What is Collective Intelligence?

Collective intelligence is a term for the knowledge embedded within societies or large groups of individuals. It can be explicit, in the form of knowledge gathered and recorded by many people (for example, the Wikipedia (http://wikipedia.org) is the result of collective intelligence); but perhaps more interesting, and more powerful, is the tacit intelligence that results from the data generated by the activities of many people over time. Discovering and harnessing the intelligence in such data — revealed through analyses of patterns, correlations, and flows — is enabling ever more accurate predictions about people’s preferences and behaviors, and helping researchers and everyday users understand and map relationships, and gauge the relative significance of ideas and events.

Two new forms of information stores are being created in real time by thousands of people in the course of their daily activities, some explicitly collaborating to create collective knowledge stores like the Wikipedia and Freebase, some contributing implicitly through the patterns of their choices and actions. The data in these new information stores has come to be called collective intelligence, and both forms have already proven to be compelling applications of the network. Explicit knowledge stores refine knowledge through the contributions of thousands of authors; implicit stores allow the discovery of entirely new knowledge by capturing trillions of key clicks and decisions as people use the network in the course of their everyday lives.

Examples of uses for this type of intelligence already exist in industry. Google’s PageRank system, which assigns value to a web page based on the number of other pages that link to it, uses patterns discovered in hundreds of millions of links to determine which web pages are most likely to be relevant in a list of search results. Amazon.com examines patterns in hundreds of buyer variables to recommend purchases that a shopper might like based on previous purchases by the shopper as well as by other people who may have similar tastes or preferences.

Collective intelligence applications are an outgrowth of “open data,” the practice and philosophy that certain data should, or even must be freely available to everyone (Wikipedia, “open data,” retrieved December 2007). Collective intelligence refers to knowledge that can be uncovered by combing these open data stores, and already businesses and governments are using tools to mine these storehouses; there are obvious applications to medicine, manufacturing, and economics, just to name a few disciplines.

While the approaches that enable collective intelligence have their roots in the open source movement, there are clear distinctions between the data stores that constitute collective intelligence and other approaches to open information such as the Open Educational Resources (OER) movement. Specifically, collective intelligence is by definition highly distributed, both in its implicit and explicit forms. The data are not organized in the traditional sense, and indeed it is in part the unstructured nature of collective intelligence which allows it to be created and mined in ways that often lead to multiple levels of new insights.

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Please "sign" your contributions by marking with the code of 4 tildes (~) in a row so that we can follow up with you if we need additional information or leads to examples- this produces a signature when the page is updated, like this: - alan alan Jan 25, 2011

(1) How might this technology be relevant to the educational sector you know best?

  • Being able to track the 'thinking process' of a student as he/she navigates through learning materials/tasks/assignments etc can provide invaluable feedback to both the learners and teachers. If such technology can be integrated with diagnostic tools, it can provide useful/important intervention suggestions to teachers/learners so as to make the learning more effective - horncheah horncheah Feb 25, 2011
  • One of the most potent applications will be providing recommendation services from collective intelligence for "long-tail learning" resources that can be used to explore deeper learning as a function of the interests of the learner; we recommend such developments in the 2010 US National Education Technology Plan (http://www.ed.gov/technology/netp-2010); also see Brown & Adler 2008 (http://net.educause.edu/ir/library/pdf/ERM0811.pdf).- roy.pea roy.pea Feb 27, 2011

(2) What themes are missing from the above description that you think are important?

  • Perhaps issues of privacy can be highlighted here as such data collection could potentially be exploitative - horncheah horncheah Feb 25, 2011
  • The over-worship of collective intelligence as an emerging 'singularity' of computer and mind is well developed in the recent book by Jaron Lanier, inventor of virtual reality, in his important manifesto: "You are not a gadget" (http://www.amazon.com/You-Are-Not-Gadget-Manifesto/dp/0307269647)- roy.pea roy.pea Feb 27, 2011
  • While tracking of who is hitting what is valuable, another application will be in content analysis of computer mediated conversations. With more and more people have conversations in online spaces, collective intelligence tools that look at flow (who is talking to whom), function (the purpose of the conversation) and content (about what) will serve more valuable in educational settings. - sheryl.nusbaum-beach sheryl.nusbaum-beach Feb 28, 2011

(3) What do you see as the potential impact of this technology on teaching, learning, or creative expression?

  • When viewed inclusively to include the choice patterns of millions of people in music, books, movies, and one hopes in the future, learning resources, the impact of receiving just-right recommendations for learning resources along one's learning pathway (whether in informal learning or formal learning contexts) would be one of the most important developments in learning design ever. - roy.pea roy.pea Feb 27, 2011
  • The more sophisticated the collective intelligence tools and the more widespread, the more we can understand lurking in deeper ways in the k-12 realm. For example, lurking is seen as an entry level cognitive processing or knowledge construction skill- what if through collective intelligence we found that learners clicked through deep, abstract material and actually spent more time in spaces or with material that represented higher thinking challenges than on lower level tasks such as resource sharing? Would we come to understand lurking as more than a legitimate peripheral activity and find that deep thinking and interaction with content happens with lurkers too. - sheryl.nusbaum-beach sheryl.nusbaum-beach Feb 28, 2011

(4) Do you have or know of a project working in this area?

Please share information about related projects in our Horizon K-12 Project form.