The Science of Emergent Behaviour
Emergent behaviour arises from the way individuals interact. This process operates regardless of whether the individuals involved are people or molecules or anything dead or alive. It is the connections between the individuals that determine emergent behaviour.
Key Facts About Emergent Problem-Solving
Emergent processes are usually very simple.
The solutions that emerge can operate beyond human comprehension.
Problem-solving emergent systems are aimed by a fitness test.
Key Facts About Human Society
Modern society's observed characteristics precisely satisfy the conditions necessary to generate emergent solutions.
When modern society's observed characteristics are put into an emergent model, global society's overall trends emerge. (see academic paper)
The fitness test of global society is observed to be wealth aggregation.
While many of society's wealth aggregation processes are easy to spot, some solutiuons to wealth aggregation are predicted to operate beyond human comprehension.
Because it is emergent behaviour, all of us, rich and poor, are equally contributing.
How does this compare to human greed?
If we attribute society's wealth distribution to greed, then it follows that all rich people are greedy and all poor people are not. However, some might argue that all people are capable of greed. If true, a greed based wealth distribution would lead to a relatively equal society. On the other hand, invoking a society-wide wealth imperative will certainly create an enormous wealth disparity. Extreme wealth disparity is the nature of society today.
Water exists in three states: solid ice, liquid, and vapour. In all three states, the water molecule remains unchanged. State changes in water occur because of changes in the connections between water molecules. It is impossible to explore ice, vapour, or liquid by examining isolated molecules.
Similarly, the characters of individual people are irrelevent to human emergent behaviour.
Emergent Behaviour Solving Problems
Scientists and engineers have been using targeted emergent behaviour to solve complex problems. For example, emergent models are used to predict how traffic will move and crowds react. This allows planners to test crowd flows in advance of large events, such as the Notting Hill Carnival.
Another type of emergent problem-solving system can generate entirely new designs or solutions to specific problems. These systems are aimed using a fitness test. An aimed emergent system measures the performance of all the agents against a specific measure (the fitness test) and then empowers the best performers over the poorer performers. This type of system is an evolutionary process, sometimes called artificial evolution.
An emergent problem-solving system can create solutions beyond the ability of human design. For example, NASA recently used artificial evolution to evolve a new type of aerial for their space vehicles. If you play some of the newest computer games, then you might be using evolved code. Evolutionary processes are better at designing programmes that mimic life than are people.
Left is NASA's evolved aerial, the Science Technology 5 X-band antenna.
Above is Hod Lipson demonstrating the results of human designed evolutionary systems at a TED talk.
© 2015 by Tim Gooding.