Societal-Scale Decision-Support System

Collective intelligence has been defined as the ability of a group to provide more effective solutions to problems than could be otherwise provided by any of its individual members working alone. Social-structures are the means by which humans are able to synergistically combine their efforts to provide high-quality solutions to the problems facing the group. Over time, these structures have grown in scale and complexity to encompass political institutions that span vast landscapes of heterogeneous individuals to militaristic forms capable of orchestrating effective large-scale behavioral feats. With computer and network technologies, the potential for more advanced societal-scale information-processing systems is now possible such that a general-purpose societal-scale decision-support system may begin to be envisioned. Unlike typical group decision-support research, a societal-scale system is faced with both a heterogeneous user population and problem-space. In designing such a system it is important to understand how the 'collective's mind' is modeled via a shared mental map of the group and how the 'collective's mindset' is maintained over fluctuating participation levels of its constituent members. Methods in both problem-space partitioning and group preference modeling are presented within a theoretical and design framework to further the potential development of a societal-scale decision-support system capable of providing synergistically derived solutions to any representable problem. In concert, all of these ideas provide the foundation for the implementation of societal-scale decision-making system in a real-world context.