What does this research mean for the field?

AI governance is best structured as a systems architecture emerging from the interdependent fields of authority, structural constraint, execution control, and dynamic stability, where governance failures primarily manifest as coupling failures between these domains. Novelty: ClaimNovelty.METHODOLOGICAL. Consensus alignment: ConsensusAlignment.ESTABLISHES_NEW_DIRECTION.

What question did this study set out to answer?

This work aims to create a conceptual map for AI governance focusing on the interdependencies of various fields.

April 6, 2026Open Access

A SYSTEMS ARCHITECTURE FOR AI GOVERNANCE Toward an Architecture of Governance in AI Systems

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Authors

RARicardo Rubio Albacete

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Overview

This conceptual paper maps AI governance frameworks in complex systems, suggesting interconnected fields impact effectiveness.

Key Points

This work aims to create a conceptual map for AI governance focusing on the interdependencies of various fields.
Proposes a four-field model for AI governance.
Analyzes elements from law, engineering, software, and control theory.
Identifies governance failures as failures in coupling between fields.
Highlights the need for integrated approaches to governance.
Emphasizes that current frameworks are structurally incomplete.
Suggests that understanding these interconnections can improve governance effectiveness.

Cite This Study

Ricardo Rubio Albacete (2026) studied this question.

synapsesocial.com/papers/69d34e949c07852e0af982fc https://doi.org/10.5281/zenodo.18906019

View Full Paper

Ask AI

Bookmark

April 6, 2026Open Access

A SYSTEMS ARCHITECTURE FOR AI GOVERNANCE Toward an Architecture of Governance in AI Systems

View Full Paper

Ask AI

Bookmark

Authors

RARicardo Rubio Albacete

Discussion

Member takes

Overview

This conceptual paper maps AI governance frameworks in complex systems, suggesting interconnected fields impact effectiveness.

Key Points

This work aims to create a conceptual map for AI governance focusing on the interdependencies of various fields.
Proposes a four-field model for AI governance.
Analyzes elements from law, engineering, software, and control theory.
Identifies governance failures as failures in coupling between fields.
Highlights the need for integrated approaches to governance.
Emphasizes that current frameworks are structurally incomplete.
Suggests that understanding these interconnections can improve governance effectiveness.

Cite This Study

Ricardo Rubio Albacete (2026) studied this question.

synapsesocial.com/papers/69d34e949c07852e0af982fc https://doi.org/10.5281/zenodo.18906019

View Full Paper

Ask AI

Bookmark