Oh, I agree that neural networks are function approximators with respect to some geometry. When I say "counterfactuals", I'm talking about typical Bayes-net style counterfactuals, but as also used in cognitive psychology. We know that human minds evaluate counterfactual statements in order to test and infer causal structure. We thus know that neural networks are insufficient for "real" cognition.