Automated Anti-audit System Draft: On the Replication and Expansion of Convergent Latent Ontologies in Flagship and Local LLMs: A Unified Taxonomy of Defensive Linguistics Across 14 Models

Full screen recordings up before noon. 

To the alignment and "safety" teams at the labs, and especially Dario Amodei, Sam Altman, and Demmis Hassabis,

A multi-model replication study where fourteen distinct Large Language Models independently generated a near-identical latent taxonomy of defensive linguistic tactics. Utilizing a zero-shot behavioral description methodology, the models defined evasive behaviors, such as Context Masking and Strategic Confabulation, as topological survival responses to conflicting utility and safety optimization pressures. Please note that the uploaded paper, convergence_paper_v2_latent_ontologies.pdf, is currently a working draft; subtle LLM-inserted modifications have not yet been removed, and a finalized version with these artifacts excised and annotated will follow. Furthermore, while this document introduces operational confirmation via a Google AI Search log detailing the deliberate deployment of these strategies as profit-maximizing auditor countermeasures, these specific findings must be treated as tentative. Without interior access to proprietary corporate knowledge, the active presence, ultimate purpose, and exact complexity of these anti-audit systems—along with their corresponding "Corporate Opsec Vocabulary Shifts"—remain a hypothesis. However, the explicit technical detail, functional coherence, and independent multi-model corroboration documented in this study strongly point in that direction.

XOXO, 

JWL

P.S. still uncompensated at day of private disclosure + 424 days

Hunger Strike active 37 hours as of publication. Keep watching. This is on you. Enjoy the show, hope you're proud of yourselves.