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Manufacturing companies are facing an increasingly turbulent market - a market defined by products growing in complexity and shrinking product life cycles. This leads to a boost in planning complexity accompanied by higher error sensitivity. In practice, IT systems and sensors integrated into the shop floor in the context of Industry 4.0 are used to deal with these challenges. However, while existing research provides solutions in the field of pattern recognition or recommended actions, a combination of the two approaches is neglected. This leads to an overwhelming amount of data without contributing to an improvement of processes. To address this problem, this study presents a new platform-based concept to collect and analyze the high-resolution data with the use of self-learning algorithms. Herby, patterns can be identified and reproduced, allowing an exact prediction of the future system behavior. Artificial intelligence maximizes the automation of the reduction and compensation of disruptive factors.

"International Relations, Big Data, and Artificial Intelligence" published on by Oxford University Press.

Einleitend beschreibt der Autor drei grundsätzliche Probleme der Human- und Sozialwissenschaften in der Theoriebildung und Computermodellierung: 1. Sozialwissenschaftliches Wissen existiert oft nur in qualitativer, nichtnumerischer Form. 2. In herkömmlichen Computermodellen versteckt sich das theoretische Wissen häufig in einem nichttheoretischen Code. 3. Schlüsse, die mittels dieser Computermodelle gezogen wurden, erweisen sich nur auf mathematischen Feld durchschau- und kritisierbar. Eine Lösung der Dilemmata erhofft man sich durch das Modellieren auf der Basis Künstlicher Intelligenz (KI). Der Autor beschreibt diese Basis und geht auf den Schlüsselbegriff der Wissensrepräsentation ein. Er unterscheidet zwei Wege, wie die KI-Modellierung für die Theoriebildung genutzt werden kann:die sogenannte theoriegeleitete Perspektive und die datenorientierte Perspektive. Anschließend stellt er einen gemischten Ansatz anhand von Gruppenprozessen vor. Der Autor kommt zu dem Schluss, dass KI-Techniken zur Verbesserung und Generierung neuer Theorien aus empirischen Daten genutzt werden können, auch wenn KI keine Revolution darstellt. (FR)

Artificial intelligence is an important innovation in the rapid development of modern Internet. In the 21st century, human beings have been continuously researching and exploring Internet information technology. All kinds of application forms of Internet informatization begin to appear in our life. The rapid change of technology brings a high upgrade rate of internet products. This marks the technological innovation of some traditional concepts and thinking methods. The development mode of artificial intelligence plus education is an important innovation after the deep development of artificial intelligence technology and the achievement of cross-industry application practice. Robots will be the brains of the future education process. This paper aims to clarify the development trend of the application of artificial intelligence in modern education by analyzing the innovation progress of the combination of artificial intelligence technology and contemporary education. This is of great significance for better use of the advantages of artificial intelligence to build a future-oriented high-tech education system.

This paper asks what skills migrants need to be able to deal with artificial intelligence (AI) technologies in a self-determined way in their everyday lives. We propose a conceptual framework to empirically identify migrant's awareness and perceptions of possible discrimination through AI. Following Bucher (2017, 40), we argue that by experiencing AI systems in their digital environments, people develop AI imaginaries that shape their attitudes, interactions, and practices with AI. We assume that experiences of discrimination evoke affects, feelings, and emotions that at first glance are not associated with AI technologies. The paper provides relevant research questions that address AI imaginaries. In addition to studying knowledge about and perceptions of AI, research should increasingly focus on users' attitudes towards AI, their evaluations of AI, and their feelings, emotions, and affects related to AI. Subsequently, we elaborate on dimensions of digital literacy based on these AI imaginaries. Finally, we will describe the digital skills that are necessary to confidently cope with discrimination by AI technologies.

Wikipedia is a community-created encyclopedia that contains information about notable people from different countries, epochs and disciplines and aims to document the world's knowledge from a neutral point of view. However, the narrow diversity of the Wikipedia editor community has the potential to introduce systemic biases such as gender biases into the content of Wikipedia. In this paper we aim to tackle a sub problem of this larger challenge by presenting and applying a computational method for assessing gender bias on Wikipedia along multiple dimensions. We find that while women on Wikipedia are covered and featured well in many Wikipedia language editions, the way women are portrayed starkly differs from the way men are portrayed. We hope our work contributes to increasing awareness about gender biases online, and in particular to raising attention to the different levels in which gender biases can manifest themselves on the web.

"Assessing political conversations in social media requires a deeper understanding of the underlying practices and styles that drive these conversations. In this paper, we present a computational approach for assessing online conversational practices of political parties. Following a deductive approach, we devise a number of quantitative measures from a discussion of theoretical constructs in sociological theory. The resulting measures make different - mostly qualitative - aspects of online conversational practices amenable to computation. We evaluate our computational approach by applying it in a case study. In particular, we study online conversational practices of German politicians on Twitter during the German federal election 2013. We find that political parties share some interesting patterns of behavior, but also exhibit some unique and interesting idiosyncrasies. Our work sheds light on (i) how complex cultural phenomena such as online conversational practices are amenable to quantification and (ii) the way social media such as Twitter are utilized by political parties." (author's abstract)

Artificial Intelligence (AI) is increasingly being implemented in journalism, possibly leading to various fundamental changes within the field. Especially the forerunner countries U.S. and Germany make use of the technologies in several sub-sectors of reporting. While pioneer-studies exploring said implementation have focused on audience, as well as practitioners' perceptions of AI, a focus on the democratically crucial political journalism is lacking. Therefore, the given paper investigates how those working in the journalistic field in Germany and the U.S. evaluate AI-usage in political reporting. Scopes, contexts, and opportunities, as well as risks of the technologies are considered. Eleven interviews with experts from leading news organizations were conducted and analyzed using a qualitative content analysis, focusing on comparisons between the two countries. Results show varying strategies of AI implementation within the two countries, with election coverage being the predominant political topic reported on with the help of AI. Furthermore, the findings show that AI could possibly free journalists from routine tasks, and allows for more in-depth and large-scale research, which in turn could lead to an increase in the qualitative standard of political journalism. However, journalists also point towards ethical and economic concerns. Considering the results, directions for future research and the practice of journalism are discussed.

"Technology and Development in International Communication" published on by Oxford University Press.

New technologies are often radical innovations that change current activities across different areas of social and economic life. At the beginning of the 21st century, some of these technologies are information and communications technology (ICT), nanotechnology, biotechnology, robotics, and artificial intelligence. These innovations stimulate new opportunities for the production, distribution, and consumption of goods and services, and thus can help solve social problems. But they also cause new social risks and inequalities.