AI & medicine: safe systems and their certification

Carl Zeiss Foundation funds research project with five million euros

Modern deep-learning systems in healthcare have the potential to make diagnostic decisions of similar quality to treating physicians. However, there are concerns about the transparency, robustness, fairness and reliability of these systems. The project “Certification and Foundations of Safe Machine Learning Systems in Healthcare” by a research group at the University of Tübingen aims to address these issues. Potential trade-offs of various aspects (fairness, accuracy, interpretability, and privacy) as well as their ethical implications are being explored using concrete applications in the healthcare sector. The Carl Zeiss Foundation is now funding the project as part of its “Scientific Breakthroughs in Artificial Intelligence” program with five million euros over six years.

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University of Tübingen
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University of Tübingen
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University of Tübingen
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University of Tübingen
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University of Tübingen
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University of Tübingen
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ELLIS Institute Tübingen, Max Planck Institute for Intelligent Systems & Tübingen Al Center
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University of Tübingen
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Max Planck Institute for Intelligent Systems

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