Functional robustness refers to a system’s ability to maintain a function in the face of perturbations to the causal structures that support performance of that function. Modularity, a crucial element of standard methods of causal inference and difference-making accounts of causation, refers to the independent manipulability of causal relationships within a system. Functional robustness appears to be at odds with modularity. If a function is maintained despite manipulation of some causal structure that supports that function, then the relationship between that structure and function fails to be manipulable independent of other causal relationships within the system. Contrary to this line of reasoning, I argue that functional robustness often attends feedback control, rather than failures of modularity. Feedback control poses its own challenges to causal explanation and inference, but those challenges do not undermine modularity—and indeed, modularity is crucial to grappling with them.

中文翻译：

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稳健性和模块化

功能鲁棒性是指系统在面对支持该功能性能的因果结构的扰动时维持该功能的能力。模块化是因果推理和因果关系差异解释标准方法的关键要素，是指系统内因果关系的独立可操作性。功能稳健性似乎与模块化不一致。如果尽管对支持该功能的某些因果结构进行了操纵，但仍维持了该功能，那么该结构和功能之间的关系就无法独立于系统内的其他因果关系进行操纵。与这种推理相反，我认为功能稳健性通常涉及反馈控制，而不是模块化的失败。反馈控制对因果解释和推理提出了自己的挑战，但这些挑战不会破坏模块化——事实上，模块化对于解决这些挑战至关重要。