General Collective Intelligence

General Collective Intelligence has the potential to exponentially increase the intelligence of a group. Creating true general problem-solving ability can break through the barriers that restrict groups to solving the wrong problems with the wrong solutions. Exponentially increasing that ability can enable problems like digital inclusion to become reliably solvable. Deploying a subset of a GCI platform to a smart device to address the problem of digital inclusion can radically increase the speed and scale at which "solutions that ensure everyone has access to the digital economy" can be deployed by enabling groups to self-organize into self-sustaining networks of cooperation that create enough value for the solutions to self-propagate, so they can reliably be deployed at global scale. GCI is a model of collective cognition based on the same functional model of individual cognition used to define the first published model of Artificial General Intelligence, as shown in the video.

This proposal will develop a General Collective Intelligence platform on a smart device to maximize digital inclusion. The application of GCI to a specific subset of problems involved in digital inclusion is described here "The Role of Cognitive Computing and Collective Cognitive Computing in the Future Internet", and here "The Role of General Collective Intelligence in Overcoming the Barriers to Achieving an Internet of Things". The scale of the problem in rural Africa is large, since few are reliably connected. But the scale in the first world is large as well since increasingly the flood of highly polarizing misinformation on the one hand and big tech censorship on the other hand are threatening to reduce the ability of even well-connected citizens to be included in the shaping of the digital platforms that are so important to their lives. Because all these problems boil down to a lack of a sufficient "general collective intelligence factor" to solve them, the ubiquity of this problem means that billions of people are affected. GCI removes the barriers to cooperation, so that where cooperation contributes to general problem-solving ability, that general problem-solving ability can reliably be scaled sufficiently to solve these problems.

Decentralized, self-organizing processes are required in order to solve collective optimization problems like digital inclusion. E.g. a social media platform might provide its users with a set of functionality decided by the social media platform owner. That functionality can't be separated from being aligned with his interests, because he might decide to limit what users can do or whether they can even join the platform. In a decentralized approach, an individual wanting to interact socially might choose from a menu of social interaction processes, and then might use a General Collective Intelligence platform to connect with individuals in their network who would like to interact through those processes, who might use GCI to connect with individuals in their networks who might like to do the same, and so on, until the network self-assembles into a social media application that does exactly what the network of individuals wants it to do. General Collective Intelligence is essentially a platform that provides this ability to self-assemble to execute any process in this decentralized way to optimize collective outcomes, like optimizing ability to assemble a network for the purpose of "access to commerce, credit lines, safety nets, and saving mechanisms".

The history of this project began with the work of Nobeah Foundation and it's for-profit sister company (Nobeah Technologies) to develop a radically cost effective hybrid educational laptop/e-reader called the Afripad in response to the $300 M USD tender offered by the government of Kenya. At about the cost of textbooks for one year the Afripad had the potential to address the lack of learning materials in African schools when combined with free or low-cost e-textbooks. The foundation had a staff of around 200 mainly volunteer staff and had partnerships with the leading vendors in that space, including a partnership with Datawind, the world's leading manufacturer of low cost computers. The project had the endorsement of the two top engineering universities in the country, as well as the endorsement of the governors of multiple counties in Kenya. Through engaging 40-50 engineering interns from those universities to help design the computer, as well as to design the solar powered charging stations and other infrastructure, some of which were patented, the project demonstrated the capacity to build the computer locally, rather than to build it in China and merely assemble it locally as the other competing projects planned to do. Because of this, the project was estimated to create tens of thousands more jobs than the other competing bids. Since the computer was also targeted at a cost that was a tenth of that of the computers being offered by the other bids, it was thought that the Afripad had such a better value proposition that it could not lose the award. However, potentially due to corruption, the Afripad was not selected. Furthermore, the winning bidders have not successfully delivered the project and the project has been widely criticized as being corrupt and failed. Through all these developments it became clear that the solution to radically increasing social impact in Africa was not "building a better mousetrap". Instead the solution was building a system of decision-making capable of reliably selecting and funding the best mousetrap. The Nobeah Foundation then took the radical step of deciding to focus the next few years on developing a collective decision-making system with the capacity to reliably achieve that. The result was the first model of "General Collective Intelligence". Since that model was developed, a great deal of additional research was necessary to understand the psychology driving decision-making in groups in order to overcome the barriers to deployment of such a system. This profoundly important work was the result of years of research that required inspiring the commitment, faith, and dedication of followers, not knowing if the outcome would be success, which was a source of immense accomplishment.

The solution planned for the MIT Solve challenge is a GCI based communication device, and a GCI infrastructure platform (see here). Over time this platform will be used to deploy a number of GCI based applications, and social programs that together will make this solution sustainably self-funding once launched. This solution will begin by targeting those without digital access in East Africa, but is intended to be reapplied in the first world. To understand the needs of these people the GCI itself is intended to maximize collective capacity to gather the needs of the people and to engage them as the solution is being developed. This solution is also intended to leverage GCI to gain the capacity to address a very wide variety of needs. For example, in phase I only a small amount of GCI functionality will be implemented. While this functionality has been shown to have the potential to increase impact on collective outcomes by up to 750X (see here), in phase I it will be focused on limited industrial sectors and limited populations. In each progressive phase the GCI functionality implemented will be increased so that it's possible to achieve larger and larger impact on a greater and greater range of areas for higher and higher numbers of people. My expertise is that I've developed what I believe to be the first model of a "General Collective Intelligence" platform as described in the paper "Defining a Continuum from Individual, to Swarm, to Collective Intelligence, to General Collective Intelligence" currently in print in the International Journal of Collaborative Intelligence https://www.inderscience.com/info/ingeneral/forthcoming.php?jcode=ijci Just as an Artificial General Intelligence (AGI) is an Artificial Intelligence (AI) with general problem-solving ability, a General Collective Intelligence (GCI) is a Collective Intelligence (CI) platform with general problem-solving ability. A GCI is intended to enable groups to self-assemble in a self-sustaining way into massive networks of cooperation with the potential capacity to exponentially increase impact on any targeted collective outcome. I've written a number of papers describing how GCI can potentially be included into education solutions, health care solutions, or other solutions, to exponentially increase outcomes per program dollar. As described in the paper that I was recently invited to submit to the journal African Scientist ("General Problem-Solving v5") it is hypothesized that an exponential increase in general problem-solving ability, and therefore an exponential increase in ability to address any general problem, has never been reliably achievable before at any time in human history, and that this exponential increase has the potential to make some of the "wicked problems" reliably solvable, where those problems are existential human challenges today. Implementing a subset of GCI functionality to address any challenge has the benefit of making that functionality available to address every other collective challenge. For these reasons, GCI is hypothesized to potentially be the most important innovation today with respect to all of the MIT Solve challenges.

Challenges typically restrict solutions so that unforeseen approaches that are far more effective are ineligible. General Collective Intelligence maximizes a group's capacity to achieve any and all of the objectives of this challenge by defining a universal way of measuring fitness at achieving the targeted objective, and by defining an algorithm allowing groups to self-assemble into potentially massive networks of cooperation able to significantly increase impact on that objective. The specific objective within the challenge that is chosen will be decided by the GCI itself according to what choice is fittest in terms of maximizing collective impact per program dollar.

Multiple rapid prototype of GCI based solutions have been developed for slightly different problems (Afripad, Social Impact Marketplace, etc.). But for this problem of digital inclusion GCI is still in the concept stage. These GCI based platforms currently being conceptualized radically increase capacity to address the problems of access to commerce, credit lines, safety nets, and saving mechanisms.

General Collective Intelligence creates the potential for an exponential increase in the general problem-solving ability of groups, as well as the potential to exponentially increase impact on collective challenges such as the Sustainable Development Goals. This has never been achievable before in the history of human civilization as described here, and represents a fundamental shift. Implementing a subset of GCI functionality to address any challenge has the benefit of making that functionality available to address every other collective challenge. For these reasons, GCI is hypothesized to potentially be the most important innovation today with respect to all of the MIT Solve challenges.

This year: Current activities are mostly giving talks and writing papers, impacts of these activities remains to be assessed.

In one year: depends on funding

In five years: depends on funding

One indicator of progress are the papers published or submitted for review:

⦁ Article: General Problem-Solving Ability in Natural Systems as a Model for Solving Problems from Sustainable and Self-Financing Development in Africa to Artificial General Intelligence
⦁ Submitted to: Scientific African

⦁ Article: Human-Centric Functional Modeling of Individual and Collective Biological Systems

⦁ In Process of being Submitted to: International Journal of Biomedical Engineering and Technology

⦁ Article: Human-Centric Functional Modeling of Biocomputers
⦁ In Process of being Submitted to: International Journal of Bio-Inspired Computation

⦁ Article: Breaking Through the Barriers Between Centralized Collective Intelligence and Decentralized General Collective Intelligence to Achieve Transformative Social Impact
⦁ Submitted to: International Journal of Society Systems Science

⦁ Article: The Potential Necessity of a First-Person Approach in Achieving Artificial General Intelligence
⦁ Submitted to: Argumentation

⦁ Article: Defining and Quantifying an Exponential Increase in General Problem-Solving Ability Within Groups

⦁ Submitted to: Int. J. of Collab. Intelligence

⦁ Article: The Feasibility of Exponentially Increasing General Problem-Solving Ability in Groups

⦁ Submitted to: International Conference on Computational Collective Intelligence

⦁ Article: Are Wicked Problems a Lack of General Collective Intelligence?
⦁ Submitted to: AI & Society

⦁ Article: General Collective Intelligence and the Transition to Collective Super-Intelligence
⦁ Submitted to: Frontiers in Hybrid Collective Intelligence

⦁ Article: Approximating an Artificial General Intelligence or a General Collective Intelligence (requires editing and resubmission by June 1, 2021)
⦁ Submitted to: International Journal of Collaborative Intelligence

Full-time staff: 1

Part-time staff: 5

I'm the inventor of the only model for a General Collective Intelligence platform. There is literally no human on the planet better equipped to implement this model.

Still experimenting in this area.

I'm currently working with a small team to use game theory to demonstrate that group problems of "higher order complexity" can't reliably be solved without GCI. For this reason I believe that General Collective Intelligence is the most important innovation today with regards to every "wicked problem" and every existential challenge facing human civilization today. This effort has largely been conducted in isolation. But there is an African proverb that says "if you want to go fast, go alone. If you want to go far, go together". Actually implementing a GCI will require spreading the idea and creating the mind share that only the MIT Solve network can provide. It is time to walk together.

All efforts have been focused on developing the model of General Collective Intelligence and in understanding how it might be applied to products, services, and programs. We have defined detailed plans for all required activities, but lack the personnel or funding to execute the activities. Any assistance available will be leveraged.

Partnering with the MIT Center for Collective Intelligence could help build mind share for this concept. The partnership could take the form of the MIT CCI evaluating our progress and using it to define a case study regarding the claims about General Collective Intelligence.

One of the solutions planned for deployment on our radically more cost effective hybrid e-reader/educational computer was the "Education Management Platform". This platform is in the concept stage, but is planned to leverage General Collective Intelligence to radically increase capacity to deploy higher quality educational content and educational experiences, along with significantly improving the teaching workflow.

Some 430,000 refugees reside in the Dadaab and Kakuma refugee camps in Kenya. The Dadaab refugee camp is is one of the world's largest. Kenya is preparing to shut down two camps hosting over 430,000 refugees by June 2022. Deploying a General Collective Intelligence based digital inclusion solution to the camps is intended to significantly increase capacity to mobilize and organize individuals in the camps to create economic and educational opportunities.

General Collective Intelligence has the potential to make economic development in minority communities sustainably self-funding so that development might be achieved at the scale required to serve all such communities. No other solution has this potential.

General Collective Intelligence orchestrates cooperation between individuals or intelligent agents working on behalf of those individuals in order to radically increase the general problem-solving ability of groups, and therefore to radically increase the ability of groups to solve any general problem. When applied to Solve's Global Challenges, GCI has the potential to increase impact on those challenges per program dollar to the point that impact is sustainably self-funding, so impact can potentially be achieved at the scale required to be globally transformative. These intelligent agents are implement a subset of a functional model of AGI described here, that in turn  vastly increases the speed and scale at which it is possible to leverage AI.