Towards interactive explanations of machine learning methods through dialogue systems
Language-based interactions promise natural and easy access to explanations of machine learning decisions. As complexity of current artificial intelligence (AI) system increases, transparency and thus explanations of the system behaviour get more important especially in critical applications for domains like law or medicine. Towards this goal, my research focuses on implementing a generic dialogue model for interactive machine learning, that describes user and system behaviour on a semantic level (i.e. dialogue moves) and identifies common user requests that are agnostic to the underlying explainable AI method or domain.
Ich betreue gerne Bachelor und Master Arbeiten aus dem Bereich meines Promotionsthemas. Bei Interesse, schreibe mir gerne eine E-Mail, wenn du Interesse hast.
I am pleased to supervise Bachelor's or Master's theses within my PhD Topic. If you are interested, please feel free to reach out to me via email, and we can explore potential topics.
