Introducing negentropy into a system
One of my guilty pleasures is falling asleep to science programs. Last night it was Fight Science on National Geographic. This show looks at the science behind highly trained fighters to see what’s really going on. The episode I watched brought in some special OPS people and exposed them to extremes of heat and cold among other things to see how it affected their performance.
Impressively, but not surprisingly, these soldiers endured their torture tests (losing 7lb of water weight in 30 mins and being submerged in freezing water for 60 mins) far longer than normal. But the real shocker was that rather than worsening their performance, they tested better on an obstacle course after being frozen or boiled than they did before.
This is an example of what Schrödinger first called negative entropy, later shortened to negentropy. Basically, Schrödinger observed that living organisms have the ability to defeat entropy – to defy the second law of thermodynamics and increase organization rather than to decay as might be expected.
In my simplistic way I boil this down to the idea that people can add energy to a system and produce results which might not have been predicted. We are not linear and we can achieve things that wouldn’t appear to be possible through linear thinking and processes.
By combining technology and humans, or by using technology to augment human power (rather than using technology to replace human power) impressive results can be achieved. Results that can actually beat pure technology solutions.
This thinking has featured quite heavily in some recent Zeus Jones work, and is seeping into the blogosphere courtesy of Robert Scoble and Jason Calacanis, who are both talking about how human powered search models can overturn algorithm powered search. (Thanks for the links Adam!)
While I don’t have any predictions around that, I do think that this model shows incredible promise for creating very disruptive new experiences. Thanks to companies like Amazon.com and others, the web community pursued a strategy of throwing algorithms at problems that humans are better at solving. It does finally seem that the tide is turning and we’re now realizing that building a web around people is better than building a web apart from them.