I stumbled accros this incredibly interesting read by Mark White, who discusses the (academic) theory behind, inner workings, and example (R) applications of causal random forests:
EXPLICITLY OPTIMIZING ON CAUSAL EFFECTS VIA THE CAUSAL RANDOM FOREST: A PRACTICAL INTRODUCTION AND TUTORIAL (By Mark White)
These so-called “honest” forests seem a great technique to identify opportunities for personalized actions: think of marketing, HR, medicine, healthcare, and other personalized recommendations. Note that an experimental setup for data collection is still necessary to gather the right data for these techniques.
