Abstract

While "standard" AI / machine learning is based on correlations and mostly tailored for predictions, many interesting real world problems are causal. The new, emerging field of Causal AI combines Causal Inference and modern machine learning methods. In this talk an introduction to the so-called Double Machine Learning approach is given, which also for valid inference in high-dimensional settings. Moreover, experiences from applying these new methods in real world applicatinos are shared.