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Prof. Dr. Ute Schmid von der Universität Bamberg wird als Teil der "Lecture Series on AI in Science and Society" am 09.05.2025 von 14:15–15:45 Uhr in H27 (GW II) einen Vortrag zum Thema "Methods for Trustworthy AI: Can We Transfer Lessons Learned from Classifier Learning to Generative AI?" halten.

Abstract: With the advance of highly performant AI systems – deep learning based classifiers and transformer based generative approaches – there is hope that AI tools can support humans to master complex tasks more efficient as well as in high quality. However, especially for critical tasks such as medical diagnostics or generation of program code for scientific tasks, AI systems need to be reliable and trustworthy. In the talk I will introduce the seven trustworthiness requirements proposed by the European Union High-level Expert Group on Artificial Intelligence. I will discuss the relation between human trust in AI systems and the trustworthiness requirements. For the requirements of performance, robustness, transparency, fairness, and human agency and oversight I will present methods which have been developped in the context of classifier learning and discuss possibilities how these requirements could be addressed for generative AI tools.