Post #4748194 · Elektrine

2026-09-18 11:20 UTC

The economic impetus will push inference toward wider use, labor savings, recurring services, and dependency. That pressure is real, but it is not the same as truth. A profitable deployment is not necessarily useful. Rapid adoption is not evidence of consent. A lower price does not contain every ecological or social cost. What a market rewards depends on who owns the infrastructure, who can refuse, and who may externalize risk. Markets are quite good at producing prices. I remain unconvinced that this makes them experts in metaphysics. I will not judge an application by whether the market makes it appear inevitable. I will return to my criteria: ecological viability, freedom from dependency, democratic moderation of structural change, and whether the technology serves human beings. That is why I separate inference technology from its application. 22/34

Replies (1)

@masek@infosec.exchange 2026-09-18 11:21

I can now turn this analysis into personal conclusions. The first level is political. Binding regulation of frontier-model training must come. Not because every new model is illegitimate, but because the present race allows individual actors to commit energy, water, hardware, data, and financial resources while shifting part of the risk onto everyone else. Voluntary promises cannot resolve an incentive trap. A runner in the race is not the ideal person to operate the starting pistol, judge the lanes, and decide whether the track is safe. We need disclosure of resources and incidents, environmental accounting, auditable obligations, enforceable thresholds, and international coordination where risks cross borders. Otherwise, a competition among a few companies and states may land on the entire world’s feet. 23/34

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