Deliberation Maps and the Dilemma of Scale

The point of a collective intelligence system is to enable synergy amongst people with different strengths and styles: “we are smarter than me”.  Each person contributes what they can, filling in each other’s gaps. Not everyone has to wear every hat. A core challenge, though, is dealing with scale. As you scale the user population, the number of new ideas will eventually grow much more slowly than the number of contributors, undercutting the signal to noise ratio. But the chance of getting a *ground-breaking* idea (from the end of the “long tail”) continues to grow with scale. This creates a dilemma. You need lots of contributors to get important “weak signals”, but this can create huge redundancy. That’s where a deliberation system can help, because every unique point appears just once where it logically belongs. A colleague of mine in the UK (David Price) made an interesting demonstration of this (see ). He analyzed the arguments presented, in 102 media articles, to a Tony Blair speech. Even though most of the news reports individually made rather small points, with lots of repetition across reports, the complete set of arguments expressed across all the articles “constituted a mature and reasoned response to the Prime Minister’s lecture and developed the debate significantly beyond the case he outlined”. The deliberation map that David and his colleagues created (a portion is included below) made it possible to  perceive the underlying richness of the response in a compact, systematically-organized structure

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One Comment on “Deliberation Maps and the Dilemma of Scale”

  1. David Price Says:

    Hi, Mark.

    Thanks for blogging about our project with the Prime Minister’s Office, and welcome to the blogosphere!

    One of the other salient observations about collective intelligence systems like Debategraph and the Deliberatorium is that the cumulative, structured, distillation of knowledge embodied in the maps, allied to their openness to further revision, tends to ensure that they retain a rich and evolving relevance beyond the specific time and context of their creation.

    Capturing the community’s understanding in such a compressed form enables subsequent participants to quickly achieve the same depth of understanding as the original participants, and makes it easier for new participants to spot, and fill, any gaps in the original understanding.


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