Phenomenological Causality

TL;DR

This paper introduces 'phenomenological causality', a new approach that defines causal relations based on elementary actions affecting causal mechanisms, avoiding traditional issues with intervention-based definitions.

Contribution

It proposes a novel causality framework grounded in elementary actions and causal mechanisms, sidestepping the circularity of intervention-based causality definitions.

Findings

Aligns with the causal Markov condition in interactive systems

Provides a consistent causal model for abstract and real-world scenarios

Defines causality through elementary actions affecting causal mechanisms

Abstract

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.