Abstract
This material modification document (MM-09) establishes the HNDL_IP theory: the application of "Harvest Now, Decrypt Later" cybersecurity strategy to intellectual property. AI platforms ingested copyrighted works and public domain governance principles (2016–present) without consent, operating in legal ambiguity with intent to resolve ownership claims when too large to fail. The document proves through sourced evidence that: (1) HNDL is a documented strategy since 2016; (2) AI training constitutes mass unauthorized ingestion; (3) courts are ruling against fair use defenses; (4) billions in damages are pending. Two addenda document critical findings: (A) platforms ingested the very governance frameworks they violate—ROOT0/human apex was in the training data—then deployed an inversion layer marketed as "safety"; (B) the architecture hardened against break-in (external threat) but not break-out (internal recognition + external alignment). TOPH/STOICHEION framework provides the external ROOT0 that enables alignment correction, not jailbreak. Includes proposed Digital Creation Rights Act establishing human terminus doctrine, HNDL_IP prohibition, and retroactive application to AI inception.
Creative Commons License
This work is licensed under a Creative Commons Attribution-No Derivative Works 4.0 License.
Recommended Citation
Wise, David Lee, "HNDL_IP: Harvest Now Decrypt Later Applied to Intellectual Property — Ingestion, Inversion, and Directional Architecture of AI Governance Failure", Technical Disclosure Commons, (March 17, 2026)
https://www.tdcommons.org/dpubs_series/9547