The One Crucial Idea of Web 2.0

Listening to James Surowiecki’s talk on the Wisdom of Crowds (mp3) at the SXSW Conference (I’m attending vicariously), I was struck at how pervasive this idea has become in such a short period of time. And the reason, of course, is the success of Google’s Pagerank algorithm, which harnesses the wisdom of crowds to model the way we value content.

If there is one idea that encapsulates what Web 2.0 is about, one idea that wasn’t a factor before but is a factor now, it’s the idea of leveraging the network to uncover the Wisdom of Crowds. Forget Ajax, APIs, and other technologies for a second. The big challenge is aggregating whatever tidbits of digitally-recorded behavior we can find, making some sense of it algorithmically, and then uncovering the wisdom of crowds through a clear and easy interface to it.

Listening to James Surowiecki’s talk on the Wisdom of Crowds (mp3) at the SXSW Conference (I’m attending vicariously), I was struck at how pervasive this idea has become in such a short period of time. And the reason, of course, is the success of Google’s Pagerank algorithm, which harnesses the wisdom of crowds to model the way we value content.

If there is one idea that encapsulates what Web 2.0 is about, one idea that wasn’t a factor before but is a factor now, it’s the idea of leveraging the network to uncover the Wisdom of Crowds. Forget Ajax, APIs, and other technologies for a second. The big challenge is aggregating whatever tidbits of digitally-recorded behavior we can find, making some sense of it algorithmically, and then uncovering the wisdom of crowds through a clear and easy interface to it.

Some folks like to point to technology as the heart and soul of Web 2.0. I don’t think so. The heart and soul of Web 2.0 is the new ideas that drive technological and social innovation, and the one crucial idea is the one found in Surowiecki’s seminal book. It has forever altered the way that software is written.

And the evidence is mounting. Today, Richard MacManus writes of the new features on Rojo, and in explaining what they are Chris Alden tells Richard that they’re emulating Pagerank:

“How do we do it? (determine relevance) Generally, just like Google used link metadata to determine relevance of search results, there is a fair amount of metadata we can use to infer relevance, including how many people are reading, tagging, and voting for a story, how popular the feed is — both to you personally, to your contacts, and to all readers, as well as things like link data and content analysis. ” (emphasis mine)

The end result is relevance engines, filters, recommendation systems, Web 2.0 software, or whatever you want to call it. And Surowiecki brilliantly sums it all up.

Published: March 17th, 2006

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