44th German Conference on Artificial Intelligence, September 27 – Oct 1, 2021: Berlin, Germany

Special Meetings


CLAIRE National Meeting @ KI 2021

Christoph Benzmüller, Philip Slusallek, Janina Hoppstädter, Daniel Krupka

Trusted AI — Unattainable vision or social mission? Opportunity or burden? How can it be implemented? Such questions are the focus of the first meeting of the German chapter of CLAIRE, the Confederation of Laboratories for AI Research in Europe. Trusted AI puts a special emphasis on providing (verifiable) guarantees for the correct functioning of modern AI-based systems, and in this sense it significantly strengthens the more unspecific notion of Trustworthy AI . The meeting brings CLAIRE members together with representatives from industry, politics and academia and offers all interested parties the opportunity to get in touch with CLAIRE, learn about CLAIRE's mission and discuss the topic of Trusted AI.
A separate registration, free of charge, is necessary to join this event. Please follow the registration link.


The newly established task force KiS aims at initiating and establishing the discourse of AI experts with experts on computer science education on central topics and methods of AI and educational concepts for introducing them in school. The kick-off meeting at KI 2021 invites all members of the AI community interested in teaching AI. The meeting will start with short highlight talks from members of the KiS steering committee. Teachers and education managers interested in AI education has been invited. In an open discussion, we plan to identify core points of interest and action points. Attendees are encouraged to become a member of the AK KiS.



7th Workshop on Formal and Cognitive Reasoning (FCR-2021)

Christoph Beierle, Marco Ragni, Frieder Stolzenburg, and Matthias Thimm

Information for real life AI applications is usually pervaded by uncertainty and subject to change, and thus demands for non-classical reasoning approaches, possibly in combination with machine learning methods. Therefore papers are solicited that provide a base for connecting formal-logical models of knowledge representation and cognitive models of reasoning and learning, addressing formal and experimental or heuristic issues.


Computational Intelligence (cancelled)

Johannes Fähndrich and Sebastian Ahrndt

We apply Artificial Intelligence in ever more application domains but AI still lacks the adaptability and resilience of most biological systems. One of those gaps is probabilistic reasoning and decision making. Nature as a paragon brings fuzzy reasoning, neuronal networks, and learning together, e.g., to decide on a fight-or-flight response. The inspiration of Computational Intelligence originating from natural systems, therefore, aims at closing this gap with theoretical results as well as applying them in real-world applications.Like the IEEE Computational Intelligence Society which describes its focus as "the theory, design, application, and development of biologically and linguistically motivated computational paradigms emphasizing neural networks, connectionist systems, genetic algorithms, evolutionary programming, fuzzy systems, and hybrid intelligent systems in which these paradigms are contained" the Workshop on Computational Intelligence aims to bring together scientists and specialist form industry to tackle some of the challenges of AI and their application.


Trustworthy AI in the Wild

Barbara Hammer, Malte Schilling, and Laurenz Wiskott

Artificial Intelligence (AI) is entering more and more our lives with the goal of supporting and helping us as humans in our homes, at our workplace, and as a society as such. As we want to benefit from these technologies, at the same time we want to be able to trust how AI technologies operate and to be able to understand their decisions. The goal of trustworthy AI, therefore, is to offer intelligent methods and agents that, on the one hand, produce robust and adaptive behavior in real world scenarios, and, on the other hand, are transparent in their decision making as they are able to justify and explain their decisions.
Trustworthy AI aims for technologies that not only provide solutions to an earlier defined task, but that as well allow for insight on the functioning of the underlying system. Why did the system acted in a certain way and did not choose a different solution? Which features were important for the decision and how sure is the system of its choice, i.e. can I trust this decision? The workshop aims, first, at understanding Machine Learning based approaches towards explainable AI solutions. Secondly, a focus of the workshop is on how we can make AI solutions more trustworthy.
The workshop will be hosted on zoom, please follow the organizers' instructions on the workshop's website get zoom meeting credentials.


WLP 2021 - 35th Workshop on (Constraint) Logic Programming

Ulrich John, Petra Hostedt, and Mario Wenzel

WLP 2021 provides a forum for exchanging ideas on declarative logic programming, constraint logic programming, non-monotonic reasoning, knowledge representation, and facilitates interactions between research in theoretical foundations and the design, implementation and application of (constraint) logic-based systems. Declarative approaches – especially in combination with other AI technologies and disruptive non-AI technologies – have an increasing relevance for digitalization projects in many sectors.
The workshop will be hosted on zoom, please follow the organizers' instructions on the workshop's website get zoom meeting credentials.


Humanities-Centred AI (CHAI)

Sylvia Melzer, Stefan Thiemann, and Jost Gippert

AI can support research in the Humanities making it easier and more efficient. It is thus essential that AI practitioners and Humanities scholars take a Humanities-centred approach to the development, deployment and application of AI methods for the Humanities.


Planen und Konfigurieren (PuK) @ KI 2021

Jürgen Sauer and Stefan Edelkamp

The PuK workshop has its focus on Artificial Intelligence used in planning, scheduling, design and configuration. With the actual hype in Artificial Intelligence applications these application domains are even more interesting. So the PuK provides a forum for presentation and discussion on these topics.


Artificial Intelligence and Ethics

Andreas Hein, Mark Schweda, Silke Schicktanz, Stefan Teipel, and Thomas Kirste

The omnipresence of intelligent machines poses substantial ethical and legal challenges. Therefore, in order, to ensure the beneficence of autonomous agents towards humans (and other machines), we need to introduce ethical and legal mechanisms that govern and align actions executed by AI-based algorithms according to our societal ethical and moral norms. The aim of this workshop "Artificial Intelligence and Ethics" is therefore primarily to initiate an interdisciplinary dialogue between the individual disciplines, such that the state of research of the respective discipline can be understood by the participants and conceptual ambiguities, which exist especially in interdisciplinary projects, can be cleared up. As organisers we hope that our workshop will help to establish a platform for interdisciplinary collaboration and will pave the way to find a common ground among these disciplines such that a roadmap towards ethics-aware Artificial Intelligence can be proposed.
The workshop will be hosted on zoom, please contact the organiser (muhammad.shaukat (at) to get zoom meeting credentials.



Adversarial Robustness in Deep Learning (cancelled)

Dipanjan Sarkar and Sayak Paul

This tutorial focuses on adversarial robustness in deep learning.We will cover its importance, different types of adversarial attacks, and some approaches to training neural networks with adversarial regularisation. The nature of this tutorial is going to be hands-on, with examples being showcased for each type of adversarial attack, how to perform these attacks and mitigate them with techniques implemented in TensorFlow.


In this half-day tutorial, we'll use real-world ECG datasets to demonstrate deep learning approaches in MATLAB to show sequence-to-sequence classification frameworks for 1-D signals. The target audience of this tutorial are practitioners of artificial intelligence interested in workflow discussions based on hands-on examples. The presented workflows generalize beyond ECG datasets to other types of signals and time-series data. There are no prerequisites other than general knowledge of deep learning methodologies.