  We postulate a principle stating that the initial condition of a physical
system is typically algorithmically independent of the dynamical law. We argue
that this links thermodynamics and causal inference. On the one hand, it
entails behaviour that is similar to the usual arrow of time. On the other
hand, it motivates a statistical asymmetry between cause and effect that has
recently postulated in the field of causal inference, namely, that the
probability distribution P(cause) contains no information about the conditional
distribution P(effect|cause) and vice versa, while P(effect) may contain
information about P(cause|effect).
