judicial driving bans on diesel vehicles have been imposed in many places since those vehicles emit critical pollutant groups. For the increasing urban population, the challenge is whether and how a change of the modal split in favor of the more environmentally and climate-friendly public transport can be achieved.
This paper presents the case of the Federal City of Bonn, one of five model cities sponsored by the German federal government that are testing measures to reduce traffic-related pollutant emissions by expanding the range of public transport services on offer. We present the results of a quantitative survey (N = 14,296) performed in the Bonn/Rhein-Sieg area and the neighboring municipalities as well as the ensuing logistic regressions confirming that a change in individual mobility behavior in favor of public transport is possible through expanding services. Our results show that individual traffic could be reduced, especially on the city's main traffic axes. To sustainably improve air quality, such services must be made permanently available.
Smart heating systems are one of the core components of smart homes. A large portion of domestic energy consumption is derived from HVAC (heating, ventilation and air conditioning) systems, making them a relevant topic of the efforts to support an energy transition in private housing. For that reason, the technology has attracted attention both from the academic and the industry communities. User interfaces of smart heating systems have evolved from simple adjusting knobs to advanced data visualization interfaces, that allow for more advanced setting such as time tables and status information. With the advent of AI, we are interested in exploring how the interfaces will be evolving to build the connection between user needs and underlying AI system. Hence, this paper is targeted to provide early design implications towards an AI-based user interface for smart heating systems.
AI systems pose unknown challenges for designers, policymakers, and users which aggravates the assessment of potential harms and outcomes. Although understanding risks is a requirement for building trust in technology, users are often excluded from legal assessments and explanations of AI hazards. To address this issue we conducted three focus groups with 18 participants in total and discussed the European proposal for a legal framework for AI. Based on this, we aim to build a (conceptual) model that guides policymakers, designers, and researchers in understanding users’ risk perception of AI systems. In this paper, we provide selected examples based on our preliminary results. Moreover, we argue for the benefits of such a perspective.
When dialogues with voice assistants (VAs) fall apart, users often become confused or even frustrated. To address these issues and related privacy concerns, Amazon recently introduced a feature allowing Alexa users to inquire about why it behaved in a certain way. But how do users perceive this new feature? In this paper, we present preliminary results from research conducted as part of a three-year project involving 33 German households. This project utilized interviews, fieldwork, and co-design workshops to identify common unexpected behaviors of VAs, as well as users’ needs and expectations for explanations. Our findings show that, contrary to its intended purpose, the new feature actually exacerbates user confusion and frustration instead of clarifying Alexa's behavior. We argue that such voice interactions should be characterized as explanatory dialogs that account for VA’s unexpected behavior by providing interpretable information and prompting users to take action to improve their current and future interactions.
Konsument:innen scheint die Lust vergangen zu sein, individuellen Kleidungsstil auszudrücken, da der Onlinehandel zur Steigerung von Auswahlmöglichkeiten geführt hat. Dies mündet unter anderem in der Nutzung virtueller Stilberatungen. Diese Dienste dienen dazu, Kund:innen möglichst effizient, individuell und authentisch „zu machen“, und sind somit als paradoxaler Demokratisierungsprozess zu verstehen. Eine Erklärung für den Erfolg dieser Dienstleistungen soll mit Reckwitz’ Singularisierungsthese gestützt werden.
Trust-Building in Peer-to-Peer Carsharing: Design Case Study for Algorithm-Based Reputation Systems
(2024)
Peer-to-peer sharing platforms become increasingly important in the platform economy. From an HCI-perspective, this development is of high interest, as those platforms mediate between different users. Such mediation entails dealing with various social issues, e.g., building trust between peers online without any physical presence. Peer ratings have proven to be an important mechanism in this regard. At the same time, scoring via car telematics become more common for risk assessment by car insurances. Since user ratings face crucial problems such as fake or biased ratings, we conducted a design case study to determine whether algorithm-based scoring has the potential to improve trust-building in P2P-carsharing. We started with 16 problem-centered interviews to examine how people understand algorithm-based scoring, we co-designed an app with scored profiles, and finally evaluated it with 12 participants. Our findings show that scoring systems can support trust-building in P2P-carsharing and give insights how they should be designed.
There has been a growing interest in taste research in the HCI and CSCW communities. However, the focus is more on stimulating the senses, while the socio-cultural aspects have received less attention. However, individual taste perception is mediated through social interaction and collective negotiation and is not only dependent on physical stimulation. Therefore, we study the digital mediation of taste by drawing on ethnographic research of four online wine tastings and one self-organized event. Hence, we investigated the materials, associated meanings, competences, procedures, and engagements that shaped the performative character of tasting practices. We illustrate how the tastings are built around the taste-making process and how online contexts differ in providing a more diverse and distributed environment. We then explore the implications of our findings for the further mediation of taste as a social and democratized phenomenon through online interaction.
Background
Consumers rely heavily on online user reviews when shopping online and cybercriminals produce fake reviews to manipulate consumer opinion. Much prior research focuses on the automated detection of these fake reviews, which are far from perfect. Therefore, consumers must be able to detect fake reviews on their own. In this study we survey the research examining how consumers detect fake reviews online.
Methods
We conducted a systematic literature review over the research on fake review detection from the consumer-perspective. We included academic literature giving new empirical data. We provide a narrative synthesis comparing the theories, methods and outcomes used across studies to identify how consumers detect fake reviews online.
Results
We found only 15 articles that met our inclusion criteria. We classify the most often used cues identified into five categories which were (1) review characteristics (2) textual characteristics (3) reviewer characteristics (4) seller characteristics and (5) characteristics of the platform where the review is displayed.
Discussion
We find that theory is applied inconsistently across studies and that cues to deception are often identified in isolation without any unifying theoretical framework. Consequently, we discuss how such a theoretical framework could be developed.
Western consumption patterns are strongly associated with environmental pollution and climate change, which challenges us with transforming our society and consumption towards a sustainable future. This thesis takes up this challenge and aims to contribute to this debate at the intersection of ICT artifacts and social practices through the examples of food and mobility consumption. The social practice lens is employed as an alternative to the predominant persuasive or motivational lens of design in the respective consumption domains. Against this background, this thesis first presents three research papers that contribute to a broader understanding of dynamic practices and their transformation towards a sustainable stable state. The following research takes up these sections' empirical results that more intensely focus on the appropriation of materials and infrastructures utilizing Recommender Systems. Given this approach, this thesis contributes to three fields - practice-based Computing, Recommender Systems, and Consumer Informatics.
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.
