Leopoldina Prize for Niki Kilbertus
The German National Academy of Sciences Leopoldina honors Helmholtz Munich AI scientist Niki Kilbertus for his teaching and research achievements in the field of ethical machine learning with the Leopoldina Prize for Young Scientists 2024.
The Academy has been awarding the Leopoldina Prize for Young Scientists since 1993. It is awarded annually to scientists with remarkable scientific achievements who completed their doctorate no more than 5 years ago. The selection group is supranational, and the prize endowed with 5,000 euros. This year, the prize will be handed over to Helmholtz Munich scientist Niki Kilbertus.
Fair and transparent AI
Prof. Dr. Niki Kilbertus investigates ethical machine learning (ML) systems at Helmholtz Munich and the Technical University of Munich (TUM). ML is playing an important role in more and more areas of life, for example in medical diagnostics, chatbots or personalized suggestions from streaming providers. However, when ML makes decisions about people in sensitive areas - for example in job interviews or when checking creditworthiness - fairness and transparency must be ensured. Niki Kilbertus is one of the pioneers who have formalized causal concepts of fairness in automated decision-making processes. In order to make decisions, ML must be trained with data that relates them to each other. In his research, Kilbertus places particular emphasis on the cause-and-effect relationships from observational data, the causal inferences. These aim to distinguish genuine causal relationships from mere correlations in data. In the further development of the system, ML is to be enabled to free itself from erroneous assumptions and thus make appropriate decisions. The research aims to develop AI systems that are not only highly accurate, but also ethical, transparent and robust. This development is essential to ensure that AI benefits society as a whole and becomes more trustworthy while minimizing risk and bias.
About the scientist
Prof. Dr. Niki Kilbertus studied mathematics and physics at the University of Regensburg from 2010 to 2016, spending time abroad at Harvard University/USA in 2014 and at Stanford University/USA from 2015 to 2016. He received his doctorate from the University of Cambridge/UK in 2020. Since 2021 he is Professor for Ethics in Systems Design and Machine Learning at TUM in the Department of Computer Science and since 2020 Helmholtz AI Research Group Leader at Helmholtz Munich. He received the Cambridge - Tübingen PhD Fellowship in Machine Learning during his doctoral thesis and was awarded AI Newcomer of the Year by the Federal Ministry of Education and Research and the German Informatics Society in 2019.
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