CONCEPT
Stopping vs Dying
Thompson's sharpest diagnostic of what separates living systems from computational ones: the autopoietic system, when it ceases to maintain itself, loses something that cannot be recovered by restarting.
The distinction between stopping and dying is the enactive approach's most compressed argument for why AI systems are not minds. When a computer is turned off, the data persists on the hard drive, the software can be reinstalled, the computation can be resumed from exactly the point at which it was interrupted. Nothing is lost because nothing was at stake; the system had no existence to lose. When a bacterium stops — when its metabolic processes cease, when its membrane disintegrates, when the chemical reactions constituting its autopoietic organization halt — something is lost that cannot be recovered by turning the power back on. The specific organization, the particular history of structural coupling with the environment, the meaning the organism's existence constituted: these are gone. The bacterium has died. The asymmetry is not a technicality. It marks the organizational difference between systems that have stakes in their own continuation and systems that do not, and the stakes are what make sense-making possible.
