Most work in algorithmic game theory assumes that players ignore costs
incurred by their fellow players. In this paper, we consider
superimposing a social network over a game, where players are
concerned with minimizing not only their own costs, but also the costs
of their neighbors in the network. We aim to understand how
properties of the underlying game are affected by this alteration to
the standard model. The new social game has its own equilibria, and
the \emph{price of civil society} denotes the ratio of the social cost
of the worst such equilibrium relative to the worst Nash equilibrium
under standard selfish play. We initiate the study of the price of
civil society in the context of a simple class of games.
Counterintuitively, we show that when players become less selfish
(optimizing over both themselves and their friends), the resulting
outcomes may be worse than they would have been in the base game. We
give tight bounds on this phenomenon in a simple class of
load-balancing games, over arbitrary social networks, and present some
extensions.