Published September 18, 2025 | Version v1
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AI Syntactic Power and Legitimacy: How AI Structures Shape Power

  • 1. ROR icon Universidad de la República
  • 2. ROR icon Universidad de la Empresa
  • 3. Universidad de Palermo

Description

AI Syntactic Power and Legitimacy: How AI Structures Shape Authority

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).

Publisher: LEFORTUNE

ISBN: 9798266066687

DOI: https://doi.org/10.5281/zenodo.17154108 and https://doi.org/10.6084/m9.figshare.30158239 

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ISBN
979-8--26606668-7

Related works

Cites
Journal: 10.2139/ssrn.5272361 (DOI)