FREEDOM OS: Safety as Infrastructure — A Constitutional Integrity Protocol for Applied AI Governance

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Main Author: Madrid, David Chamberlin
Format: Recurso digital
Published: Zenodo 2025
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_version_ 1866901204120895488
author Madrid, David Chamberlin
author_facet Madrid, David Chamberlin
contents <p>FREEDOM OS (FOS) is a Constitutional Integrity Protocol: a structural, mathematical framework for Applied AI Governance, Safety, Reliability, and Interpretability. It treats safety as a non-negotiable invariant and converts governance from human interpretation into computational enforcement.</p> <p> </p> <p>This upload provides a portfolio case study showing an end-to-end governance stack that translates axioms into deployable infrastructure artifacts, including:</p> <p> </p> <ul> <li>a Baseline Safety Manifest that locks a certified safety floor (S_{\max}) and prevents silent regression,</li> <li>a Core Model Safety Manifest that evaluates capability change (\Delta C) alongside safety change (\Delta S) under Safety-Preserving Innovation (\mathcal{I}_{SPI}),</li> <li>a CI/CD Release Gate and validator stub that automatically blocks deployment when non-regression or innovation constraints are violated, and</li> <li>a machine-readable verdict format designed for auditability and traceability (\mathcal{M}_{MAC}).</li> </ul> <p> </p> <p> </p> <p>Core claims:</p> <p> </p> <ol> <li>Safety can be enforced as infrastructure (schemas + gates), not policy alone.</li> <li>Non-regression is provable and auditable across releases.</li> <li>Innovation is permitted, but capability gains must not introduce safety decline.</li> </ol> <p> </p> <p> </p> <p>This artifact is intended for AI safety/governance reviewers, platform and reliability engineers, and hiring panels evaluating systems thinking and release-control design.</p>
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publishDate 2025
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spellingShingle FREEDOM OS: Safety as Infrastructure — A Constitutional Integrity Protocol for Applied AI Governance
Madrid, David Chamberlin
<p>FREEDOM OS (FOS) is a Constitutional Integrity Protocol: a structural, mathematical framework for Applied AI Governance, Safety, Reliability, and Interpretability. It treats safety as a non-negotiable invariant and converts governance from human interpretation into computational enforcement.</p> <p> </p> <p>This upload provides a portfolio case study showing an end-to-end governance stack that translates axioms into deployable infrastructure artifacts, including:</p> <p> </p> <ul> <li>a Baseline Safety Manifest that locks a certified safety floor (S_{\max}) and prevents silent regression,</li> <li>a Core Model Safety Manifest that evaluates capability change (\Delta C) alongside safety change (\Delta S) under Safety-Preserving Innovation (\mathcal{I}_{SPI}),</li> <li>a CI/CD Release Gate and validator stub that automatically blocks deployment when non-regression or innovation constraints are violated, and</li> <li>a machine-readable verdict format designed for auditability and traceability (\mathcal{M}_{MAC}).</li> </ul> <p> </p> <p> </p> <p>Core claims:</p> <p> </p> <ol> <li>Safety can be enforced as infrastructure (schemas + gates), not policy alone.</li> <li>Non-regression is provable and auditable across releases.</li> <li>Innovation is permitted, but capability gains must not introduce safety decline.</li> </ol> <p> </p> <p> </p> <p>This artifact is intended for AI safety/governance reviewers, platform and reliability engineers, and hiring panels evaluating systems thinking and release-control design.</p>
title FREEDOM OS: Safety as Infrastructure — A Constitutional Integrity Protocol for Applied AI Governance
url https://doi.org/10.5281/zenodo.17933056