Veterinarians experience high workloads and stress levels in their daily work, of which they need to be relieved as much as possible. The general public is showing great interest in digital health services. At the same time, animal owners and veterinarians are seeing telehealth services as particularly positive for triage aspects in veterinary medicine. One approach to support veterinarians may be to enable pet owners to, for instance, make informed decisions on how urgent their animal needs to be examined by a veterinary professional through an mHealth application. For this, stakeholder requirements need to be gathered, which should provide as a starting point for the development of such a decision support system. 955 publications were screened, resulting in the extraction of 10 requirements to mHealth applications for animal owners from 13 publications. Most frequently mentioned aspects were: ensuring complete information input by the user (6 mentions) and displaying a disclaimer about application limitations prominently (5 mentions). Most of the extracted requirements focus on the design of the human-computer interface, revealing this as a crucial point to such applications, especially in guiding animal owners through information and ensuring understanding, particularly of application limitations. However, the small number of included publications shows that primary research in this field, in general, and in this specific topic in particular, is needed in order to fully reflect the requirements for an mHealth application to help animal owners decide on their animal’s need to be examined by a veterinary professional.

We are experiencing a massive and volatile expansion of AI-based products and services. The current intermeshing of digital technologies, people, and society is shaping how we live and bringing algorithms to the forefront of decision making. The algorithmification of society and the narratives used to make it appear inevitable serve specific interests, mostly profitable for and controlled by few actors. It is not AI in itself, but the utilitarian sophistication of optimisation mechanisms and the power structures behind them that profit from controlling all that we do, when and how we do it, our behaviours, and even ourselves. In education, this is of serious concern as academia is gradually moving to uncertain dependencies on corporate interests. This paper calls for radical changes in dealing with the AI narratives that have monopolised recent public debates and discussions. It sheds light on the key terminology surrounding today's AI algorithms and the technological background that makes them possible. It shows examples of the negative impacts and the implications of not addressing or ignoring certain issues, especially in education. This paper also suggests good practices through consistent advocacy, grounded materials, and critical work on digital literacy, particularly AI literacy.

Introduction: Existing research agrees that a well-thought design of the user interface is a key point for an mHealth application for animal owners, supporting them obtain information and make decisions regarding their pet’s specific situation. However, there is currently a lack of specific advice on the design of such an application. Methods: As part of a user-centered design (UCD) process, a formative, explorative usability test with n = 5 users was conducted for collecting design ideas. The test was conducted for two applications that were already available on the market. Results: The need of supporting comprehensive information input in guided processes that can be adapted to the individual level of knowledge, was identified as a key aspect. Conclusion: In this paper, recommendations for the design of a suitable user interface are suggested to support application developers and designers.

Animal owners may increasingly rely on large language models for gathering animal health information alongside internet sources in the future. This study therefore aims to provide initial results on the accuracy of ChatGPT-4o in triage and tentative diagnostics, using horses as a case study. Ten test vignettes were used to prompt situation assessments from the tool, which were then compared to original assessments made by a veterinary specialist for horses. The most probable diagnosis suggested by ChatGPT-4o was found to be quite accurate in most cases, with the urgency to contact a veterinarian sometimes assessed as higher than necessary. When provided with all relevant information, the tool does not seem to compromise horse health by recommending excessively long waiting times, although there is still potential for improving the relief of veterinarians’ workload.

BRIDGING GENERATIONS OF LEARNERS AND ENHANCING THE UNDERGRADUATE EXPERIENCE: LESSONS LEARNED FROM A DAY OF COMPUTER SCIENCE

Das aktuelle KI-Momentum spricht für den Einsatz intelligenter Algorithmen in einer Vielfalt von Anwendungsbereichen, die unser Leben schon verändern oder verändern werden. Allerdings stellt in letzter Zeit der KI-Hype andere Teilgebiete in den Schatten und verschleiert gleichzeitig die Implikationen und Risiken, die KI-basierte Systeme mit sich bringen können. Die Chancen und Herausforderungen solcher Systeme brauchen sowohl moderne, ethisch konforme Handlungsempfehlungen als auch eine Forschungsagenda, die eine richtige, an den Nutzer*innen orientierte Gestaltung ermöglichen. Wir untersuchen in diesem Beitrag die Grundlagen und Merkmale KI-basierter Systeme und schlagen einen auf der sozio-technischen Systemtheorie basierenden Gestaltungsrahmen vor, um KI in Organisationen erfolgreich umzusetzen.

Narratives about intelligent artefacts have influenced both the public’s imaginary and the actual development of the AI field since its foundation. Yet, in times where the field seems to be flourishing on the one hand, but rushing into an AI winter on the other, factual narratives about AI applications and advancements are more essential than ever. What is the gap between the actual capabilities of today’s AI and the vocabulary used to report about them? In particular, what is the AI lingua used in official, legal documents in business? To find out, we analysed leading share index companies’ annual reports from a representative fraction of the German economy (DAX 30), as a starting step in this direction. In this paper, we present a fact-based methodology for systematically assessing the true state of enterprise AI of those companies. Our initial empirical investigation covers only the annual reports of leading listed German enterprises in the DAX 30 as of May 2021 (i.e. before the DAX’s expansion to 40 members). For this concrete example, we collected their annual reports from 2010 to 2020 (N=312). We then built upon previous work by extending natural language processing (NLP) algorithms we developed for these purposes. The idea is to systematically process and automatically detect the use of AI-related terminology in those annual reports. Such a terminology is part of a classification schema we introduce for differentiating concrete types of AI-related terms. We also compare different NLP libraries regarding their suitability and speculate on the reasons behind the poor performance of some of them. Furthermore, we look at relevant AI keywords and phrases, thereby conducting a human-based semantic analysis of the context – tasks that machines still cannot do effectively. We also give guidance on how to proceed in similar studies, i.e. on how to extend our methodology and the key findings to other national economies. This way, we are contributing not only to an informed perception about the state of enterprise AI, but also to filling the gap between the narratives it uses and the actual state of AI development.

D. Monett 1, C. Lemke1, M. Cunneen2, D. Coulter3, M. Bloomfield4, G. Faustmann1 1Berlin School of Economics and Law (GERMANY) 2University of Limerick (IRELAND) 3Independent Researcher (GERMANY) 4York Associates International Limited (UNITED KINGDOM)

Much has been speculated about intelligent artefacts and their potential abilities to automate entire industries or at least a broad variety of human- related tasks and processes. Recent advancements in the fields of Artificial Intelligence (AI) and Robotics have fueled these views, thereby propelling hyped narratives, unfounded fears, and dystopian futures alike. Some of the reasons behind such behaviors originate from the time-old dispute on what intelligence (e.g. in humans and in machines) truly means. Others, to the disparate realities between the promise of AI, i.e. to build machines with human-like intelligence and to consider what abilities current "intelligent" machines possess. The speedy automation of human labour and processes has been around since the industrial revolution. Automation wears new clothes in the digital era, especially that involving the development of emerging technologies, but it is still far from including countless human activities that require genuine intelligence and are not easy to automate. The aim of this paper is twofold. On the one hand, it clarifies why we are no closer to having truly intelligent systems. We base our statements on a thorough discussion about what genuine intelligence means. On the other hand, it presents an analysis of new jobs created in Robotics and related fields by mining and processing job offers posted to the mailing list "robotics-worldwide." By using natural language processing techniques, not only is the evolution of all job offers posted over the last 15 years to that renowned mailing list presented, but also their most salient characteristics and backgrounds. In addition to the continuously growing number of job offers in the analyzed period, the results indicate substantial demand for jobs predominantly within the field of academic and scientific research. Proliferating innovation in AI and Robotics combined with a growing lack of experts in these domains indicates that both are broad fields that are yet to be thoroughly explored. The analysis of "The robotics-worldwide Archives" resoundingly displays that an obvious solution to this is the increased employment of researchers and academics to undertake this exploration. No, robots will not take all the jobs. At least not yet.

Digital technologies are and will continue to be changing the way we learn and teach today and in the future. This includes not only offering every learner and teacher equal access to these technologies, but it also involves completely new forms of content delivery. Additionally, digital skills must be fundamentally strengthened as a basic human skill that is urgently needed today. It is therefore essential that learners own or have easy access to the necessary digital technologies to participate fully in the digital education era. How learners concretely use them in diverse and creative ways is of particular interest not only for educators. In this regard, we sought to study the changing landscape of technology ownership and use by students for both learning and leisure. To accomplish this, we designed and conducted three surveys. After an analysis of related work, we present a comparative, quantitative analysis of the survey results from 2013 (N-1=275), 2015 (N-2=336), and 2020 (N-3=481). It investigates the evolution of ownership and use of digital technologies over the years. Then, we explore the extent to which the use of different digital technologies has changed during this period, and the purposes for which technologies are now used in enhancing and supporting student learning. We also present a qualitative evaluation of the learners' responses. The aim is to determine how digital technologies are used and how they may depend on specific learning contexts. Finally, we give some recommendations and suggestions for further research.

ZusammenfassungDigitale Ethik fokussiert auf die moralischen Werte und Normen im Umgang mit den modernen Technologien des digitalen Zeitalters, reflektiert menschliche Handlungen im Design von Technologien und liefert Prinzipien für einen verantwortungsvollen Einsatz. Datengetriebene Organisation leben von der wertschöpfenden Datenanalyse zur Entscheidungsdurchsetzung. Die ethisch korrekte Nutzung solcher Technologien wird hierbei zu einem Schlüsselfaktor. Dieser Beitrag führt in datengetriebene Organisationen ein, zeigt wesentliche Begriffe zur digitalen Ethik und erläutert anhand ethischer Grundsätze die Implikationen für eine datengetriebene Wertschöpfung. Das Beispiel Deutsche Telekom AG demonstriert, wie digital-ethische Grundsätze entwickelt und konkret genutzt werden für einen zunehmenden Einsatz von intelligenten Systemen in datengetriebenen Organisationen. Es zeigt, wie eine KI-Ethik im Geschäftsalltag erfolgreich eingesetzt wird und einen besseren Umgang mit diesen Technologien schafft.

Eine zeitgemase Ausbildung im Bereich der Kunstlichen Intelligenz ist essentiell, um zu verstehen, was KI bedeutet, wo ihre derzeitigen Grenzen liegen und welchen Beitrag sie fur Wirtschaft und Ges...

M. Bloomfield1, C. Lemke2, D. Monett 2 1York Associates (UNITED KINGDOM) 2Berlin School of Economics and Law (GERMANY)

ZusammenfassungDigitale Ethik beschäftigt sich mit den Wechselwirkungen von Mensch und digitaler Technologie, reflektiert die moralischen Werte und liefert anhand ethischer Grundsätze einen Erkenntnisbeitrag. Im Bildungskontext zeigen sich gesonderte digitalethische Herausforderungen, bedingt durch ihre besondere Stellung und Bedeutung für Wissensgesellschaften. Dafür wird der Begriff der digitalen Ethik der Bildung definiert und systematisiert. Auf der Grundlage des Stilmittels von Narrativen werden für eine beispielhafte Bildungstechnologie ethische Implikationen aufgezeigt und durch eine erste empirische Validierung evaluiert.

D. Monett 1, L. Hoge2, L. Haase3, L. Schwarz4, M. Normann5, L. Scheibe6 1Berlin School of Economics and Law (GERMANY) 2Robert Koch Institute (GERMANY) 3Technical University of Applied Sciences Wildau (GERMANY) 4Hochschule Stralsund (GERMANY) 5NORDAKADEMIE Graduate School (GERMANY) 6DB Systel GmbH (GERMANY)