  We propose predictive information, that is information between a long past of
duration T and the entire infinitely long future of a time series, as a
universal order parameter to study phase transitions in physical systems. It
can be used, in particular, to study nonequlibrium transitions and other exotic
transitions, where a simpler order parameter cannot be identifies using
traditional symmetry arguments. As an example, we calculate predictive
information for a stochastic nonequilibrium dynamics problem that forms an
absorbing state under a continuous change of a parameter. The information at
the transition point diverges as log(T), and a smooth crossover to constant
away from the transition is observed.
