General Collective Intelligence as a Platform for Computational Social Systems

Abstract

The emerging science of General Collective Intelligence or GCI defines the requirements for a hypothetical platform able to self-organize individuals in a self-sustaining way into massive networks of cooperation with the capacity to execute collective reasoning in a way that might exponentially increase the general problem-solving ability of the group. Some of these requirements of a GCI include the property of “dynamic decentralization”, without which any modeling, simulation, analysis or understanding of social systems from a quantitative and/or computational perspective are hypothesized to be centralized in a way that prevents them from being free of being constrained to be aligned with the individual interests of any powerful decision-makers involved in any of these processes. This paper explores why, as a consequence, building computational social systems on top of GCI is critical in ensuring that any class of problem can be solved where that class relates to the misalignment between the interests of influential individual decision-makers, and the outcomes that would be beneficial for the group.