the fundamental problem of causal inference

It is fundamental because if we cannot observe both 𝑌 _𝑖 (1) and 𝑌 _𝑖 (0) , then we cannot observe the causal effect 𝑌 _𝑖 (1) − 𝑌 _𝑖 (0) . This problem is unique to causal inference because, in causal inference, we care about making causal claims, which are defined in terms of potential outcomes. For contrast, consider machine learning. In machine learning, we often only care about predicting the observed outcome 𝑌 , so there is no need for potential outcomes, which means machine learning does not have to deal with this fundamental problem that we must deal with in causal inference.