Our Guests

Kees Van Berkel

Kees van Berkel is an Assistant Professor of AI Ethics at the Institute for Logic and Computation at TU Wien. His research and teaching focus intersects at symbolic AI, ethics, and norm systems. It includes the development of logical methods for reasoning with norm codes, the study of explanations in AI, the modelling of conflict-resolution methods for norm and value conflicts, and the logical and philosophical analysis of meta-ethical principles. A shared characteristic of these topics is the interdisciplinarity of the research. Before joining TU Wien in 2024, Kees completed his B.A. in philosophy and M.Sc. in logic at the University of Amsterdam, obtained his Ph.D. in computer science at TU Wien, and worked as a postdoctoral researcher at the institute of philosophy, Ruhr University Bochum. He is currently a member of the Research Ethics Committee of TU Wien, co-coordinator of the special interest group AI Ethics at the Center for Artificial Intelligence and Machine Learning (CAIML) and a key researcher of the FWF-funded Cluster of Excellence Bilateral AI within the research modules Ethical AI Systems and Explainable A.

Alexander Pretschner

Alexander Pretschner studied computer science at RWTH Aachen and at the University of Kansas where he was a Fulbright grant recipient. After obtaining his doctorate from the Technical University of Munich (TUM), he worked as a senior researcher at ETH Zurich for five years. Within the framework of the Fraunhofer Attract Program he then moved on to head a research group at the Fraunhofer Institute for Experimental Software Engineering in Kaiserslautern. Parallel to this he was an adjunct associate professor at TU Kaiserslautern. Before joining TUM as a full professor in 2012, Professor Pretschner was a full professor at Karlsruhe Institute of Technology. Prof. Pretschner is the founding director of the Bavarian Research Institute for Digital Transformation. Since 2016, he has served as scientific director, and since 2019, as a spokesman of the scientific board of fortiss, the Bavarian state research institute for software-intensive systems and services.

Marta Sabou

Marta Sabou is a Professor for Information Systems and Business Engineering at the Department for Information Systems and Operations Management at the Vienna University of Economics and Business (WU Wien). Prior to this she was an FWF Elise-Richter Fellow at TU Wien. At TU Wien, she lead the Semantic Systems Research Lab which performs foundational and applied research in the area of information systems enabled by semantic (web) technologies. She has also held positions as Research Fellow at the Knowledge Media Institute (Open University, UK), Assistant Professor at the Department of New Media Technology (MODUL University, AT) and Key Expert in Semantic Technologies (Siemens). Her work is situated at the confluence of Semantic Web and Human Computation research areas. She is an accomplished academic (over 100 peer-reviewed papers, h-index 45) and takes an active role in the Semantic Web research community. Marta Sabou is a Key Researcher in the FWF Cluster of Excellence Bilateral AI, and she co-coordinates the WWTF Vienna Doctoral College on Digital Humanism.

Markus Schedl

Markus Schedl is a Professor at Johannes Kepler University (JKU) Linz, Austria, affiliated with the Institute of Computational Perception, where he leads the Multimedia Mining and Search (MMS) group. He also heads the Human-centered Artificial Intelligence (HCAI) group at the Linz Institute of Technology (LIT) AI Lab. His areas of expertise include recommender systems, information retrieval, algorithmic fairness, user modeling, machine learning, natural language processing, multimedia, data analysis, and web mining. Markus Schedl holds a degree in Computer Science from TU Wien and a PhD from JKU Linz. In addition, he completed studies in International Business Administration at the Vienna University of Economics and Business (WU Wien) and the University of Gothenburg (School of Business, Economics and Law), earning a Master’s degree. He has led and co-led numerous research projects funded by the Austrian Science Fund (FWF), the Austrian Research Promotion Agency (FFG), and the European Commission (EC). His collaborations extend to industry partners such as Siemens, Spotify, and Deezer.

Abstracts

Alexander Pretschner: Why GenAI won’t Replace Software Engineers

Generating code with LLMs is surprisingly and increasingly powerful, prompting the question if we can expect humans to be out of the loop anytime soon. My answer is no to replacement for professional software engineers (and trivially yes to assistance) – and something in-between for non-professionals writing software. The argument is twofold and relies on two necessary distinctions: that software engineering is not just programming; and that software engineering ranges from writing scripts over implementing websites to building complex interconnected cyber-physical systems. Software is a design artifact that embodies a sequence of many architectural and technical decisions – traditionally taken (hopefully explicitly!) by engineers who understand and design the trade-offs. That is, some human needs to say what they want and which option they prefer – and this crucial notion of “intent” cannot the realm of machines. Secondly, and also depending on the context, software development projects often fail because it is outright impossible to state the requirements upfront. This is also true for the precise criteria to be applied in every individual design decision. Agile software development processes embody that observation into an incremental process where what one wants is fully understood only while the system is built. Engineers are needed to understand and take the decisions! A discussion of the influence of risk classes and productivity gains rounds off the argument.

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