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Dr. Mahei Li

Assoziierter Mitarbeiter
Müller-Friedbergstrasse 8
9000 St. Gallen
+41 71 224 3800


The COVID-19 pandemic has brought about major changes in digitization in many areas of life and professions. New areas were digitized almost overnight, the school system in Germany was no exception leading to a demand for videoconferencing tools and communication platforms. These technologies have many different functionalities that need to be discovered, explored, and exploited by the user. Given the disruptive events that the COVID pandemic brought to us, this paper aims to shed light on how the dynamics of discovery, exploration, and exploitation unfolds. We use a functional affordance theory perspective to analyze and understand how user learn to use new technologies. To do this, we conducted an exploratory case-study-based research design including interviews with teachers from various schools to analyze how they appropriate new technologies to develop an explanatory theoretical model.

Recently, businesses are introducing low-code development platforms (LCDP) that enable employees with little to no development expertise to develop their own systems to improve their work. These so-called business unit developers (BUDs) possess necessary domain knowledge to understand how to use LCDPs to create useful (self-) services. Using job resource demand theory and the job crafting model, we conceptualize that BUDs use of LCDPs can be framed using the theoretical lens of job crafting. Job crafting stems from vocational psychology and provides well-researched positive consequences, such as wellbeing and meaningfulness. Thus, our research objective is to understand how BUDs can use LCDPs to job craft to gain access to positive job crafting consequences. We interviewed 17 experts across three organizations that employ an LDCP for chatbots. Our results suggest that job crafting is a suitable framework for understanding the effects of LCDP use.

Novel technologies such as smart personal assistants integrate digital services into everyday life. These services use personal data to offer personalized services. While they are subject to special data protection regulations at the time of development, there are few guidelines describing the transition from legal requirements to implementation. To reduce risks, services depend on external legal assessments. With developers and legal experts often missing either legal or technical knowledge, the challenge lies in bridging this gap. We observe that design patterns support both developers and legal experts, and we present an approach in which design patterns are leveraged to provide twofold value for both developers and legal experts when dealing with novel technologies. We conducted a revelatory case study for smart personal assistants and scaffolded the case interpretation through cognitive fit theory. On the basis of the findings, we develop a theoretical model to explain and predict the twofold value of design patterns to develop and assess lawful technologies.

The potentials of artificial intelligence (AI) are manifold and their discussion has gained momentum in research and practice. In the same realm, AI also raises fears among employees of being replaced by AI technologies and, therefore, shying away from using it. Generally, employees want to be empowered to do their job and seek both more responsibility, as well as make their own decisions. In this paper, we conduct a systematic literature review that investigates the current state of the literature on the potential empowering effects of AI-based human-machine behavior. We thus sorted the literature into three behavioral categories: humans shape machine behavior, machines shape human behavior, human-machine co-behavior and crossed them with psychological empowerment dimensions of significance, competence, self-determination, and influence. Our results show corresponding literature streams and provide future research directions in a field that is likely to disrupt the way we work in the future.

Viele Innovationen aus Forschungs- und Entwicklungsprojekten scheitern in der Praxis, da die Beteiligten nicht von Anfang an bzw. nicht ausreichend involviert werden. Um diesem Problem entgegenzuwirken, bietet sich das Anwenden der LabTeam-Methode an, die im Zuge des Forschungsprojekts HISS entwickelt und erprobt wurde. Diese adressiert das nicht ausreichende Berücksichtigen des Wandels der Arbeit und die mangelhafte Involvierung der Beteiligten. Dieser Beitrag stellt diese Methode dar und stellt handlungsweisende Richtlinien vor.

In our digital world, all companies need IT support. The IT support staff is under high pressure solving user-based issues and facing an increase of heterogeneous systems. Hybrid intelligence could solve many issues due to the combination of machine power and the individual strengths of humans. As a part of a bigger design science research project, this paper derives requirements for an IT support system based on hybrid intelligence (ISSHI). 17 requirements from the literature and 21 requirements from 24 indepth interviews with IT support managers and support-agents from three different companies have been derived. These were evaluated and refined with a second interview series of five IT support stakeholders that led to a total of 24 consolidated requirements. Finally, these requirements were used to inform a system architecture for an ISSHI. This architecture shall serve as a foundation for future research directions regarding hybrid intelligence in IT support.

Die Verbindung von menschlicher und künstlicher Intelligenz, die wir hybride Intelligenz (HI) nennen, soll Mitarbeitende im IT-Support entlasten und unterstützen. In diesem Beitrag gestalten wir nutzungszentriert eine HI-basierte Dienstleistung am Beispiel des IT-Supports. Wir beginnen mit einer Problemidentifizierung am Beispiel von drei unterschiedlich groß aufgestellten Unternehmen. Basierend auf diesen identifizierten Herausforderungen des IT-Supports wurden die Interaktionen während der Dienstleistungserbringung zwischen allen Beteiligten (Mitarbeitende, Kund:innen und System) nutzungszentriert neu gestaltet.

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.