The BIFOLD summer school will take place from 20-24 June 2022 at the Weizenbaum Institute for the Networked Society (near Zoo station). It will focus on the latest ethical considerations in machine learning and data management by offering lectures and workshops on two main tracks. The school is designed for doctoral students of the BMBF‘s network of AI competence centres and organized by the BIFOLD Graduate School in collaboration with the Ethics in Residence Program with researchers of the Weizenbaum Institute for the Networked Society – the German Internet Institute.
The summer school complements technological research on artificial intelligence (AI) within the AI competence centres with ethical aspects of explainability and sustainability. It is part of the Ethics in Residence program. The program includes multiple hands-on workshops to advance individual research projects, several guest lectures including Q&A, a panel discussion, and Ph.D. student presentation sessions with expert jury feedback. The summer school offers two tracks on explainable deep neural networks (XNN) and sustainable AI (SAI) for more specialized training of the doctoral students. All of BIFOLD’s PhD students are invited to participate. In addition BIFOLD offers places for the PhD students of the German AI competence centre network (ML2R, MCML, TUE-AI, ScaDS, DFKI).
Summer School Website
INVITED INTERNATIONAL EXPERTS
International expert researchers with backgrounds in computing within limits, disaster research, and COVID-19 data research are joining the summer school as speakers and are reachable for individual feedback.
Daniel Pargman, Ph.D.
KTH Royal Institute of Technology, Stockholm, Sweden
Teresa Cerratto Pargman, Ph.D.
Stockholm University, Sweden
Yuya Shibuya, Ph.D.
The University of Tokyo, Japan
Raphael Sonabend, Ph.D.
Imperial College London, UK & University of Kaiserslautern, Germany
Rainer Mühlhoff, Ph.D.
Osnabrück University, Germany
Enrico Costanza, Ph.D.
University College London, U
Track XNN focuses on evaluating interpretable machine learning to provide students with the ability to empirically validate claims about interpretability:
- Critical review of XAI methods: taxonomies of XAI approaches, review of explanation goals, user benefits and current results from user studies
- Rigorous methods for validating explanation methods with users: interdisciplinary methodological training, suitable evaluation datasets, user tasks and study designs, participant recruitment, validity, and reproducibility considerations
Track SAI emphasizes on ecological and socio-political aspects of AI to understand how AI and data can contribute to action in the name of sustainability transition:
- Sustainability in research and policies: What is sustainability? United Nations SDGs, COVID-19, critical thinking on AI, environmental monitoring, sustainable smart cities and communities
- SAI approaches and methods: data feminism, digital civics, computing within limits, citizen science, social media data, and mixed methods.
The complete program can be found here.
Participants are expected to attend the entire program, arrival from 19. June, departure 25. June 2022. There is no tuition fee.
Please get in touch with us in case you need child care.
Program venue: Weizenbaum Institute for the Networked Society
Accomodation: Hampton by Hilton Berlin City West, in walking distance to Weizenbaum & TU Berlin, in the heart of Berlin, with the nearby Tiergarten Park providing plenty of greenery
Please send one pdf-file, including your CV, an abstract of your (preliminary) Ph.D. project, and a short motivation message describing why you would like to participate and what you would like to learn during the summer school, to email@example.com.
Application deadline is 30. April 2022.
Doctoral Researcher, Research Group “Responsibility and the Internet of Things”, Weizenbaum Institute for the Networked Society & TU Berlin, Germany
Dr. Stefan Ullrich
Weizenbaum Institute for the Networked Society, Berlin, Germany
Prof. Dr. Volker Markl
Prof. Dr. Klaus-Robert Müller