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Dr. Andreas Janson

+41 71 224 2592


Digital nudging is a promising approach from behavioral economics. In deci-sions where individuals tend to struggle, nudges can support users of digital systems by aligning their behavior with their preferences. Despite their wide use, most digital nudges are designed to support the intended behavior from the perspective of a company while neglecting potential legal, ethical, or individual constraints or preferences. With modern technologies such as artificial intelli-gence or big data, these issues multiply and with the increasing effectiveness of digital nudges and use of new technologies, this has become even more critical. Thus, in this paper we follow a Design Science Research approach to develop a process model for the systematic development of legitimate nudges (DELEN). Legitimacy requires that dealings between different entities shall be fair. Unlike other models, we set normative boundaries derived from literature, expert in-terviews, and target group segmentation as integral elements. Target group seg-mentation increases nudge effectiveness and avoids unnecessary burdens for other individuals. By doing so, the DELEN process model paves the way for legitimate and effective digital nudges.

Argumentation is an omnipresent foundation of our daily communication and thinking. The ability to form convincing arguments is not only the fundament for persuading an audience of novel ideas but also plays a major role in strategic decision-making, negotiation, and productive civil discourse. However, students often struggle to develop argumentation skills due to a lack of individual and instant feedback in their learning journey, since providing feedback on the individual argumentation skills of learners is very time consuming and not scalable if conducted manually by educators. Following a design science research approach, we propose a new class of argumentation learning systems that provide students with individual and ongoing tutoring to support them in learning how to argue. We build our socio-technical design on a combination of user-centered design principles, a conceptualization of argumentation structures in student-written text, and Natural Language Processing and Machine Learning classifiers to provide individual feedback. To investigate if the new system class of AI-based argumentation tutoring systems helps students to improve their argumentation skills, we evaluated the novel artifact class in two empirical studies in comparison to traditional argumentation learning systems. In a laboratory experiment (study 1), as well as in a field experiment in a large-scale lecture over three months (study 2), we found that AI-based argumentation tutoring systems based on our design principles, argumentation schemes, and algorithms improve the short- and long-term argumentation skills of students significantly compared to the traditional argumentation learning approaches.

Gendered voice based on pitch is a prevalent design element in many contemporary Voice Assistants (VAs) but has shown to strengthen harmful stereotypes. Interestingly, there is a dearth of research that systematically analyses user perceptions of different voice genders in VAs. This study investigates gender-stereotyping across two different tasks by analyzing the influence of pitch (low, high) and gender (women, men) on stereotypical trait ascription and trust formation in an exploratory online experiment with 234 participants. Additionally, we deploy a gender-ambiguous voice to compare against gendered voices. Our findings indicate that implicit stereotyping occurs for VAs. Moreover, we can show that there are no significant differences in trust formed towards a gender-ambiguous voice versus gendered voices, which highlights their potential for commercial usage.

Several authors have illustrated the benefits of data in organizations. For realizing benefits, we see two major challenges for organizations. First, there are necessary investments, which have to be justified. Second, adequate data analytics competencies can be seen as enablers for realizing benefits. We aim to support organizations by showing relevant competencies and achievable business values. We present theoretical propositions and a research agenda on how to move the field of data analytics competencies forward.

Die Digitalisierung verändert nicht nur unser privates, sondern auch unser Arbeitsleben. Immer mehr Daten über Individuen sind online verfügbar und werden für die Nutzung von bestimmten Online Services vorausgesetzt. Hierbei verlieren die Nutzenden oft den Überblick, wie und welche Daten sie von sich preisgeben. Dies birgt nicht nur das Risiko der Preisgabe von privaten Daten, sondern auch unternehmensseitig das Risiko, dass wichtige Daten außerhalb des Unternehmens veröffentlicht werden. Hier kann das Konzept des digitalen Nudgings angewandt werden, welches nunmehr auch als edukatives Privacy Nudging genutzt werden kann. Das Konzept bezweckt, Individuen durch bestimmte Elemente wie beispielsweise Defaults zu Verhaltensänderungen anzuregen. Dieser Beitrag hat zum Ziel, einen Überblick darüber zu geben, welche Privacy Nudges es im edukativen Bereich gibt und wie diese mit verschiedenen Lerntheorien in Einklang gebracht werden können. Der Text soll Forschern und Praktikern eine Orientierung geben, selbst edukative Privacy Nudges zu gestalten und endet mit einem Fallbeispiel, das aufzeigt wie einfache Gestaltungsänderungen Individuen dazu anregen können, sich privatheitsfreundlicher zu verhalten und sorgsamer mit ihren privaten Daten umzugehen.

Künstliche Intelligenz durchdringt immer stärker verschiedene Lebensbereiche und macht auch vor der beruflichen Bildung nicht halt. In diesem Zusammenhang gibt es derzeit vielfältige Diskussionen zur Rolle der menschlichen Intelligenz in zukünftigen Arbeitsprozessen und damit verknüpft Fragen zur Auswirkung auf die Aus- und Weiterbildung von Arbeitskräften. Ziel dieses Beitrags ist es darzulegen, warum in den kommenden Jahrzehnten die effektive Kombination der komplementären Stärken von menschlicher und künstlicher Intelligenz im Sinne des Hybrid Intelligence (HI)-Gedankens im Vordergrund stehen wird. Anschließend werden Potentiale und Grenzen von HI im Kontext der beruflichen Aus- und Weiterbildung mit besonderem Fokus auf die Individualisierung von Lehr-/Lernprozessen diskutiert.

Designing novel technologies provide challenges to developers. To support developers in designing these technologies, design knowledge must be codified and made applicable for the future. In systems development, design patterns provide proven solutions to solving recurring problems. They contain templates for describing design information, often in tabular form, and are established tools for making complex knowledge accessible and applicable. Design patterns play a critical role in both practice and research in finding potential solutions. For researchers, patterns can provide a method for codifying design knowledge for future research. For practitioners, design patterns provide established solutions to recurring problems. By applying them in a particular context, the pattern represents elements of both the problem-space and the solution-space, providing an opportunity to bridge the gap between the two spaces. Due to the abstraction of design patterns, they can be used for different application scenarios. The preparation of the design knowledge in the design pattern is a critical step to support the user in the best possible way, that determines the usefulness of the pattern.

Higher legal standards with regards to data protection of individuals such as the European General Data Protection Regulation (GDPR) increase the pressure on developing lawful technologies. The development requires feedback from stakeholders such as legal experts that lack technical knowledge but are required to understand IT artifacts. As a solution, patterns can support interdisciplinary system development. We demonstrate how interdisciplinary patterns can support legal experts in arguing about technologies in court by introducing a law simulation study which is a well-known evaluation method in law. Our results show that patterns support legal experts in their argumentation about technologies in court. We provide theoretical contributions concerning cognitive fit theory about how patterns act as a bridge between the internal and external representation of problems and improve problem-solving performance related to the legal assessment of technology. In addition, we provide practical guidance for codifying and communicating design knowledge through patterns.

Based on recent advances in Artificial Intelligence (AI), chatbots are now increasingly offered as an alternative source of customer service. For their uptake user trust in critical. However, little is known about how these interfaces fundamentally influence trust perceptions. In particular, it’s unclear what exactly causes perceptual differences - the change towards a conversational interface or the usage of anthropomorphic design elements. In this study, an online experiment with 160 participants was conducted to examine the differential effects of conversational interaction and anthropomorphism on trust in the interface or the provider within the context of online loan applications. The results show that both treatment conditions affect trust in the interface and the provider by increasing perceptions of social presence. Meanwhile, trust in the interface significantly effects the intention to share information, while trust in the provider has no effect on behavioral intention.

Higher legal standards regarding the data protection of individuals, such as the European General Data Protection Regulation, increase the pressure on developing lawful systems. In the development of technologies, not only developers are involved. It also requires knowledge from other stakeholders, such as legal experts, that lack technical knowledge but are required to understand IT artifacts. We see two strings that can benefit from the use of design patterns: first, the well-known use of design patterns to support developers in case of recurring problems. Second, we see potential that legal experts, who have to interact with and understand complicated, novel technologies, benefit from the same patterns. We conduct a revelatory case study using design patterns to develop and assess a smart learning assistant. We scaffolded the case interpretation through the human-centered view of socio-materiality and provide contributions concerning the use of design patterns in the development and assessment of lawful technologies.



Academy of Management (AOM), OCIS und MED Division
Association for Information Systems (AIS)
Association for Computing Machinery – Special Interest Group Computer-Human Interaction (ACM SIGCHI)
Bundesnetzwerk Verbraucherforschung des des Bundesministerium der Justiz und für Verbraucherschutz
Verband der Hochschullehrer für Betriebswirtschaft (VHB)