  This paper proposes self-organization as a method to improve the efficiency
and adaptability of bureaucracies and similar social systems. Bureaucracies are
described as networks of agents, where the main design principle is to reduce
local "friction" to increase local and global "satisfaction". Following this
principle, solutions are proposed for improving communication within
bureaucracies, sensing public satisfaction, dynamic modification of
hierarchies, and contextualization of procedures. Each of these reduces
friction between agents (internal or external), increasing the efficiency of
bureaucracies. "Random agent networks" (RANs), novel computational models, are
introduced to illustrate the benefits of self-organizing bureaucracies.
