Theoretical background - collective intelligence
The OVN model is thought as to enhance social/collective intelligence. Moreover, the model itself is improved by its participants in practice, by constantly tweaking the IT infrastructure, the governance, work methodologies, and culture.
We believe that p2p is a new paradigm that can lead to a new socioeconomic order, because we believe that this paradigm can engender models that have an edge, which comes precisely from enhancing and leveraging social/collective intelligence for innovation processes (crowdthinking), and crowdsourcing for production and dissemination. Otherwise, traditional hierarchical models have reached their pick of innovation and productivity. There is no more juice to be squeezed out of the traditional hierarchical and competitive models. But we can do a lot more and better using p2p models, which tap into this new layer that is emerging now, crowdthinking and crowdsourcing. We're trying to connect people and incentivize people to get to that next level.
We say: from global commons to local economies. The global commons is seen as memory (the repositories of open source designs -digital assets, abundant, non-rivalrous), or as process (the open source development process, its tools, governance, methodologies, etc.).
See Pierre Levy's work, he provides another way to see the work around the OVN model.
NOTE: this topic is connected to Living systems.
Between 2017-19 social intelligence took a practical turn, mostly through discussions with Dmitry Sokolov, as it became an integral part of Sensorica's methods of co-production. For example, templates were created for collaborative text production that took into consideration psycho-social dynamics among contributors. See for example (S) TEMPLATE paper study report proposal.
Dmitry Sokolov worked on the "human brain", which is about mapping concepts into a digital form.
Collective intelligence (CI) is shared or group intelligence that emerges from the collaboration, collective efforts, and competition of many individuals and appears in consensus decision making. The term appears in sociobiology, political science and in context of mass peer review and crowdsourcing applications. And in Education (open pedagogies).
It may involve consensus, social capital and formalisms such as voting systems, social media and other means of quantifying mass activity. Collective IQ is a measure of collective intelligence, although it is often used interchangeably with the term collective intelligence.
It can be understood as an emergent property from the synergies among: 1) data-information-knowledge; 2) software-hardware; and 3) experts (those with new insights as well as recognized authorities) that continually learns from feedback to produce just-in-time knowledge for better decisions than these three elements acting alone. Or more narrowly as an emergent property between people and ways of processing information. This notion of collective intelligence is referred to as "symbiotic intelligence" by Norman Lee Johnson.
The concept is used in sociology, business, computer science, mass communications, and in science fiction. Pierre Lévy defines collective intelligence as, "It is a form of universally distributed intelligence, constantly enhanced, coordinated in real time, and resulting in the effective mobilization of skills. I'll add the following indispensable characteristic to this definition: The basis and goal of collective intelligence is mutual recognition and enrichment of individuals rather than the cult of fetishized/hypostatized communities." According to researchers Pierre Lévy and Derrick de Kerckhove, it refers to capacity of networked ICTs (Information communication technologies) to enhance the collective pool of social knowledge by simultaneously expanding the extent of human interactions.
Collective intelligence strongly contributes to the shift of knowledge and power from the individual to the collective. According to Eric S. Raymond (1998) and JC Herz (2005), open source intelligence will eventually generate superior outcomes to knowledge generated by proprietary software developed within corporations (Flew 2008). Media theorist Henry Jenkins sees collective intelligence as an 'alternative source of media power', related to convergence culture. He draws attention to education and the way people are learning to participate in knowledge cultures outside formal learning settings.
Both Pierre Lévy (2007) and Henry Jenkins (2008) support the claim that collective intelligence is important for democratization, as it is interlinked with knowledge-based culture and sustained by collective idea sharing, and thus contributes to a better understanding of diverse society.
Writers who have influenced the idea of collective intelligence include Francis Galton, Douglas Hofstadter (1979), Peter Russell (1983), Tom Atlee (1993), Pierre Lévy (1994), Howard Bloom (1995), Francis Heylighen (1995), Douglas Engelbart, Louis Rosenberg, Cliff Joslyn, Ron Dembo, Gottfried Mayer-Kress (2003).
Pierre Lévy: I was predicting (along with a small minority of thinkers) that the Internet would become the centre of the global public space and the main medium of communication, in particular for the collaborative production and sharing of knowledge and the dissemination of news.
Engelbart attended the Program for the Future 2010 Conference where hundreds of people convened at The Tech Museum in San Jose and online to engage in dialog about how to pursue his vision to augment collective intelligence.  "Douglas Engelbart". Corporation to Community. February 16, 2011.
Engelbart reasoned that the state of our current technology controls our ability to manipulate information, and that fact in turn will control our ability to develop new, improved technologies. He thus set himself to the revolutionary task of developing computer-based technologies for manipulating information directly, and also to improve individual and group processes for knowledge-work.
The dynamic knowledge repository (DKR) is a concept developed by Douglas C. Engelbart as a primary strategic focus for allowing humans to address complex problems.[when?] He has proposed that a DKR will enable us to develop a collective IQ greater than any individual's IQ. References and discussion of Engelbart's DKR concept are available at the Doug Engelbart Institute.
The Doug Engelbart Institute, previously known as The Bootstrap Alliance, is a collaborative organization founded in 1988 by the late Douglas Engelbart and his daughter Christina Engelbart, to research into the enhancement of human ability to solve complex, urgent problems. Engelbart believed that it is possible to enhance society's collective intelligence by applying his strategies.
Wenger2 (2005) développe le concept de communautés de pratique comme un groupe de personnes qui travaillent ensemble (à travers des plateformes internet par exemple tels que des forums, des vidéo-conférences, des courriels…) et qui sont en fait conduites à inventer constamment des solutions locales aux problèmes rencontrés dans leur pratiques professionnelles. Après un certain temps et au fur et à mesure que ces personnes partagent leurs connaissances, leurs expertises, ils apprennent ensemble.
Pour Wenger, trois dimensions structurent les communautés de pratique (Wenger, 1998) :
- Un engagement mutuel : Tous les membres de la communauté doivent respecter cet engagement. La confiance et l’ouverture aux autres sont des caractéristiques primordiales. Le but est d’utiliser les compétences et les complémentarités de chacun. Ainsi, les membres doivent être capable de partager leurs connaissances et de les lier à celles des autres membres. L’objectif principal de l’engagement mutuel est donc que chacun aide et soit aidé par un autre membre de la communauté.
- Une entreprise commune : D’après Wenger, il est important de créer une entreprise commune interne à la communauté. Cette entreprise aura pour but de faire interagir ses membres afin d’accomplir l’objectif de l’entreprise commune et de la faire évoluer en fonction des nouveaux enjeux et problèmes intervenants.
- Un répertoire partagé : Ce répertoire est primordial pour l’entreprise commune. Il caractérise les ressources permettant aux membres de communiquer, de résoudre des problèmes. Les ressources peuvent être de différents types : mots, outils, routines, procédures, dossiers…
+ Learning Organizations, by Peter Senge.
How do we measure network intelligence?
We can think of this as the ability of the organization to solve problems. One way to assess the level of intelligence is to look at the complexity of problems the organization can solve.
How well is the information distributed throughout the network. A good indication of high intelligence level would show information related to problem solving reaching far towards the edge of the network (into the long tail). If the problem is only the concern of the core group there's a problem. Communication and messaging is an important IT infrastructure component.
An indication is the documentation process, how well the network captures and structured information related to the problem and makes it available to all affiliates. The content management system, an IT infrastructure component is an important element.
Ability to learn from mistakes and recycle past work
The organization has procedures to document failures in problem solving and turn them into new learning. Also the ability of reusing partial solutions to failed problem solving attempts into new problem solving activities. Sensorica's [NRP-CAS] is an IT infrastructure component that allows remix of all resources, which include digital resources such as designs, reports, etc.
Type of problem
Problems can range from simple to very complex. Complex problems are also called wicked problems. They are multi-dimensional, require a larger number of competencies, involve a larger number of stakeholders. Past results on complex problem solving is definitely an indication of organizational intelligence level.