DOI
DOI
DOI
This book consolidates a cycle of research on the structural foundations of authority in artificial intelligence. It brings together a series of peer-reviewed articles that demonstrate how power in AI systems no longer depends on meaning, interpretation, or intention, but on syntactic sufficiency.
The argument develops in fourteen chapters, beginning with the autonomy of sense beyond reference and culminating in the colonization of temporality by predictive infrastructures. Along the way, it formalizes a set of theoretical contributions: the regla compilada as a Type 0 grammar of executable authority, the figure of the soberano ejecutable as operator of legitimacy without subject, the theorem of Disconnected Syntactic Authority (DSAT), the theorem of the Limit of Conditional Obedience (TLOC), the δ [E] → ∅ rule of ethical trace deletion, and the formalization of compiled norms as computable legal speech.
The book demonstrates that:
Authority migrates from agents to structures, producing the sujeto evanescente.
Ethical, interpretative, and referential markers can be structurally erased without breaking execution.
Legal norms can be transformed into executable grammars with cross-linguistic validity.
Predictive infrastructures colonize time, replacing futurity with executable closure.
AI Syntactic Power and Legitimacy marks the closure of a first syntactic phase of research, while opening the way to further studies on structural delegation, institutional obedience, and computable legality.
Author: Agustin V. Startari, linguistic theorist and researcher in historical studies (UdelaR and University of Palermo).
DOI
This work is part of the Working Papers series (No.?11), and is released for public academic use under the LEFORTUNE label, following an author-publishing model.
Keywords:
syntactic authority, executable grammar, compiled rule, predictive systems, language infrastructure, LLMs, algorithmic obedience, impersonal normativity
Canonical DOI: 10.5281/zenodo.15800175
Mirror version (Figshare): 10.6084/m9.figshare.29469518
DOI: https://doi.org/10.5281/zenodo.15754714
This work is also published with DOI reference in Figshare https://doi.org/10.6084/m9.figshare.29424524 and Pending SSRN ID to be assigned. ETA: Q3 2025.
A balanced corpus of 1 000 model outputs was analysed: 600 medical texts from PubMed (2019-2024) and 400 legal summaries from Westlaw (2020-2024). Standard syntactic parsing tools identified structures linked to authority simulation. Example: a 2022 oncology note states “Treatment is advised” with no cited trial; a 2021 immigration decision reads “It was determined” without precedent.
Two audit metrics are introduced, agency score (share of clauses naming an agent) and reference score (proportion of authoritative claims with verifiable sources). Outputs scoring below 0.30 on either metric are labelled high-risk; 64 % of medical and 57 % of legal texts met this condition. The framework runs in <0.1 s per 500-token output on a standard CPU, enabling real-time deployment.
Quantifying this lack of syntactic clarity offers a practical layer of oversight for safety-critical applications.
This work is also published with DOI reference in Figshare https://doi.org/10.6084/m9.figshare.29390885 and SSRN (In Process )
]]>This work is also published with DOI reference in Figshare https://doi.org/10.6084/m9.figshare.29665697 and Pending SSRN ID to be assigned. ETA: Q3 2025.
]]>