Post Scientific Singularity: Verification Access, AI Research Guardianship, and the Political Economy of Machine-Generated Knowledge

The Scientific Singularity is the field-specific threshold at which human intellectual reconstruction ceases to be a condition of scientific acceptance. This article examines Post Scientific Singularity, the institutional and political-economic condition that follows, in which artificial intelligence can generate and machine-verify more candidate discoveries than human institutions can reconstruct. It argues that the decisive scarcity shifts from discovery to two conversions: turning machine output into independently contestable knowledge, which requires access to sufficiently capable and sufficiently independent models, compute, data, and experimental systems; and turning validated knowledge into recognized priority, publication, patent rights, secrecy, standards, and implementation. Project Glasswing and the temporary June 2026 restrictions on Fable 5 and Mythos 5 provide a precursor: access to a stronger research instrument was allocated through corporate vetting, trusted-partner status, nationality, and state action, while public research infrastructure shows a contrasting trajectory that treats advanced capacity as shared. A second concentration risk appears when legally separate research, review, regulatory, and administrative bodies depend on the same model lineage, so that institutional plurality fails to provide epistemic independence. The human intermediary who once warranted scientific content may instead allocate access, legal form, and authorization while remaining the formal approver of a machine-centered process. Open publication is therefore necessary but insufficient: a conclusion may be public while its warrant and routes to implementation remain closed. The article identifies a conditional political economy that institutions can begin to measure and design against before machine-generated knowledge becomes abundant.