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The MIT Center for Collective Intelligence recently published an important overview of the theory and mechanisms behind successful crowdsourcing efforts. Their report, called “Harnessing Crowds: Mapping the Genome of Collective Intelligence“, can be found here.
( http://cci.mit.edu/publications/CCIwp2009-01.pdf )
According to the Center for Collective Intelligence, a good collective intelligence platform (CI) must address the following themes:
Goals, referring to the desired outcome;
Incentives, referring to the motivational factors;
Structure/process, referring to the business model and organizational structure to complete the task; and
Staffing, referring to the people required to support the business model and sustainability of CI within the organization.
These four themes then translate into the following four questions:
What is to be accomplished?
Why should anyone help out?
How are they meant to contribute?
Who will perform the necessary work?
Figure 1, below, illustrates how these four themes and questions interact to form the building blocks of any collective intelligence system.
Figure 1, the basic building blocks of a CI system
Developing a detailed decision tree
This approach then asks a series of sequential, logical questions, the answers of which form specific guidelines for all CI systems:
Can activities be divided into pieces? Are necessary resources widely distributed or in unknown locations?
Are there adequate incentives to participate?
What kind of activity needs to be done?
Can the activity be divided into small, independent pieces?
Are only a few good (best) solutions needed?
Does the entire group need to abide by the same decision?
Are money or resources required to exchange hands or motivate decision?
The answer to these questions comes in the form of specific “genetic” building blocks, such as the “Create” gene, the “Crowd” gene, or the “Decide” gene. The paper concludes with a detailed table listing these genes and how they interact with the questions above.
In my own work developing online scenario planning systems, I have found it useful to translate these questions into a flowchart that can be used to help navigate this process. This chart is presented in Figure 2, below, which presents each of these questions and possible answers in the form of a decision tree (full PDF by clicking on the image or downloading here http://www.noahraford.com/files/CI_flowchart_raford.pdf ).