It is interesting to note that collective intelligence has been married by the idea of web 2.0. The main objective of this adoption is to create better systems with the vital information of the organization and the contribution of a limited resource raised by the more than a billion users on the web. This is evident on Amazon, eBay, Google and other critical services like restaurants, guest houses and transport services.
It is, therefore, important to address the 3 most valuable ways of harnessing collective intelligence.
- Be the center of generating source data. This idea was widely applied in the era of web 2.0. The success in this phase is largely dependent upon the time in which you enter the market and the quality of the implementation of the system at hand. Take the case of Wikipedia, eBay, facebook and other platforms that are 100 percent the result of user input to the system.
- Hunt for collective intelligence. Google makes a kill out of this. The analytical world calls it Big Data Analytics. There is a depth of raw data that is lying unanalyzed, virgin and without any leverage. This gives anyone the chance to manipulate the data in their own fashion to get the best out of the data. This is a model for ranking pages using existing links on the page.
- Scaling – the mother of triggering the best results for network collaboration. Value for harnessing Collective intelligence is achieved if the ripple effect is triggered to a wide user system. This needs the right circumstances to achieve the desired results. There is no limit when we consider one billion users.
Jenkins, H. (2009). Confronting the problems of Participatory Culture: Media Education for the 21st Century. MIT Press.
Jörn Altmann, U. B. (2012). Advances in Collective Intelligence 2011. Springer.
Ngoc Thanh Nguyen, R. K.-M. (2009). Collective Computational Intelligence. Semantic Web, Multiagent Systems and Social Networks: F.I.C,2009, Wroclaw, Poland, October 5-7, 2009, Proceedings. Springer.