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Auflistung nach Schlagwort "Generative AI"

1 - 10 von 18
  • Student Paper
    AI-based chatbots as enabler for efficient external knowledge management in public administration
    (7. Fachtagung Rechts- und Verwaltungsinformatik (RVI 2024): Neue Wege der Zusammenarbeit und Vernetzung für digitale Transformation und Verwaltungsmodernisierung, 2024) Wiethölter, Jost; Kühl, Linus; Feldmann, Carsten
    This study addresses the pressing issue of staff shortages in German public administrations through the lens of digitalization, focusing on the potential of AI-based chatbots to solve this problem by replacing human labour. Employing a Design Science Research Process (DSRP) methodology, the research synthesizes theoretical foundations and regulatory frameworks to develop a robust chatbot concept. The artifact presented is a comprehensive architectural framework integrating user-centric design, linguistic processing, and regulatory compliance. The proposed artifact navigates complex federal structures and diverse IT infrastructures, promoting accessibility and inclusivity. Implications suggest enhanced efficiency and accessibility in public service delivery for potentially increasing citizen satisfaction and decreasing employee workload. The study underscores the importance of legal compliance and the evolving regulatory landscape in AI deployment. Future research will involve prototyping and evaluating the artifact's performance and applicability throughout the course of the DSRP, thus contributing to the advancement of digital transformation in public administrations.
  • Konferenzbeitrag
    AI-based Tools in Higher Education: A Comparative Analysis of University Guidelines
    (Proceedings of Mensch und Computer 2024, 2024) Hofmann, Paula; Brand, Alexa; Späthe, Eva; Lins, Sebastian; Sunyaev, Ali
    Im Bildungswesen werden verstärkt KI-basierte Tools wie ChatGPT eingesetzt. Allerdings sind viele Studierende und Lehrende unsicher, ob, wie und in welchem Maß sie diese Tools im Hochschulkontext einsetzen dürfen. Insgesamt mangelt es in Deutschland an Universitäten an Richtlinien zum Umgang mit KI-basierten Tools. Aus diesem Grund führt diese Studie eine vergleichende Analyse von bereits existierenden Richtlinien durch, um die wichtigsten Empfehlungen für den Umgang zu extrahieren und zu aggregieren. Die Ergebnisse zeigen, dass die Relevanz von Richtlinien hoch ist und dabei insbesondere geklärt werden sollte, unter welchen Bedingungen KI-basierte Tools als Hilfsmittel gelten, welche Verantwortlichkeiten bei den Akteuren liegen und wie Risiken und Herausforderungen begegnet werden können, um u.a. die akademische Integrität sicherzustellen. Die Ergebnisse der Arbeit unterstützen bei der Ableitung und Synthese von Richtlinien im Hochschulkontext.
  • Konferenzbeitrag
    Augmentation through Generative AI: Exploring the Effects of Human-AI Interaction and Explainable AI on Service Performance
    (Mensch und Computer 2024 - Workshopband, 2024) Reinhard, Philipp
    Generative artificial intelligence (GenAI), particularly large language models (LLMs), offer new capabilities of natural language understanding and generation, potentially reducing employee stress and high turnover rates in customer service delivery. However, these systems also present risks, such as generating convincing but erroneous responses, known as hallucinations and confabulations. Thus, this study investigates the impact of GenAI on service performance in customer support settings, emphasizing augmentation over automation to address three key inquiries: identifying patterns of GenAI infusion that alter service routines, assessing the effects of human-AI interaction on cognitive load and task performance, and evaluating the role of explainable AI (XAI) in detecting erroneous responses such as hallucinations. Employing a design science research approach, the study combines literature reviews, expert interviews, and experimental designs to derive implications for designing GenAI-driven augmentation. Preliminary findings reveal three key insights: (1) Service employees play a critical role in retaining organizational knowledge and delegating decisions to GenAI agents; (2) Utilizing GenAI co-pilots significantly reduces the cognitive load during stressful customer interactions; and (3) Novice employees face challenges in discerning accurate AI-generated advice from inaccurate suggestions without additional explanatory context.
  • Konferenzbeitrag
    Do Users Really Care? Evaluating the User Perception of Disclosing AI-Generated Content on Credibility in (Sports) Journalism
    (Proceedings of Mensch und Computer 2024, 2024) Rossner, Alexander; Cassel, Marie; Huschens, Martin
    AI-generated journalism (robot journalism) enables the automated creation of news articles through Artificial Intelligence (AI). Especially in sports reporting robot journalism enables providers to publish standardized match reports quickly after sporting events (e.g. soccer games). This study examines the influence of disclosing the type of origin (human and AI) on the perception of the credibility of sports reporting. For this purpose, an quantitative online survey was conducted with 154 participants, where two match reports about the same soccer game were compared: One of these reports was written by a journalist, while the other was AI-generated. The participants were divided into three groups, with varying disclosures on the type of origin (no disclosure, correct disclosure, manipulated disclosure). The analysis showed that the origin disclosures had no significant influence on credibility. Both expertise and trustworthiness were rated similarly. Since readers are indifferent about the source of information, this suggests that the use of AI in sports reporting can be useful to increase efficiency. However, in a wider sense, this indifference poses challenges to policymakers trying to contain the spread of misinformation and fake news based on the use of AI.
  • Zeitschriftenartikel
    Foundation Models
    (Business & Information Systems Engineering: Vol. 66, No. 2, 2024) Schneider, Johannes; Meske, Christian; Kuss, Pauline
  • Konferenzbeitrag
    Generative AI and Gametheory for the development and deployment of Honeypots to enhance the Security of Industrial Automation and Control Systems
    (INFORMATIK 2024, 2024) Peters, Ludger; Gkoktsis, Georgios
    The computing hardware and software of modern Industrial automation and control system has evolved to be like traditional IT hardware in the first decade of this century. Due to the specialized demands on these systems introduced, e.g., by specialized measurement equipment or additional safety requirements, typical IT update and security procedures cannot be followed. This paper explores the use of generative AI models in honeypots for enhancing the cybersecurity in industrial automation and control systems. As honeypots are used as traps for system attackers, the deployment of generative AI models enables the creation of more convincing and sophisticated decoy environments. This increases the likelihood of an attacker’s engagement with the environment, improving the detection and analysis of malicious activities. Through a brief summary, this paper quantifies the existing research on generative AI in honeypots. The findings highlight the significant potential of generative AI models in enhancing the security of IACS through their integration into honeypot systems. This can ultimately lead to organizations being able to gain more in-depth insights into emerging cyber threats, improve their incident response capabilities, and enhance the resilience of their industrial control systems. To quantify the impact of employing such advanced deception technologies on the behavior of the attacker, this paper proposes a novel approach using a non-cooperative game-theoretic framework for deploying honeypots in OT systems. This methodology enables strategic analysis that balances limited resources with the need to predict and counter sophisticated cyber adversaries’ actions.
  • Konferenzbeitrag
    GRANITE – EJEA: Europe meets Japan: Intercultural Workshop on Data Sovereignty and Generative AI. Applications, Design, Social, Ethical, and Technological Impact
    (INFORMATIK 2024, 2024) Reiners, René; Ganter-Richter, Sabine
    The workshop's primary goal is to bring together experts from academia and industry to discuss and develop new collaborative efforts with regard to the topics data sovereignty and generative AI. It serves as a platform to exchange knowledge, identify common challenges, and explore innovative solutions for Europe and Japan. The workshop is commonly organized by the GRANITE Network and the European-Japanese Experts Association (EJEA). GRANITE focuses on fostering global cooperation by creating a network of ambassadors in various fields of science and technology, whereas EJEA is dedicated to enhancing cooperation between Europe and Japan through various activities, including conferences, workshops, and research projects. On the European side, Fraunhofer FIT and the Network for Science play pivotal roles in driving the initiatives for both, GRANITE and EJEA. From Japan, the prefectures of Nagano and Kagawa are instrumental in facilitating the collaboration.
  • Conference paper
    Immersive Räume zur Kreativitätsunterstützung: Ein intelligenter Lehr- und Lernraum
    (Proceedings of DELFI 2024, 2024) Fuchs, Andreas; Appel, Sven; Grimm, Paul
    Dieser Beitrag präsentiert einen neuartigen Ansatz zur Gestaltung immersiver Räume für die Hochschullehre, die basierend auf Verhalten, gesprochenem Wort und Stimmung eine Unterstützung für kollaborative Kreativitätsprozesse bieten. Ziel ist es, Lehrenden sowie Lernenden in einer interaktiven Virtual Reality-Umgebung durch KI-analysierte und -generierte Inhalte neue Gedankenanstöße zu geben. Durch die Integration von Natural language processing (NLP) und künstlicher Intelligenz wird die Mensch-Computer-Interaktion verbessert, um eine nahtlose Zusammenarbeit zu fördern. Das intelligente System verarbeitet Nutzerdaten und passt die Umgebung an die individuellen Bedürfnisse der Teilnehmenden an. Dies ermöglicht kollaboratives Arbeiten in einer geteilten und zugleich individualisierten Umgebung. Die Anwendung nutzt generative KI zur Erzeugung von Bildern, die auf der verarbeiteten Sprache bzw. den Gesprächsinhalten basieren und beeinflusst gestaltende Elemente wie Beleuchtung, Farbstimmung und Akustik. Der Beitrag erörtert technische Aspekte und potenzielle Anwendungen in Bildung, Unterhaltung und am Arbeitsplatz. Die Forschungsergebnisse deuten darauf hin, dass dieser Ansatz vielversprechend ist, um Kreativität zu fördern und das Wohlbefinden zu steigern.
  • Workshopbeitrag
    Integrating Declarative and Imperative Process Modeling Paradigms in the Age of Generative AI
    (Modellierung 2024 Satellite Events, 2024) Kampik, Timotheus; Berg, Gregor; Eickhoff, David
    This brief paper summarizes a talk introducing and discussing the notion of process atoms, small facts or queries, each describing an organizationally relevant property or constraint of a business process that cannot be further split without losing its business meaning. An example of a process atom is: “only if an order with a purchase amount greater than 10,000€ is requested, management approval has to take place afterwards” (more abstractly: “only if A then eventually B”). As process atoms are executable as queries on data and allow for dynamic contextualization across process and organizational scopes, they complement and augment traditional process models, such as BPMN diagrams, particularly in the age of data-driven process analysis and generative AI-created process content.
  • Konferenzbeitrag
    Integrating Generative AI in Music Education: With AI in a Musical Question-Answer Game
    (INFORMATIK 2024, 2024) Arnecke, Jörn; Eck, Sebastian Oliver; Steuck, Pia; Vaughan, Alexander
    This paper focuses on the integration of Generative AI (GenAI) in music theory education, with the specific aim of replicating historical musical styles. Traditional AI applications in music generation assist composers in creating basic compositions but fall short in complex tasks like style imitation. Our project ’Musik-Automat – Mit der KI im musikalischen Frage-Antwort-Spiel’ (’Music Automaton – With AI in a Musical Question-Answer Game’, University of Music Franz Liszt Weimar; project duration: October 2023 - December 2024 [Un23]) addresses this gap by developing a GenAI capable of generating and understanding symbolic musical data, allowing for a dialogic interaction between students and AI. This interaction aims to enhance educational and creative processes by enabling students to engage in a musical question-and-answer game, promoting both stylistic knowledge and creativity. We create an educational web application that supports composing in historical styles. Our methodology emphasizes human-machine collaboration, where human feedback guides the music generation model, ensuring the human role remains central to artistic innovation and the creative process. The project is designed to be inclusive of various skill levels and classical musical genres, with a focus on practical application in music theory education. Initial experiments demonstrate that this interactive model stimulates critical thinking and classroom discussions about musical style and authenticity, therefore augmenting the overall learning experience. Supported by the Stifterverband and the Thuringian Ministry of Economics, Science and Digital Society [St23], this project aims to support digital transformation in higher education, preparing students to effectively use AI in academic and later professional environments.