Here goes a claim that you will not only find in popular-science books but in some scientific circles as well:
Nature is complex, not linear. Science has ignored such simple fact until the 2nd half of the 20th century, and to a great extent it still does.
It is true that Nature is non-linear. The problem is, until the advent of computers it would have been impossible to achieve any practical results unless a first-order linear approximation was used.
Not only that. In many applications, you don’t care whether the context is really non-linear, as long as things behave linearly within the performance range of interest.
And indeed, along the lines of conscious linearity approximations, huge scientific and technological advances have been made.
Approximations happen all the time in science and technology. Some examples?
- We know that Nature is relativistic. However, as long as things move at speeds much smaller than light’s and do not travel intergalactic distances, we ignore the relativistic effects because we know they are negligible for most practical purposes.
- We know that Nature is quantistic. However, in most meso-scale situations (i.e., neither at an extremely small or at an extremely large one), we ignore quantum mechanics and continue designing applications (or build theories) in accordance with Newton-Laplace mechanics. (Pop-complex people think that Newton and Laplace should be trashed as relicts of the past. They think so because all they know about science is what they have read about “complexity”).
- Geometry is but an idealized approximation of reality. You will never find in Nature a perfect circle, triangle or square. Does than mean that their math equations are useless? No.
When we realize that the approximation no longer holds, we revert to the “real thing”. For example, practical GPS location requires that hardware and firmware take Relativity into account. Otherwise, relativistic effects, not negligible in this case, would provide us with wrong locations given the required response times.
Nature will always be non-linear, and science will continue to use linear approximations in all situations where it makes sense.