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Protocol as Prescription: Governance Gaps in Automated Medical Policy Drafting
Agustin V. Startari.
AI Power and Discourse, vol. 1, núm. 1, 2025, pp. 1-10.
  ARK: https://n2t.net/ark:/13683/p0c2/2Bd
Resumen
This article examines how health policy texts drafted with large language models can detach legal responsibility from the formal circuit of governance. Treating “protocol” as regla compilada, anchored to a Type 0 production in the Chomsky hierarchy, it specifies a provenance standard that binds each clause of an issued policy to its generating inputs, including prompts, parameters, retrieval sources, reviewers, timestamps, and cryptographic hashes. The method combines version-controlled diffs across scoping, drafting, legal review, and publication with a formal alignment of authority bearing constructions, focusing on deontic stacks, default scopes, agent deletion, and nominalizations. A simulated ministry case demonstrates end to end traceability, producing an exportable evidence bundle that links surviving clauses to their inputs and human approvals. Findings show where machine introduced formulations change duty of care or obscure decision rights, and define mandatory human sign offs when high risk constructions appear. The article delivers three operational artifacts for health agencies, a provenance specification, a responsibility matrix across drafting stages, and an audit checklist calibrated to inspection and courtroom needs. By reattaching authorship and justification to the formal record, the blueprint closes a governance gap in automated policy drafting and states the conditions under which AI assisted procedures remain defensible. DOI Primary archive: https://doi.org/10.5281/zenodo.17259810 Secondary archive: https://doi.org/10.6084/m9.figshare.30275833
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