Modern Machine Learning (ML) algorithms are considered to be black-boxes we have no epis-temic access to. XAI tackles this assumption by providing methods that allow gaining insights into thebehaviour of ML algorithms. This course introduces the central philosophical concepts and challenges inXAI such as explanation, interpretability, and opacity. Moreover, we discuss state-of-the-art XAI meth-ods and their strengths and weaknesses. We focus particularly on causal explanations, the role of XAI for Science, and model-agnostic interpretation techniques.
The course is held together with students from MCMP.
Fridays 12:15-13:45 pm
Opening Event: Online
Key: xai-philo-21
- Trainer/in: Gunnar König