It seems as if attempts to use knowledge to understand and manage social networks are everywhere. Millions, if not billions, of dollars are being spent in an attempt to derail terrorist networks, with much of it being invested in making sense of massive data streams. There is growing concern that much of this money is being squandered on approaches that will never deliver on their promises.
Our armed forces are being prepared to combat terrorist threats by the introduction of “network centric approaches” and “digital battlefields” – basically attempts to provide warfighters with a complete picture of the battlespace. However, the experience of practitioners suggests that the “data smog” this creates is actually counterproductive.
From the arena of politics, the recent invigorating battle between senators Clinton and Obama has thrown the spotlight on the deficiencies in political polling (Economist, 2008b). Changes in the structure of the situation (e.g. high turnouts) have thrown the whole industry into chaos. Complexity is being discounted and the results are stark. The conclusion formed in the media was that the situation was wildly unpredictable (so anyone’s to win), and ended up having real consequences for the Democratic challenger in November 2008 (Baldwin, 2008).
Turning to business, we find that Société Générale recently lost $7.2bn as the result of a single rogue trader making a series of bogus transactions amid turbulent markets in 2007 and 2008. There has been much speculation on what was known, when it was known, and who knew it. In other words, we have speculation that this is an example of the role of knowledge in the mismanagement of social networks – with spectacular effect.
At a glance, the problems highlighted above seem positively overwhelming. Where do you start? But start we must. Simple “cause and effect” thinking doesn’t seem to be able to cut the mustard. There is broad agreement that even if the Kyoto t