The first AI Developer Working Group of the year took place this Monday. Prof. Dr. Emmanuel Müller from TU Dortmund University visited us with a lecture on “Trustworthy Machine Learning: Explainable & Verifiable Anomaly Detection”.
The processes by which algorithms can perform reliable anomaly detection were the core topic. He cites the automotive industry, healthcare and infrastructure as current areas of application for these technologies, where he sees algorithms that detect faults, anomalies and the need for repair at an early stage as particularly valuable. To increase the reliability of these algorithms, they need to be trained not only to detect anomalies, but also to describe them in the best possible way. Only then will they become effective tools that can bridge the gap between the amount of data and the human decision maker.
Many thanks to Prof. Dr. Emmanuel Müller and all those present who asked questions with interest and linked interdisciplinary approaches to the lecture. This time, the closing event proved to be an intensive networking opportunity, which many visitors took advantage of.
