Explainable AI

With AI being ever-present in our lives now, it becomes crucial that we understand how AI works and why it recommends certain things. I work on AI Explainability (XAI), which is a research field dedicated to understanding and explaining AI models. During my PhD I developed new methods for XAI and looked inside large AI models to understand how they build knowledge, what they learn in general and why they make certain decisions. I strongly believe that for a safe use of AI, we should all understand how these models work, what they know, and most importantly, what they don't know. I would love to visit your class to talk about AI and Explainability and hopefully inspire the students to critically question their use of AI and learn in which cases it is crucial to understand the models decisions.

During my visit I would give a short introduction into how AI/machine learning works in general and then show the students what they can gain when we look inside these models. I will bring some use-cases of AI in health care and hearing research and show what we can gain by using XAI tools to understand the models better.

I will also talk about my career path and how I ended up in Denmark. I originally come from Germany, where I studied Biotechnology, then I moved to Sweden for my masters degree in Machine Learning and then to Denmark where I am now doing my PhD in AI explainability. I am looking forward to telling the students about the student life in different countries.