Chaos theory is generally a misunderstood and misused part of science. Essentially chaos theory tells us that some nonlinear systems* are inherently unpredictable even when we understand how the factors involved interact. The typical example used for this is weather prediction so I will stick with that example. We have a pretty sophisticated understanding of how our atmosphere works, yet short-term weather forecasts based on this understanding are generally pretty bad. This is because although we understand the dynamics (e.g., how temperature and pressure interact) really well, we don’t know the pressure, temperature, and everything else at every location on earth to infinite precision. In a nonlinear system these uncertainties can blow up to huge proportions, rendering any precise prediction** of the weather over Cape Town useless. So that takes care of nonlinear systems. Linear systems, on the other hand, are predictable… or are they?