I study the nature of causation, as well as the meta-philosophical question of how philosophers ought to study the nature of causation.

Like most philosophers, I used to think that the best way of studying the nature of causation was to design various simple but ingenious thought experiments, and then to look at the typical person's intuitions about what causes what in these thought experiments. In Paper 11, I explain why I am disillusioned with this approach to studying the nature of causation. In particular, I think that one can conclusively show that no good metaphysical theory of causation can do justice to one' s intuitions in both "redundancy" thought experiments and "threat and saviour" thought experiments.

I have almost completed a draft manuscript of a monograph Causation Redefined, in which instead I take a conceptual engineering approach to our causal concepts. Some highlights:

​

1. I give an alternative interpretation of Kevin Hoover's concept of a causal parameter. This alternative interpretation agrees with what Hoover says about the relationship between parameters and causation, and it justifies this relationship on conceptual engineering grounds.

2. I extend this parameter-based approach to causation so that one can define the notion of causal structure and of structural equations in terms of parameters.

3. On conceptual engineering grounds, I argue that there is an intimate conceptual connection between chance and causation. Indeed, I prove that a qualified version of the Principle of the Common Cause and of the Causal Markov Principle holds for the conceptually engineered concept of causation. These qualified principles show that Cartwright and Sober were part right and part wrong in their criticisms of these principles.

4. On conceptual engineering grounds, I offer a principled theory of counterfactual conditionals. On the one hand, whenever counterfactual conditionals are meaningful, then a qualified version of the principle of modularity holds. On the other hand, the principle of modularity does not hold in general. Thus the interventionist approach to causation is shown to get something right and something wrong.