Analytical framework assesses human intention limits in machine optimization, suggesting governance improvements.
Boundary-5 is a structured analytical framework for evaluating where human intention ends and machine optimization begins within complex socio-technical systems. The framework is designed to support governance analysis, regulatory review, system audits, and research into human–machine interaction, particularly in contexts involving algorithmic optimization, platform incentives, and institutional decision-making. This document represents the initial public disclosure of the Boundary-5 framework and is intended to function as a stable reference version for citation and review. The framework is published as an open reference, with controlled evolution and certification. This work is currently under review on SSRN (Abstract ID: 6191078). The present Zenodo record serves as the canonical, DOI-stamped public version of the framework. Suggested citation:Mendoza, R. (2026). Boundary-5: A Framework for Evaluating Human–Machine Intention Boundaries. Zenodo. https://doi.org/10.5281/zenodo.18514576
No takes yet. Share an insight, caveat, or question.
Mendoza Ruston (2026) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: