Detection of Unfaithfulness and Robust Causal Inference
Detection of Unfaithfulness and Robust Causal Inference
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不忠行为检测和稳健因果推理
作者：
Jiji Zhang;P. Spirtes
最近关于因果认识论的大部分工作都集中在两个假设上，即因果马尔可夫条件和因果忠实条件。关于后一种情况的哲学讨论已经显示出它很可能失败的情况。本文将因果忠实条件作为弱条件的结合来研究。我们表明，一些较弱的连词可以经过经验检验，因此不必先验地假设。我们的结果导致了两个方法论上重要的观察结果：(1)忠实条件的一些常见类型的反例仅构成对条件的经验可测试部分的反对意见；(2)忠实条件的一些常见防御没有为条件的可测试部分提供理由或证据。因此，研究在较弱信度条件下可靠因果推理的可能性是值得的。事实证明，使标准过程在较弱版本的忠实条件下工作所需的修改，也具有在标准忠实条件实际成立时使其更健壮的实际效果。我们认为，这与因果推理中用有限样本量（“一致一致性”）控制错误概率的可能性有关。
Much of the recent work on the epistemology of causation has centered on two assumptions, known as the Causal Markov Condition and the Causal Faithfulness Condition. Philosophical discussions of the latter condition have exhibited situations in which it is likely to fail. This paper studies the Causal Faithfulness Condition as a conjunction of weaker conditions. We show that some of the weaker conjuncts can be empirically tested, and hence do not have to be assumed a priori. Our results lead to two methodologically significant observations: (1) some common types of counterexamples to the Faithfulness condition constitute objections only to the empirically testable part of the condition; and (2) some common defenses of the Faithfulness condition do not provide justification or evidence for the testable parts of the condition. It is thus worthwhile to study the possibility of reliable causal inference under weaker Faithfulness conditions. As it turns out, the modification needed to make standard procedures work under a weaker version of the Faithfulness condition also has the practical effect of making them more robust when the standard Faithfulness condition actually holds. This, we argue, is related to the possibility of controlling error probabilities with finite sample size (“uniform consistency”) in causal inference.