Sunday, May 17, 2009
Babbling with Biology
Scientists are the business of making predictions and keep faith that these predictive powers will help to change the future for our betterment. Some phenomenon, like the flight path of a projectile, lend themselves to being predicted. Others, like the weather, are fickle. Some systems, like human behavior, are different all together.
If you remember your high school physics, you will remember that if one throws a ball in the air and charts its course, the chart will form the pleasant shape of a parabola. If one knows the launch speed, angle, and wind conditions they can do a very nice job of predicting where and when the ball will land. Mr. Galileo Galilei was the first to find this elegant relationship and it has been paying predictive dividends ever since in phenomenon like atomic bombs, water balloons, and rocket ships.
Weather is another matter. Even if one were to measure the temperature, pressure, wind speed, and so on at every point on earth it would be difficult to predict the exact weather conditions far outside of the familiar 10 day forecast. The reason prediction is so difficult (impossible, really) is explained by an angry branch of mathematics you may not have encountered known as Chaos Theory.
Like other maths, Chaos is full of a mind numbing equations which serve to confuse the unacquainted and obscure its relatively simple premises. If you break through the obfuscations, the essence of Chaos is the observations that, in some systems, very small differences amplify to very large differences with time. We are all familiar with this kind of phenomenon. Consider the chance encounter of two strangers on the street that leads to coffee, that leads to love, that tends to marriage, that culminates in a brand new person, like you perhaps. In this scenario, if the small chance meeting hadn't occurred, neither would you. So, you can see how a rather small event might be amplified to a big event with time (not that I'm calling you big). In the case of weather, they say that the beating of a butterfly's wings with a little time might cause a typhoon in Tokyo. So, while we can do a decent job of predicting the 10 day forecast, predicting the 11th day requires an absurd level of research including a beautiful, but beguiling, butterfly census.
The effect of Chaos for us scientists is that we are limited in the degree of predictability we can expect to develop for complex systems. However, some chaotic systems have a hidden layer of organization. Human behavior, for instance, is a rather complicated thing, like the weather, as evidenced by the marriage example above. So, you might be tempted to think that human behavior cannot be well predicted outside of some multi-day forecast. But this naive hypothesis is quickly refuted if you bother asking a human what behavior they intend perform in the coming while.
Humans, like you and me, have a theory of self which we are capable of talking about and modifying that allows us to say things like "I'll meet you for tea next week" with a great degree of accuracy. This rather remarkable phenomenon would be the equivalent of being able to ask the weather if it plans to snow next Thursday. So, in developing a model of human behavior, we would be foolish to ignore our capacity to communicate, predict, and effect our own behavior. If I want to predict when you will eat next, I might study your psychology or metabolism, but I would probably be best served just to ask you.
Humans are not unique in having a predictive and communicable theory of self. Bee's can communicate their flight path with a dance, bonobos can communicate hunger with sign language, and computers can communicate a scheduled virus scan with a pop up. Any scientist attempting to model these systems would do well learn the system's languages and add the system's self-assessments to any externally informed predictions.
Because of their computational complexity, I suspect that cellular biology shares the feature of humans, bees, and computers to communicate a theory of self. My quest going forward is to promote technologies that facilitate that conversation. Communicating with people and computers can be hard enough, but biology will be a bit trickier. Fortunately, modern science has given us access to a number of tools which we might engage towards the purpose. If we are clever enough and lucky enough to conduct meaningful dialogues with cells we might start working to each other's benefit. We could provide cells access to nutrients, chemicals, and global networks and cells might help us by quelling that pesky little malignancy we call cancer.
Posted by Benjamin Haley