A Computationally Feasible Framework for Causal Probabilistic Explanation

Key Takeaway

PCI makes causal explanations computationally practical by framing the problem as Monte Carlo estimation rather than counterfactual enumeration, letting you get theoretically grounded blame/credit assignments at scale without sacrificing causal reasoning.