Information theory introduced the image of system boundaries as implicitly projecting “input categories” upon reality, parsing it into “variables” with an associated space of possible outcomes.
So far reality has been depicted as a disorderly mist, fractured with a scatter of low-entropy pockets – “systems” – that feed on each other in a swirling, co-adaptive dance towards ever-increasing complexity.
“Order” and “disorder”, we have seen, are observer-dependent categories of a dynamical system’s state space. What characterizes disordered states, relative to any observer, is that different disordered states do not differ in any meaningful way.
Shannon’s measure of information is actually known as “entropy”, a word better known from thermodynamics, whose famous second law states that, in a closed system, it always increases to a maximum
Most psychologists studying perception and cognition today argue that Gibson’s radio-metaphor is flawed because a brain, unlike a radio, identifies a “signal” not directly, but in a memory-dependent way.
