What can statistics contribute to a causal understanding?

We discuss the concept of causality in a broad manner. The traditional attitude in statistics has been to shy away from the causality concept. In recent years, however, a more proactive attitude to the causality concept has developed among statisticians. On the one hand, there is the school of counterfactual causality directed towards forming a better basis for clinical trials and epidemiology. On the other hand, there is the mechanistic view of causality. These developments are discussed and set into a larger context, where the often ignored role of time is emphasized. An extension of path analysis to stochastic processes is briefly presented. Causality is furthermore discussed in relation to genetic studies and to the emerging field of systems biology. Statisticians should also relate to the philosophical content of causality, especially that found in the foundations of physics.