Uncertainty and Unpredictability
Not the same
Uncertainty is a feeling.
Unpredictability is an action.
You feel uncertain of an outcome.
But an outcome is unpredictable
Elaine Lorefield
Among the capabilities that brains enable is the capacity to predict. This capacity appeared pretty early in the evolution of creatures with brains. Amphibians, reptiles, fish, birds and mammals all predict. Without being able to predict things like intentional movement would be impossible. In people prediction has capacities that a frog does not have. A frog can predict the path of a flying bug with great skill and can snap it up with it's tongue. Only now do our most advanced anti-missile systems approach that capacity. But people exist in a meaningful world. That is, we interpret raw sense data and perceive meaningful information. An assumption of predictability is built into the concept of meaning. For instance: to say that something is black is to predict that it will absorb most light falling on it. The prediction is what black means.
So for people, predictable is the way the world usually seems to be. We do encounter unpredictability a lot, from the weather to the behavior of the people around us, but we assume that we just don't know enough to make the prediction. And we assume that if we did know enough we would be able to predict the future and retrodict the past.
As scientists learned more and more about reality that simple deterministic view encountered many challenges. Newton's physics was perfect for predicting how two bodies would orbit each other - give the parameters of position and mass and velocity then you could predict the state of the system at any future time. It doesn't work for more than 2 bodies. Quantum Mechanics was shocking because of the way it mixed determinism with uncertainty. It works with a mathematical structure whose future evolution is perfectly deterministic, but whose physical predictions were probabilistic. That is, individual physical events were unpredictable, but given many events a certain occurrence would happen a predictable percentage of the time (predicted by QM). This is passing strange :-) But it seems to be the way things are. QM is very well tested and confirmed and the knowledge is now embedded in many of the devices we use every day. But QM also deals with reality at the atomic level of abstraction. People need very specialized training and equipment to be able to work at that level. And we can work well at that level in an instrumental way, but visualization still fails. :-) I think that when we find a way to visualize reality at that level then the uncertainty will fall away. But maybe not.
From the middle of the last century a new kind of unpredictability was discovered. The generic term for this is chaos theory. There are many different systems that exhibit chaotic behavior. I've studied quite a few of them over the years by writing programs that use them to place dots on a computer screen. You can explore them yourself using Fractint found at https://www.fractint.org/ My explorations have been of mathematical systems that are quite simple and deterministic, but they are also unpredictable. The systems I work with generally decide the color of a pixel by performing a repeated computation on a set of parameters. A screen full of such pixels shows a pattern. You can't predict what that pattern will be like precisely. but if you run the system again using the same parameters then you get the same pattern. A famous example is the Mandelbrot Set. You can zoom in on a region of this image by changing the parameters you use for your computation; ie change the coordinates of the bounding box of the image. With the M Set you see regions where all the pixels are the same color and then regions of random color. If you zoom in on the random region, then regions of same colored pixels appear. Within those regions you can predict what you will see if you zoom in further. But in the randomly colored regions you can't predict. Hence we have a deterministic system that is so unpredictable that it's not always unpredictable.
I've been working on a new system that simulates fields like the electric or magnetic field It draws "lines of force" between "poles". It's a deterministic system. You get the same result each time you run it with the same parameters. But the lines can be unpredictable sometimes. They propagate between poles making pretty smooth curves usually, but there are situations where a line will suddenly make a right angle turn. That is, the slope of the line was changing predictably up to a certain point and then it unpredictably changed.
Thinking about Elaine's words again as I watch my program run. I can see the lines propagate towards their desination - and usually I know the destination but sometimes I don't - the sharper the curvature of the line, the more uncertain I am about the destination. And the system is deterministic - I get the same result each time I run it
what do yu think?