An introduction to the emerging fusion of machine learning and causal inference. The book presents ideas from classical structural equation models (SEMs) and their modern AI equivalent, directed acyclical graphs (DAGs) and structural causal models (SCMs), and covers Double/Debiased Machine Learning methods to do inference in such models using modern predictive tools.
@article{arxiv.2403.02467,
title = {Applied Causal Inference Powered by ML and AI},
author = {Victor Chernozhukov and Christian Hansen and Nathan Kallus and Martin Spindler and Vasilis Syrgkanis},
journal= {arXiv preprint arXiv:2403.02467},
year = {2024}
}