Structural Dependency: From Physics to Alignment Architecture
Abstract
This paper bridges the prior law stack into engineering by mapping the four PIEC constraints onto AI alignment architectures. It analyzes multiple architecture classes in terms of feasibility, channel irreducibility, sustained exogenous access, and corrective authenticity, and introduces the ideas of corrective ecology, amplification over substitution, and the complexity-starvation threshold as bridge-level engineering concepts. The focus is not on proving a single favored architecture, but on showing how physical correction constraints translate into architectural requirements and vulnerabilities.
Fields of Study & Subjects
Physical Unclonable Functions (PUFs) and Hardware Security
Adversarial Robustness in Machine Learning
Security and Verification in Computing
Publication details
- Journal / source
- Zenodo (CERN European Organization for Nuclear Research)
- Publication date
- 6 April 2026
- Language
- EN
- Document type
- Preprint