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Why controlling dangerous scientific capabilities is an execution-authority problem, not a knowledge problem.

As scientific AI becomes more capable, restricting what models know is not the answer. The challenge is determining who has authority to access sensitive knowledge, under what conditions, and whether that authority remains valid when disclosure occurs. Chris Ciappa examines how Samirac's Drift Stack™ and SAQ™ architecture apply execution-boundary control, runtime admissibility, and external correction to high-risk scientific capabilities without sacrificing legitimate research.
Member article
This article is available to Synth members. Membership is $50 per year and unlocks member articles through your Samirac account.