Discussions on causal relations in real life often consider variables for
which the definition of causality is unclear since the notion of interventions
on the respective variables is obscure. Asking 'what qualifies an action for
being an intervention on the variable X' raises the question whether the action
impacted all other variables only through X or directly, which implicitly
refers to a causal model.
To avoid this known circularity, we instead suggest a notion of
'phenomenological causality' whose basic concept is a set of elementary
actions. Then the causal structure is defined such that elementary actions
change only the causal mechanism at one node (e.g. one of the causal
conditionals in the Markov factorization). This way, the Principle of
Independent Mechanisms becomes the defining property of causal structure in
domains where causality is a more abstract phenomenon rather than being an
objective fact relying on hard-wired causal links between tangible objects. We
describe this phenomenological approach to causality for toy and hypothetical
real-world examples and argue that it is consistent with the causal Markov
condition when the system under consideration interacts with other variables
that control the elementary actions.

通过基本行动的集合作为基本概念，建立元因果结构并确定有效的因果结构特性，避免了现实生活中因果关系交叉引用的循环问题，以适用于抽象领域和假想现实世界场景下的因果学习。