Actual causation and the art of modeling

TL;DR

This paper examines how the modeling choices in structural equations influence causal inferences, emphasizing the subjectivity involved in selecting variables and values, and discussing criteria for appropriate models including defaults.

Contribution

It provides a detailed analysis of the impact of modeling decisions on causality and explores what constitutes an appropriate causal model, especially with default assumptions.

Findings

Modeling choices significantly affect causal conclusions.

Subjectivity plays a role in selecting variables and values.

Defaults are important in defining appropriate causal models.

Abstract

We look more carefully at the modeling of causality using structural equations. It is clear that the structural equations can have a major impact on the conclusions we draw about causality. In particular, the choice of variables and their values can also have a significant impact on causality. These choices are, to some extent, subjective. We consider what counts as an appropriate choice. More generally, we consider what makes a model an appropriate model, especially if we want to take defaults into account, as was argued is necessary in recent work.