The second BIFOLD Weizenbaum Summer School took place from September 11-15, 2023, at the TU Campus EUREF in Berlin Schöneberg. The school focused on the overarching theme of "AI and environmental sustainability", exploring the complex relationship between AI and sustainability, in particular AI or machine learning as tools for sustainable development. The event was jointly organized by the BIFOLD Graduate School and the research group "Digitalization, Sustainability and Participation" at the Weizenbaum Institute for the Networked Society in Berlin. Participants and speakers from BIFOLD, Lamarr, MCML (all from the network of German Centers of Excellence for AI), the Weizenbaum Institute, TU Berlin and other universities and research institutes in Germany and Europe discussed Machine Learning, Data Management and the impact of cutting-edge Artificial Intelligence on society and sustainability.

The summer school gave young researchers from different scientific disciplines the unique opportunity to learn about other fields of work and methods thereby gaining a new perspective on their own work. They listened to keynote speeches from areas of social sciences, machine learning and data management and worked together in mixed groups on the development of sustainable AI applications.

Keynotes on Balancing Business, Sustainability, and Social Impact in AI and E-Commerce

Keynotes focused on the question of how the economic interests of companies in e-commerce can be reconciled with sustainability goals through efficient optimization of recommendation systems (Sebastian Schelter, University of Amsterdam, Netherlands), the cutting-edge XAI technique known as Concept Relevance Propagation (CRP), which explains individual predictions in terms of human-understandable concepts (Wojciech Samek, Fraunhofer Heinrich Hertz Institute & BIFOLD) and on power asymmetries, exploitation and social inequality and the dimensions of sustainability in the context of today's AI (Rainer Mühlhoff, Osnabrück University).

Exploring the Intersection of AI, Sustainability, and Society: From Cutting-Edge Technologies to Ethical Considerations

Participants could choose from different tracks to dive deeper into specific topics. One track covered Machine Learning state-of-the-art topics, such as XAI, efficient Machine Learning, Generative Modelling and Quantum Chemistry. In the Data Management track participants were taught resource-aware ML, Data Management for the Internet of Things, DM and ML for Earth observation and Urban Sustainability. The track focusing on the societal impact covered the intricate relationship between AI and capitalism and the ethics of digitization, where they could design, build and pitch sensor systems and discuss ethical issues using case studies.

Lectures focused on how to use AI to improve environmental sustainability and the risks of technological approaches. Tabea Rößner, Head of the Committee for Digital Affairs and a member of the Committee for the Environment, Nature Conservation, Nuclear Safety, and Consumer Protection and member of the German Bundestag belonging to the Green Party, shared insights on recent political obstacles and answered the critical and interested questions of the Summer School participants.

Final highlight was the presentation of the group work results. Throughout the week, the participants worked in interdisciplinary teams on creative ideas and concepts for solving environmental problems with AI technologies also considering the social perspective. The teams designed and worked on projects focusing on the reduction of energy consumption in system performance, AI-supported waste sorting based on crowdsourcing, rooftop detection for solar energy promotion, the use of AI to enforce the High Seas Treaty, a re-integration system for electronic waste and a project on how to cool cities with the help of machine learning.
An exciting and inspiring week - we extend our heartfelt thanks to all participants for their commitment and to all organizers for their preparation.