142.

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		2.6.5— Biological Implications of the Control of Chaos (Continued)

		2— Are biological systems stable or unstable?

		We do not understand enough about biology to know how to think about living things. Thus we interpret the results of biological experiments using concepts from machines that we build and understand.

		Our technology has strived to build things that are stable. Stable systems are tolerant to small errors in control or small changes in the environment. An airplane continues to fly when the hand eases on the control or there is an additional gust of wind. We have thought of biological systems as also having these properties. That is, that biological systems are stable and that they are always trying to keep themselves stable. This concept is called homeostatis.

		But stability means that a system is hard to control. The stable airplane wants to fly straight, and doesn't want to turn. In order to make an airplane more maneuverable, we must make it unstable, and then control it. This means that the wires and the computer must work or the airplane will crash.

		Now that we have faster ways to process information, we are beginning to build systems that are inherently unstable and then control them. Unstable systems, such as chaotic systems, can be controlled finer and faster than stable systems. Perhaps living things have also chosen to use unstable systems to achieve better control.

		In the Lorenz system, cylinders of air rotate clockwise or counterclockwise. The old way of biological thinking would be to interpret each direction of rotation as a stable state and that a force then switches the rotation of the system. This is not what happens in the Lorenz system. Both directions of rotation are unstable. The act of rotating in one direction causes the switching to the other direction of rotation.

		This suggests a new way to think about biological systems. Instead of a biological system switching between stable homeostatic states, perhaps we need to think more of how the dynamics of being in one condition itself causes the system to switch to another condition.

 

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