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

The Future of Causal Inference

Nandita Mitra, Jason Roy, Dylan Small

The Future of Causal Inference

Nandita Mitra et al. Am J Epidemiol. .

Abstract

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.

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