  The aim of this paper is to extend the framework of causal inference, in
particular as it has been developed by Judea Pearl, in order to model actions
and identify their intended effects, in the direction opened by Elisabeth
Anscombe. We show how intentions can be inferred from a causal model and its
implied correlations observable in data. The paper defines confounding effects
as the reasons why teleological inference may fail and introduces interference
as a way to control for them. The ''fundamental problem'' of teleological
inference is presented, explaining why causal analysis needs an extension in
order to take intentions into account.
