We interweave Critical and Computational Approaches in Research, Teaching and Transfer


Almost every field of human endeavor nowadays requires some form of computer support and algorithmic expertise.

At the same time, the unreflected use of existing techniques and tools can only insufficiently exploit their full potential or, in the worst case, even lead to major damage. Over the years this gap has become a critical brake on innovation. Based on sustainable technological foundations, C3S with its multi- and trans-disciplinary approach is set out to narrow this gap by exploring the interactions between (1) computation of the critical, (2) computational critique, and (3) critique of the computational.


The Center for Critical Computational Studies will be an educational hub for the transfer of knowledge between the disciplines. It will be a place to acquire basic and advanced computational skills, as well as insights regarding the benefits and implications of computational methods for science and society. The connection of previously distant academic areas through data and methodology will lead to new research questions, new modes of teaching, and act as an ideal setting to emanate Critical Computational Literacy as a future skill.

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The research topic Critical Computational Studies will be embedded into the study programs and teaching profiles at GU, focusing on Critical Computational Literacy.

Teaching in these areas is intended to expand understanding of complex relationships in socio-technical systems, and to provide specific, computational skills and knowledge. During the founding phase, we will establish several modules in cooperation with colleagues affiliated or associated with C3S. Possible topics include (but are not limited to):

  • Interdisciplinary Introduction to Bias, Discrimination, Power & Computing

  • Interdisciplinary Introduction to Computer and Data Science

  • Interdisciplinary Introduction to Research Data Management and FAIR Principles

  • Interdisciplinary Introduction to Modelling of Complex Systems

For the choice of the pioneering modules, we aim for an open and participative procedure, involving students, lecturers, and GU "Fachbereiche", and close communication with our GU "Fachzentren". The newly established modules can, after the initial testing phase, be included in the current curricula of the different GU "Fachbereiche". To reduce strain on teaching resources and to optimally serve interests of the different partners and "Fachbereiche", we will evaluate current needs regarding modules in Critical Computational Literacy, and are open to offers of already existing and suitable modules.

We will further identify appropriate external modules and adapt them into the C3S curriculum, e.g. to cover basic programming skills.

We will investigate current departmental regulations and identify options for their harmonization and standardization, paving the way for joint modules of several "Fachbereiche", or for opening teaching modules at one "Fachbereich" for students from other "Fachbereiche".


C3S develops and establishes forms and structures of cooperation between different disciplines, as well as mutual (mulit-directional) interactions between research and teaching as well as between academia and society, politics, and the economy. This opens three fields of action:

  1. Computation of the Critical as a focus on transformation processes and dynamics of complex systems (science and research, society, politics, and economy)
  2. Computational Critique as a field of analysis and design (processing digi-gaps etc.) that considers dynamics of power.
  3. Critique of the Computational as a metaperspective on the transformation of society and research (through the analysis of new (inter-) organizational systems


< December 2023 >
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Virtual Talk with Anthony Lin

Prof. Dr. Anthony Lin, TU Kaiserslautern

Trustworthy Automated Reasoning on Complex Systems

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Critical phenomena and challenges emerging from dormancy

Interdisciplinary Workshop

Supported by

  • Fachgebiet Stochastik, Institut für Mathematik, FB 12, Goethe-University Frankfurt

  • C3S Center for Critical Computational Studies, Goethe-University Frankfurt

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Virtual Talk with Martin Mundt

Dr. Martin Mundt, TU Darmstadt

Lifelong Machine Learning as a Sustainable Foundation for Human-Aware AI

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Virtual Talk with Carina Prunkl

Dr. Carina Prunkl, Research Fellow at University of Oxford’s Institute for Ethics in AI

Noise - a flaw in algorithmic judgment?

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Past events of the last 3 months:

Virtual Talk with Jörg Noller

Jörg Noller, München / Leipzig

Digitale Aufklärung und künstliche Intelligenz

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Virtual Talk with Maximilian Weber

Dr. Maximilian Weber, Goethe-Universität Frankfurt

Large Language Models in the Wild: A Comparative Analysis of AI Discourse in Social and Traditional Media Post-November 2022

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Virtual Talk with Corinna Coupette

Dr. Corinna Coupette, Max-Planck Institute for Informatics, Saarbrücken.

Constructing Connected Worlds: Defining, Documenting, and Distributing Network Data across Disciplines

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Virtual Talk with Sandra Kiefer

Dr. Sandra Kiefer, University of Oxford and Jesus College Oxford.

The Combinatorial Side of Graph Neural Networks

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Virtual Talk with Christoph Burchard

Vortrag 23.10.23, 18:00-20:00 Uhr via ZOOM

Prof. Dr. Christoph Burchard

"Künstliche Intelligenz als Machtfrage: Das Beispiel ChatGPT"

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The Digital Administration of Justice: Brazilian-German Experiences (20.10.2023)

Workshop (TBC)

Justice and Former Chief Justice of the Constitutional Court of Brazil
Professor Luiz Fux
The Technological Transformation of Justice

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Virtual Talk with Danilo Dessi

Dr. Danilo Dessì , GESIS Leibniz Institute for the Social Sciences in Cologne, Germany

Scholarly Knowledge Graphs: the New Paradigm for Scholarly Information Representation

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Critical Computational Studies & Law: Towards a Research Agenda (Frankfurt a.M.)


Summer School on Algorithm Engineering for Network Problems (Potsdam)

Summer School

Organized in cooperation with DFG research unit ADYN and HPI Potsdam.

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Virtual Talk with Julian Gerstenberg

Dr. Julian Gerstenberg, Interim Professor of Stochastics at Philipps University Marburg

Probability Distributions in Machine Learning: Beyond Expected Values and Across Domains

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