A Model for General Collective Intelligence

2020

Preprint

Self Cite

Section: Resultsmentioning

confidence: 99%

Section: The Root Of the Problemmentioning

confidence: 99%

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The Need for General Collective Intelligence in Addressing the Sustainable Development Goals

2020

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“…If cognitive capacity places a limit on the size and complexity of designs that can be created, and if as suggested General Collective Intelligence expands the limit on a group's collective cognitive capacity to be far higher than the limit on the cognitive capacity possible for any individual, and expands the limit on the collective cognitive capacity of the group to be far higher than that of any group without GCI [14], then since GCI has not yet been implemented in the design process, there must be certain classes of design problems outside the capacity of groups to reliably define, and certain classes of solutions too complex to reliably be created to solve those problems. The question is how to intuitively understand what those limits to problem solving and design complexity are.…”

Section: Introductionmentioning

confidence: 99%

General Collective Intelligence, Human-Centric Functional Modeling and the Current Limitations on Collective Design Cognition

2020

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This paper explores the limits to the size and complexity of designs that can be created by humans. Beginning with the existence of a finite limit to the design output of any single individual, as a result, some design efforts require teams. However, anecdotally, when it comes to contributing to a single design objective, there is a limit to the size of groups, a limit to the diversity of skill sets, a limit to the diversity of design techniques and other problem-solving tools, and there is a limit to the range of objectives, at which the group can remain effective. Design processes are cognitive (reasoning or understanding) processes. And design tools are an automation of cognitive processes. Therefore design techniques and other problem-solving tools can be represented as the cognitive processes by which design problems are solved. The execution of these cognitive processes is then design cognition. Equating the term objective with the problem that has been defined, equating design techniques and other problem-solving tools with the cognitive processes by which those problems are solved, and defining the execution of these cognitive processes as design cognition, then since large complex designs must be created by teams, the limit to the capacity of groups for this cognition imposes a limit on the size and complexity of designs that can be created by humans. General Collective Intelligence has been defined as a system that organizes groups into a single collective intelligence with vastly greater general problem solving ability. Design based on General Collective Intelligence has been suggested to have the capacity to expand current limits to collective design cognition that might take certain classes of problems outside the capacity of groups to reliably define or solve. In any GCI based design process, Human-Centric Functional Modeling is a critical requirement in defining design problems as well as in creating the designs that solve those problems. This paper explores GCI based design, and the classes of problems that can’t reliably be defined or solved without it.

“…General Collective Intelligence or GCI has been described as software that organizes a group into a single collective intelligence with the potential for vastly greater general problemsolving ability than any individual in the group. A recently defined model of GCI incorporates a recently defined model of AGI [8]as intelligent agents to interact on behalf of users, to enable users to interact and achieve outcomes at potentially exponentially greater speed and scale [6], [7].…”

Section: Introductionmentioning

confidence: 99%

Cognitive Computing and its Relationship to Computing Methods and Advanced Computing from a Functional Modeling Perspective

2020

Preprint

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Recent advances in modeling human cognition have resulted in what is suggested to be the first model of Artificial General Intelligence (AGI) with the potential capacity for human-like general problem-solving ability, as well as a model for a General Collective Intelligence or GCI, which has been described as software that organizes a group into a single collective intelligence with the potential for vastly greater general problem-solving ability than any individual in the group. Both this model for GCI and this model for AGI require functional modeling of concepts that is complete in terms of meaning being self-contained in the model and not requiring interpretation based on information outside the model. This definition of a model for cognition has also been suggested to implicitly provide a semantic interpretation of functional models created within the functional modeling technique defined to meet the data format requirements of this AGI and GCI, so that the combination of the model of cognition to define an interpretation of meaning, and the functional modeling technique, together result in fully self-contained definitions of meaning that are suggested to be the first complete implementation of semantic modeling. With this semantic modeling, and with these models for AGI and GCI, cognitive computing is far better defined. This paper explores the various computing methods and advanced computing paradigms from the perspective of this cognitive computing.