The Future of Causal Inference

Am J Epidemiol. 2022 Sep 28;191(10):1671-1676. doi: 10.1093/aje/kwac108.


The past several decades have seen exponential growth in causal inference approaches and their applications. In this commentary, we provide our top-10 list of emerging and exciting areas of research in causal inference. These include methods for high-dimensional data and precision medicine, causal machine learning, causal discovery, and others. These methods are not meant to be an exhaustive list; instead, we hope that this list will serve as a springboard for stimulating the development of new research.

Keywords: algorithms; causal discovery; causal machine learning; distributed learning; high-dimensional data; interference; transportability.

Publication types

  • Research Support, N.I.H., Extramural

MeSH terms

  • Causality
  • Humans
  • Machine Learning*