As PSM rely increasingly on AI and large amounts of data to perform their work, it is important to look into the environmental impact of these technologies. What are the carbon and material footprints of AI-based applications? How do you minimize this impact while still being able to provide a quality public service to your audiences?
In this micro-workshop, co-organized by AIDI and the Sustainability for Public Service Media Group, on Thursday 10 March 13:00-15:00 CET, we explored these questions with leading experts on the subject from Imec, Warwick University, University of Zurich, and ETHZ.
This was an introductory session to a series of workshops throughout the year, which will dive deeper into specific AI technologies and how to reduce their footprint.
- Tackling Climate Change with Machine Learning – Raphaela Kotsch (University of Zurich, CH), Kai Jeggle (ETHZ, CH), Konstantin Klemmer (University of Warwick, UK)
- Energy-Efficient AI – Axel Nackaerts (Imec, Belgium)
- Structured group discussion and next steps
Raphaela Andrea Kotsch is a PhD student in Political Economy and Development at the University of Zurich. Her work lies at the intersection of climate policy, environmental economics and machine learning. She holds a BSc in Economics from Vienna University of Economics and Business and a MSc in Environmental Economics and Climate Change from the London School of Economics. At Climate Change AI she strives to bridge between economics, the computational and climate social sciences.
Kai Jeggle is pursuing a PhD at the Institute for Atmosphere and Climate at ETH Zurich. In his work he researches the formation of clouds and their impact on climate change using explainable machine learning methods. He holds a MSc in Computer Science and has industry experience from working in startups and consulting. At CCAI (Climate Change AI) he focuses on growing the community of enthusiasts interested in tackling climate change with machine learning.
Konstantin Klemmer is a PhD student in Urban Science and Computer Science at the University of Warwick and, as a visiting student, at New York University. He was also an Enrichment student at the Alan Turing Institute and a Beyond Fellow at TUM / DLR. Konstantin’s research focuses on the representation of spatial phenomena in machine learning methods. Beyond that, he is interested in the application of these methods in urban environments, tackling issues in crime or transportation. Konstantin is a board member of CCAI where he also leads the Communications Committee.
Axel Nackaerts is Program Manager Artificial Intelligence at Imec in Belgium. He obtained a PhD on Audio Digital Signal Processing from the Katholieke Universiteit Leuven in 2003. He was researcher at Imec, and moved to NXP Semiconductors in 2007, as System Architect for healthcare IoT products and Innovation Manager. In 2020, he returned to Imec where he acts as the bridge between software and hardware AI research. His main interests are sustainable computing for AI, cyber-physical systems, system of systems, and the global convergence towards the metaverse.