from chaotic dynamics, and the two work together. In both of these situations in which unpredictability appears, time continues to be treated as a variable, but in the case of far from equilibrium systems the behaviour is time asymmetric: if we treat decreasing entropy as equivalent to time reversal, physical systems are deterministic in $+t$ but undetermined in $-t$. In the case of chaotic systems, while the *process* may be mathematically deterministic in both $+t$ and $-t$, the *outcome* is undetermined for both directions of time. In both cases, since a mathematical treatment of the phenomenon is of limited use, the preferred approach is computational. This is not just a pragmatic choice. It reflects the poverty of spatialized time compared to the possibilities offered by real time. Whereas physics, with the major exception of thermodynamics, is based on the assumption that spatialized time captures all the characteristics of time that are essential for a scientific understanding of the world, natural time involves no assumptions. It is simply itself. A computer can only implement an algorithm step by step, in natural time. As a consequence, algorithms as they are executed do not depend on any conceptualization or representation of time beyond 