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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.
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?
Aim of this study is to investigate the effects of user experience (UX) on shopping mall customers’ intention to use a social robot. Therefore, we used a Wizard of Oz approach that enabled data collection in situ. Quantitative data was obtained from a questionnaire completed by shopping mall customers who interacted with a social robot. Data was used in a regression analysis, where user experience factors served as predictors for robot use in retail. The regression model explains up to 23.2% of the variance in customers’ intention to use a social robot. In addition, we collected qualitative data on human-robot-interactions and used the data to complement the interpretation of statistical results. Our findings suggest that only hedonic qualities significantly contribute to the prediction of customers’ intention, that shopping mall customers are reluctant to grant pragmatic qualities to social robots, and that UX evaluation in HRI requires additional predictors.
New cars are increasingly "connected" by default. Since not having a car is not an option for many people, understanding the privacy implications of driving connected cars and using their data-based services is an even more pressing issue than for expendable consumer products. While risk-based approaches to privacy are well established in law, they have only begun to gain traction in HCI. These approaches are understood not only to increase acceptance but also to help consumers make choices that meet their needs. To the best of our knowledge, perceived risks in the context of connected cars have not been studied before. To address this gap, our study reports on the analysis of a survey with 18 open-ended questions distributed to 1,000 households in a medium-sized German city. Our findings provide qualitative insights into existing attitudes and use cases of connected car features and, most importantly, a list of perceived risks themselves. Taking the perspective of consumers, we argue that these can help inform consumers about data use in connected cars in a user-friendly way. Finally, we show how these risks fit into and extend existing risk taxonomies from other contexts with a stronger social perspective on risks of data use.
Since stationary self-checkout is widely introduced and well understood, previous research barely examined newer generations of smartphone-based Scan&Go. Especially from a design perspective, we know little about the factors contributing to the adoption of Scan&Go solutions and how design enables consumers to take full advantage of this development rather than being burdened with using complex and unenjoyable systems. To understand the influencing factors and the design from a consumer perspective, we conducted a mixed-methods study where we triangulated data of an online survey with 103 participants and a qualitative study with 20 participants. Based on the results, our study presents a refined and nuanced understanding of technology as well as infrastructure-related factors that influence adoption. Moreover, we present several implications for designing and implementing of Scan&Go in retail environments.
In the course of growing online retailing, recommendation systems have become established that derive recommendations from customers’ purchase histories. Recommending suitable food products can represent a lucrative added value for food retailers, but at the same time challenges them to make good predictions for repeated food purchases. Repeat purchase recommendations have been little explored in the literature. These predict when a product will be purchased again by a customer. This is especially important for food recommendations, since it is not the frequency of the same item in the shopping basket that is relevant for determining repeat purchase intervals, but rather their difference over time. In this paper, in addition to critically reflecting classical recommendation systems on the underlying repeat purchase context, two models for online product recommendations are derived from the literature, validated and discussed for the food context using real transaction data of a German stationary food retailer.
Frequently the main purpose of domestic artifacts equipped with smart sensors is to hide technology, like previous examples of a Smart Mirror show. However, current Smart Homes often fail to provide meaningful IoT applications for all residents’ needs. To design beyond efficiency and productivity, we propose to realize the potential of the traditional artifact for calm and engaging experiences. Therefore, we followed a design case study approach with 22 participants in total. After an initial focus group, we conducted a diary study to examine home routines and developed a conceptual design. The evaluation of our mid-fidelity prototype shows, that we need to study carefully the practices of the residents to leverage the physical material of the artifact to fit the routines. Our Smart Mirror, enhanced by digital qualities, supports meaningful activities and makes the bathroom more appealing. Thereby, we discuss domestic technology design beyond automation.
An der Hochschule Bonn-Rhein-Sieg fand am Donnerstag, den 23.9.21 das erste Verbraucherforum für Verbraucherinformatik statt. Im Rahmen der Online-Tagesveranstaltung diskutierten mehr als 30 Teilnehmer:innen über Themen und Ideen rund um den Bereich Verbraucherdatenschutz. Dabei kamen sowohl Beiträge aus der Informatik, den Verbraucher- und Sozialwissenschaften sowie auch der regulatorischen Perspektive zur Sprache. Der folgende Beitrag stellt den Hintergrund der Veranstaltung dar und berichtet über Inhalte der Vorträge sowie Anknüpfungspunkte für die weitere Konstituierung der Verbraucherinformatik. Veranstalter waren das Institut für Verbraucherinformatik an der H-BRS in Zusammenarbeit mit dem Lehrstuhl IT-Sicherheit der Universität Siegen sowie dem Kompetenzzentrum Verbraucherforschung NRW der Verbraucherzentrale NRW e. V. mit Förderung des Bundesministeriums der Justiz und für Verbraucherschutz.
Advocates of autonomous driving predict that the occupation of taxi driver could be made obsolete by shared autonomous vehicles (SAV) in the long term. Conducting interviews with German taxi drivers, we investigate how they perceive the changes caused by advancing automation for the future of their business. Our study contributes insights into how the work of taxi drivers could change given the advent of autonomous driving: While the task of driving could be taken over by SAVs for standard trips, taxi drivers are certain that other areas of their work such as providing supplementary services and assistance to passengers would constitute a limit to such forms of automation, but probably involving a shifting role for the taxi drivers, one which focuses on the sociality of the work. Our findings illustrate how taxi drivers see the future of their work, suggesting design implications for tools that take various forms of assistance into account, and demonstrating how important it is to consider taxi drivers in the co-design of future taxis and SAV services.
With the debates on climate change and sustainability, a reduction of the share of cars in the modal split has become increasingly prevalent in both public and academic discourse. Besides some motivational approaches, there is a lack of ICT artifacts that successfully raise the ability of consumers to adopt sustainable mobility patterns. To further understand the requirements and the design of these artifacts within everyday mobility adopted a practice-lens. This lens is helpful to get a broader perspective on the use of ICT artifacts along consumers’ transformational journey towards sustainable mobility practices. Based on 12 retrospective interviews with car-free mobility consumers, we argue that artifacts should not be viewed as ’magic-bullet’ solutions but should accompany the complex transformation of practices in multifaceted ways. Moreover, we highlight in particular the difficulties of appropriating shared infrastructures and aligning own practices with them. This opens up a design space to provide more support for these kinds of material-interactions, to provide access to consumption infrastructures and make them usable, rather than leaving consumers alone with increased motivation.
Recent publications propose concepts of systems that integrate the various services and data sources of everyday food practices. However, this research does not go beyond the conceptualization of such systems. Therefore, there is a deficit in understanding how to combine different services and data sources and which design challenges arise from building integrated Household Information Systems. In this paper, we probed the design of an Integrated Household Information System with 13 participants. The results point towards more personalization, automatization of storage administration and enabling flexible artifact ecologies. Our paper contributes to understanding the design and usage of Integrated Household Information Systems, as a new class of information systems for HCI research.
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.
Diese Studie untersucht die Aneignung und Nutzung von Sprachassistenten wie Google Assistant oder Amazon Alexa in Privathaushalten. Unsere Forschung basiert auf zehn Tiefeninterviews mit Nutzern von Sprachassistenten sowie der Evaluation bestimmter Interaktionen in der Interaktionshistorie. Unsere Ergebnisse illustrieren, zu welchen Anlässen Sprachassistenten im heimischen Umfeld genutzt werden, welche Strategien sich die Nutzer in der Interaktion mit Sprachassistenten angeeignet haben, wie die Interaktion abläuft und welche Schwierigkeiten sich bei der Einrichtung und Nutzung des Sprachassistenten ergeben haben. Ein besonderer Fokus der Studie liegt auf Fehlinteraktionen, also Situationen, in denen die Interaktion scheitert oder zu scheitern droht. Unsere Studie zeigt, dass das Nutzungspotenzial der Assistenten häufig nicht ausgeschöpft wird, da die Interaktion in komplexeren Anwendungsfällen häufig misslingt. Die Nutzer verwenden daher den Sprachassistenten eher in einfachen Anwendungsfällen und neue Apps und Anwendungsfälle werden gar nicht erst ausprobiert. Eine Analyse der Aneignungsstrategien, beispielsweise durch eine selbst erstellte Liste mit Befehlen, liefert Erkenntnisse für die Gestaltung von Unterstützungswerkzeugen sowie die Weiterentwicklung und Optimierung von sprachbasierten Mensch-Maschine-Interfaces.
Die Bundesrepublik Deutschland erlebt in jüngster Vergangenheit verstärkt Dieselfahrverbote in Großstädten. Gleichzeitig erfahren Großstädte als Lebensmittelpunkt eine steigende Beliebtheit. Für Verkehrsunternehmen gilt es, der Bevölkerung nachhaltige Mobilitätslösungen zu bieten, die ein Höchstmaß an Flexibilität ermöglichen. Moderne Mobility-as-a-Service-Konzepte und Innovationen in der Mobilität stellen den klassischen, planorientierten, öffentlichen Personennahverkehr und damit auch die Existenz von Bushaltestellen infrage. Mittels qualitativer Experten-Interviews lässt sich feststellen, dass sich die Bushaltestelle in den Innenstädten vor dem Hintergrund zunehmender digitaler Vernetzung von Mobilitätsanbietern und daraus resultierender modernen Mobility-as-a-service-Konzepte verändern wird. Die Ergebnisse deuten darauf hin, dass die Bushaltestelle in den Innenstädten auch in Zukunft bestehen bleibt und um „on demand“-Verkehre ergänzt wird. Ein radikaler Wandel, wie eine flächendeckende Einführung von autonom fahrenden Bussen, könnte langfristig eine Runderneuerung der Haltestelle zur Folge haben.
Bei genauer Betrachtung heutiger Sharing Plattformen wie AirBnB, Uber, Drivy oder Fairleihen fällt auf, dass diese eines gemein haben. Als Plattformökonomien basieren sie auf mindestens zwei Nutzergruppen, Anbietern und Nachfragern für Güter oder Dienstleistungen. Ein Problem solcher zweioder mehrseitigen Märkte ist jedoch häufig, dass der Wertezuwachs, der durch die Nutzer generiert wird, nicht gleichmäßig unter der Plattform und den aktiven Nutzern verteilt wird, sondern meist ausschließlich als Gewinn an die Plattformen geht. Mit der Blockchain-Technologie könnte dieses Problem gelöst werden, indem der Informations- und Wertetransfer sicher und dezentral organisiert wird und viele Funktionen traditioneller Intermediäre dadurch obsolet werden. Diese Arbeit bietet einen Überblick über Anwendungsfelder und das Grundkonzept der Sharing Economy. Wir zeigen auf, wie sich Geschäftsmodelle und Infrastrukturen in einer Blockchain abbilden lassen, welche Potentiale eine Blockchain-basierte Infrastruktur bietet, wann diese in der Sharing Economy sinnvoll sein kann und welche Probleme dadurch gelöst werden können.
Die nutzerInnenfreundliche Formulierung von Zwecken der Datenverarbeitung von Sprachassistenten
(2020)
2019 wurde bekannt, dass mehrere Anbieter von Sprachassistenten Sprachaufnahmen ihrer NutzerInnen systematisch ausgewertet haben. Da in den Datenschutzhinweisen angegeben war, dass Daten auch zur Verbesserung des Dienstes genutzt würden, war diese Nutzung legal. Für die NutzerInnen stellte diese Auswertung jedoch einen deutlichen Bruch mit ihren Privatheitsvorstellungen dar. Das Zweckbindungsprinzip der DSGVO mit seiner Komponente der Zweckspezifizierung fordert neben Flexibilität für den Verarbeiter auch Transparenz für den Verbraucher. Vor dem Hintergrund dieses Interessenkonflikts stellt sich für die HCI die Frage, wie Verarbeitungszwecke von Sprachassistenten gestaltet sein sollten, um beide Anforderungen zu erfüllen. Für die Erhebung einer Nutzerperspektive analysiert diese Studie zunächst Zweckangaben in den Datenschutzhinweisen der dominierenden Sprachassistenten. Darauf aufbauend präsentieren wir Ergebnisse von Fokusgruppen, die sich mit der wahrgenommenen Verarbeitung von Daten von Sprachassistenten aus Nutzersicht befassen. Es zeigt sich, dass bestehende Zweckformulierungen für VerbraucherInnen kaum Transparenz über Folgen der Datenverarbeitung bieten und keine einschränkende Wirkung im Hinblick auf legale Datennutzung erzielen. Unsere Ergebnisse über von Nutzern wahrgenommene Risiken erlauben dabei Rückschlüsse auf die anwenderfreundliche Gestaltung von Verarbeitungszwecken im Sinne einer Design-Ressource.