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.

Increasing the Societal Impact of Science, Technology, Engineering, and Math with General Collective Intelligence

“…GCI is important because without GCI it is predicted that wicked problems like poverty and climate change are currently not reliably solvable due to factors in group organization that prevent the exploration of potentially optimal solutions [21]. The time window of GCI is potentially limited because of an effect called the "technology gravity well" [20] which is predicted to act to increase the centralization of technology more and more, until deployment of a decentralized system of decision-making like GCI is no longer reliably possible, at which point problems requiring decentralized collective optimization in order to maximize outcomes for groups that include entire civilizations, will no longer be reliably achievable. Instead, after having fallen into the technology gravity well it is predicted that societies will be constrained to follow goals aligned with the interests of powerful centralized entities (likely corporations and/or governments) in ways that might openly conflict with the public good, where those entities evolve technology too quickly for any significant number of the public to understand, or for any government regulations or corporate policies to be effective in changing even if they did.…”

“…Using Human-Centric Functional Modeling as a methodology for understanding societal impact or for understanding learning systems is relevant to a number of problems in a wide variety of disciplines [23], [24], [20]. In order to effectively target these problems, General Collective Intelligence is believed to be required to create the capacity for groups to execute collective reasoning processes that are reliably able to converge on a single coherent conclusion, and therefore to achieve the significantly increased outcomes of STEM activities that might accompany that conclusion.…”

Towards a Data Science for General Collective Intelligence

“…In order to have general problem-solving ability at all, a GCI is theorized to require a decentralized architecture in which each individual's identities, data, and processes reside within a private repository in each user's sole control, and in which each individual's interactions with the GCI might be brokered by an intelligent agent working on that individual's sole behalf, so that clones of those agents might be used to increase the speed and scale of that interaction. In the natural world this decentralization of the design of organisms right down to the processes that manage their homeostasis, cellular reproduction, and other administrative processes, can be represented through "Human-Centric Functional Modeling" or HCFM as having existed in multicellular organisms for hundreds of millions of years, but according to this HCFM theory such decentralization in all processes has not yet been implemented in any artificial technology, even those that purport to be decentralized such as blockchain platforms, or web 3.0 [3].…”