Zum Schreiben mit der Hand - Kokew, Stephan Matthias

Graphical AI workflow modelling: Identifying relevant competencies in AI-based automation of business processes - Gräßler, Iris; Özcan, Deniz (AHFE International)
This research investigates how Artificial Intelligence (AI) can be systematically integrated into existing business processes by combining suitable competencies with graphical AI workflow modelling. While AI offers a high potential for automation and increased efficiency, its implementation often fails due to a lack of interdisciplinary competencies that bridge the gap between domain expertise and IT know-how. Low-code platforms and visual modelling tools are increasingly recognised as enablers, empowering non-programmers to intuitively create graphical AI- based workflows. Nevertheless, specific competencies are required to realise the full potential of AI, the domain specific knowledge and align technical understanding with AI capabilities. The paper reviews the state of the art in AI-driven business process automation and competencies for visual low-code approaches. It then presents a practical solution to identify and systematise essential competence areas. Based on this, a practical competence model is developed to support the design of user-friendly, AI-enabled workflows. This is tested in a practical application context — emergency management — where it supports critical decision-making processes and is validated through expert feedback. The study concludes by offering actionable recommendations to help organisations foster the necessary competencies and methods for competently integrating AI into their digital processes.

Automation 2035 - Gräßler, Iris; Özcan, Deniz; Tusek, Alena Marie; Bilgic, Attila; Lange, Christian; Stich, Christian; Maul, Christine; Heizmann, Michael; Weyrich, Michael; Dessel,, Sascha; Miny, Torben; Jumar, Ulrich
Executive summary Die vorliegende Zukunftsstudie „Automation 2035“ gibt einen Ausblick auf die Entwicklung der Automatisierungstechnik in den nächsten 10 Jahren. Neben der Beschreibung von Trends wie Kreislaufwirtschaft, Automatisierung der Märkte, Biologisierung, autonome Systeme und Robotik sowie IT-Sicherheit wird die zu erwartende Veränderung in der Bildung beschrieben. Dazu verwenden wir Methoden der Zukunftsforschung und arbeiten mit der Szenarientechnik, um Zukunftsperspektiven der Automation aufzuzeigen. Personas werden eingesetzt, um die zukünftigen Entwicklungen plastisch aus den Augen der Personen im Jahr 2025 und in der Zukunft im Jahr 2035 zu beschreiben. Schlüsselthemen und Trends: ... ... Inhalt Executive summary 1 1 Einführung 3 2 Zukunftsfelder für die Automatisierungstechnik 2035 4 2.1 Kreislaufwirtschaft 4 2.2 Automatisierung der Märkte 7 2.3 Biologisierung 8 2.4 Autonome Systeme und Robotik 10 2.5 Security 12 2.6 Veränderung der Ausbildung 13 3 Szenario der Automation 2035 16 4 Personas 18 4.1 Unternehmer 18 4.2 Ingenieurin 19 4.3 Schüler 20 5 Thesen und Ausblick 22 Methodik 24 Autorenteam 25 Schrifttum 26...

CRC: Compressed Reservoir Computing on FPGA via Joint HSIC LASSO-based Pruning and Quantization - Jafari, Atousa; Ghasemzadeh Mohammadi, Hassan; Platzner, Marco (WiPiEC Journal - Works in Progress in Embedded Computing Journal)
While reservoir computing (RC) networks offer advantages over traditional recurrent neural net- works in terms of training time and operational cost for time-series applications, deploying them on edge devices still presents significant challenges due to re- source constraints. Network compression, i.e., pruning and quantization, are thus of utmost importance. We propose a Compressed Reservoir Computing (CRC) framework that integrates advanced pruning and quantization techniques to optimize throughput, latency, energy efficiency, and resource utilization for FPGA- based RC accelerators.We describe the framework with a focus on HSIC LASSO as a novel pruning method that can capture non-linear dependencies between neurons. We validate our framework with time series classification and regression tasks, for which we generate FPGA accelerators. The accelerators achieve a very high throughput of up to 188 Megasamples/s with a latency of 5.32 ns, while reducing resource utilization by 12× and lowering the energy by 10× compared to a baseline hardware implementation, without compromising accuracy.

Ultra-Low Latency and Extreme-Throughput Echo State Neural Networks on FPGA - Jafari, Atousa; Platzner, Marco (Lecture Notes in Computer Science)

No Student Should Be an Island: A Peer-Approach to Decoding and Disrupting - Schmöckel, Sabrina; Scharlau, Ingrid (Transformative Dialogues: Teaching and Learning Journal)
his article describes a new student-based approach to Decoding and Disrupting. This approach consists of an educational programme that works with a multidisciplinary group of undergraduate students, so-called Culture Fellows. In the programme, the students learn about theories on disciplinary cultures and their practices, Decoding the Disciplines, and communication. The programme focuses on the implicitness of disciplinary practices and how to explore them, i.e., it seeks to address the importance of making disciplinary practices, norms, and values more accessible to students. Within the programme, the Culture Fellows use a student-based variant of the Decoding the Disciplines Paradigm that we call ‘Culture Quest’. The Culture Quest supplies students with the tools to question, explore, and decode their respective disciplines and practices. Disciplinary practices often remain implicit because lecturers, with their wealth of experience and expertise in their discipline, may be operationally blind and thus no longer aware of the fact that certain practices might need to be explained. This lack of explanation or explicitness can lead to students feeling bewildered, confused or puzzled. The Culture Fellows and in particular the Culture Quest can encourage dialogue about and exploration of disciplinary cultures and their practices and can thus allow students to grasp the implicit cultural norms and expectations within their respective disciplines more clearly. The Culture Fellows and the Culture Quest provide students – and maybe even lecturers – with opportunities to engage with and reflect on teaching and learning strategies and practices.

Nachwuchs-Café: Symposium zur interdisziplinären Vernetzung von Doktorand/ innen und Postdocs - Rumlich, Dominik; Matz, Frauke (Grenzen, Grenzräume, Entgrenzungen)

Reliabilität - Rumlich, Dominik (Leistungsmessung, Evaluation und Feedback im Fremdsprachenunterricht)

Lernen in Bewegung: Warum Aktivität für Motivation und Schulerfolg entscheidend ist - Satzinger, Nicole

Hör mal, wer da spricht – Eine dialogische Perspektive auf studentische Äußerungen zu Fachkulturen - Schmöckel, Sabrina (die hochschullehre)

Qualifikationen für Bewegung, Spiel und Sport im Ganztag an Grundschulen. Einblicke in Schulen in Nordrhein-Westfalen und Niedersachsen - Noetzel, Ida; Fögen, Yvonne; Satzinger, Nicole; Miriam, Kehne (sportunterricht)

Possible Fashion Images: Operative Ekphrasis and the Reduction of Fashion Through Multimodal AI - Brachtendorf, Charlotte (Image: The Interdisciplinary Journal of Image Sciences)
With the rise of multimodal AI tools, such as DALL-E, Midjourney, or Stable Diffusion, it has never been easier and faster to produce compelling fashion images. While the proliferation of AI-generated fashion images can be seen as the ultimate triumph of the fashion image over both fashion text and fashionable garments, this paper critically examines how these images are produced, what exactly they show, and ultimately, how this impacts our understanding of fashion. Building on current research on multimodal AI, specifically text-to-image models, I argue that AI-generated fashion images are produced through textual means, that is, through “operative ekphrasis” (Bajohr 2024: 83). This means that the generation of fashion images created via multimodal AI is based on textual prompts that extract statistically probable images from a latent space, which, in turn, is the result of previously indexed and labeled image-text pairs. Because the indexing of images requires a reduction of complexity, images generated through multimodal AI are often generic. In the case of fashion images, this is reflected in the lack of texture and the reproduction of fashion photography’s conventions. As fashion photography is not necessarily a representation of ‘the world’ or even fashionable garments, it resembles AI-generated images more than other photographic genres. AI-generated fashion images are then not images of fashionable garments, but images about fashion images—a statistically probable permutation of fashion photographs from the past (cf. Meyer 2023: 108). As such, AI-generated fashion images are not only the product of a mediated collective imaginary but also feed back into it. The view on fashion shaped by AI-generated fashion images is then based on reduction and stylized normativity.

Ressourceneffiziente Fertigung von Leichtbaustrukturen - Weck, Daniel; Müller-Pabel, Michael; Krampitz, Thomas; Hecker, Christine; Selvaggio, Alessandro; Gilich, Julian; Gude, Maik; Lieberwirth, Holger; Tekkaya, A. Erman; Meschut, Gerson (Werkstattstechnik online)
Zur Steigerung der Ressourceneffizienz technischer Komponenten sind neben dem Leichtbau insbesondere neuartige Fertigungstechnologien und Prozessketten mit geschlossenen Stoffkreisläufen von großer Bedeutung. Im Beitrag werden am Beispiel einer Demonstratorstruktur aus hybriden Leichtbauprofilen (Aluminium und faserverstärktes Polyamid) technisch-technologische Lösungsoptionen für die gesamte Prozesskette inklusive des Recyclings vorgestellt und in Pilotversuchen bewertet.

An Empirical Examination of the Evaluative AI Framework - Kornowicz, Jaroslaw (International Journal of Human–Computer Interaction)

Hausdorffness of certain nilpotent cohomology spaces - Januszewski, Fabian; Sun, Binyong; Ying, Hao (Journal of Functional Analysis)
Let $(π,V)$ be a smooth representation of a compact Lie group $G$ on a quasi-complete locally convex complex topological vector space. We show that the Lie algebra cohomology space $H ^\bullet(\mathfrak{u}, V)$ and the Lie algebra homology space $H_\bullet(\mathfrak{u}, V)$ are both Hausdorff, where $\mathfrak{u}$ is the nilpotent radical of a parabolic subalgebra of the complexified Lie algebra $\mathfrak{g}$ of $G$.

Rational quiver representations: tame and wild - Januszewski, Fabian (arXiv:2510.00924)
We study representation finite $K$-rational quivers over fields of characteristic $0$ and their indecomposable representations, exploiting that all Brauer obstructions for descent of representations are trivial in this case. Contrasting the tame case, we give an example of a simple quiver of wild representation type, where we realize every possible Brauer obstruction of a given Galois extension $L/K$ in the category of quiver representations over $L$.

"One-sided, prejudiced view of Germans": Das Ressentiment als literarischer Ausdruck jüdischer Antiversöhnlichkeit bei Olga Grjasnowa und Dana Vowinckel - Spener, Anna Maria (Rückkehr des Ressentiments? Stereotype in Medien, Kulturphilosophie und Literatur (Sonderheft der Zeitschrift für deutsche Philologie))

Algorithmische Kulturen des Pflanzensammelns? Das Beispiel der Computerisierung des Botanischen Gartens und Botanischen Museums Berlin - Alpsancar, Suzana (Algorithmische Wissenskulturen. Der Einfluss des Computers auf die Wissenschaftsentwicklung)

Healthy Distrust in AI systems - Paaßen, Benjamin; Alpsancar, Suzana; Matzner, Tobias; Scharlau, Ingrid (arXiv)
nder the slogan of trustworthy AI, much of contemporary AI research is focused on designing AI systems and usage practices that inspire human trust and, thus, enhance adoption of AI systems. However, a person affected by an AI system may not be convinced by AI system design alone---neither should they, if the AI system is embedded in a social context that gives good reason to believe that it is used in tension with a person’s interest. In such cases, distrust in the system may be justified and necessary to build meaningful trust in the first place. We propose the term healthy distrust to describe such a justified, careful stance towards certain AI usage practices. We investigate prior notions of trust and distrust in computer science, sociology, history, psychology, and philosophy, outline a remaining gap that healthy distrust might fill and conceptualize healthy distrust as a crucial part for AI usage that respects human autonomy.

From Explaining to Diagnosing: A Justice-Oriented Framework of Explainable AI for Bias Detection - Fahimi, Miriam; State, Laura; Kasirzadeh, Atoosa (Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society)
Explainable AI (XAI) methods can support the identification of biases in automated decision-making (ADM) systems. However, existing research does not sufficiently address whether these biases originate from the ADM system or mirror underlying societal inequalities. This distinction is important because it has major implications for how to act upon an explanation: while the societal bias produced by the ADM system can be algorithmically fixed, societal inequalities demand societal actions. To address this gap, we propose the RR-XAI-framework (recognition-redistribution through XAI) that builds on a distinction between socio-technical and societal bias and Nancy Fraser's justice theory of recognition and redistribution. In our framework, explanations can play two distinct roles: as a socio-technical diagnosis when they reveal biases produced by the ADM system itself, or as a societal diagnosis when they expose biases that reflect broader societal inequalities. We then outline the operationalization of the framework and discuss its applicability for cases in algorithmic hiring and credit scoring. Based on our findings, we argue that the diagnostic functions of XAI are contingent on the provision of such explanations, the resources of the audiences, as well as the current limits of XAI techniques.