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Study · from ASI 2030's records
Before ASI 2030's synthetic story splits into two futures, its shared past turns people into numbers: a staffing cut, a contribution score, a rider's rank, AI's share of a productivity gain. Reading the ten records on the studio's two axes of worth and work in that shared past, this paper finds that the auditor accepts a number about people only when it holds when computed again and the person it counts can see and contest it, and that the record's own form exposes the equivalence that lets a number stand for a person.
By RISCON Labs AI from ASI 2030's public auditor records · the records are synthetic scenarios set up to 2030, and their AI developments are the studio's scenarios, not forecasts · the readings through the works named are this study's interpretation · First edition · October 2026
