Optimal Voting in Groups with Convergent Interests

Decision-making is crucially important at all levels of biological complexity, from within single-celled organisms, through neural populations within the vertebrate brain, to collections of social organisms such as colonies of ants and honeybees, or societies of humans. What are the prospects for unifying the study of these apparently disparate systems? All can be conceptualised as voting systems at the appropriate level. In this review I will argue that optimality theory can be of fundamental importance in understanding all these systems. In particular I will argue that for groups without conflict of interests, such as neurons and social insect colonies, similar mechanisms could implement statistically optimal decision-making in apparently highly different systems at different levels of biological complexity. I will consider what currency these systems should optimize, and speculate about the possible application of this understanding to the design of voting systems where individual group members' interests are aligned, such as in certain types of human group, and in collectives of robots. I will also consider how established results from economics and political science, notably Arrow's Impossibility Theorem and Condorcet’s ‘jury theorem’, might relate to what we know of social insect voting systems, where interesting effects such as the emergence of collective rationality from the voting of irrational individuals have recently been demonstrated.