Logo des Repositoriums

Auflistung nach Autor:in "Satzger, Gerhard"

1 - 9 von 9
  • Zeitschriftenartikel
    Data-Centric Artificial Intelligence
    (Business & Information Systems Engineering: Vol. 66, No. 4, 2024) Jakubik, Johannes; Vössing, Michael; Kühl, Niklas; Walk, Jannis; Satzger, Gerhard
    Data-centric artificial intelligence (data-centric AI) represents an emerging paradigm that emphasizes the importance of enhancing data systematically and at scale to  build effective and efficient AI-based systems. The novel paradigm complements recent model-centric AI, which focuses on improving the performance of AI-based systems based on changes in the model using a fixed set of data. The objective of this article is to introduce practitioners and researchers from the field of Business and Information Systems Engineering (BISE) to data-centric AI. The paper defines relevant terms, provides key characteristics to contrast the paradigm of data-centric AI with the model-centric one, and introduces a framework to illustrate the different dimensions of data-centric AI. In addition, an overview of available tools for data-centric AI is presented and this novel paradigm is differenciated from related concepts. Finally, the paper discusses the longer-term implications of data-centric AI for the BISE community.
  • Zeitschriftenartikel
    Electronic Commerce: Ein Instrument Zur Steuergestaltung?
    (Wirtschaftsinformatik: Vol. 41, No. 1, 1999) Satzger, Gerhard
  • Konferenzbeitrag
    IT und dienstleistungen für die energiewende und die elektromobilität (IDEE 2016)
    (Informatik 2016, 2016) Satzger, Gerhard; Beverungen, Daniel; Matzner, Martin; Stryja, Carola
  • Konferenzbeitrag
    Looking Through the Deep Glasses: How Large Language Models Enhance Explainability of Deep Learning Models
    (Proceedings of Mensch und Computer 2024, 2024) Spitzer, Philipp; Celis, Sebastian; Martin, Dominik; Kühl, Niklas; Satzger, Gerhard
    As AI becomes more powerful, it also becomes more complex. Traditionally, eXplainable AI (XAI) is used to make these models more transparent and interpretable to decision-makers. However, research shows that decision-makers can lack the ability to properly interpret XAI techniques. Large language models (LLMs) offer a solution to this challenge by providing natural language text in combination with XAI techniques to provide more understandable explanations. However, previous work has only explored this approach for inherently interpretable models–an understanding of how LLMs can assist decision-makers when using deep learning models is lacking. To fill this gap, we investigate how different augmentation strategies of LLMs assist decision-makers in interacting with deep learning models. We evaluate the satisfaction and preferences of decision-makers through a user study. Overall, our results provide first insights into how LLMs support decision-makers in interacting with deep learning models and open future avenues to continue this endeavor.
  • Zeitschriftenartikel
    Retained Organizations in IT Outsourcing
    (Business & Information Systems Engineering: Vol. 59, No. 2, 2017) Goldberg, Marius; Kieninger, Axel; Satzger, Gerhard; Fromm, Hansjörg
    IT outsourcing is a strategic option which enables companies to focus on their core competencies. Over time however, many outsourcing arrangements suffer from severe problems. While the design of retained organizations is generally seen as a critical element, there is hardly any empirical evidence on how the choice of the organizational setup is linked to the occurrence of outsourcing management problems later on. In this work, a quantitative study across various outsourcing arrangements is used to identify the key outsourcing management problems and their interdependency with organizational attributes of retained organizations. It is shown that the key problems differ by outsourcing degree, and critical organizational attributes for each of these problems are unveiled. The paper’s objective is to enhance the design of retained organizations to enable more mature and successful outsourcing solutions as well as to provide foundations for future IS research.
  • Konferenzbeitrag
    Service Level Management 2010 (SLM 2010). Vorwort
    (INFORMATIK 2010. Service Science – Neue Perspektiven für die Informatik. Band 1, 2010) Ludwig, André; Kieninger, Axel; Satzger, Gerhard; Böhmann, Tilo; Leimeister, Stefanie
  • Zeitschriftenartikel
    Technologische Innovation und die Auswirkung auf Geschäftsmodell, Organisation und Unternehmenskultur – Die Transformation der IBM zum global integrierten, dienstleistungsorientierten Unternehmen
    (Wirtschaftsinformatik: Vol. 51, No. 1, 2009) Jetter, Martin; Satzger, Gerhard; Neus, Andreas
    Im vorliegenden Beitrag wird der Einfluss von Innovationen der Informations- und Kommunikationstechnologie (IKT) auf die Transformation von Unternehmen untersucht. Zunächst werden die allgemeinen IKT-getriebenen Entwicklungslinien der Globalisierung und der Dienstleistungsorientierung beschrieben. Die nachfolgende Analyse der Transformation der IBM Corporation über die letzten 50 Jahre zu einem global integrierten, dienstleistungsorientierten Unternehmen macht deutlich, dass IKT-Innovationen mit gleichzeitigen Anpassungen des Geschäftsmodells, der Organisation und der Unternehmenskultur begegnet werden muss. Die Fähigkeit zu derartiger Adaption gewinnt eine zunehmend zentrale Bedeutung für Unternehmen.AbstractThis article investigates the influence of information and communication technology (ICT) on business transformation. First, the general, ICT-driven development lines of globalization and service-orientation are described. Then, an analysis of the IBM Corporation’s transformation over the past 50 years into a globally integrated, service-oriented company illustrates that ICT innovations must be dealt with by simultaneous adaptation of business model, organization and corporate culture. For many companies the ability to manage this change becomes increasingly critical.
  • Zeitschriftenartikel
    Virtual Sensors
    (Business & Information Systems Engineering: Vol. 63, No. 3, 2021) Martin, Dominik; Kühl, Niklas; Satzger, Gerhard
  • Konferenzbeitrag
    (X)AI as a Teacher: Learning with Explainable Artificial Intelligence
    (Proceedings of Mensch und Computer 2024, 2024) Spitzer, Philipp; Goutier, Marc; Kühl, Niklas; Satzger, Gerhard
    Due to changing demographics, limited availability of experts, and frequent job transitions, retaining and sharing knowledge within organizations is crucial. While many learning systems already address this issue, they typically lack automation and scalability in teaching novices and, thus, hinder the learning processes within organizations. Recent research emphasizes the capability of explainable artificial intelligence (XAI) to make black-box artificial intelligence systems interpretable for decision-makers. This work explores the potential of using (X)AI-based learning systems for providing learning examples and explanations to novices. In an exploratory study, we evaluate novices’ learning performance in a learning setting taking into account their cognitive abilities. Our results show that novices increase their learning performance throughout the exploratory study. These results shed light on how XAI can facilitate learning, taking first steps towards understanding the potential of XAI in learning systems.