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Ideas:
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My work renders AI architecture legible as liability: from V = 0 and J = 0, through J = 1, to P = 1. I developed the KEV diagnostic to examine verification absence in generative AI and the governance failures that follow when institutions treat capability, human presence or approval as proof. The series traces how unverified AI-assisted reliance moves from micro-architecture to macroeconomic consequence: confabulation, benchmark reliance, epistemic debt, evidential burden, provider-shaped pathways and market mispricing. Its central question is practical and legal-evidential: can the institution prove the decision was defensible when consequence attached?
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