 Section 3.3  above discussed counterfactuals in the context of deterministic causal models. The introduction of probability adds a number of complications. In particular, we can now talk meaningfully about the probability of a counterfactual being true. Counterfactuals play a central role in the potential outcome framework for causal models pioneered by Neyman (1923), and developed by Rubin (1974) and Robins (1986), among others.