Limitation Principles
Present-day science has long invalidated the basic tenets of the Newtonian/Laplacean
worldview. Most obviously, the twentieth century has produced a raft of “limitation
principles” proving that complete, certain knowledge is impossible—not just in
practice, but in principle [Barrow, 1998]. The most famous ones are:
1) the Heisenberg uncertainty principle, which shows that the observable
properties of particles are intrinsically indeterminate,
2) the theorem of Godel, which shows that even in pure mathematics we will
never be able to establish with certainty the truth or falsity of certain
propositions,
3) the existence of deterministic chaos, more colloquially known as the “butterfly
effect”, which notes that many physical systems, even when they are in
principle deterministic, are so sensitive to unobservably small fluctuations in
their initial conditions that we will never be able to predict their future
evolution [Prigogine & Stengers, 1984].
As an illustration that this list of limitations on predictability is merely the top of an
iceberg, let me just mention two lesser-known limitations:
4) the halting problem, which shows that even in the completely regulated world
of computer programs, we can in general not predict whether a particular
program will come to some conclusion or continue to run indefinitely;
5) the finiteness of the speed of light, which implies that in whatever way we get
information about remote parts of the universe this information will be
inaccurate when we get it, because the situation will have changed in the time
that the information needed to travel to us.
The conclusion is that the demon of Laplace will not only be unable to get all the
information he needs, but unable to calculate future trajectories based on that
information, partly because of intrinsic limitations on computability, partly because
the trajectories are fundamentally indeterminate and chaotic.
This means that uncertainty, and therefore surprise, has to be a part of the
scientific worldview. Prigogine [1997] has explored some of the philosophical
implications of this “end of certainty”, arguing that it opens the way to reconnect
science with the humanities by allowing for the appearance of novelty [Prigogine &
Stengers, 1984]. However, merely acknowledging uncertainty’s role in science is
hardly sufficient to unify scientific and narrative modes of thought.
Complex Adaptive Systems
More important even than the theoretical limitations on predictability are the practical
constraints [Gigerenzer & Goldstein, 1996]. Complete, accurate and reliable
predictions are in practice only possible for simple, isolated, “clockwork-like”