Artificial Intelligence (AI) and Machine Learning (ML) methods are becoming increasingly important in both science and society. In climate science - where complex biophysical and societal processes interact across diverse temporal and spatial scales, and datasets are often large, heterogenous and incomplete - AI and ML methods offer new powerful solutions.
In our last session for this year Finn Müller-Hansen from Potsdam Institute for Climate Impact Research (PIK) will present approaches to use AI for evidence synthesis.
Finn Müller-Hansen is a senior researcher in the Evidence for Climate Solutions group at Potsdam Institute for Climate Impact Research (PIK). He applies machine learning, natural language processing, scientometrics and network theory to study the interplay of social, economic, and political factors in climate mitigation and energy transitions. His current work focuses on innovation and public perceptions of carbon removal. Finn holds a PhD from Humboldt University of Berlin and a MSc in Physics from the Freie Universität Berlin.
For online participation, a registration is necessary.
Please register here.
Title:
Evidence synthesis with AI: Building trusted knowledge for climate action
Abstract:
Rigorous assessments of the state of knowledge about climate solutions is crucial for decision makers in times of eroding trust in institutions. While the medical field has developed and adopted standardized methods for evidence synthesis to provide trusted and proven knowledge for practitioners, such efforts are only slowly picked up in climate mitigation research. In this talk, I show how advances in AI can help to accelerate and scale evidence synthesis for climate mitigation, while ensuring high quality standards through rigorous evaluation. I show AI applications in evidence synthesis from research projects on climate technologies and policies and discuss current limitations of AI systems for high-quality research synthesis.
The monthly AI seminar at IIASA features global experts in the field of AI and ML who will showcase the newest methodological advancements and applications in the field. Through a series of invited talks, the seminar showcases cutting edge research with the aim of strengthening AI and ML expertise at IIASA and to foster external collaborations. Additionally, it serves as an institute-wide platform for discussions and knowledge exchange across programs and working groups to spark new ideas and innovations.
As an initiative from the ECE/ ICI Theme on Extreme Weather and Climate Dynamics, this seminar is designed for both experts already integrating AI and ML into their workflows and those eager to expand their knowledge in these fields.
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