Product & Startup Builder

Algorithms Vs. Group Intelligence

Added on by Chris Saad.
I saw a Presentation/Q&A session with one of the Google founders who, when asked about his opinions about the (then) new trend of tagging responded with (and I paraphrase):

At Google we have always thought that computer algorithms should be responsible for indexing and classifying information for people rather than the other way around.

It struck me that this statement revealed a potentially growing philosophical divide between companies like Google who believe in machine based indexing, ranking and searching vs. the latest 'web 2.0' creations that seem to focus on explicit user/community interaction (and a belief in Group Intelligence) in order to achieve the same thing.

As far as I can tell, Google has resisted most forms of tagging in their applications while Web 2.0 apps continue to integrate it as one of their primary content classification methodologies.

While the question and answer was about tagging specifically, I think it applies more broadly.

For example, Google uses computer algorithms to determine which search results belong on the front page of a search and their news page uses yet more algorithms to work out what's 'front page news'. In fact, even some meme trackers have the same philosophy and use algorithms to discover and rank news and blogs – these include Tailrank, Techmeme and Technorati.

Digg and Wikipedia (as well as other similar sites), on the other hand, use direct human interaction on a mass scale. Group Intelligence.

However, I don't recall anyone ever saying 'I just got Tailranked'. Tailrank (and similar sites) do not seem to generate the level of traffic and interest as Digg has recently.

However, as most people know, Digg is in the middle of some controversy over their ranking systems which is causing many to wonder if ‘Group Intelligence’ (particularly when it comes to voting/popularity/value judgments) is actually just another name for Herd Mentality'?

With Touchstone, we have mainly made a bet on Algorithms in order to determine the 'Personal Relevancy' of an incoming item - but that's not to say that those algorithms can't take into account a broader set of factors including direct user rankings and feedback.