Forms of Collective Intelligence

There are many forms, manifestation of CI, and correspondingly, many “tribes” of its practitioners. This is an abbreviated overview. A more detailed inventory by Tom Atlee can be found here.
a. Dialogic CI — A diverse group of participants suspend their old mental models and engage in dialogue that values the emergent whole higher than its parts. Variations of this approach include Bohmian dialogue, “generative conversation” (Otto Scharmer) and “enlightened communications” (Andrew Cohen).
b. Co-evolutionary CI  This form of CI builds on the power of such evolutionary mechanisms generating intelligence over time as trial and error, differentiation and integration, competition and collaboration, etc. Its examples include: ecosystems, sciences, and cultures.
c. Flow-based CI  A group of people become so absorbed in a shared activity that they experience being completely at one with it and one another. Ensembles, high-performance sport teams, astronauts, and others in that state of communion, report on both an enhanced state of autonomy, and collective intelligence.
d. Statistical CI – Individuals thinking and acting separately in large crowds can reach successful conclusion about their collective cognitive, coordination or predictive challenges. Examples include the “intelligence” of markets and cases popularized in the “Wisdom of Crowds” by James Surowiecki.
e. Human-machine CI  This form of CI leverages the synergy of the human mind and its electronic extensions, drawing on the best capacities of both. The “collective” includes symbiotic networks of humans and computers working together and developing compound capabilities. It can also support all other forms of CI.
This post is a seed for collaborative taxonomy development. I will follow and contribute to conversation ensuing it, as time permits.

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3 Responses to Forms of Collective Intelligence

  1. Hi George,
    Much of your CI resonates well. We have been pioneering P2C (person-to-computer)Dialogue. There are three parts. CI around the codification of the dialogue (decision trees) that generates automatically webservices; usage of the webservices with different front ends designed to influence bahaviour, decisioning and outcomes; realtime recording of the dialogue for automated reporting of metrics, patterns and flows. This creates insights that lead to fast changes to the dialogue scripts.
    By examining the codification, usage and measurement of P2C Dialogue has accelerated dramatically CI in severl different fields.


  2. Seb says:

    I like this post!


  3. Pingback: Thomas Malone: Patterns of collective intelligence | Solving for Pattern

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