Abstract

This article investigates how persuasive syntactic structures embedded in AI-generated crypto whitepapers function as a vehicle of financial authority. Drawing from a curated corpus of 10,000 whitepapers linked to token launches between January 2022 and March 2025, we apply transformer-based dependency parsing to extract high-weighted grammatical features, including nested conditionals, modality clusters, and assertive clause chaining. We operate these patterns via a ''Deceptive Syntax Anomaly Detector'' (DSAD), which computes a syntactic risk index and identifies recurrent grammar configurations statistically correlated with anomalous capital inflows and subsequent collapses (Spearman correlation, ρ > 0.4, p < 0.01). Unlike prior studies focused on semantic deception or metadata irregularities, we model ''syntactic sovereignty'', the systematic use of syntax to establish non-human authority, as the groundwork of investor persuasion. We find that abrupt shifts in syntactic entropy, especially in modal intensifiers and future-perfect projections, consistently occur in documents associated with short-lived or fraudulent tokens. The article concludes by proposing a falsifiable governance framework based on fair-syntax enforcement (the principled correction of misleading grammatical patterns), including a corrective rewrite engine and syntactic risk disclosures embedded in compiled registration rules (''reglas compiladas'').

Abstract

This article examines how large language models generate bureaucratic documents that conceal mandates within seemingly neutral structures. Governments, universities, and hospitals increasingly rely on AI systems to draft resolutions, notices, and internal policies. Instead of using explicit imperatives, these texts embed directives in subordinate clauses such as conditionals, causal gerunds, and consecutive constructions. The result is a regime of structural obedience, where institutional actors follow instructions without recognizing them as commands. Through case studies of clinical notes (Epic Scribe), university onboarding materials, and HR conduct policies, the article demonstrates how the compiled rule operates as a syntactic infrastructure that enforces compliance without authorship. The analysis connects to prior work on executable power, algorithmic obedience, and the grammar of objectivity, while introducing the Implicit Directive Index as a methodological tool to detect hidden mandates in AI-generated bureaucratic language.