Auflistung nach Schlagwort "Artificial Intelligence"
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- KonferenzbeitragA Speech-Based AI for Political Participation(Mensch und Computer 2022 - Tagungsband, 2022) Bräuer, Paula; Mazarakis, AthanasiosThis study presents a first experimental approach for the use of intelligent virtual assistants (IVA) to support political participation. In order to involve as many citizens as possible in participatory political processes, such as the search for a repository site for high-level radioactive waste, IVAs could offer a possibility to convey information in an interactive way and to arouse interest in such complex topics. However, the question arises whether an IVA can adequately convey such a topic and ensure appropriate usability despite many complex dialogues with the user. The explorative study presents the results with a prototypically implemented Amazon Alexa Skill. Compared to a website that addresses the same questions as the Skill, a slightly poorer usability was found. Based on this first study, various questions arose that need to be investigated in future studies. These include questions related to the trustworthiness of such applications and challenges related to the auditive representations of different political opinions.
- KonferenzbeitragEin ABC aktueller Herausforderungen für sichere interaktive Systeme(Mensch und Computer 2018 - Workshopband, 2018) Mentler, TiloDie Potenziale und Grenzen maschineller Lernverfahren (unter dem Schlagwort „Artificial Intelligence“), großer verfügbarer Datenmengen („Big Data“) sowie vernetzter softwaretechnischer und mechanischer Komponenten („Cyber-Physical Systems“) werden derzeit hinsichtlich verschiedener sicherheitskritischer Domänen diskutiert. Unabhängig von konkreten Anwendungen (z.B. Umgang mit Fake News, „smarte“ Energieverteilnetze oder E-Health) gilt es, Herausforderungen für die Gestaltung entsprechender Computersysteme systematisch zu erfassen. Sie müssen dann insbesondere hinsichtlich der Mensch-Maschine-Schnittstelle bewertet werden. In diesem Beitrag wird auf Grundlage der Forschungsarbeiten im Projekt „Artificial Intelligence and the Automated Ordering of Digital Communication“ das zuvor benannte ABC aktueller Herausforderungen für die Gestaltung sicherer interaktiver Systeme diskutiert und Forschungsbedarf im Bereich Mensch-Technik-Interaktion identifiziert.
- KonferenzbeitragAdversarial N-player Search using Locality for the Game of Battlesnake(SKILL 2019 - Studierendenkonferenz Informatik, 2019) Schier, Maximilian Benedikt; Wüstenbecker, NiclasThis paper presents an approach to designing a planning agent for simultaneous N-player games. We propose to reduce the complexity of such games by limiting the search to players in the locality of the acting agent. For Battlesnake, the game at hand, an iterative deepening search strategy utilizing both alpha-beta and max^n search is suggested. Useful metrics for estimating player advantage are presented, especially using a diamond flood filler for measuring board control. Furthermore, the process of our heuristic parameter tuning with a grid search and a genetic algorithm is described. We provide a qualitative analysis of our algorithm's performance at the international artificial intelligence competition Battlesnake, Victoria. Here, our agent placed second in the intermediate division.
- KonferenzbeitragAI Defenders: Machine learning driven anomaly detection in critical infrastructures(INFORMATIK 2024, 2024) Nebebe, Betelhem; Kröckel, Pavlina; Yatagha, Romarick; Edeh, Natasha; Waedt, KarlPrevious studies have evaluated the suitability of different machine learning (ML) models for anomaly detection in critical infrastructures, which are pivotal due to the potential consequences of disruptions that can lead to safety risks, operational downtime, and financial losses. Ensuring robust anomaly detection for these systems within a company is vital to mitigate risks and maintain continuous operation. In this paper, we utilize a time-series labeled dataset obtained from a hydraulic model simulator (ELVEES simulator) to conduct a comprehensive and comparative analysis of various ML models. The study aims to demonstrate how different models effectively identify and respond to anomalies, underscoring the potential artificial intelligence (AI) driven systems to mitigate attacks. With the chosen approach, we expect to achieve the best performance in detecting two types of anomalies: point anomaly and contextual anomaly.
- KonferenzbeitragAI in the Wild: Challenges of Remote Deployments(INFORMATIK 2023 - Designing Futures: Zukünfte gestalten, 2023) Dede, Jens; Wewetzer, David; Förster, AnnaThe effect of humanity on the earth becomes more and more apparent. Besides the publicly discussed climate change and overpopulation, also the number of conflicts with wildlife increases. The technological progress of the past years helped to understand these challenges better. Monitoring solutions, known to the public as the Internet of Things (IoT), increase the amount of collected data, whereas artificial intelligence (AI) supports analyzing and gathering a deeper understanding. Most projects in the area of wildlife try to achieve a more sustainable usage of natural resources and a better coexistence with our environment. The mAInZaun project focuses on the conflict between wolves and livestock. It aims to introduce these new technologies into grazing management and foster non-lethally coexistence between livestock and predators. Artificial intelligence (AI) analyzes images and videos of the areas surrounding the pasture. The algorithms detect possible attackers or predators, such as wolves, stray dogs, bobcats, etc. In the second step, these animals are scared away using adaptive technologies. These can be sound, ultrasound, scent, light, etc. These systems are usually operated in remote environments, raising challenges like hardware design, power requirements, and maintenance. This paper will discuss these challenges and how we address them in the mAInZaun project.
- Student PaperAI-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, CarstenThis 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.
- ZeitschriftenartikelAIOps – Artificial Intelligence für IT-Operations(HMD Praxis der Wirtschaftsinformatik: Vol. 56, No. 2, 2019) Andenmatten, MartinTraditionelle IT Service Management Konzepte mögen anstehende Herausforderungen der Unternehmen nicht mehr zu lösen. Der ungebremste Drang des Business nach Digitalisierung, die damit verbundene Vernetzung von Produkten zu Services sowie die Dynamik der Cloud und das „Everything as a Service“ stellt alle Unternehmen und IT-Organisationen vor ein grosses Problem: wie lassen sich die hohen Anforderungen an Verfügbarkeit, Performance, Kosten, Sicherheit und Compliance der IT-Services in einem hybriden Multi-Cloud-Ökosystem wirksam steuern, wenn sich die Zusammensetzung der Komponenten und Beteiligten praktisch täglich ändert? Manuell ist dies eine „Mission Impossible“. Aber auch automatisierte Roboter können hier nicht mehr genügen, weil die permanente Anpassung von Regeln und Workflows der dynamischen Realität hinterherhinkt. Die Zukunft von IT-Operations liegt nur noch in der Anwendung von künstlicher Intelligenz: AI für IT-Operations. Traditional IT service management concepts may not be able to solve upcoming business challenges. The unrestrained urge of the business for digitization, the associated networking of products to services as well as the dynamics of the cloud and the “Everything as a Service” pose a big problem for all companies and IT organizations: how can the high demands on availability, performance, cost, security, and compliance of IT services in a hybrid, multi-cloud ecosystem effectively managed as the composition of components and stakeholders changes on an almost daily basis? Manually this is a “mission impossible”. But even automated robots can no longer suffice because the permanent adaptation of rules and workflows lags behind the dynamic reality. The future of IT-Operations lies only in the application of artificial intelligence: AI for IT-Operations.
- KonferenzbeitragThe application of Articial Intelligence for Cyber Security in Industry 4.0(INFORMATIK 2019: 50 Jahre Gesellschaft für Informatik – Informatik für Gesellschaft (Workshop-Beiträge), 2019) Ben Zid, Ines; Parekh, Mithil; Waedt, Karl; Lou, XinxinThe use of Artificial Intelligence (AI) in different domains is continuously growing. In particular for cybersecurity, we can see the implementations of AI solutions, e.g. machine learning, in a wide range of applications from various domains. While some consider this step as risk for cybersecurity, others agree that it is in fact a solution to many issues as well. This leads to a higher necessity of having a right understanding as well as handling of cybersecurity controls that enforce meeting domain, project and application specific security targets. This implies that more efforts and resources have to be focused and invested towards cybersecurity. One reason for this is that attackers (threat agents) may integrate AI based algorithms and AI based evaluation of data, which forces the security staff to respond at a similar level. Thus, we are considering AI as a potential solution for satisfying a set of rising needs and objectives. In this paper, we present the concept for merging and integration of these three major domains and applications. Also, we detail the relevant motivations, requirements and challenges to be considered when coming to such combination.
- ZeitschriftenartikelAssessing the Attitude Towards Artificial Intelligence: Introduction of a Short Measure in German, Chinese, and English Language(KI - Künstliche Intelligenz: Vol. 35, No. 1, 2021) Sindermann, Cornelia; Sha, Peng; Zhou, Min; Wernicke, Jennifer; Schmitt, Helena S.; Li, Mei; Sariyska, Rayna; Stavrou, Maria; Becker, Benjamin; Montag, ChristianIn the context of (digital) human–machine interaction, people are increasingly dealing with artificial intelligence in everyday life. Through this, we observe humans who embrace technological advances with a positive attitude. Others, however, are particularly sceptical and claim to foresee substantial problems arising from such uses of technology. The aim of the present study was to introduce a short measure to assess the Attitude Towards Artificial Intelligence (ATAI scale) in the German, Chinese, and English languages. Participants from Germany (N = 461; 345 females), China (N = 413; 145 females), and the UK (N = 84; 65 females) completed the ATAI scale, for which the factorial structure was tested and compared between the samples. Participants from Germany and China were additionally asked about their willingness to interact with/use self-driving cars, Siri, Alexa, the social robot Pepper, and the humanoid robot Erica, which are representatives of popular artificial intelligence products. The results showed that the five-item ATAI scale comprises two negatively associated factors assessing (1) acceptance and (2) fear of artificial intelligence. The factor structure was found to be similar across the German, Chinese, and UK samples. Additionally, the ATAI scale was validated, as the items on the willingness to use specific artificial intelligence products were positively associated with the ATAI Acceptance scale and negatively with the ATAI Fear scale, in both the German and Chinese samples. In conclusion we introduce a short, reliable, and valid measure on the attitude towards artificial intelligence in German, Chinese, and English language.
- TextdokumentBlueprint for a Production-Ready Information Retrieval System based on Multi-Modal Embeddings(INFORMATIK 2021, 2021) Ebert, André; Apel, Anika; Chodyko, Piotr; Hiroyasu, Kyle; Ismali, Festina; Koo, Hyein; Kronburger, Julia; Pesch, RobertDeep Learning models for mapping documents from different domains, e.g., text, images, and audio, into a common vector space, enable a seamless information retrieval between the different domains and, thus, significantly improve the user experience of many expert tools. Despite various models for multi-modal mappings presented in scientific literature, the implementation and integration remain a challenge within the industry, especially for small or medium-sized companies. Reasons are, that developing such retrieval systems for production use-cases is a non-trivial task, requiring scalable, reliable, and cost-efficient infrastructure, services as well as adequate Deep Learning models. We present a generic and flexible blueprint architecture, targeting the development of a production-ready image-text retrieval search system using Kubernetes, MLflow, Elasticsearch, and integrating state-of-the-art Deep Learning models.