  Non-Equilibrium Social Science (NESS) emphasizes dynamical phenomena, for
instance the way political movements emerge or competing organizations
interact. This paper argues that predictive analysis is an essential element of
NESS, occupying a central role in its scientific inquiry and representing a key
activity of practitioners in domains such as economics, public policy, and
national security. We begin by clarifying the distinction between models which
are useful for prediction and the much more common explanatory models studied
in the social sciences. We then investigate a challenging real-world predictive
analysis case study, and find evidence that the poor performance of standard
prediction methods does not indicate an absence of human predictability but
instead reflects (1.) incorrect assumptions concerning the predictive utility
of explanatory models, (2.) misunderstanding regarding which features of social
dynamics actually possess predictive power, and (3.) practical difficulties
exploiting predictive representations.
