What question did this study set out to answer?

The research aims to create a framework for trustworthy AI deployment by aligning policies with practical implementation.

April 14, 2026Open Access

Policy-Bounded AI Work Capsule

Key Points

The research aims to create a framework for trustworthy AI deployment by aligning policies with practical implementation.
Developed governance primitives with mandatory properties
Defined mechanisms for institutional scaling
Mapped alignment across an agenda of 20 items
Created an evaluation framework focusing on job quality and agency
Outlined implementation pathways and policy proposals
Established a foundational framework for policy-bounded AI deployment
Identified key properties for effective governance in AI systems
Provided guidelines for scaling and standardizing AI practices
Highlighted the importance of job quality and agency as outcomes

Abstract

Policy-Bounded AI Work Capsule: A Trust Infrastructure for People-First AI Deployment Author: Raman Marozau · April 2026 Companion implementation framework to OpenAI's Industrial Policy for the Intelligence Age (April 2026). Included in this release Governance primitive definition (4 mandatory properties) Institutional scaling mechanism (standardization, certification, procurement, workforce, interoperability) Alignment mapping across OpenAI's 20-item agenda Evaluation framework (job quality and agency as primary outcomes) Implementation pathway and policy asks Asset: PDF attached to this release.

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Raman Marozau (Sun,) studied this question.

synapsesocial.com/papers/69ddda22e195c95cdefd7970 https://doi.org/https://doi.org/10.5281/zenodo.19540556

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