Summary

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In this chapter, we have learned the following concepts:

• Challenges in active causal inference: practical, ethical and legal challenges
• When confounders were observed: Regression, inverse probability weighting and matching
• When confounders were not observed: instrument variables

There are a few other widely used passive causal inference algorithms, but they are left for the final section on \SRemaining Topics Remaining Topics, such as difference-in-difference, regression discontinuity and double machine learning.

General references

Cho, Kyunghyun (2024). "A Brief Introduction to Causal Inference in Machine Learning". arXiv:2405.08793 [cs.LG].