Defining a General Collective Intelligence Based Renewable Energy Solution Development Program
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Date
2020-12-31
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Abstract
The choice of which problem renewable energy programs target is one that might benefit from greater General Collective Intelligence or GCI. Where a collective intelligence uses the intelligence of crowds to maximize impact on a given problem, a GCI is defined as having the capacity for general problem solving ability, and therefore the capacity to increase outcomes by choosing the optimal problem to solve. Collectively intelligent development aims to solve the problems required to create the ability for groups to reliably explore all of the currently possible solution space and to reliably converge on the best available solution in that space, so that developing solutions which facilitate a significantly improved impact on targeted outcomes as compared to other development processes is reliably achievable. Where conventional development processes have known cognitive or other biases that may prevent certain categories of solutions from being selected by groups even where optimal, collectively intelligent development aims to create the capacity to reliably converge on the optimal overall solution. A proposed Collective Intelligence Based Renewable Energy Program aims to leverage human-centric functional modeling to provide groups with a common model of the problem being solved. This proposed program then leverages a newly developed model of General Collective Intelligence to collectively reason in terms of those common functional models as required to develop a solution that optimizes impact on the targeted problem, such as the problem of achieving a significantly lower cost of access to sustainable renewable energy, or achieving a significant increase in environmental sustainability of that renewable energy, as defined by metrics that might be related to carbon emissions.
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General Collective Intelligence, Human-Centric Functional Modelling, renewable energy