The In-Between as a Calibration Architecture for Autarkic Superintelligence

Abstract

Proposes the In-Between as a calibration architecture for governing autarkic superintelligence — AI systems that operate with increasing self-sufficiency. Argues that calibration, not control, is the appropriate governance paradigm.

Keywords

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