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.

INSTRUCTIONS: Enter your responses to the questions below. This is most easily done by moving your cursor to the end of the last item and pressing RETURN to create a new bullet point. Please include URLs whenever you can (full URLs will automatically be turned into hyperlinks; please type them out rather than using the linking tools in the toolbar).

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 27, 2010

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

  • I think that museums really miss out in not having any useful recommender technology for their collections (and other assets). Amazon and the like can harness huge volumes of implicitly generated data and create useful recommendations from it, but museums individually struggle to create the mass of data to do that effectively. Generic systems like Flickr or Delicious must hold a rich dataset on how people interact with museum-related resources, but pulling that out is not currently possible, so museums cannot use that to make recommendations or otherwise learn from behaviour. - jeremy.ottevanger jeremy.ottevanger May 4, 2010
  • another response here

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

  • The challenge facing museums is aggregating enough of this data to make any sense (or getting it out of third party systems). This is one reason why I think it would be great for museums to collaborate on logins. If users had a profile that operated over multiple museum websites, key information on behaviour (tagging, searches, favourites etc) could be collected centrally in a large enough mass to really learn. Users would benefit from being offered (a) a single login and integrated profile management, (b) useful recommendations, and (c) all their stuff (faves etc) in one place. Museums would benefit from (a) login being more worthwhile and managed centrally (including basic services such as bookmarking), (b) data on their users' behaviour being put in the context of a larger pool of data and therefore making more sense. Sorry, I know that's not all exactly on-topic for this subject, and you'll find it alluded to under my entry for digital identities too! - jeremy.ottevanger jeremy.ottevanger May 4, 2010
  • another response here

(3) What do you see as the potential impact of this technology on education and interpretation in museums?

  • your response here
  • another response here

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

Please share information about related projects in our Horizon Project sharing form.