The Decoherence Trap: When AI slop drowns out the signal in an endless sea of noise
TL;DR
This essay introduces the concept of decoherence: the accumulation of locally valid but mutually incompatible or redundant models within a system, such that the cost of change is dominated by translating among those models and preventing unintended side-effects.
In other words, it's what happens when slop drowns out the signal in an endless sea of noise.
Decoherence grows relative to the rate of change of a system, and it increases faster the more decoherent a system is, resulting in runaw...
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