Title: Modeling Social Organizations as Communication Networks,
Abstract: We identify the "organization" of a human social group as the communication
network(s) within that group. We then introduce three theoretical approaches to
analyzing what determines the structures of human organizations. All three
approaches adopt a group-selection perspective, so that the group's network
structure is (approximately) optimal, given the information-processing
limitations of agents within the social group, and the exogenous welfare
function of the overall group. In the first approach we use a new sub-field of
telecommunications theory called network coding, and focus on a welfare
function that involves the ability of the organization to convey information
among the agents. In the second approach we focus on a scenario where agents
within the organization must allocate their future communication resources when
the state of the future environment is uncertain. We show how this formulation
can be solved with a linear program. In the third approach, we introduce an
information synthesis problem in which agents within an organization receive
information from various sources and must decide how to transform such
information and transmit the results to other agents in the organization. We
propose leveraging the computational power of neural networks to solve such
problems. These three approaches formalize and synthesize work in fields
including anthropology, archeology, economics and psychology that deal with
organization structure, theory of the firm, span of control and cognitive
limits on communication.