Andy Williams

My research interests are exploring how General Collective Intelligence or GCI might significantly increase the general problem-solving ability (intelligence) of groups. GCI is a model of collaborative computing believed to create the capacity to reliably optimize any collective outcome, for example increasing access to affordable health care, or education per program dollar. The theory behind this model also suggests that optimizing any given collective outcome is not reliably achievable without GCI, and in addition suggests that the opportunity to implement GCI is likely to be temporary, and therefore the decision to implement or not to implement GCI might be a one-way fork in the road with tremendous consequences in terms of the well-being of people and the planet. GCI appears to have the capacity to execute self-organizing processes. Such processes might enable groups to self-assemble into potentially massive networks of cooperation that can target any impact, that can radically increase the probability of achieving that impact, that can radically increase the magnitude of that impact, and that can create sufficient value to make that impact self-sustaining. This approach allows us to see that nature has already solved the problems of sustainability, poverty, universal access to health care, and other existential challenges human beings face. Nature targets outcomes through self-assembling processes that grow, evolve, or become more fit in other adaptive domains, so life can find the resources to feed its own increase in ability to target those outcomes from resources that are already there in the environment. All these processes that nature spent billions of years researching and perfecting are modeled and replicated within GCI. For example, rather than nonprofits competing for donor funding, a GCI might organize cooperation between thousands of NGOs to radically increase social, economic, or other impacts per dollar of program funds so programs are self-funding once launched. Rather than developing new networks of cooperation a GCI might use an evolution algorithm, or use a reproduction or other adaptive algorithm, to adapt an existing network. A conceptual case study suggests that increasing social impact per dollar by a thousand fold might be reliably achievable. And that rather than being limited to the social impact possible with any finite amount of funding, social impact might be made sustainably self-funding so impact might be achieved at the scale required to transform communities globally. If so, then poverty, and other human suffering might have reliably achievable solutions. The challenge in launching GCI is to convey the concept to a sufficient number of people. So I try to find potential collaborations anywhere there is common ground in order to slowly build a community of like minds. There are opportunities for collaboration everywhere. The exponential increase in general problem-solving ability that is possible through GCI has profound implications in every discipline from physics, to economics, sociology, philosophy, medicine, and others. At the heart of GCI is Human-Centric Functional Modeling, which defines a semantic model that all problems and solutions can fit into. This in turn enables problems and solutions to fit within the capacity of human cognition regardless of their complexity. And it enables us to generalize our many problems in our many different disciplines into solving the single problem of implementing GCI. Human-Centric Functional Modeling of this human system allows us to understand ourselves through exploring our own awareness as opposed to doing so solely through properties that can be measured externally. Human-Centric Functional Modeling can also be used to model external systems, from blockchain or other computing technology as I’ve validated in papers co-authored with academic researchers in these fields, to the entire physical universe, as I’ve validated in working papers co-authored with academic physicists as well. This modeling of the physical universe allows us to draw analogies between the physical universe and human systems like consciousness and cognition, because any “functional state space” describing the functional states of any system appears to be required to have common properties in order to be defined semantically. These commonalities in turn appear to allow us to gain insight into the profound complexity of the universe by looking inwards and becoming more aware of our own human system. This approach of modeling the outside world in a human-centric way so that it is possible to understand the world better through looking inwards, is a formalization of the Vedic philosophical tradition that is thousands of years old.

Contact Andy at andy [dot] williams /at/ ronininstitute {dot} org

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